The impact of growth mindset on adolescents’ health risk behaviors: the chain mediating roles of core self-evaluation and coping styles

The impact of growth mindset on adolescents’ health risk behaviors: the chain mediating roles of core self-evaluation and coping styles | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of growth mindset on adolescents’ health risk behaviors: the chain mediating roles of core self-evaluation and coping styles Xiaomeng Xu, Yun Ding, Yaohua Zhang, Min Xu, Yunyun Huang, Song Chang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8204472/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Feb, 2026 Read the published version in BMC Psychology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Health risk behaviors pose serious threats to adolescents’ physical and psychological well-being as well as their long-term development. Previous studies suggest that a growth mindset can serve as a positive cognitive resource influencing such behaviors, but the underlying mechanisms remain underexplored, especially over time. Guided by the transactional model of stress and coping, this study aimed to examine a longitudinal model linking growth mindset to later health risk behaviors via core self-evaluation and coping style. Methods A three-wave longitudinal study was conducted using cluster sampling to recruit middle school students in eastern China. Assessments occurred at three-month intervals: growth mindset was measured at Time 1 (T1), core self-evaluation and coping style at Time 2 (T2), and health risk behaviors at Time 3 (T3). In total, 534 students ( M age = 12.40, 50.2% male) completed all three waves. Results Findings indicated that growth mindset at T1 negatively predicted health risk behaviors at T3. Core self-evaluation and positive coping style at T2 independently mediated this relationship and also operated sequentially as a chain mediation pathway, highlighting the longitudinal mechanism linking cognitive beliefs to behavioral outcomes. Conclusion Growth mindset functions as a protective cognitive factor against adolescents’ health risk behaviors by fostering positive self-evaluation and adaptive coping strategies. These findings extend cognitive-behavioral accounts of health risk behaviors and support multicomponent interventions targeting adolescents’ mindsets, core self-evaluation, and coping skills. growth mindset core self-evaluation coping style health risk behaviors adolescents Figures Figure 1 Introduction Adolescents’ health risk behaviors (HRBs), including unhealthy eating, physical inactivity, sleep problems, substance use, and injury-related behaviors [ 1 , 2 ], threaten adolescents’ physical and mental health and can undermine healthy development and overall well‑being [ 3 – 5 ]. HRBs are prevalent in adolescence and often cluster, amplifying the risks of chronic disease and premature mortality [ 6 – 8 ]. They therefore constitute a pressing global public health concern [ 9 , 10 ]. To effectively lessen the negative impact of HRBs on adolescents’ health, it is of great importance to explore the factors influencing these behaviors and the mechanisms underlying them. A number of theoretical frameworks have been proposed to explain the development of adolescents’ HRBs. Problem Behavior Theory (PBT) posits that adolescents’ involvement in risky behaviors reflects a dynamic interaction between risk and protective factors across individual and environmental domains [ 11 , 12 ]. When stressors are salient and protective resources are limited, adolescents are more likely to engage in risky or maladaptive behaviors [ 13 ]. Complementing PBT, Lazarus and Folkman’s transactional model of stress and coping (TMSC) posits that behavioral choices under stress are shaped by cognitive appraisals and subsequent coping processes [ 14 ]. Taken together, these perspectives suggest that adaptive cognitive and coping resources serve as protective factors that reduce the occurrence of HRBs. One such cognitive resource is growth mindset, defined as the belief that personal traits and abilities are malleable rather than fixed [ 15 ], which is widely recognized as a protective factor that facilitates adaptive responses to challenges and failures [ 16 , 17 ]. Adolescents who hold a growth mindset are more likely to interpret setbacks as opportunities for learning, develop positive self-evaluations, and employ constructive coping strategies [ 18 , 19 ]. Beyond academic and emotional domains [ 20 – 22 ], accumulating evidence links growth mindset to health-related outcomes, including better sleep [ 23 ], lower substance use [ 24 – 27 ], reduced self-harm and suicidal ideation [ 28 , 29 ], and healthier lifestyles [ 30 , 31 ]. These findings indicate that a growth mindset has a beneficial effect on adolescents’ HRBs. However, the mechanisms through which a growth mindset influences HRBs remain unclear. Grounded in the TMSC, stress arises from dynamic person-environment transactions in which individuals first conduct a primary appraisal (harm/threat vs. challenge) and then a secondary appraisal (resources and perceived controllability), guiding the use of problem- versus emotion-focused coping [ 14 ]. Drawing on this model, we propose that the association between growth mindset and adolescents’ HRBs operates through two psychological mechanisms, CSE and coping style. A growth mindset biases appraisals toward challenge and higher perceived controllability, strengthens CSE, and promotes more problem-focused and active coping, which together are expected to relate to fewer HRBs. CSE reflects an individual’s fundamental evaluation of self-worth and competence, encompassing self-esteem, generalized self-efficacy, locus of control, and emotional stability [ 32 , 33 ]. Consistent with CSE theory, when individuals confront stress and challenge, their CSEs shape emotional responses and behavioral patterns [ 34 , 35 ], positioning CSE as a proximal cognitive resource that guides stressor appraisals (e.g., challenge vs. threat) and the selection of coping strategies. Empirical research has highlighted the protective role of CSE in preventing adolescents’ engagement in HRBs and promoting adaptive functioning. High levels of CSE have been associated with lower depression, anxiety, and risk-taking, as well as higher life satisfaction and psychological resilience [ 36 ]. Conversely, low CSE has been linked to problematic smartphone use, self-injury, and victimization [ 37 – 39 ]. In adolescent samples, higher CSE also reframes cognitive appraisals under stress, buffers the adverse impact of stressors, and predicts lower engagement in HRBs [ 40 , 41 ]. Furthermore, growth mindset has been linked to higher CSE, as individuals who believe in self-improvement are more likely to develop a coherent and positive self-concept [ 42 , 43 ]. Therefore, we hypothesize that CSE mediates the relationship between growth mindset and adolescents’ HRBs. Coping styles refer to the cognitive and behavioral efforts individuals use to manage internal and external demands [ 44 ]. Positive coping styles, such as problem solving and seeking social support, are associated with better emotion regulation, enhanced well-being, and fewer maladaptive outcomes [ 45 – 49 ]. By contrast, negative coping styles, including avoidance and denial, have been linked to heightened stress reactivity and higher involvement in HRBs, such as substance use [ 50 ], unhealthy eating [ 51 ], and problematic internet use [ 52 ]. In turn, coping styles are closely tied to individuals’ mindsets. A growth mindset may encourage adolescents to adopt more adaptive coping by strengthening perceived control, challenge appraisals, and psychological flexibility [ 22 , 53 ]. Such malleability beliefs may translate into proactive, problem-focused coping styles (positive coping) while constraining avoidant and emotion-focused coping styles (negative coping), thereby interrupting the pathway from stress to HRBs, including substance use, self-injury, and problematic internet use [ 17 , 46 ]. Accordingly, coping style is posited to serve as a proximal pathway linking growth mindset to lower involvement in HRBs. Existing research evidence suggests a serial pathway from cognition to behavior. Individuals with higher CSE are more likely to appraise stressors as manageable and to adopt positive coping approaches [ 54 ], and adaptive coping is associated with lower subsequent involvement in HRBs [ 55 ]. Related work has also documented a serial link of CSE and coping in other outcomes, including academic burnout [ 56 ] and aggression among college students with disabilities [ 57 ]. Conceptually, a growth mindset is a malleability belief that can foster higher CSE [ 58 , 59 ], which in turn promotes adaptive coping. Based on this perspective, we propose a serial mediation model in which growth mindset is related to lower HRBs through CSE and coping. Most previous studies have adopted cross-sectional designs, which limit causal inference. Against this backdrop, we conducted a three-wave longitudinal study to examine the prospective association between growth mindset and adolescents’ HRBs and to test CSE and coping styles as explanatory mechanisms. Given that adolescents’ HRBs often co-occur and cluster, with cumulative risk amplifying adverse outcomes [ 2 , 60 , 61 ], a multi-domain perspective is warranted to test mechanisms across categories. Accordingly, we assessed multiple domains of HRBs in this study. Specifically, we formulated four hypotheses: (1) A higher growth mindset at T1 would predict lower HRBs at T3. (2) CSE assessed at T2 would mediate this association. (3) Coping styles assessed at T2 would also mediate this association, with a higher growth mindset at T1 predicting greater positive coping and less negative coping at T2, and positive coping at T2 predicting lower HRBs at T3, whereas negative coping at T2 predicting higher HRBs at T3. (4) CSE and coping would operate sequentially such that a higher growth mindset at T1 would be associated with higher CSE at T2, which in turn would foster more positive and less negative coping styles at T2, ultimately relating to lower HRBs at T3. By testing this longitudinal serial mediation model, this study extends growth mindset theory to the domain of health behaviors and delineates cognitive pathways ordered in time that may underlie adolescents’ behavioral development. Methods Participants A total of 842 eighth-grade students from a middle school in an eastern province of China were recruited through cluster sampling. Data were collected at three waves separated by three months: T1 in late December 2024, T2 in late March 2025, and T3 in late June 2025. After excluding invalid responses (missing identifiers, more than 30% missing data, or all items omitted for any variable), 701 valid participants remained at T1 ( M age = 12.39, SD = 0.56, 52.2% male), 706 at T2 ( M age = 12.90, SD = 0.57, 50.7% male), and 721 at T3 ( M age = 13.05, SD = 0.51, 51.9% male). At T2 and T3, changes in class organization resulted in the inclusion of additional students who had not participated in earlier waves, thereby yielding slightly larger sample sizes at these assessment points. Of the 701 participants with valid data at T1, 534 were retained across all three waves ( M age = 12.40, SD = 0.55, 50.2% male). To assess the potential attrition bias, participants who dropped out after T1 (attrition group, n = 167) were compared with those who completed all waves (retained group, n = 534). Results indicated no statistically significant differences between the groups on key demographic variables, including age ( t (699) = -0.20, p = 0.840, Cohen’s d = -0.02), gender distribution (χ² = 3.68, p = 0.055), father’s education level ( t (693) = -0.76, p = 0.449, Cohen’s d = -0.07), and mother’s education level ( t (693) = 0.09, p = 0.926, Cohen’s d = 0.00). Regarding the core variables, the attrition group reported significantly higher levels of negative coping ( t (699) = 2.19, p = 0.029, Cohen’s d = 0.19) and excessive screen use ( t (699) = 2.22, p = 0.027, Cohen’s d = 0.20). However, the effect sizes were small (Cohen’s d < 0.20), suggesting that attrition had a limited impact on the validity of the study’s main findings [62]. Procedure Ethical approval for this study was obtained from the Ethics Committee of Ludong University. Informed consent was obtained from students and their parents prior to data collection. Data were gathered in class across three waves approximately three months apart: at T1, students completed the growth mindset measure; at T2, they completed measures of CSE and coping style; and at T3, they completed measures of HRBs. All questionnaires were administered during regular class sessions. Participants were reminded of confidentiality and their right to withdraw at any time. Measures Health risk behaviors HRBs were assessed using the China Adolescent Health-Related Behavior Questionnaire (Middle School Version), a standardized Chinese adaptation of the Youth Risk Behavior Survey (YRBS) that measures seven dimensions of health-related and risk behaviors among adolescents [51, 63]. Based on the questionnaire manual and the characteristics of the target population, this study focused on five dimensions: sedentary behavior, unhealthy eating behavior, excessive screen use, sleep problems, and interpersonal violence. Previous studies using the China Adolescent Health-Related Behavior Questionnaire have similarly selected subsets of items or specific subscales to assess particular health-related behaviors (e.g., dietary behaviors, physical activity, and school violence), and have reported acceptable reliability and validity for these item sets [64, 65]. In the present study, items assessing sedentary behavior, unhealthy eating behavior, excessive screen use, and interpersonal violence were drawn directly from the China Adolescent Health-Related Behavior Questionnaire (Middle School Version), whereas the three items assessing sleep problems were selected from the Pittsburgh Sleep Quality Index (PSQI) [66]. Details are presented below. (1) Sedentary behavior This dimension was measured with two items (“On a typical day, how much time do you usually spend sitting or lying down in low- or high-cognitive-effort activities?”). Response options ranged from 1 to 9, representing durations from less than 5 minutes to more than 12 hours per day. Higher scores indicated longer sedentary time. The mean of the two items was calculated to generate the sedentary behavior score. (2) Unhealthy eating behavior Three items assessed the frequency of drinking sugary beverages, eating desserts, and consuming fast food. A sample item was: “During the past 30 days, how many times per day did you usually drink soft drinks such as Coca-Cola, Pepsi, or Sprite?” The three items were rated on 7-point, 5-point, and 8-point scales, respectively, with higher scores reflecting more frequent unhealthy eating. Because the response scales differed, all items were standardized into z-scores and then averaged to yield the composite score for this dimension. (3) Excessive screen use This construct was measured with three items. A sample item was: “During the past seven days, how much time did you usually spend watching TV or videos?” Responses ranged from 1 (“never”) to 6 (“more than 4 hours”), with higher scores indicating longer durations of screen use. The mean of the three items represented the score for this dimension. (4) Sleep problems Three items adapted from the Pittsburgh Sleep Quality Index (PSQI) were used to assess sleep problems. A sample item was: “During the past month, how often have you been bothered by taking more than 30 minutes to fall asleep?” Each item was rated on a 4-point scale (1 = never, 2 = less than once per week, 3 = 1-2 times per week, 4 = at least three times per week), with higher scores indicating more frequent sleep problems. The mean of the three items was calculated to indicate the severity of sleep problems. (5) Interpersonal violence This dimension covered experiences of being bullied (e.g., mocked, extorted, socially excluded, physically assaulted or confined, or subjected to sexual jokes) and engagement in physical fights. Bullying was measured using six 3-point items and fighting using one 8-point item. Higher scores indicated greater frequencies of violence-related behaviors. Because these items used different response scales, all were standardized as z-scores and then averaged to form the composite score for interpersonal violence. Given the inconsistency in response formats across dimensions, all dimension scores were transformed into z-scores before conducting correlation and mediation analyses. Growth mindset Adolescents’ growth mindset was assessed using the Implicit Theories of Thoughts–Emotion–Behavior Questionnaire (ITEB-Q) [67]. This instrument conceptualizes implicit beliefs in the domains of thoughts, emotions, and behaviors and has demonstrated strong internal consistency as well as concurrent validity with measures of life satisfaction, psychological resilience, emotion regulation, and emotional problems [16, 67]. Its cross-group stability has also been supported [68]. Twelve items were rated on a 6-point Likert scale (1 = “strongly disagree,” 6 = “strongly agree”). Scores were averaged, with higher values indicating a stronger growth mindset. At Time 1, the scale showed excellent internal consistency, with a Cronbach’s α of 0.96. Confirmatory factor analysis (CFA) indicated good model fit (χ²/ df = 3.29, CFI = 0.98, TLI = 0.98, RMSEA = 0.07), with all factor loadings exceeded 0.60, supporting the strong construct validity of the measure in the present study. Core Self-Evaluation Adolescents’ core self-evaluation was measured using the Chinese version of the Core Self-Evaluation Scale (CSES), a 10-item localized adaptation of Judge’s original instrument by Du J, Zhang X and Zhao Y [69]. The scale comprises four dimensions: self-esteem, generalized self-efficacy, locus of control, and emotional stability. Items are rated on a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The questionnaire includes both positively and negatively worded items: items 1, 4, 6, and 9 are scored positively, whereas items 2, 3, 5, 7, 8, and 10 are reverse-scored. Higher total scores indicate higher levels of core self-evaluation. At Time 2, the scale demonstrated good internal consistency (Cronbach’s α = 0.88). CFA indicated an acceptable model fit (χ²/ df = 2.39, CFI = 0.98, TLI = 0.97, RMSEA = 0.05), with all factor loadings exceeding 0.60, supporting the construct validity of the scale in the present study. Coping Style Coping styles were assessed using the Simplified Coping Style Questionnaire (SCSQ) [70], which evaluates the relationship between coping styles and mental health. The scale contains 20 items grouped into two dimensions: positive coping (items 1-12) and negative coping (items 13-20). Responses are rated on a 4-point Likert scale ranging from 0 (“never”) to 3 (“frequently”). In the present study, the scale demonstrated good internal consistency at T2, with Cronbach’s α was 0.89 for the total scale, 0.91 for the positive coping subscale, and 0.83 for the negative coping subscale. The CFA initially indicated suboptimal model fit (χ²/ df = 4.45, CFI = 0.88, TLI = 0.87, RMSEA = 0.08). Modification indices indicated that item 20 (“self-reassurance”) showed a substantial potential cross-loading on the other coping factor (MI = 20.69), suggesting that its content overlapped across dimensions. Given its conceptual ambiguity and the goal of achieving a more homogeneous factor structure, item 20 was removed, which led to improved overall model fit. After its deletion, the model exhibited an improved fit (χ²/ df = 3.39, CFI = 0.93, TLI = 0.92, RMSEA = 0.07). Standardized factor loadings for all remaining items ranged from 0.47 to 0.82, demonstrating satisfactory construct validity for the revised model. Statistical analyses All analyses were performed using SPSS 26.0 and Mplus 8.3. In SPSS, Harman’s single-factor test was first conducted to assess potential common method bias. Descriptive statistics and correlation analyses were also performed. Given that the continuous variables exhibited non-normal distributions, Spearman’s rank-order correlations were used. Mplus 8.3 was employed to perform CFA and test the sequential mediation model. Model parameters were estimated using the robust maximum likelihood estimator (MLR), and missing data were handled with full information maximum likelihood (FIML). Model fit was assessed using standard indices (χ²/ df , CFI, TLI, RMSEA), and mediation effects were tested via bootstrapping with 5,000 resamples to obtain 95% bias-corrected confidence intervals. All continuous variables were standardized before analysis. In accordance with cumulative evidence from meta-analyses and international assessments, gender, age, and parental education were included as covariates [71-75]. Because participants were nested within classes, we computed intraclass correlation coefficients (ICCs) using class as the grouping factor to evaluate potential design effects. ICCs for all variables ranged from 0.00 to 0.03, well below the conventional 0.05 threshold [76], indicating minimal class-level variance and supporting the use of single-level analyses. Results Common method bias test We assessed common method bias using Harman’s single-factor test. Twelve factors exhibited eigenvalues greater than 1, and the first factor explained 23.29% of the total variance, which is below the conventional 40% criterion. These results suggest that common method bias is not a substantial threat to the validity of our findings. Descriptive and correlation analysis Table 1 presents the descriptive statistics and the correlation matrix of the study variables. To ensure comparability in the descriptive statistics, scores within the unhealthy eating behavior and interpersonal violence dimensions were first standardized at the item level and then averaged, because items in these dimensions used different response formats. Consequently, the means and standard deviations for unhealthy eating behavior and interpersonal violence in Table 1 are expressed as z-scores, while other variables are presented in their original metrics. For subsequent correlation and mediation analyses, all variables were standardized as z-scores prior to modeling. Correlation results showed that growth mindset at T1 was positively associated with CSE and positive coping at T2 but negatively associated with negative coping at T2 and all dimensions of HRBs at T3. CSE at T2 was positively correlated with positive coping and negatively correlated with negative coping and all HRBs dimensions at T3. Positive coping at T2 was negatively related to unhealthy eating, excessive screen use, sleep problems, and interpersonal violence at T3, but not significantly associated with sedentary behavior. In contrast, negative coping at T2 was positively correlated with all dimensions of HRBs at T3. Table 1 Descriptive statistics and correlation matrix for key variables (N = 534) Variable 1 2 3 4 5 6 7 8 9 1.T1GM 1 2.T2CSE 0.51 *** 1 3.T2CP-p 0.47 *** 0.50 *** 1 4.T2CP-n -0.13 ** -0.18 *** 0.14 ** 1 5.T3HRBs-SB -0.09 * -0.11 * -0.01 0.14 ** 1 6.T3HRBs-UEB -0.14 ** -0.16 *** -0.09 * 0.09 * 0.26 *** 1 7.T3HRBs-ESU -0.16 *** -0.20 *** -0.14 ** 0.18 *** 0.35 *** 0.30 *** 1 8.T3HRBs-SP -0.28 *** -0.34 *** -0.29 *** 0.14 ** 0.21 *** 0.21 *** 0.20 *** 1 9.T3HRBs-IV -0.21 *** -0.25 *** -0.13 ** 0.20 *** 0.20 *** 0.20 *** 0.26 *** 0.29 *** 1 M ± SD 4.81 ± 1.15 3.64 ± 0.88 1.85 ± 0.78 1.00 ± 0.79 4.11 ± 1.85 0.00 ± 0.74 2.12 ± 0.88 1.71 ± 0.76 0.00 ± 0.80 Notes. GM = growth mindset, CSE = core self-evaluation, CP‑p = positive coping, CP‑n = negative coping, HRBs = health risk behaviors, SB = sedentary behavior, UEB = unhealthy eating behavior, ESU = excessive screen use, SP = sleep problems, IV = interpersonal violence. For the UEB and IV, item scores were standardized as z-scores and then averaged to compute the dimension scores. * p < 0.05, ** p < 0.01, *** p < 0.001. Longitudinal Sequential Mediation Analysis Mplus 8.3 was used to estimate a longitudinal serial mediation model in which T1 growth mindset predicted the latent outcome T3 HRBs via T2 CSE, T2 positive coping, and T2 negative coping. The latent construct of HRBs at T3 was indicated by five observed variables. All standardized factor loadings were statistically significant ( p < 0.001). The loadings were as follows: sleep problems (0.82), interpersonal violence (0.74), excessive screen use (0.57), unhealthy eating (0.47), and sedentary behavior (0.30). Although the loadings varied in magnitude, each indicator reached or approximated the commonly cited minimum threshold of about 0.30 for standardized factor loadings [ 77 , 78 ]. We therefore retained all indicators to capture more comprehensively the breadth of adolescent HRBs. The model’s acceptable fit indices (χ²/ df = 1.38, CFI = 0.98, TLI = 0.96, RMSEA = 0.03, SRMR = 0.03) provide support for the overall validity of the measurement model. The standardized path coefficients of the structural model are presented in Fig. 1 . Controlling for gender, age, and parental education, T1 growth mindset predicted higher T2 CSE (β = 0.504, p < 0.001) and higher positive coping (β = 0.230, p 0.05) and T2 negative coping (β = -0.049, p > 0.05). T2 CSE predicted higher positive coping (β = 0.385, p < 0.001), lower negative coping (β = -0.113, p < 0.05) and lower T3 HRBs (β = -0.265, p < 0.001). In addition, T2 positive coping predicted lower T3 HRBs (β = -0.184, p < 0.01), whereas T2 negative coping predicted higher T3 HRBs (β = 0.187, p < 0.01). The results of the mediation analysis are presented in Table 2 . T1 growth mindset exerted a significant negative total effect on T3 adolescents’ HRBs (c = -0.327, p 0.05), whereas the total indirect effect remained significant, consistent with full mediation (β = -0.231, 95% CI [-0.299, -0.164]). Decomposing the indirect effects further clarified the pathways. Growth mindset indirectly influenced later HRBs through higher CSE (β = -0.134, 95% CI [-0.200, -0.068]). It also reduced HRBs via increased positive coping (β = -0.042, 95% CI [-0.075, -0.009]), whereas the mediating effect of negative coping was nonsignificant (β = -0.009, 95% CI [-0.031, 0.013]). Furthermore, the chain mediation effects of CSE and coping styles received partial support. Specifically, the indirect path through positive coping (T1 GM → T2 CSE → T2 CP-p → T3 HRBs) was significant (β = -0.036, 95% CI [-0.061, -0.010]), whereas the corresponding chain through CSE and negative coping (T1 GM → T2 CSE → T2 CP-n → T3 HRBs) was not statistically significant (β = -0.011, 95% CI [-0.023, 0.001]). Overall, these findings support the hypothesized sequential mediation model, suggesting that a stronger growth mindset indirectly reduces adolescents’ HRBs through enhanced CSE and adaptive coping styles. Table 2 Bootstrap test of mediation effects Effect SE 95%CI Effect sizes Total -0.327 0.056 [-0.437, -0.218] 100% Direct -0.096 0.058 [-0.210, 0.019] 29.36% Total indirect -0.231 0.034 [-0.299, -0.164] 70.64% T1GM→T2CSE→T3HRBs -0.134 0.034 [-0.200, -0.068] 40.98% T1GM→T2CP-p→T3HRBs -0.042 0.017 [-0.075, -0.009] 12.84% T1GM→T2CP-n→T3HRBs -0.009 0.011 [-0.031, 0.013] 2.75% T1GM→T2CSE→T2CP-p→T3HRBs -0.036 0.013 [-0.061, -0.010] 11.01% T1GM→T2CSE→T2CP-n→T3HRBs -0.011 0.006 [-0.023, 0.001] 3.36% Notes. GM = growth mindset, CSE = core self-evaluation, CP-p = positive coping, CP-n = negative coping, HRBs = health risk behaviors. All effects are standardized. Confidence intervals are bias-corrected 95% bootstrap CIs based on 5,000 resamples. Robustness check HRBs can be scored using different methods. In addition to the standardized z-scores used in the main analyses, a common alternative is binary coding (0 = no behavior reported, 1 = behavior reported), as adopted in prior studies [ 63 , 65 , 79 ]. To assess robustness, we reanalyzed the model using binary-coded HRBs. Results remained consistent in direction and significance (see Supplementary Materials). Discussion Drawing on the TMSC and informed by PBT, this study examined whether the cognitive resource of a growth mindset is related to adolescents’ HRBs over time through the intervening processes of CSE and coping styles, with the aim of providing actionable guidance for school settings. The primary objective was to extend evidence on the time-ordered association between growth mindset and HRBs and to clarify the mediating mechanisms. In the primary model, a stronger growth mindset predicted lower subsequent HRBs. After CSE and positive coping were included, the direct path from growth mindset to HRBs was no longer significant, consistent with substantial mediation. A robustness analysis using binary outcomes reproduced this pattern, although a small residual direct association emerged. In contrast, the mediating pathway through CSE and negative coping was not significant. The sections that follow position these findings in the prior literature and consider limitations as well as practical and policy implications for school-based health promotion. Growth mindset and Health risk behaviors In line with Hypothesis 1, T1 growth mindset was significantly associated with fewer HRBs at T3 after adjusting for demographic covariates. These results are consistent with the mindset framework and the TMSC. Malleability beliefs shape appraisal and self-regulation [ 80 ], foster adaptive attributions and goal directed strategy use [ 81 ], and are associated with lower engagement in risk behaviors as adolescents view setbacks as surmountable challenges and invest effort in constructive strategies [ 82 ]. Within the TMSC framework, the association is plausibly driven by appraisal based mechanisms: a growth mindset increases perceived controllability, strengthens positive self-appraisals, and encourages problem focused, active coping while constraining maladaptive responses [ 16 , 17 , 83 ]. Taken together, the evidence supports viewing growth mindset as a modifiable psychological resource associated with healthier behavioral choices during adolescence [ 18 , 84 ]. Core self-evaluation as a mediator Consistent with Hypothesis 2, CSE served as a significant mediator between T1 growth mindset and T3 HRBs, accounting for roughly 41% of the total effect. This finding suggests that adolescents with a stronger growth mindset tend to develop more positive and coherent self-views over time, which in turn is associated with lower involvement in HRBs. Prior work shows that endorsing the malleability of abilities strengthens adaptive beliefs and self‑concepts [ 43 , 58 ], whereas holding a weaker growth mindset is associated with diminished self-appraisals and lower perceived competence [ 85 ]. Prior evidence links higher CSE to fewer adolescent HRBs, indicating that youth with stronger self-views show less maladaptive behavior and greater resilience to psychosocial risks [ 86 – 88 ]. Recent longitudinal evidence further supports this protective role, indicating that higher CSE can buffer the adverse impact of stressful life events on maladaptive outcomes, such as suicidal behaviors, partly through reduced depressive symptoms [ 89 ]. In contrast, adolescents with lower CSE tend to internalize negative self-perceptions and are more likely to adopt maladaptive behavioral patterns [ 90 , 91 ]. However, the protective effect of CSE is not uniform across risk domains. For example, associations tend to be weaker or non-significant for behaviors like substance use and risky sexual activity [ 92 ]. Likewise, reviews suggest that links between certain core CSE facets (e.g., self-esteem) and HRBs depend on the specific domain and context [ 93 ]. These mixed findings imply that factors such as gender and sociocultural context may moderate CSE’s influence. Recognizing these boundary conditions is important for a nuanced understanding of when and how CSE contributes to risk behavior outcomes. Taken together, the evidence positions CSE as a proximal cognitive resource that helps transmit the influence of a growth mindset to reduced involvement in HRBs. In line with our serial framework, higher CSE is likely to precede and foster more adaptive appraisal and coping, although the strength of this pathway appears to vary across behavioral domains and contexts. Coping styles as a mediator Partially supporting Hypothesis 3, coping styles mediated the relationship between growth mindset and later HRBs. The indirect effect through positive coping was significant, whereas the pathway through negative coping alone was not significant. In addition, both coping indices showed direct associations with HRBs, which underscores coping as a proximal mechanism connecting beliefs with behavior [ 94 – 96 ]. The absence of a significant association between growth mindset and negative coping diverges from some earlier findings. One plausible developmental explanation is that adolescents’ still maturing executive functions limit their ability to translate abstract growth-oriented beliefs into the inhibition of avoidant or emotion-focused responses, especially under high emotional arousal [ 53 , 97 ]. In contrast, positive coping typically involves planning, problem solving, and support seeking, which aligns more closely with the sense of agency emphasized by a growth mindset. Indeed, in our data, greater use of positive coping was prospectively associated with fewer HRBs. Prior studies similarly show that positive coping enhances emotion regulation and is linked to lower levels of aggression, substance use, and other risk behaviors [ 98 – 100 ]. Conversely, heavier reliance on negative coping has been associated with outcomes such as unhealthy eating [ 51 ], suicidal behavior [ 101 ], and problematic internet use [ 102 ]. Overall, these patterns suggest that a growth mindset relates to lower HRBs primarily by fostering positive coping. This highlights the central role of coping in the TMSC framework and provides a rationale for examining the sequential mediation via CSE and positive coping in the next section. Finally, we note a domain-level difference: positive coping was not associated with sedentary behavior, suggesting heterogeneity across HRBs domains and indicating that sedentary behavior may depend more on habits or environmental constraints than on momentary coping strategies. Core self-evaluation and coping styles as sequential mediators Consistent with Hypothesis 4, this study provides the first longitudinal evidence for a time-ordered pathway whereby growth mindset enhances CSE, which in turn promotes positive coping and is associated with lower involvement in HRBs. As a positive cognitive framework, growth mindset was associated with higher CSE, and higher CSE was linked with greater use of positive coping when facing stress [ 103 ], and to a higher likelihood of adopting constructive strategies with fewer maladaptive behaviors [ 104 ]. By contrast, low CSE may hinder positive coping and increase vulnerability to aggression and other risk behaviors [ 57 ]. This pattern aligns with TMSC and with evidence that CSE shapes appraisal and coping under stress, thereby influencing behavioral choices [ 105 ]. Prior studies support this mechanism. For example, self-efficacy, a key facet of CSE, together with coping has been found to jointly mediate the association between school bullying and adolescent mental health outcomes [ 106 ]. The alignment between our longitudinal pathway and this literature corroborates theoretical coherence, reinforces construct validity for CSE and coping as mechanisms, and supports generalizability across samples and contexts. In our primary model, the direct path from growth mindset to HRBs was not significant after including the mediators, whereas a supplementary analysis with binary outcomes found a small direct effect. Indirect effects via CSE and positive coping accounted for around 71% of the total association, indicating that the majority of the linkage operates through enhanced self-evaluation and more positive coping. In the robustness analysis with binary HRB outcomes, the indirect effect via negative coping reached statistical significance; however, the effect size was small and the finding did not replicate in the primary continuous-outcome model, so this pathway should be interpreted with caution. Taken together, these results support a time-ordered pathway from cognition to appraisal to coping: growth mindset enhances CSE, CSE facilitates adaptive coping, and adaptive coping is associated with lower involvement in HRBs. Theoretical and practical implications This study offers several theoretical contributions. First, it extends the protective role of growth mindset beyond mental health to the broader domain of adolescents’ HRBs. Second, by identifying CSE and coping styles as mediators, it provides empirical support for both PBT and TMSC, clarifying the cognitive pathways through which personal beliefs influence behavior. Third, evidence of a time-ordered pathway from growth mindset to CSE to coping advances our understanding of adolescent adaptation by specifying how cognitive appraisals are translated into behavioral choices. The findings also carry practical implications. School and clinical programs aimed at reducing HRBs can incorporate growth mindset training to strengthen students’ beliefs in malleability and to build psychological resilience. Interventions that enhance CSE may further reduce youths’ vulnerability to maladaptive behaviors, for example by promoting self-esteem, perceived control, and emotional stability. Additionally, teaching positive coping strategies, such as problem-solving and seeking social support, offers a concrete route to risk reduction. An integrated, multilevel approach that targets cognitive beliefs, self-evaluation, and coping skills in parallel is likely to be more effective than single-component interventions. Limitations and future directions This study has several limitations. First, all variables were measured via self-report, which can introduce social desirability and recall biases. Future work should triangulate self-reports with multiple informants or objective indicators (e.g., teacher or parent ratings, behavioral records, passive digital traces) to improve validity. Second, although the design was longitudinal, it included only three waves over a relatively short time span. This limits inferences about long-term trajectories. Studies with longer observation periods, additional waves, and more advanced longitudinal models would allow stronger conclusions about developmental pathways over time. Third, participants were drawn from specific regions of China, so findings may not generalize to other populations. Replication across more diverse cultural and institutional contexts is needed to verify generalizability. Fourth, attrition analyses showed that dropouts had slightly higher levels of negative coping and greater screen use. Although these effects were small, this pattern suggests a conservative bias that may have led to underestimating certain associations. It is advisable for future studies to implement strategies to minimize attrition and to document reasons for participant dropout. Fifth, to improve model fit and conceptual clarity, we removed one poorly performing item from the negative coping subscale of the SCSQ. This decision was consistent with the scale’s bidimensional structure and avoided cross-loading content, but it slightly reduces comparability with studies that used the full SCSQ. Replication using the complete scale or alternative coping measures is warranted to confirm the findings. Finally, we cannot rule out the influence of unmeasured confounding variables or domain-specific processes. To better establish causality, future research should complement observational designs with randomized or quasi-experimental interventions that manipulate growth mindset, strengthen CSE, and train positive coping, and then evaluate the downstream effects on specific types of HRBs. Conclusion Our longitudinal findings demonstrate that adolescents with a stronger growth mindset are less likely to engage in HRBs over time. The findings revealed four key results: (1) growth mindset showed a significant negative total association with HRBs; (2) CSE mediated this relationship; (3) positive coping styles also played a mediating role; and (4) CSE and positive coping styles jointly formed a sequential mediation pathway linking growth mindset to HRBs. Overall, the findings indicate that a growth mindset functions as a protective factor of adolescents’ health. Indirect pathways operated through higher CSE and greater use of positive coping. This study provides longitudinal evidence for a pathway from cognition to appraisal to coping, clarifying the cognitive and behavioral mechanisms that may link growth mindset to lower HRBs. These results offer actionable guidance for multicomponent programs that cultivate growth mindset, strengthen CSE, and build positive coping skills to foster healthier behaviors in adolescence. Declarations Acknowledgements We are grateful to all the students, schools, and research assistants who participated in and supported this study, particularly for their assistance with data collection. We used ChatGPT (OpenAI) solely for English language polishing (grammar and style). All scientific content was written, verified, and approved by the authors. Authors’ contributions X.X. conceived and designed the study, performed the statistical analyses, and drafted the manuscript. Y.D. organized and entered the data and conducted the preliminary analyses. Y.Z., M.X. and Y.H. contributed to data verification, study design, and statistical analysis. S.X. and S.C. made substantial contributions to the conception and design of the work and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work. Funding This study was supported by the Ministry of Education Humanities and Social Sciences Research Project (No. 23YJC880119), the Shandong Provincial Social Science Planning Project (No. 24DJYJ06), and the Shandong Postdoctoral Science Foundation (No. sDCX-RS-202400006). Data availability The datasets generated and/or analyzed during the current study are not publicly available due to institutional and ethical restrictions related to participant confidentiality, but are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study adhered to the ethical guidelines and regulations outlined in the Helsinki Declaration regarding the involvement of human participants. The research protocol received approval from the Ethics Committee of Ludong University (ES002510). Informed consent was obtained from all participants, or in the case of participants under 18 years of age, from their parent and/or legal guardian. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Atorkey P, Owiredua C. Clustering of multiple health risk behaviours and association with socio-demographic characteristics and psychological distress among adolescents in Ghana: a latent class analysis. SSM-Population Health. 2021;13:100707. Wijbenga L, de Winter AF, Almansa J, Vollebergh WA, Korevaar EL, Hofstra J, Reijneveld SA. Multiple health risk behaviors and mental health from a life course perspective: The Dutch TRAILS study. Preventive Medicine. 2022;154:106870. Jahangard L, Behmanesh H, Ahmadpanah M, Poormoosavi SM, Solitanian A, Highighi M. Risky behaviors and health-promoting behaviors in young adults: An epidemiological study. Iranian Journal of Psychiatry. 2019;14(4):302. Tariq N, Gupta V. High risk behaviors. Treasure Island (FL): StatPearls Publishing; 2023. Ge G, Huangfu C, Ge M, Gao Y, Tang N. Influence factors associated with health risk behaviors of middle school students in the poverty area of China: An observational study. Medicine. 2022;101(33):e29922. Noble N, Paul C, Turon H, Oldmeadow C. Which modifiable health risk behaviours are related? A systematic review of the clustering of Smoking, Nutrition, Alcohol and Physical activity (‘SNAP’) health risk factors. Preventive Medicine. 2015;81:16–41. Ssewanyana D, Abubakar A, Newton CR, Otiende M, Mochamah G, Nyundo C, Walumbe D, Nyutu G, Amadi D, Doyle AM. Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting. PLOS ONE. 2020;15(11):e0242186. Matias TS, Silva KS, Silva JAd, Mello GTd, Salmon J. Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school-based health survey (PeNSE 2015). BMC Public Health. 2018;18:1–9. Yang R, Li D, Hu J, Tian R, Wan Y, Tao F, Fang J, Zhang S. Association between health literacy and subgroups of health risk behaviors among Chinese adolescents in six cities: a study using regression mixture modeling. International Journal of Environmental Research and Public Health. 2019;16(19):3680. WHO. Adolescent and young adult health. Available from: www.who.int/news-room/fact-sheets/detail/adolescents-health-risks-and-solutions. Accessed 20 Nov 2024. Jessor R, Turbin MS, Costa FM, Dong Q, Zhang H, Wang C. Adolescent problem behavior in China and the United States: A cross‐national study of psychosocial protective factors. Journal of Research on Adolescence. 2003;13(3):329–360. Jessor R, Van Den Bos J, Vanderryn J, Costa FM, Turbin MS. Protective factors in adolescent problem behavior: Moderator effects and developmental change. Developmental Psychology. 1995;31(6):923. Rutter M. Psychosocial resilience and protective mechanisms. American Journal of Orthopsychiatry. 1987;57(3):316–331. Lazarus RS. Stress, appraisal, and coping. New York: Springer; 1984. Dweck CS. Mindset: The new psychology of success. New York: Random House; 2006. Walker KA, Jiang X. An examination of the moderating role of growth mindset in the relation between social stress and externalizing behaviors among adolescents. Journal of Adolescence. 2022;94(1):69–80. Zhang L, Qi H, Wang C, Wang T, Zhang Y. How does growth mindset affect mental health of high school students during the COVID-19 epidemic? The role of grit and coping strategies. Frontiers in Psychiatry. 2022;13:969572. Yeager DS, Hanselman P, Walton GM, Murray JS, Crosnoe R, Muller C, Tipton E, Schneider B, Hulleman CS, Hinojosa CP. A national experiment reveals where a growth mindset improves achievement. Nature. 2019;573(7774):364–369. Yeager DS, Dweck CS. Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist. 2012;47(4):302–314. Guo M. The longitudinal relationship between perceived parental growth mindset and children's math‐specific grit: The mediational role of growth mindset and self‐efficacy. Journal of Adolescence. 2025;97(5):1261–1271. Tang X, Wang M-T, Guo J, Salmela-Aro K. Building grit: The longitudinal pathways between mindset, commitment, grit, and academic outcomes. Journal of Youth and Adolescence. 2019;48(5):850–863. Burnette JL, Knouse LE, Vavra DT, O'Boyle E, Brooks MA. Growth mindsets and psychological distress: A meta-analysis. Clinical Psychology Review. 2020;77:101816. Bernecker K, Job V. Too exhausted to go to bed: Implicit theories about willpower and stress predict bedtime procrastination. British Journal of Psychology. 2020;111(1):126–147. Thai CL, Rice EL, Taber JM, Kaufman AR, Klein WM. Implicit theories of smoking and association with interest in quitting among current smokers. Journal of Behavioral Medicine. 2020;43:544–552. Fitz CC, Kaufman A, Moore PJ. Lay theories of smoking and young adult nonsmokers’ and smokers’ smoking expectations. Journal of Health Psychology. 2015;20(4):438–445. Lindgren KP, Burnette JL, Hoyt CL, Peterson KP, Neighbors C. Growth mindsets of alcoholism buffer against deleterious effects of drinking identity on problem drinking over time. Alcoholism: Clinical and Experimental Research. 2020;44(1):233–243. Sridharan V, Shoda Y, Heffner JL, Bricker J. Addiction mindsets and psychological processes of quitting smoking. Substance Use & Misuse. 2019;54(7):1086–1095. Schroder HS, Yalch MM, Dawood S, Callahan CP, Donnellan MB, Moser JS. Growth mindset of anxiety buffers the link between stressful life events and psychological distress and coping strategies. Personality and Individual Differences. 2017;110:23–26. Zhu S, Li X, Wong PW. Risk and protective factors in suicidal behaviour among young people in Hong Kong: A comparison study between children and adolescents. Psychiatry Research. 2023;321:115059. Ehrlinger J, Burnette JL, Park J, Harrold ML, Orvidas K. Incremental theories of weight and healthy eating behavior. Journal of Applied Social Psychology. 2017;47(6):320–330. Orvidas K, Burnette J, Russell V. Mindsets applied to fitness: Growth beliefs predict exercise efficacy, value and frequency. Psychology of Sport and Exercise. 2018;36:156–161. Judge TA, Locke EA, Durham CC, Kluger AN. Dispositional effects on job and life satisfaction: the role of core evaluations. Journal of Applied Psychology. 1998;83(1):17. Judge TA, Erez A, Bono JE, Thoresen CJ. The core self‐evaluations scale: Development of a measure. Personnel Psychology. 2003;56(2):303–331. Liu F, Zhu Z, Jiang B. The influence of Chinese college students’ physical exercise on life satisfaction: the chain mediation effect of Core self-evaluation and positive emotion. Frontiers in Psychology. 2021;12:763046. Ma X, Li Z, Lu F. The influence of stressful life events on procrastination among college students: multiple mediating roles of stress beliefs and core self-evaluations. Frontiers in Psychology. 2023;14:1104057. Cherewick M, Hipp E, Njau P, Dahl RE. Growth mindset, persistence, and self-efficacy in early adolescents: Associations with depression, anxiety, and externalising behaviours. Global Public Health. 2023;18(1):2213300. Gong Y, Yang H, Bai X, Wang Y, An J. The relationship between physical exercise and smartphone addiction among Chinese College Students: the mediating effect of Core Self-evaluation. Behavioral Sciences. 2023;13(8):647. Wang S, Ding W, Song S, Tan Y, Ahmed MZ, Xie R, Li L. The relationship between adolescent victimization, nonsuicidal self-injury, and core self-evaluation: a cross-lagged study. Current Psychology. 2024;43(1):28–38. Feng Y, Luo X, Li X, Liu Y, Zeng Y. Bayesian network analysis of individual-level factors associated with bullying among high school students. BMC Psychology. 2025;13(1):658. Zou S, Song X, Tan W, Deng F, Zhang H, Xu H, Tao Y, Tang X, Tang X, Xiong P. Core self-evaluation as mediator between depressive symptoms and suicidal ideation in adolescents. Journal of Affective Disorders. 2022;302:361–366. Qi W, Cui L. Eat to avoid negative self-awareness: Locus of control and core self-evaluation as serial mediators in the effect of stress on food intake. Appetite. 2019;143:104401. Claro S, Paunesku D, Dweck CS. Growth mindset tempers the effects of poverty on academic achievement. Proceedings of the National Academy of Sciences. 2016;113(31):8664–8668. Zhao H, Zhang M, Li Y, Wang Z. The relationship between a growth mindset and junior high school students’ meaning in life: a serial mediation model. Behavioral Sciences. 2023;13(2):189. Folkman S, Lazarus RS, Gruen RJ, DeLongis A. Appraisal, coping, health status, and psychological symptoms. Journal of Personality and Social Psychology. 1986;50(3):571. Kpeno A, Sahoo S, Sahu AK, Sahu PK. Problem-solving and coping skills training for youth with deliberate self-harm behaviors: A scoping review. Journal of Indian Association for Child and Adolescent Mental Health. 2024:09731342241278964. Liang J, Kõlves K, Lew B, De Leo D, Yuan L, Abu Talib M, Jia C-x. Coping strategies and suicidality: A cross-sectional study from China. Frontiers in Psychiatry. 2020;11:129. Xu J, Yang X. The influence of resilience on stress reaction of college students during COVID-19: the mediating role of coping style and positive adaptive response. Current Psychology. 2024;43(13):12120–12131. Xie Z, Bi K, Feng N, Ji X, Liu Y, Lam H, Yu H, Cui L. Prospective associations between heterogeneous sleep profiles and depressive symptoms in adolescents: The mediating role of coping styles. Journal of Adolescence. 2025;97(2):499–513. Wang Y, Fu T, Wang J, Chen S, Sun G. The relationship between self-compassion, coping style, sleep quality, and depression among college students. Frontiers in Psychology. 2024;15:1378181. Leonard NR, Gwadz MV, Ritchie A, Linick JL, Cleland CM, Elliott L, Grethel M. A multi-method exploratory study of stress, coping, and substance use among high school youth in private schools. Frontiers in Psychology. 2015;6:140070. Yang C, Li F, Khalid NF. Disordered eating in young Chinese adults: role of parenting styles, attachment anxiety, and negative coping styles. BMC Public Health. 2025;25(1):1–18. Yang Y, Guo Y, Wang W, Cai B, Ning H, Gong H. Harsh parenting and smartphone addiction: the mediating role of core self-evaluation and the moderating role of nature connectedness. Computers in Human Behavior. 2024;152:108049. Janssen T, van Atteveldt N. Coping styles mediate the relation between mindset and academic resilience in adolescents during the COVID-19 pandemic: a randomized controlled trial. Scientific Reports. 2023;13(1):6060. Obbarius N, Fischer F, Liegl G, Obbarius A, Rose M. A modified version of the transactional stress concept according to Lazarus and Folkman was confirmed in a psychosomatic inpatient sample. Frontiers in Psychology. 2021;12:584333. He Y-Z, Yuan X-Q, Ye W-Y, Yang S-Y, Ng KX, Dou K. Longitudinal links between time perspective and problematic internet use among Chinese adolescents: testing a dual-path model of coping style. Current Psychology. 2024;43(28):23517–23525. Yu H. The relationship between family functioning and academic burnout of college students: The mediating role of core self-evaluation and coping style. Scalable Computing: Practice and Experience. 2024;25(4):2336–2344. Huang Y, Zhou N, Liang S. Analyzing the effect of perceived discrimination on aggressive behavior in college students with disability using the chain mediation model. Scientific Reports. 2025;15(1):25645. Dweck CS. Carol Dweck revisits the growth mindset. Education Week. 2015;35(5):20–24. Furnham A. Increasing your intelligence: Entity and incremental beliefs about the multiple “intelligences”. Learning and Individual Differences. 2014;32:163–167. Feng S, Liu R, Tomar A, Ma P. Sex differences in the associations of mental health, suicidality, screentime, and sleep: A mediation effect analysis of sleep using Youth Risk Behavioral Surveillance Survey 2021. Psychological Reports. 2024:00332941241277096. Purba AK, Thomson RM, Henery PM, Pearce A, Henderson M, Katikireddi SV. Social media use and health risk behaviours in young people: systematic review and meta-analysis. BMJ. 2023;383:e073552. Little RJ, Rubin DB. Statistical analysis with missing data. Hoboken (NJ): John Wiley & Sons; 2019. Ji C. Comprehensive report on health-related/risky behaviors of adolescents in China, 2005. Beijing: People’s Medical Publishing House; 2007. Yang M, Guo K, Liu W, Fang X, Liu T. Coping tendency as a mediator in the relationship between psychological resilience and health problems among college students. Psychology Research and Behavior Management. 2024:2619–2630. Yu J, Liu Y, Liao L, Yan J, Wang H. Cluster analysis of sleep time and adolescent health risk behaviors. INQUIRY: The Journal of Health Care Organization, Provision, and Financing. 2023;60:00469580231153272. Buysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Research. 1989;28(2):193–213. Schleider JL, Weisz JR. Implicit theories relate to youth psychopathology, but how? A longitudinal test of two predictive models. Child Psychiatry & Human Development. 2016;47:603–617. Jiang X, Paley N, Shi D. Examining the validity and measurement invariance across gender and race of the Implicit Thoughts, Emotion, and Behavior Questionnaire. School Psychology. 2022;37(4):330. Du J, Zhang X, Zhao Y. Reliability, validation and construct confirmatory of core self-evaluations scale. Psychological Research. 2012;5(3):54–60. Xie Y. Reliability and validity of the simplified coping style questionnaire. Chinese Journal of Clinical Psychology. 1998;6(2):114–115. Ting W-H, Huang C-Y, Tu Y-K, Chien K-L. Association between weight status and depressive symptoms in adolescents: role of weight perception, weight concern, and dietary restraint. European Journal of Pediatrics. 2012;171(8):1247–1255. Xu T, Zuo F, Zheng K. Parental educational expectations, academic pressure, and adolescent mental health: An empirical study based on CEPS survey data. International Journal of Mental Health Promotion. 2024;26(2):93. OECD. PISA 2022 Results (Volume I): The state of learning and equity in education. Paris: OECD Publishing; 2023. Voyer D, Voyer SD. Gender differences in scholastic achievement: a meta-analysis. Psychological Bulletin. 2014;140(4):1174. Bedard K, Dhuey E. The persistence of early childhood maturity: International evidence of long-run age effects. The Quarterly Journal of Economics. 2006;121(4):1437–1472. Bliese PD. Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In: Klein K, Kozlowski S, editors. Multilevel theory, research, and methods in organizations: foundations, extensions, and new directions. San Francisco: Jossey-Bass; 2000. p. 349–381. Hair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. Multivariate data analysis, 7th ed. Upper Saddle River, NJ: Pearson; 2010. Tabachnick BG, Fidell LS. Using multivariate statistics, 6th ed. Boston, Ma: Pearson; 2013. Sun Z, Zhang X, Yuan W, Dong Y, Xu K, Zhao S, Chen L, Liu Z. Association of health risk behaviors with obesity and depressive symptoms in middle school students. Chinese Journal of School Health. 2024;45(10):1505–1510. Schleider JL, Weisz JR. Mental health and implicit theories of thoughts, feelings, and behavior in early adolescents: Are girls at greater risk? Journal of Social and Clinical Psychology. 2016;35(2):130–151. Yu T, Pan X, Li J, He L, Ying H, Deng J, Li L. Impacts of growth mindset on health: effects, mechanisms and interventions. Chin J Clin Psychol. 2022;30:871–875. John-Henderson NA, Tintzman CS, Counts CJ, Mueller CM. Health mindsets as a predictor of physical activity and body mass index in American Indian college students. Journal of Health Psychology. 2021;26(12):2098–2105. Yeager DS, Bryan CJ, Gross JJ, Murray JS, Krettek Cobb D, HF Santos P, Gravelding H, Johnson M, Jamieson JP. A synergistic mindsets intervention protects adolescents from stress. Nature. 2022;607(7919):512–520. Burnette JL, O'boyle EH, VanEpps EM, Pollack JM, Finkel EJ. Mind-sets matter: a meta-analytic review of implicit theories and self-regulation. Psychological Bulletin. 2013;139(3):655. Qi W, Shi J, Cui L. A developmental system perspective to interpret the link between parental fixed mindset and youth mental health: A moderated mediation model. International Journal of Environmental Research and Public Health. 2022;19(20):13285. Descartes CH, Ramesar M, Mills J. Global or domain specific self-esteem: Can it predict aggression among children and adolescents? Journal of Aggression, Maltreatment & Trauma. 2019;28(3):350–368. Sun P, Sun Y, Fang D, Jiang H, Pan M. Cumulative ecological risk and problem behaviors among adolescents in secondary vocational schools: the mediating roles of Core self-evaluation and basic psychological need satisfaction. Frontiers in Public Health. 2021;9:591614. Valois RF, Zullig KJ, Revels AA. Aggressive and violent behavior and emotional self‐efficacy: Is there a relationship for adolescents? Journal of School Health. 2017;87(4):269–277. Li Y, Shen X, Wang J. Association between negative life events and suicidal behavior in adolescents: roles of core self-evaluation, depression and gender. Social Psychiatry and Psychiatric Epidemiology. 2024;60:673–684. Wang Q, Tu R, Hu W, Luo X, Zhao F. Childhood psychological maltreatment and depression among Chinese adolescents: multiple mediating roles of perceived ostracism and core self-evaluation. International Journal of Environmental Research and Public Health. 2021;18(21):11283. Zhu L, Zhang Y, Wang H. Effects of core self-evaluation on tobacco and alcohol use among left-behind children: mediating role of fear of missing out and moderating role of parental migration category and gender. BMC Psychology. 2025;13(1):262. Griggs S, Crawford SL. Hope, core self-evaluations, emotional well-being, health-risk behaviors, and academic performance in university freshmen. Journal of Psychosocial Nursing and Mental Health Services. 2017;55(9):33–42. Martínez-Casanova E, Molero-Jurado M, Pérez-Fuentes M. Self-esteem and risk behaviours in adolescents: A systematic review. Behavioral Sciences. 2024;14(6):432. Dong W, Tang H, Wu S, Lu G, Shang Y, Chen C. The effect of social anxiety on teenagers’ internet addiction: the mediating role of loneliness and coping styles. BMC Psychiatry. 2024;24(1):395. Duan S, Duan Z, Li R, Wilson A, Wang Y, Jia Q, Yang Y, Xia M, Wang G, Jin T. Bullying victimization, bullying witnessing, bullying perpetration and suicide risk among adolescents: A serial mediation analysis. Journal of Affective Disorders. 2020;273:274–279. Villanueva-Blasco V, Villanueva-Silvestre V, Vázquez-Martínez A. Relationship between depression and risky alcohol consumption in women: the mediating role of coping styles and age. International Journal of Mental Health and Addiction. 2024;22(3):1376–1393. Garnefski N, Legerstee J, Kraaij V, van Den Kommer T, Teerds J. Cognitive coping strategies and symptoms of depression and anxiety: A comparison between adolescents and adults. Journal of Adolescence. 2002;25(6):603–611. Sun P, Sun Y, Jiang H, Jia R, Li Z. Gratitude and problem behaviors in adolescents: The mediating roles of positive and negative coping styles. Frontiers in Psychology. 2019;10:1547. Lazarus RS, Folkman S. Transactional theory and research on emotions and coping. European Journal of Personality. 1987;1(3):141–169. Zhang J, Li Y, Li J, Lyu M, Chen Y, Yang S, Tan C, Tao Y, Ye B, Zhang J. The effect of life events, resilience, self-esteem, and coping styles on aggressive behavior among left-behind adolescents: Structural equation modeling. Frontiers in Psychiatry. 2023;14:991608. Lin J, Su Y, Lv X, Liu Q, Wang G, Wei J, Zhu G, Chen Q, Tian H, Zhang K. Perceived stressfulness mediates the effects of subjective social support and negative coping style on suicide risk in Chinese patients with major depressive disorder. Journal of Affective Disorders. 2020;265:32–38. Wang X, Ding T, Lai X, Yang C, Luo J. Negative life events, negative coping style, and internet addiction in middle school students: A large two-year follow-up study. International Journal of Mental Health and Addiction. 2024;22(5):3233–3243. Li Y, Wang Z, You W, Liu X. Core self-evaluation, mental health and mobile phone dependence in Chinese high school students: why should we care. Italian Journal of Pediatrics. 2022;48(1):28. Shi J, Kim HK. Integrating risk perception attitude framework and the theory of planned behavior to predict mental health promotion behaviors among young adults. Health Communication. 2020;35(5):597–606. Kammeyer-Mueller JD, Judge TA, Scott BA. The role of core self-evaluations in the coping process. Journal of Applied Psychology. 2009;94(1):177. Wang X, Shi L, Ding Y, Liu B, Chen H, Zhou W, Yu R, Zhang P, Huang X, Yang Y. School bullying, bystander behavior, and mental health among adolescents: The mediating roles of self-efficacy and coping styles. Healthcare. 2024;12(17):1738. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterials.docx Cite Share Download PDF Status: Published Journal Publication published 28 Feb, 2026 Read the published version in BMC Psychology → Version 1 posted Editorial decision: Revision requested 16 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviews received at journal 26 Dec, 2025 Reviewers agreed at journal 26 Dec, 2025 Reviewers agreed at journal 18 Dec, 2025 Reviewers invited by journal 18 Dec, 2025 Editor assigned by journal 17 Dec, 2025 Editor invited by journal 09 Dec, 2025 Submission checks completed at journal 06 Dec, 2025 First submitted to journal 01 Dec, 2025 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-8204472","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":563037741,"identity":"362b122d-0bfc-4af0-b74f-2394bd1a4dc8","order_by":0,"name":"Xiaomeng Xu","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Xiaomeng","middleName":"","lastName":"Xu","suffix":""},{"id":563037742,"identity":"999aa2de-a579-4733-9889-5edab3e0492d","order_by":1,"name":"Yun Ding","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Ding","suffix":""},{"id":563037743,"identity":"facfb244-0b62-4b78-9cf6-c51e5a7e9124","order_by":2,"name":"Yaohua Zhang","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Yaohua","middleName":"","lastName":"Zhang","suffix":""},{"id":563037744,"identity":"1ed72411-7ea5-48e3-8690-f8045c28054a","order_by":3,"name":"Min Xu","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Xu","suffix":""},{"id":563037745,"identity":"eb608ef8-cea2-4dcf-9cf0-f7d7f7276b6b","order_by":4,"name":"Yunyun Huang","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Yunyun","middleName":"","lastName":"Huang","suffix":""},{"id":563037746,"identity":"eb281976-9941-4b24-8e32-5fe82971a109","order_by":5,"name":"Song Chang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYLACxgYgwd7cIAFjE6mF5yDJWiQSidQi3957+MXPHXZ58pEPG2/zMNjIbjjA/OwBPi0GZ86lWfaeSS42vJ3YbM3DkGa84QCbuQFeLRI5ZsaMbcyJG2cntknzMBxO3HCAh00Cr8NmgLXUJ26ceRCk5T9hLQw3cowfM7YdTpwvwQjScoCwFoMzZ8wYe9uOJ27gSWy2nGOQbDzzMJsZfoe19xh/+NlWnTi//fDBG28q7GT7jjc/w+8wBgaIMwwOgEkgZiagHqTkA9i6BsIqR8EoGAWjYIQCAJDHTBtpRqJqAAAAAElFTkSuQmCC","orcid":"","institution":"Ludong University","correspondingAuthor":true,"prefix":"","firstName":"Song","middleName":"","lastName":"Chang","suffix":""},{"id":563037747,"identity":"d837986d-98e1-4cce-8776-0dacb1a7279e","order_by":6,"name":"Sufei Xin","email":"","orcid":"","institution":"Ludong University","correspondingAuthor":false,"prefix":"","firstName":"Sufei","middleName":"","lastName":"Xin","suffix":""}],"badges":[],"createdAt":"2025-11-25 14:38:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8204472/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8204472/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40359-026-04211-3","type":"published","date":"2026-02-28T15:59:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":99306852,"identity":"24e24871-4438-4594-b680-bfd88895417f","added_by":"auto","created_at":"2025-12-31 16:01:44","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":214175,"visible":true,"origin":"","legend":"","description":"","filename":"TheimpactofgrowthmindsetonadolescentshealthriskbehaviorsthechainmediatingrolesofcoreselfevaluationandcopingstylesRevised.docx","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/5049ee884afb1a95c84e6d47.docx"},{"id":98803503,"identity":"ca525e6e-b6e4-43d1-942f-bf1bcd07d03c","added_by":"auto","created_at":"2025-12-22 14:20:32","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":9017,"visible":true,"origin":"","legend":"","description":"","filename":"fbffd3c0ed5c409b8e833087b20eefe2.json","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/2c0fa083e96852702ec8b964.json"},{"id":99306916,"identity":"54894488-56cc-45d4-ac6f-754e6c76b186","added_by":"auto","created_at":"2025-12-31 16:04:07","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":37135,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/7f24b5e536e3bda71cf6295e.docx"},{"id":98803237,"identity":"76b89ee7-6dee-42b5-92a9-e23ae08619e6","added_by":"auto","created_at":"2025-12-22 14:20:14","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":210555,"visible":true,"origin":"","legend":"","description":"","filename":"fbffd3c0ed5c409b8e833087b20eefe21enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/a4fa6a074e55e8be845af5cf.xml"},{"id":98803451,"identity":"0f5a05a3-5c89-4fb4-9d9f-83d4396003ef","added_by":"auto","created_at":"2025-12-22 14:20:28","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":176485,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/7d2f1a6037f14f13c3e1cb82.jpeg"},{"id":98803058,"identity":"2434f7ee-f99b-45c5-adb0-6a858bb88b49","added_by":"auto","created_at":"2025-12-22 14:20:03","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":43766,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/a6db7f39a8aa6dd98a5452e9.png"},{"id":98803680,"identity":"ff5894d9-325e-44c1-8467-9ad9c1f1c970","added_by":"auto","created_at":"2025-12-22 14:20:52","extension":"xml","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":206317,"visible":true,"origin":"","legend":"","description":"","filename":"fbffd3c0ed5c409b8e833087b20eefe21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/bac876193f18171ad361ab9f.xml"},{"id":98803234,"identity":"2ffff898-bf81-40a3-8b74-8c196f133a87","added_by":"auto","created_at":"2025-12-22 14:20:14","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":224568,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/fd5864cf1b55276ae6c5efe4.html"},{"id":98803266,"identity":"a465e30e-3b0f-457c-be60-0eb9648a2b73","added_by":"auto","created_at":"2025-12-22 14:20:16","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":176485,"visible":true,"origin":"","legend":"\u003cp\u003eSequential mediation effects of core self-evaluation and coping styles. \u003cem\u003eNote. \u003c/em\u003eStandardized path coefficients are shown. Solid lines indicate significant paths; dashed lines indicate non-significant paths. GM = growth mindset, CSE = core self-evaluation, CP-p = positive coping, CP-n = negative coping, HRBs = health risk behaviors, SB = school bullying, UEB = unhealthy eating behavior, ESU = excessive screen use, SP = sleep problems, IV = interpersonal violence. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.01, \u003csup\u003e***\u003c/sup\u003e\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/9973a882a753f86d7ef0ebef.jpeg"},{"id":103765831,"identity":"d210a61b-2122-4bc9-bd89-052deccca3fd","added_by":"auto","created_at":"2026-03-02 16:09:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1126857,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/3b66709a-4e88-466e-a472-d92566774e16.pdf"},{"id":98803356,"identity":"f2472f5c-0bd9-44ce-8216-46cbfcc0997b","added_by":"auto","created_at":"2025-12-22 14:20:20","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":37135,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-8204472/v1/97f2afc987741c146a69f54d.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of growth mindset on adolescents’ health risk behaviors: the chain mediating roles of core self-evaluation and coping styles","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAdolescents\u0026rsquo; health risk behaviors (HRBs), including unhealthy eating, physical inactivity, sleep problems, substance use, and injury-related behaviors [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], threaten adolescents\u0026rsquo; physical and mental health and can undermine healthy development and overall well‑being [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. HRBs are prevalent in adolescence and often cluster, amplifying the risks of chronic disease and premature mortality [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. They therefore constitute a pressing global public health concern [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. To effectively lessen the negative impact of HRBs on adolescents\u0026rsquo; health, it is of great importance to explore the factors influencing these behaviors and the mechanisms underlying them.\u003c/p\u003e \u003cp\u003eA number of theoretical frameworks have been proposed to explain the development of adolescents\u0026rsquo; HRBs. Problem Behavior Theory (PBT) posits that adolescents\u0026rsquo; involvement in risky behaviors reflects a dynamic interaction between risk and protective factors across individual and environmental domains [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. When stressors are salient and protective resources are limited, adolescents are more likely to engage in risky or maladaptive behaviors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Complementing PBT, Lazarus and Folkman\u0026rsquo;s transactional model of stress and coping (TMSC) posits that behavioral choices under stress are shaped by cognitive appraisals and subsequent coping processes [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Taken together, these perspectives suggest that adaptive cognitive and coping resources serve as protective factors that reduce the occurrence of HRBs.\u003c/p\u003e \u003cp\u003eOne such cognitive resource is growth mindset, defined as the belief that personal traits and abilities are malleable rather than fixed [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], which is widely recognized as a protective factor that facilitates adaptive responses to challenges and failures [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Adolescents who hold a growth mindset are more likely to interpret setbacks as opportunities for learning, develop positive self-evaluations, and employ constructive coping strategies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Beyond academic and emotional domains [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], accumulating evidence links growth mindset to health-related outcomes, including better sleep [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], lower substance use [\u003cspan additionalcitationids=\"CR25 CR26\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], reduced self-harm and suicidal ideation [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and healthier lifestyles [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. These findings indicate that a growth mindset has a beneficial effect on adolescents\u0026rsquo; HRBs. However, the mechanisms through which a growth mindset influences HRBs remain unclear.\u003c/p\u003e \u003cp\u003eGrounded in the TMSC, stress arises from dynamic person-environment transactions in which individuals first conduct a primary appraisal (harm/threat vs. challenge) and then a secondary appraisal (resources and perceived controllability), guiding the use of problem- versus emotion-focused coping [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Drawing on this model, we propose that the association between growth mindset and adolescents\u0026rsquo; HRBs operates through two psychological mechanisms, CSE and coping style. A growth mindset biases appraisals toward challenge and higher perceived controllability, strengthens CSE, and promotes more problem-focused and active coping, which together are expected to relate to fewer HRBs.\u003c/p\u003e \u003cp\u003eCSE reflects an individual\u0026rsquo;s fundamental evaluation of self-worth and competence, encompassing self-esteem, generalized self-efficacy, locus of control, and emotional stability [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Consistent with CSE theory, when individuals confront stress and challenge, their CSEs shape emotional responses and behavioral patterns [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], positioning CSE as a proximal cognitive resource that guides stressor appraisals (e.g., challenge vs. threat) and the selection of coping strategies. Empirical research has highlighted the protective role of CSE in preventing adolescents\u0026rsquo; engagement in HRBs and promoting adaptive functioning. High levels of CSE have been associated with lower depression, anxiety, and risk-taking, as well as higher life satisfaction and psychological resilience [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Conversely, low CSE has been linked to problematic smartphone use, self-injury, and victimization [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In adolescent samples, higher CSE also reframes cognitive appraisals under stress, buffers the adverse impact of stressors, and predicts lower engagement in HRBs [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Furthermore, growth mindset has been linked to higher CSE, as individuals who believe in self-improvement are more likely to develop a coherent and positive self-concept [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, we hypothesize that CSE mediates the relationship between growth mindset and adolescents\u0026rsquo; HRBs.\u003c/p\u003e \u003cp\u003eCoping styles refer to the cognitive and behavioral efforts individuals use to manage internal and external demands [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Positive coping styles, such as problem solving and seeking social support, are associated with better emotion regulation, enhanced well-being, and fewer maladaptive outcomes [\u003cspan additionalcitationids=\"CR46 CR47 CR48\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. By contrast, negative coping styles, including avoidance and denial, have been linked to heightened stress reactivity and higher involvement in HRBs, such as substance use [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], unhealthy eating [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and problematic internet use [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In turn, coping styles are closely tied to individuals\u0026rsquo; mindsets. A growth mindset may encourage adolescents to adopt more adaptive coping by strengthening perceived control, challenge appraisals, and psychological flexibility [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Such malleability beliefs may translate into proactive, problem-focused coping styles (positive coping) while constraining avoidant and emotion-focused coping styles (negative coping), thereby interrupting the pathway from stress to HRBs, including substance use, self-injury, and problematic internet use [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Accordingly, coping style is posited to serve as a proximal pathway linking growth mindset to lower involvement in HRBs.\u003c/p\u003e \u003cp\u003eExisting research evidence suggests a serial pathway from cognition to behavior. Individuals with higher CSE are more likely to appraise stressors as manageable and to adopt positive coping approaches [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], and adaptive coping is associated with lower subsequent involvement in HRBs [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Related work has also documented a serial link of CSE and coping in other outcomes, including academic burnout [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and aggression among college students with disabilities [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Conceptually, a growth mindset is a malleability belief that can foster higher CSE [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], which in turn promotes adaptive coping. Based on this perspective, we propose a serial mediation model in which growth mindset is related to lower HRBs through CSE and coping.\u003c/p\u003e \u003cp\u003eMost previous studies have adopted cross-sectional designs, which limit causal inference. Against this backdrop, we conducted a three-wave longitudinal study to examine the prospective association between growth mindset and adolescents\u0026rsquo; HRBs and to test CSE and coping styles as explanatory mechanisms. Given that adolescents\u0026rsquo; HRBs often co-occur and cluster, with cumulative risk amplifying adverse outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], a multi-domain perspective is warranted to test mechanisms across categories. Accordingly, we assessed multiple domains of HRBs in this study.\u003c/p\u003e \u003cp\u003eSpecifically, we formulated four hypotheses:\u003c/p\u003e \u003cp\u003e(1) A higher growth mindset at T1 would predict lower HRBs at T3.\u003c/p\u003e \u003cp\u003e(2) CSE assessed at T2 would mediate this association.\u003c/p\u003e \u003cp\u003e(3) Coping styles assessed at T2 would also mediate this association, with a higher growth mindset at T1 predicting greater positive coping and less negative coping at T2, and positive coping at T2 predicting lower HRBs at T3, whereas negative coping at T2 predicting higher HRBs at T3.\u003c/p\u003e \u003cp\u003e(4) CSE and coping would operate sequentially such that a higher growth mindset at T1 would be associated with higher CSE at T2, which in turn would foster more positive and less negative coping styles at T2, ultimately relating to lower HRBs at T3.\u003c/p\u003e \u003cp\u003eBy testing this longitudinal serial mediation model, this study extends growth mindset theory to the domain of health behaviors and delineates cognitive pathways ordered in time that may underlie adolescents\u0026rsquo; behavioral development.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 842 eighth-grade students from a middle school in an eastern province of China were recruited through cluster sampling. Data were collected at three waves separated by three months: T1 in late December 2024, T2 in late March 2025, and T3 in late June 2025. After excluding invalid responses\u0026nbsp;(missing identifiers, more than 30% missing data, or all items omitted for any variable), 701 valid participants remained at T1 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e = 12.39, \u003cem\u003eSD\u003c/em\u003e = 0.56, 52.2% male), 706 at T2 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e = 12.90, \u003cem\u003eSD\u003c/em\u003e = 0.57, 50.7% male), and 721 at T3 (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e = 13.05, \u003cem\u003eSD\u003c/em\u003e = 0.51, 51.9% male).\u0026nbsp;At T2 and T3, changes in class organization resulted in the inclusion of additional students who had not participated in earlier waves, thereby yielding slightly larger sample sizes at these assessment points.\u003c/p\u003e\n\u003cp\u003eOf the 701 participants with valid data at T1, 534 were retained across all three waves (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e = 12.40, \u003cem\u003eSD\u003c/em\u003e = 0.55, 50.2% male).\u0026nbsp;To assess the\u0026nbsp;potential attrition bias, participants who dropped out after T1 (attrition group, \u003cem\u003en\u003c/em\u003e = 167) were compared with those who completed all waves (retained group, \u003cem\u003en\u003c/em\u003e = 534). Results indicated no statistically significant differences between the groups on key demographic variables, including age (\u003cem\u003et\u003c/em\u003e(699) = -0.20, \u003cem\u003ep\u003c/em\u003e = 0.840, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = -0.02), gender distribution (\u0026chi;\u0026sup2; = 3.68, \u003cem\u003ep\u003c/em\u003e = 0.055),\u0026nbsp;father\u0026rsquo;s education level (\u003cem\u003et\u003c/em\u003e(693) = -0.76, \u003cem\u003ep\u003c/em\u003e = 0.449, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = -0.07),\u0026nbsp;and mother\u0026rsquo;s education level (\u003cem\u003et\u003c/em\u003e(693) = 0.09, \u003cem\u003ep\u003c/em\u003e = 0.926, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.00). Regarding the core variables, the attrition group reported significantly higher levels of negative coping (\u003cem\u003et\u003c/em\u003e(699)\u003cem\u003e\u0026nbsp;\u003c/em\u003e= 2.19, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.029, Cohen\u0026rsquo;s \u003cem\u003ed\u0026nbsp;\u003c/em\u003e= 0.19) and excessive screen use (\u003cem\u003et\u003c/em\u003e(699)\u003cem\u003e\u0026nbsp;\u003c/em\u003e= 2.22, \u003cem\u003ep\u0026nbsp;\u003c/em\u003e= 0.027, Cohen\u0026rsquo;s \u003cem\u003ed\u0026nbsp;\u003c/em\u003e= 0.20). However, the effect sizes were small (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e \u0026lt; 0.20), suggesting that attrition had a limited impact on the validity of the study\u0026rsquo;s main findings [62].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Ethics Committee of Ludong University. Informed consent was obtained from students and their parents prior to data collection. Data were gathered in class across three waves approximately three months apart: at T1, students completed the growth mindset measure; at T2, they completed measures of CSE and coping style; and at T3, they completed measures of HRBs. All questionnaires were administered during regular class sessions. Participants were reminded of confidentiality and their right to withdraw at any time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eHealth risk behaviors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHRBs were assessed using the China Adolescent Health-Related Behavior Questionnaire (Middle School Version), a standardized Chinese adaptation of the Youth Risk Behavior Survey (YRBS) that measures seven dimensions of health-related and risk behaviors among adolescents [51, 63]. Based on the questionnaire manual and the characteristics of the target population, this study focused on five dimensions: sedentary behavior, unhealthy eating behavior, excessive screen use, sleep problems, and interpersonal violence. Previous studies using the China Adolescent Health-Related Behavior Questionnaire have similarly selected subsets of items or specific subscales to assess particular health-related behaviors (e.g., dietary behaviors, physical activity, and school violence), and have reported acceptable reliability and validity for these item sets [64, 65]. In the present study, items assessing sedentary behavior, unhealthy eating behavior, excessive screen use, and interpersonal violence were drawn directly from the China Adolescent Health-Related Behavior Questionnaire (Middle School Version), whereas the three items assessing sleep problems were selected from the Pittsburgh Sleep Quality Index (PSQI) [66]. Details are presented below.\u003c/p\u003e\n\u003cp\u003e(1) \u003cem\u003eSedentary behavior\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis dimension was measured with two items (\u0026ldquo;On a typical day, how much time do you usually spend sitting or lying down in low- or high-cognitive-effort activities?\u0026rdquo;). Response options ranged from 1 to 9, representing durations from less than 5 minutes to more than 12 hours per day. Higher scores indicated longer sedentary time. The mean of the two items was calculated to generate the sedentary behavior score.\u003c/p\u003e\n\u003cp\u003e(2) \u003cem\u003eUnhealthy eating behavior\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree items assessed the frequency of drinking sugary beverages, eating desserts, and consuming fast food. A sample item was: \u0026ldquo;During the past 30 days, how many times per day did you usually drink soft drinks such as Coca-Cola, Pepsi, or Sprite?\u0026rdquo; The three items were rated on 7-point, 5-point, and 8-point scales, respectively, with higher scores reflecting more frequent unhealthy eating. Because the response scales differed, all items were standardized into z-scores and then averaged to yield the composite score for this dimension.\u003c/p\u003e\n\u003cp\u003e(3) \u003cem\u003eExcessive screen use\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis construct was measured with three items. A sample item was: \u0026ldquo;During the past seven days, how much time did you usually spend watching TV or videos?\u0026rdquo; Responses ranged from 1 (\u0026ldquo;never\u0026rdquo;) to 6 (\u0026ldquo;more than 4 hours\u0026rdquo;), with higher scores indicating longer durations of screen use. The mean of the three items represented the score for this dimension.\u003c/p\u003e\n\u003cp\u003e(4) \u003cem\u003eSleep problems\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThree items adapted from the Pittsburgh Sleep Quality Index (PSQI) were used to assess sleep problems. A sample item was: \u0026ldquo;During the past month, how often have you been bothered by taking more than 30 minutes to fall asleep?\u0026rdquo; Each item was rated on a 4-point scale (1 = never, 2 = less than once per week, 3 = 1-2 times per week, 4 = at least three times per week), with higher scores indicating more frequent sleep problems. The mean of the three items was calculated to indicate the severity of sleep problems.\u003c/p\u003e\n\u003cp\u003e(5) \u003cem\u003eInterpersonal violence\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis dimension covered experiences of being bullied (e.g., mocked, extorted, socially excluded, physically assaulted or confined, or subjected to sexual jokes) and engagement in physical fights. Bullying was measured using six 3-point items and fighting using one 8-point item. Higher scores indicated greater frequencies of violence-related behaviors. Because these items used different response scales, all were standardized as z-scores and then averaged to form the composite score for interpersonal violence.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGiven the inconsistency in response formats across dimensions, all dimension scores were transformed into z-scores before conducting correlation and mediation analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGrowth mindset\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdolescents\u0026rsquo; growth mindset was assessed using the Implicit Theories of Thoughts\u0026ndash;Emotion\u0026ndash;Behavior Questionnaire (ITEB-Q) [67]. This instrument conceptualizes implicit beliefs in the domains of thoughts, emotions, and behaviors and has demonstrated strong internal consistency as well as concurrent validity with measures of life satisfaction, psychological resilience, emotion regulation, and emotional problems [16, 67]. Its cross-group stability has also been supported [68]. Twelve items were rated on a 6-point Likert scale (1 = \u0026ldquo;strongly disagree,\u0026rdquo; 6 = \u0026ldquo;strongly agree\u0026rdquo;).\u0026nbsp;Scores were averaged, with higher values indicating a stronger growth mindset. At Time 1, the scale showed excellent internal consistency, with a Cronbach\u0026rsquo;s \u0026alpha; of 0.96.\u0026nbsp;Confirmatory factor analysis (CFA) indicated good model fit (\u0026chi;\u0026sup2;/\u003cem\u003edf\u0026nbsp;\u003c/em\u003e= 3.29, CFI = 0.98, TLI = 0.98, RMSEA = 0.07), with all factor loadings exceeded 0.60, supporting the strong construct validity of the measure in the present study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCore Self-Evaluation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdolescents\u0026rsquo; core self-evaluation was measured using the Chinese version of the Core Self-Evaluation Scale (CSES), a 10-item localized adaptation of Judge\u0026rsquo;s original instrument by Du J, Zhang X and Zhao Y [69]. The scale comprises four dimensions: self-esteem, generalized self-efficacy, locus of control, and emotional stability. Items are rated on a 5-point Likert scale ranging from 1 (\u0026ldquo;strongly disagree\u0026rdquo;) to 5 (\u0026ldquo;strongly agree\u0026rdquo;). The questionnaire includes both positively and negatively worded items: items 1, 4, 6, and 9 are scored positively, whereas items 2, 3, 5, 7, 8, and 10 are reverse-scored. Higher total scores indicate higher levels of core self-evaluation. At Time 2, the scale demonstrated good internal consistency (Cronbach\u0026rsquo;s \u0026alpha; = 0.88).\u0026nbsp;CFA indicated an acceptable model fit (\u0026chi;\u0026sup2;/\u003cem\u003edf\u003c/em\u003e = 2.39, CFI = 0.98, TLI = 0.97, RMSEA = 0.05), with all factor loadings exceeding 0.60, supporting the construct validity of the scale in the present study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCoping Style\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCoping styles were assessed using the Simplified Coping Style Questionnaire (SCSQ) [70], which evaluates the relationship between coping styles and mental health. The scale contains 20 items grouped into two dimensions: positive coping (items 1-12) and negative coping (items 13-20). Responses are rated on a 4-point Likert scale ranging from 0 (\u0026ldquo;never\u0026rdquo;) to 3 (\u0026ldquo;frequently\u0026rdquo;). In the present study, the scale demonstrated good internal consistency at T2, with Cronbach\u0026rsquo;s \u0026alpha; was 0.89 for the total scale, 0.91 for the positive coping subscale, and 0.83 for the negative coping subscale. The CFA initially indicated suboptimal model fit (\u0026chi;\u0026sup2;/\u003cem\u003edf\u0026nbsp;\u003c/em\u003e= 4.45, CFI = 0.88, TLI = 0.87, RMSEA = 0.08). Modification indices indicated that item 20 (\u0026ldquo;self-reassurance\u0026rdquo;) showed a substantial potential cross-loading on the other coping factor (MI = 20.69), suggesting that its content overlapped across dimensions. Given its conceptual ambiguity and the goal of achieving a more homogeneous factor structure, item 20 was removed, which led to improved overall model fit. After its deletion, the model exhibited an improved fit (\u0026chi;\u0026sup2;/\u003cem\u003edf\u003c/em\u003e = 3.39, CFI = 0.93, TLI = 0.92, RMSEA = 0.07). Standardized factor loadings for all remaining items ranged from 0.47 to 0.82, demonstrating satisfactory construct validity for the revised model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were performed using SPSS 26.0 and Mplus 8.3. In SPSS, Harman\u0026rsquo;s single-factor test was first conducted to assess potential common method bias. Descriptive statistics and correlation analyses were also performed. Given that the continuous variables exhibited non-normal distributions, Spearman\u0026rsquo;s rank-order correlations were used. Mplus 8.3 was employed to perform CFA and test the sequential mediation model. Model parameters were estimated using the robust maximum likelihood estimator (MLR), and missing data were handled with full information maximum likelihood (FIML). Model fit was assessed using standard indices (\u0026chi;\u0026sup2;/\u003cem\u003edf\u003c/em\u003e, CFI, TLI, RMSEA), and mediation effects were tested via bootstrapping with 5,000 resamples to obtain 95% bias-corrected confidence intervals. All continuous variables were standardized before analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn accordance with cumulative evidence from meta-analyses and international assessments, gender, age, and parental education were included as covariates [71-75]. Because participants were nested within classes, we computed intraclass correlation coefficients (ICCs) using class as the grouping factor to evaluate potential design effects. ICCs for all variables ranged from 0.00 to 0.03, well below the conventional 0.05 threshold [76], indicating minimal class-level variance and supporting the use of single-level analyses.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eCommon method bias test\u003c/h2\u003e \u003cp\u003eWe assessed common method bias using Harman\u0026rsquo;s single-factor test. Twelve factors exhibited eigenvalues greater than 1, and the first factor explained 23.29% of the total variance, which is below the conventional 40% criterion. These results suggest that common method bias is not a substantial threat to the validity of our findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive and correlation analysis\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the descriptive statistics and the correlation matrix of the study variables. To ensure comparability in the descriptive statistics, scores within the unhealthy eating behavior and interpersonal violence dimensions were first standardized at the item level and then averaged, because items in these dimensions used different response formats. Consequently, the means and standard deviations for unhealthy eating behavior and interpersonal violence in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e are expressed as z-scores, while other variables are presented in their original metrics. For subsequent correlation and mediation analyses, all variables were standardized as z-scores prior to modeling. Correlation results showed that growth mindset at T1 was positively associated with CSE and positive coping at T2 but negatively associated with negative coping at T2 and all dimensions of HRBs at T3. CSE at T2 was positively correlated with positive coping and negatively correlated with negative coping and all HRBs dimensions at T3. Positive coping at T2 was negatively related to unhealthy eating, excessive screen use, sleep problems, and interpersonal violence at T3, but not significantly associated with sedentary behavior. In contrast, negative coping at T2 was positively correlated with all dimensions of HRBs at T3.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and correlation matrix for key variables (N\u0026thinsp;=\u0026thinsp;534)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.T1GM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.T2CSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.51\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.T2CP-p\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.T2CP-n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.18\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.T3HRBs-SB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.09\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.11\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.T3HRBs-UEB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.16\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.09\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.T3HRBs-ESU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.16\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.30\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.T3HRBs-SP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.28\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.34\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.T3HRBs-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.21\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.25\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.26\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.29\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u0026thinsp;\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eNotes. GM\u0026thinsp;=\u0026thinsp;growth mindset, CSE\u0026thinsp;=\u0026thinsp;core self-evaluation, CP‑p\u0026thinsp;=\u0026thinsp;positive coping, CP‑n\u0026thinsp;=\u0026thinsp;negative coping, HRBs\u0026thinsp;=\u0026thinsp;health risk behaviors, SB\u0026thinsp;=\u0026thinsp;sedentary behavior, UEB\u0026thinsp;=\u0026thinsp;unhealthy eating behavior, ESU\u0026thinsp;=\u0026thinsp;excessive screen use, SP\u0026thinsp;=\u0026thinsp;sleep problems, IV\u0026thinsp;=\u0026thinsp;interpersonal violence. For the UEB and IV, item scores were standardized as z-scores and then averaged to compute the dimension scores. \u003csup\u003e*\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, \u003csup\u003e**\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, \u003csup\u003e***\u003c/sup\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLongitudinal Sequential Mediation Analysis\u003c/h2\u003e \u003cp\u003eMplus 8.3 was used to estimate a longitudinal serial mediation model in which T1 growth mindset predicted the latent outcome T3 HRBs via T2 CSE, T2 positive coping, and T2 negative coping. The latent construct of HRBs at T3 was indicated by five observed variables. All standardized factor loadings were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The loadings were as follows: sleep problems (0.82), interpersonal violence (0.74), excessive screen use (0.57), unhealthy eating (0.47), and sedentary behavior (0.30). Although the loadings varied in magnitude, each indicator reached or approximated the commonly cited minimum threshold of about 0.30 for standardized factor loadings [\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. We therefore retained all indicators to capture more comprehensively the breadth of adolescent HRBs. The model\u0026rsquo;s acceptable fit indices (χ\u0026sup2;/\u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.38, CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.96, RMSEA\u0026thinsp;=\u0026thinsp;0.03, SRMR\u0026thinsp;=\u0026thinsp;0.03) provide support for the overall validity of the measurement model.\u003c/p\u003e \u003cp\u003eThe standardized path coefficients of the structural model are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Controlling for gender, age, and parental education, T1 growth mindset predicted higher T2 CSE (β\u0026thinsp;=\u0026thinsp;0.504, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher positive coping (β\u0026thinsp;=\u0026thinsp;0.230, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but was unrelated to T3 HRBs (β = -0.096, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) and T2 negative coping (β = -0.049, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). T2 CSE predicted higher positive coping (β\u0026thinsp;=\u0026thinsp;0.385, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower negative coping (β = -0.113, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and lower T3 HRBs (β = -0.265, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In addition, T2 positive coping predicted lower T3 HRBs (β = -0.184, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas T2 negative coping predicted higher T3 HRBs (β\u0026thinsp;=\u0026thinsp;0.187, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of the mediation analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. T1 growth mindset exerted a significant negative total effect on T3 adolescents\u0026rsquo; HRBs (c = -0.327, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). When T2 CSE and T2 coping styles were entered as mediators, the direct effect of T1 growth mindset on T3 HRBs was no longer significant (c\u0026rsquo; = -0.096, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), whereas the total indirect effect remained significant, consistent with full mediation (β = -0.231, 95% CI [-0.299, -0.164]).\u003c/p\u003e \u003cp\u003eDecomposing the indirect effects further clarified the pathways. Growth mindset indirectly influenced later HRBs through higher CSE (β = -0.134, 95% CI [-0.200, -0.068]). It also reduced HRBs via increased positive coping (β = -0.042, 95% CI [-0.075, -0.009]), whereas the mediating effect of negative coping was nonsignificant (β = -0.009, 95% CI [-0.031, 0.013]). Furthermore, the chain mediation effects of CSE and coping styles received partial support. Specifically, the indirect path through positive coping (T1 GM \u0026rarr; T2 CSE \u0026rarr; T2 CP-p \u0026rarr; T3 HRBs) was significant (β = -0.036, 95% CI [-0.061, -0.010]), whereas the corresponding chain through CSE and negative coping (T1 GM \u0026rarr; T2 CSE \u0026rarr; T2 CP-n \u0026rarr; T3 HRBs) was not statistically significant (β = -0.011, 95% CI [-0.023, 0.001]). Overall, these findings support the hypothesized sequential mediation model, suggesting that a stronger growth mindset indirectly reduces adolescents\u0026rsquo; HRBs through enhanced CSE and adaptive coping styles.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBootstrap test of mediation effects\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEffect\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEffect sizes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.437, -0.218]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e100%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.210, 0.019]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTotal indirect\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.299, -0.164]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1GM\u0026rarr;T2CSE\u0026rarr;T3HRBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.200, -0.068]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e40.98%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1GM\u0026rarr;T2CP-p\u0026rarr;T3HRBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.042\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.075, -0.009]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.84%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT1GM\u0026rarr;T2CP-n\u0026rarr;T3HRBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.031, 0.013]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eT1GM\u0026rarr;T2CSE\u0026rarr;T2CP-p\u0026rarr;T3HRBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.061, -0.010]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eT1GM\u0026rarr;T2CSE\u0026rarr;T2CP-n\u0026rarr;T3HRBs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.023, 0.001]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNotes. GM\u0026thinsp;=\u0026thinsp;growth mindset, CSE\u0026thinsp;=\u0026thinsp;core self-evaluation, CP-p\u0026thinsp;=\u0026thinsp;positive coping, CP-n\u0026thinsp;=\u0026thinsp;negative coping, HRBs\u0026thinsp;=\u0026thinsp;health risk behaviors. All effects are standardized. Confidence intervals are bias-corrected 95% bootstrap CIs based on 5,000 resamples.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRobustness check\u003c/h2\u003e \u003cp\u003eHRBs can be scored using different methods. In addition to the standardized z-scores used in the main analyses, a common alternative is binary coding (0\u0026thinsp;=\u0026thinsp;no behavior reported, 1\u0026thinsp;=\u0026thinsp;behavior reported), as adopted in prior studies [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e]. To assess robustness, we reanalyzed the model using binary-coded HRBs. Results remained consistent in direction and significance (see Supplementary Materials).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDrawing on the TMSC and informed by PBT, this study examined whether the cognitive resource of a growth mindset is related to adolescents\u0026rsquo; HRBs over time through the intervening processes of CSE and coping styles, with the aim of providing actionable guidance for school settings. The primary objective was to extend evidence on the time-ordered association between growth mindset and HRBs and to clarify the mediating mechanisms. In the primary model, a stronger growth mindset predicted lower subsequent HRBs. After CSE and positive coping were included, the direct path from growth mindset to HRBs was no longer significant, consistent with substantial mediation. A robustness analysis using binary outcomes reproduced this pattern, although a small residual direct association emerged. In contrast, the mediating pathway through CSE and negative coping was not significant. The sections that follow position these findings in the prior literature and consider limitations as well as practical and policy implications for school-based health promotion.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eGrowth mindset and Health risk behaviors\u003c/h2\u003e \u003cp\u003eIn line with Hypothesis 1, T1 growth mindset was significantly associated with fewer HRBs at T3 after adjusting for demographic covariates. These results are consistent with the mindset framework and the TMSC. Malleability beliefs shape appraisal and self-regulation [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e], foster adaptive attributions and goal directed strategy use [\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e], and are associated with lower engagement in risk behaviors as adolescents view setbacks as surmountable challenges and invest effort in constructive strategies [\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e]. Within the TMSC framework, the association is plausibly driven by appraisal based mechanisms: a growth mindset increases perceived controllability, strengthens positive self-appraisals, and encourages problem focused, active coping while constraining maladaptive responses [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. Taken together, the evidence supports viewing growth mindset as a modifiable psychological resource associated with healthier behavioral choices during adolescence [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eCore self-evaluation as a mediator\u003c/h2\u003e \u003cp\u003eConsistent with Hypothesis 2, CSE served as a significant mediator between T1 growth mindset and T3 HRBs, accounting for roughly 41% of the total effect. This finding suggests that adolescents with a stronger growth mindset tend to develop more positive and coherent self-views over time, which in turn is associated with lower involvement in HRBs. Prior work shows that endorsing the malleability of abilities strengthens adaptive beliefs and self‑concepts [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], whereas holding a weaker growth mindset is associated with diminished self-appraisals and lower perceived competence [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrior evidence links higher CSE to fewer adolescent HRBs, indicating that youth with stronger self-views show less maladaptive behavior and greater resilience to psychosocial risks [\u003cspan additionalcitationids=\"CR87\" citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Recent longitudinal evidence further supports this protective role, indicating that higher CSE can buffer the adverse impact of stressful life events on maladaptive outcomes, such as suicidal behaviors, partly through reduced depressive symptoms [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. In contrast, adolescents with lower CSE tend to internalize negative self-perceptions and are more likely to adopt maladaptive behavioral patterns [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e]. However, the protective effect of CSE is not uniform across risk domains. For example, associations tend to be weaker or non-significant for behaviors like substance use and risky sexual activity [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Likewise, reviews suggest that links between certain core CSE facets (e.g., self-esteem) and HRBs depend on the specific domain and context [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. These mixed findings imply that factors such as gender and sociocultural context may moderate CSE\u0026rsquo;s influence. Recognizing these boundary conditions is important for a nuanced understanding of when and how CSE contributes to risk behavior outcomes.\u003c/p\u003e \u003cp\u003eTaken together, the evidence positions CSE as a proximal cognitive resource that helps transmit the influence of a growth mindset to reduced involvement in HRBs. In line with our serial framework, higher CSE is likely to precede and foster more adaptive appraisal and coping, although the strength of this pathway appears to vary across behavioral domains and contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eCoping styles as a mediator\u003c/h2\u003e \u003cp\u003ePartially supporting Hypothesis 3, coping styles mediated the relationship between growth mindset and later HRBs. The indirect effect through positive coping was significant, whereas the pathway through negative coping alone was not significant. In addition, both coping indices showed direct associations with HRBs, which underscores coping as a proximal mechanism connecting beliefs with behavior [\u003cspan additionalcitationids=\"CR95\" citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe absence of a significant association between growth mindset and negative coping diverges from some earlier findings. One plausible developmental explanation is that adolescents\u0026rsquo; still maturing executive functions limit their ability to translate abstract growth-oriented beliefs into the inhibition of avoidant or emotion-focused responses, especially under high emotional arousal [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e]. In contrast, positive coping typically involves planning, problem solving, and support seeking, which aligns more closely with the sense of agency emphasized by a growth mindset.\u003c/p\u003e \u003cp\u003eIndeed, in our data, greater use of positive coping was prospectively associated with fewer HRBs. Prior studies similarly show that positive coping enhances emotion regulation and is linked to lower levels of aggression, substance use, and other risk behaviors [\u003cspan additionalcitationids=\"CR99\" citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e]. Conversely, heavier reliance on negative coping has been associated with outcomes such as unhealthy eating [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], suicidal behavior [\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e], and problematic internet use [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, these patterns suggest that a growth mindset relates to lower HRBs primarily by fostering positive coping. This highlights the central role of coping in the TMSC framework and provides a rationale for examining the sequential mediation via CSE and positive coping in the next section. Finally, we note a domain-level difference: positive coping was not associated with sedentary behavior, suggesting heterogeneity across HRBs domains and indicating that sedentary behavior may depend more on habits or environmental constraints than on momentary coping strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eCore self-evaluation and coping styles as sequential mediators\u003c/h2\u003e \u003cp\u003eConsistent with Hypothesis 4, this study provides the first longitudinal evidence for a time-ordered pathway whereby growth mindset enhances CSE, which in turn promotes positive coping and is associated with lower involvement in HRBs. As a positive cognitive framework, growth mindset was associated with higher CSE, and higher CSE was linked with greater use of positive coping when facing stress [\u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e], and to a higher likelihood of adopting constructive strategies with fewer maladaptive behaviors [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e]. By contrast, low CSE may hinder positive coping and increase vulnerability to aggression and other risk behaviors [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This pattern aligns with TMSC and with evidence that CSE shapes appraisal and coping under stress, thereby influencing behavioral choices [\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e]. Prior studies support this mechanism. For example, self-efficacy, a key facet of CSE, together with coping has been found to jointly mediate the association between school bullying and adolescent mental health outcomes [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. The alignment between our longitudinal pathway and this literature corroborates theoretical coherence, reinforces construct validity for CSE and coping as mechanisms, and supports generalizability across samples and contexts.\u003c/p\u003e \u003cp\u003eIn our primary model, the direct path from growth mindset to HRBs was not significant after including the mediators, whereas a supplementary analysis with binary outcomes found a small direct effect. Indirect effects via CSE and positive coping accounted for around 71% of the total association, indicating that the majority of the linkage operates through enhanced self-evaluation and more positive coping. In the robustness analysis with binary HRB outcomes, the indirect effect via negative coping reached statistical significance; however, the effect size was small and the finding did not replicate in the primary continuous-outcome model, so this pathway should be interpreted with caution. Taken together, these results support a time-ordered pathway from cognition to appraisal to coping: growth mindset enhances CSE, CSE facilitates adaptive coping, and adaptive coping is associated with lower involvement in HRBs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eTheoretical and practical implications\u003c/h2\u003e \u003cp\u003eThis study offers several theoretical contributions. First, it extends the protective role of growth mindset beyond mental health to the broader domain of adolescents\u0026rsquo; HRBs. Second, by identifying CSE and coping styles as mediators, it provides empirical support for both PBT and TMSC, clarifying the cognitive pathways through which personal beliefs influence behavior. Third, evidence of a time-ordered pathway from growth mindset to CSE to coping advances our understanding of adolescent adaptation by specifying how cognitive appraisals are translated into behavioral choices.\u003c/p\u003e \u003cp\u003eThe findings also carry practical implications. School and clinical programs aimed at reducing HRBs can incorporate growth mindset training to strengthen students\u0026rsquo; beliefs in malleability and to build psychological resilience. Interventions that enhance CSE may further reduce youths\u0026rsquo; vulnerability to maladaptive behaviors, for example by promoting self-esteem, perceived control, and emotional stability. Additionally, teaching positive coping strategies, such as problem-solving and seeking social support, offers a concrete route to risk reduction. An integrated, multilevel approach that targets cognitive beliefs, self-evaluation, and coping skills in parallel is likely to be more effective than single-component interventions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and future directions\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, all variables were measured via self-report, which can introduce social desirability and recall biases. Future work should triangulate self-reports with multiple informants or objective indicators (e.g., teacher or parent ratings, behavioral records, passive digital traces) to improve validity. Second, although the design was longitudinal, it included only three waves over a relatively short time span. This limits inferences about long-term trajectories. Studies with longer observation periods, additional waves, and more advanced longitudinal models would allow stronger conclusions about developmental pathways over time. Third, participants were drawn from specific regions of China, so findings may not generalize to other populations. Replication across more diverse cultural and institutional contexts is needed to verify generalizability. Fourth, attrition analyses showed that dropouts had slightly higher levels of negative coping and greater screen use. Although these effects were small, this pattern suggests a conservative bias that may have led to underestimating certain associations. It is advisable for future studies to implement strategies to minimize attrition and to document reasons for participant dropout. Fifth, to improve model fit and conceptual clarity, we removed one poorly performing item from the negative coping subscale of the SCSQ. This decision was consistent with the scale\u0026rsquo;s bidimensional structure and avoided cross-loading content, but it slightly reduces comparability with studies that used the full SCSQ. Replication using the complete scale or alternative coping measures is warranted to confirm the findings. Finally, we cannot rule out the influence of unmeasured confounding variables or domain-specific processes. To better establish causality, future research should complement observational designs with randomized or quasi-experimental interventions that manipulate growth mindset, strengthen CSE, and train positive coping, and then evaluate the downstream effects on specific types of HRBs.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur longitudinal findings demonstrate that adolescents with a stronger growth mindset are less likely to engage in HRBs over time. The findings revealed four key results: (1) growth mindset showed a significant negative total association with HRBs; (2) CSE mediated this relationship; (3) positive coping styles also played a mediating role; and (4) CSE and positive coping styles jointly formed a sequential mediation pathway linking growth mindset to HRBs.\u003c/p\u003e \u003cp\u003eOverall, the findings indicate that a growth mindset functions as a protective factor of adolescents\u0026rsquo; health. Indirect pathways operated through higher CSE and greater use of positive coping. This study provides longitudinal evidence for a pathway from cognition to appraisal to coping, clarifying the cognitive and behavioral mechanisms that may link growth mindset to lower HRBs. These results offer actionable guidance for multicomponent programs that cultivate growth mindset, strengthen CSE, and build positive coping skills to foster healthier behaviors in adolescence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to all the students, schools, and research assistants who participated in and supported this study, particularly for their assistance with data collection. We used ChatGPT (OpenAI) solely for English language polishing (grammar and style). All scientific content was written, verified, and approved by the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX.X. conceived and designed the study, performed the statistical analyses, and drafted the manuscript. Y.D. organized and entered the data and conducted the preliminary analyses. Y.Z., M.X. and Y.H. contributed to data verification, study design, and statistical analysis. S.X. and S.C. made substantial contributions to the conception and design of the work and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Ministry of Education Humanities and Social Sciences Research Project (No. 23YJC880119), the Shandong Provincial Social Science Planning Project (No. 24DJYJ06), and the Shandong Postdoctoral Science Foundation (No. sDCX-RS-202400006).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to institutional and ethical restrictions related to participant confidentiality, but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to the ethical guidelines and regulations outlined in the Helsinki Declaration regarding the involvement of human participants. The research protocol received approval from\u0026nbsp;the Ethics Committee of Ludong University (ES002510). Informed consent was obtained from all participants, or in the case of participants under 18 years of age, from their parent and/or legal guardian.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAtorkey P, Owiredua C. Clustering of multiple health risk behaviours and association with socio-demographic characteristics and psychological distress among adolescents in Ghana: a latent class analysis. SSM-Population Health. 2021;13:100707.\u003c/li\u003e\n\u003cli\u003eWijbenga L, de Winter AF, Almansa J, Vollebergh WA, Korevaar EL, Hofstra J, Reijneveld SA. Multiple health risk behaviors and mental health from a life course perspective: The Dutch TRAILS study. Preventive Medicine. 2022;154:106870.\u003c/li\u003e\n\u003cli\u003eJahangard L, Behmanesh H, Ahmadpanah M, Poormoosavi SM, Solitanian A, Highighi M. Risky behaviors and health-promoting behaviors in young adults: An epidemiological study. Iranian Journal of Psychiatry. 2019;14(4):302.\u003c/li\u003e\n\u003cli\u003eTariq N, Gupta V. \u003cem\u003eHigh risk behaviors.\u003c/em\u003e Treasure Island (FL): StatPearls Publishing; 2023.\u003c/li\u003e\n\u003cli\u003eGe G, Huangfu C, Ge M, Gao Y, Tang N. Influence factors associated with health risk behaviors of middle school students in the poverty area of China: An observational study. Medicine. 2022;101(33):e29922.\u003c/li\u003e\n\u003cli\u003eNoble N, Paul C, Turon H, Oldmeadow C. Which modifiable health risk behaviours are related? A systematic review of the clustering of Smoking, Nutrition, Alcohol and Physical activity (\u0026lsquo;SNAP\u0026rsquo;) health risk factors. Preventive Medicine. 2015;81:16\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003eSsewanyana D, Abubakar A, Newton CR, Otiende M, Mochamah G, Nyundo C, Walumbe D, Nyutu G, Amadi D, Doyle AM. Clustering of health risk behaviors among adolescents in Kilifi, Kenya, a rural Sub-Saharan African setting. PLOS ONE. 2020;15(11):e0242186.\u003c/li\u003e\n\u003cli\u003eMatias TS, Silva KS, Silva JAd, Mello GTd, Salmon J. Clustering of diet, physical activity and sedentary behavior among Brazilian adolescents in the national school-based health survey (PeNSE 2015). BMC Public Health. 2018;18:1\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eYang R, Li D, Hu J, Tian R, Wan Y, Tao F, Fang J, Zhang S. Association between health literacy and subgroups of health risk behaviors among Chinese adolescents in six cities: a study using regression mixture modeling. International Journal of Environmental Research and Public Health. 2019;16(19):3680.\u003c/li\u003e\n\u003cli\u003eWHO. Adolescent and young adult health. Available from: www.who.int/news-room/fact-sheets/detail/adolescents-health-risks-and-solutions. Accessed 20 Nov 2024.\u003c/li\u003e\n\u003cli\u003eJessor R, Turbin MS, Costa FM, Dong Q, Zhang H, Wang C. Adolescent problem behavior in China and the United States: A cross‐national study of psychosocial protective factors. Journal of Research on Adolescence. 2003;13(3):329\u0026ndash;360.\u003c/li\u003e\n\u003cli\u003eJessor R, Van Den Bos J, Vanderryn J, Costa FM, Turbin MS. Protective factors in adolescent problem behavior: Moderator effects and developmental change. Developmental Psychology. 1995;31(6):923.\u003c/li\u003e\n\u003cli\u003eRutter M. Psychosocial resilience and protective mechanisms. American Journal of Orthopsychiatry. 1987;57(3):316\u0026ndash;331.\u003c/li\u003e\n\u003cli\u003eLazarus RS. \u003cem\u003eStress, appraisal, and coping.\u003c/em\u003e New York: Springer; 1984.\u003c/li\u003e\n\u003cli\u003eDweck CS. \u003cem\u003eMindset: The new psychology of success.\u003c/em\u003e New York: Random House; 2006.\u003c/li\u003e\n\u003cli\u003eWalker KA, Jiang X. An examination of the moderating role of growth mindset in the relation between social stress and externalizing behaviors among adolescents. Journal of Adolescence. 2022;94(1):69\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eZhang L, Qi H, Wang C, Wang T, Zhang Y. How does growth mindset affect mental health of high school students during the COVID-19 epidemic? The role of grit and coping strategies. Frontiers in Psychiatry. 2022;13:969572.\u003c/li\u003e\n\u003cli\u003eYeager DS, Hanselman P, Walton GM, Murray JS, Crosnoe R, Muller C, Tipton E, Schneider B, Hulleman CS, Hinojosa CP. A national experiment reveals where a growth mindset improves achievement. Nature. 2019;573(7774):364\u0026ndash;369.\u003c/li\u003e\n\u003cli\u003eYeager DS, Dweck CS. Mindsets that promote resilience: When students believe that personal characteristics can be developed. Educational Psychologist. 2012;47(4):302\u0026ndash;314.\u003c/li\u003e\n\u003cli\u003eGuo M. The longitudinal relationship between perceived parental growth mindset and children\u0026apos;s math‐specific grit: The mediational role of growth mindset and self‐efficacy. Journal of Adolescence. 2025;97(5):1261\u0026ndash;1271.\u003c/li\u003e\n\u003cli\u003eTang X, Wang M-T, Guo J, Salmela-Aro K. Building grit: The longitudinal pathways between mindset, commitment, grit, and academic outcomes. Journal of Youth and Adolescence. 2019;48(5):850\u0026ndash;863.\u003c/li\u003e\n\u003cli\u003eBurnette JL, Knouse LE, Vavra DT, O\u0026apos;Boyle E, Brooks MA. Growth mindsets and psychological distress: A meta-analysis. Clinical Psychology Review. 2020;77:101816.\u003c/li\u003e\n\u003cli\u003eBernecker K, Job V. Too exhausted to go to bed: Implicit theories about willpower and stress predict bedtime procrastination. British Journal of Psychology. 2020;111(1):126\u0026ndash;147.\u003c/li\u003e\n\u003cli\u003eThai CL, Rice EL, Taber JM, Kaufman AR, Klein WM. Implicit theories of smoking and association with interest in quitting among current smokers. Journal of Behavioral Medicine. 2020;43:544\u0026ndash;552.\u003c/li\u003e\n\u003cli\u003eFitz CC, Kaufman A, Moore PJ. Lay theories of smoking and young adult nonsmokers\u0026rsquo; and smokers\u0026rsquo; smoking expectations. Journal of Health Psychology. 2015;20(4):438\u0026ndash;445.\u003c/li\u003e\n\u003cli\u003eLindgren KP, Burnette JL, Hoyt CL, Peterson KP, Neighbors C. Growth mindsets of alcoholism buffer against deleterious effects of drinking identity on problem drinking over time. Alcoholism: Clinical and Experimental Research. 2020;44(1):233\u0026ndash;243.\u003c/li\u003e\n\u003cli\u003eSridharan V, Shoda Y, Heffner JL, Bricker J. Addiction mindsets and psychological processes of quitting smoking. Substance Use \u0026amp; Misuse. 2019;54(7):1086\u0026ndash;1095.\u003c/li\u003e\n\u003cli\u003eSchroder HS, Yalch MM, Dawood S, Callahan CP, Donnellan MB, Moser JS. Growth mindset of anxiety buffers the link between stressful life events and psychological distress and coping strategies. Personality and Individual Differences. 2017;110:23\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eZhu S, Li X, Wong PW. Risk and protective factors in suicidal behaviour among young people in Hong Kong: A comparison study between children and adolescents. Psychiatry Research. 2023;321:115059.\u003c/li\u003e\n\u003cli\u003eEhrlinger J, Burnette JL, Park J, Harrold ML, Orvidas K. Incremental theories of weight and healthy eating behavior. Journal of Applied Social Psychology. 2017;47(6):320\u0026ndash;330.\u003c/li\u003e\n\u003cli\u003eOrvidas K, Burnette J, Russell V. Mindsets applied to fitness: Growth beliefs predict exercise efficacy, value and frequency. Psychology of Sport and Exercise. 2018;36:156\u0026ndash;161.\u003c/li\u003e\n\u003cli\u003eJudge TA, Locke EA, Durham CC, Kluger AN. Dispositional effects on job and life satisfaction: the role of core evaluations. Journal of Applied Psychology. 1998;83(1):17.\u003c/li\u003e\n\u003cli\u003eJudge TA, Erez A, Bono JE, Thoresen CJ. The core self‐evaluations scale: Development of a measure. Personnel Psychology. 2003;56(2):303\u0026ndash;331.\u003c/li\u003e\n\u003cli\u003eLiu F, Zhu Z, Jiang B. The influence of Chinese college students\u0026rsquo; physical exercise on life satisfaction: the chain mediation effect of Core self-evaluation and positive emotion. Frontiers in Psychology. 2021;12:763046.\u003c/li\u003e\n\u003cli\u003eMa X, Li Z, Lu F. The influence of stressful life events on procrastination among college students: multiple mediating roles of stress beliefs and core self-evaluations. Frontiers in Psychology. 2023;14:1104057.\u003c/li\u003e\n\u003cli\u003eCherewick M, Hipp E, Njau P, Dahl RE. Growth mindset, persistence, and self-efficacy in early adolescents: Associations with depression, anxiety, and externalising behaviours. Global Public Health. 2023;18(1):2213300.\u003c/li\u003e\n\u003cli\u003eGong Y, Yang H, Bai X, Wang Y, An J. The relationship between physical exercise and smartphone addiction among Chinese College Students: the mediating effect of Core Self-evaluation. Behavioral Sciences. 2023;13(8):647.\u003c/li\u003e\n\u003cli\u003eWang S, Ding W, Song S, Tan Y, Ahmed MZ, Xie R, Li L. The relationship between adolescent victimization, nonsuicidal self-injury, and core self-evaluation: a cross-lagged study. Current Psychology. 2024;43(1):28\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eFeng Y, Luo X, Li X, Liu Y, Zeng Y. Bayesian network analysis of individual-level factors associated with bullying among high school students. BMC Psychology. 2025;13(1):658.\u003c/li\u003e\n\u003cli\u003eZou S, Song X, Tan W, Deng F, Zhang H, Xu H, Tao Y, Tang X, Tang X, Xiong P. Core self-evaluation as mediator between depressive symptoms and suicidal ideation in adolescents. Journal of Affective Disorders. 2022;302:361\u0026ndash;366.\u003c/li\u003e\n\u003cli\u003eQi W, Cui L. Eat to avoid negative self-awareness: Locus of control and core self-evaluation as serial mediators in the effect of stress on food intake. Appetite. 2019;143:104401.\u003c/li\u003e\n\u003cli\u003eClaro S, Paunesku D, Dweck CS. Growth mindset tempers the effects of poverty on academic achievement. Proceedings of the National Academy of Sciences. 2016;113(31):8664\u0026ndash;8668.\u003c/li\u003e\n\u003cli\u003eZhao H, Zhang M, Li Y, Wang Z. The relationship between a growth mindset and junior high school students\u0026rsquo; meaning in life: a serial mediation model. Behavioral Sciences. 2023;13(2):189.\u003c/li\u003e\n\u003cli\u003eFolkman S, Lazarus RS, Gruen RJ, DeLongis A. Appraisal, coping, health status, and psychological symptoms. Journal of Personality and Social Psychology. 1986;50(3):571.\u003c/li\u003e\n\u003cli\u003eKpeno A, Sahoo S, Sahu AK, Sahu PK. Problem-solving and coping skills training for youth with deliberate self-harm behaviors: A scoping review. Journal of Indian Association for Child and Adolescent Mental Health. 2024:09731342241278964.\u003c/li\u003e\n\u003cli\u003eLiang J, K\u0026otilde;lves K, Lew B, De Leo D, Yuan L, Abu Talib M, Jia C-x. Coping strategies and suicidality: A cross-sectional study from China. Frontiers in Psychiatry. 2020;11:129.\u003c/li\u003e\n\u003cli\u003eXu J, Yang X. The influence of resilience on stress reaction of college students during COVID-19: the mediating role of coping style and positive adaptive response. Current Psychology. 2024;43(13):12120\u0026ndash;12131.\u003c/li\u003e\n\u003cli\u003eXie Z, Bi K, Feng N, Ji X, Liu Y, Lam H, Yu H, Cui L. Prospective associations between heterogeneous sleep profiles and depressive symptoms in adolescents: The mediating role of coping styles. Journal of Adolescence. 2025;97(2):499\u0026ndash;513.\u003c/li\u003e\n\u003cli\u003eWang Y, Fu T, Wang J, Chen S, Sun G. The relationship between self-compassion, coping style, sleep quality, and depression among college students. Frontiers in Psychology. 2024;15:1378181.\u003c/li\u003e\n\u003cli\u003eLeonard NR, Gwadz MV, Ritchie A, Linick JL, Cleland CM, Elliott L, Grethel M. A multi-method exploratory study of stress, coping, and substance use among high school youth in private schools. Frontiers in Psychology. 2015;6:140070.\u003c/li\u003e\n\u003cli\u003eYang C, Li F, Khalid NF. Disordered eating in young Chinese adults: role of parenting styles, attachment anxiety, and negative coping styles. BMC Public Health. 2025;25(1):1\u0026ndash;18.\u003c/li\u003e\n\u003cli\u003eYang Y, Guo Y, Wang W, Cai B, Ning H, Gong H. Harsh parenting and smartphone addiction: the mediating role of core self-evaluation and the moderating role of nature connectedness. Computers in Human Behavior. 2024;152:108049.\u003c/li\u003e\n\u003cli\u003eJanssen T, van Atteveldt N. Coping styles mediate the relation between mindset and academic resilience in adolescents during the COVID-19 pandemic: a randomized controlled trial. Scientific Reports. 2023;13(1):6060.\u003c/li\u003e\n\u003cli\u003eObbarius N, Fischer F, Liegl G, Obbarius A, Rose M. A modified version of the transactional stress concept according to Lazarus and Folkman was confirmed in a psychosomatic inpatient sample. Frontiers in Psychology. 2021;12:584333.\u003c/li\u003e\n\u003cli\u003eHe Y-Z, Yuan X-Q, Ye W-Y, Yang S-Y, Ng KX, Dou K. Longitudinal links between time perspective and problematic internet use among Chinese adolescents: testing a dual-path model of coping style. Current Psychology. 2024;43(28):23517\u0026ndash;23525.\u003c/li\u003e\n\u003cli\u003eYu H. The relationship between family functioning and academic burnout of college students: The mediating role of core self-evaluation and coping style. Scalable Computing: Practice and Experience. 2024;25(4):2336\u0026ndash;2344.\u003c/li\u003e\n\u003cli\u003eHuang Y, Zhou N, Liang S. Analyzing the effect of perceived discrimination on aggressive behavior in college students with disability using the chain mediation model. Scientific Reports. 2025;15(1):25645.\u003c/li\u003e\n\u003cli\u003eDweck CS. Carol Dweck revisits the growth mindset. Education Week. 2015;35(5):20\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eFurnham A. Increasing your intelligence: Entity and incremental beliefs about the multiple \u0026ldquo;intelligences\u0026rdquo;. Learning and Individual Differences. 2014;32:163\u0026ndash;167.\u003c/li\u003e\n\u003cli\u003eFeng S, Liu R, Tomar A, Ma P. Sex differences in the associations of mental health, suicidality, screentime, and sleep: A mediation effect analysis of sleep using Youth Risk Behavioral Surveillance Survey 2021. Psychological Reports. 2024:00332941241277096.\u003c/li\u003e\n\u003cli\u003ePurba AK, Thomson RM, Henery PM, Pearce A, Henderson M, Katikireddi SV. Social media use and health risk behaviours in young people: systematic review and meta-analysis. BMJ. 2023;383:e073552.\u003c/li\u003e\n\u003cli\u003eLittle RJ, Rubin DB. \u003cem\u003eStatistical analysis with missing data.\u003c/em\u003e Hoboken (NJ): John Wiley \u0026amp; Sons; 2019.\u003c/li\u003e\n\u003cli\u003eJi C. \u003cem\u003eComprehensive report on health-related/risky behaviors of adolescents in China, 2005.\u003c/em\u003e Beijing: People\u0026rsquo;s Medical Publishing House; 2007.\u003c/li\u003e\n\u003cli\u003eYang M, Guo K, Liu W, Fang X, Liu T. Coping tendency as a mediator in the relationship between psychological resilience and health problems among college students. Psychology Research and Behavior Management. 2024:2619\u0026ndash;2630.\u003c/li\u003e\n\u003cli\u003eYu J, Liu Y, Liao L, Yan J, Wang H. Cluster analysis of sleep time and adolescent health risk behaviors. INQUIRY: The Journal of Health Care Organization, Provision, and Financing. 2023;60:00469580231153272.\u003c/li\u003e\n\u003cli\u003eBuysse DJ, Reynolds III CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Research. 1989;28(2):193\u0026ndash;213.\u003c/li\u003e\n\u003cli\u003eSchleider JL, Weisz JR. Implicit theories relate to youth psychopathology, but how? A longitudinal test of two predictive models. Child Psychiatry \u0026amp; Human Development. 2016;47:603\u0026ndash;617.\u003c/li\u003e\n\u003cli\u003eJiang X, Paley N, Shi D. Examining the validity and measurement invariance across gender and race of the Implicit Thoughts, Emotion, and Behavior Questionnaire. School Psychology. 2022;37(4):330.\u003c/li\u003e\n\u003cli\u003eDu J, Zhang X, Zhao Y. Reliability, validation and construct confirmatory of core self-evaluations scale. Psychological Research. 2012;5(3):54\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eXie Y. Reliability and validity of the simplified coping style questionnaire. Chinese Journal of Clinical Psychology. 1998;6(2):114\u0026ndash;115.\u003c/li\u003e\n\u003cli\u003eTing W-H, Huang C-Y, Tu Y-K, Chien K-L. Association between weight status and depressive symptoms in adolescents: role of weight perception, weight concern, and dietary restraint. European Journal of Pediatrics. 2012;171(8):1247\u0026ndash;1255.\u003c/li\u003e\n\u003cli\u003eXu T, Zuo F, Zheng K. Parental educational expectations, academic pressure, and adolescent mental health: An empirical study based on CEPS survey data. International Journal of Mental Health Promotion. 2024;26(2):93.\u003c/li\u003e\n\u003cli\u003eOECD. \u003cem\u003ePISA 2022 Results (Volume I): The state of learning and equity in education.\u003c/em\u003e Paris: OECD Publishing; 2023.\u003c/li\u003e\n\u003cli\u003eVoyer D, Voyer SD. Gender differences in scholastic achievement: a meta-analysis. Psychological Bulletin. 2014;140(4):1174.\u003c/li\u003e\n\u003cli\u003eBedard K, Dhuey E. The persistence of early childhood maturity: International evidence of long-run age effects. The Quarterly Journal of Economics. 2006;121(4):1437\u0026ndash;1472.\u003c/li\u003e\n\u003cli\u003eBliese PD. Within-group agreement, non-independence, and reliability: Implications for data aggregation and analysis. In: Klein K, Kozlowski S, editors. Multilevel theory, research, and methods in organizations: foundations, extensions, and new directions. San Francisco: Jossey-Bass; 2000. p. 349\u0026ndash;381.\u003c/li\u003e\n\u003cli\u003eHair JF, Black WC, Babin BJ, Anderson RE, Tatham RL. \u003cem\u003eMultivariate data analysis, 7th ed.\u003c/em\u003e Upper Saddle River, NJ: Pearson; 2010.\u003c/li\u003e\n\u003cli\u003eTabachnick BG, Fidell LS. \u003cem\u003eUsing multivariate statistics, 6th ed.\u003c/em\u003e Boston, Ma: Pearson; 2013.\u003c/li\u003e\n\u003cli\u003eSun Z, Zhang X, Yuan W, Dong Y, Xu K, Zhao S, Chen L, Liu Z. Association of health risk behaviors with obesity and depressive symptoms in middle school students. Chinese Journal of School Health. 2024;45(10):1505\u0026ndash;1510.\u003c/li\u003e\n\u003cli\u003eSchleider JL, Weisz JR. Mental health and implicit theories of thoughts, feelings, and behavior in early adolescents: Are girls at greater risk? Journal of Social and Clinical Psychology. 2016;35(2):130\u0026ndash;151.\u003c/li\u003e\n\u003cli\u003eYu T, Pan X, Li J, He L, Ying H, Deng J, Li L. Impacts of growth mindset on health: effects, mechanisms and interventions. Chin J Clin Psychol. 2022;30:871\u0026ndash;875.\u003c/li\u003e\n\u003cli\u003eJohn-Henderson NA, Tintzman CS, Counts CJ, Mueller CM. Health mindsets as a predictor of physical activity and body mass index in American Indian college students. Journal of Health Psychology. 2021;26(12):2098\u0026ndash;2105.\u003c/li\u003e\n\u003cli\u003eYeager DS, Bryan CJ, Gross JJ, Murray JS, Krettek Cobb D, HF Santos P, Gravelding H, Johnson M, Jamieson JP. A synergistic mindsets intervention protects adolescents from stress. Nature. 2022;607(7919):512\u0026ndash;520.\u003c/li\u003e\n\u003cli\u003eBurnette JL, O\u0026apos;boyle EH, VanEpps EM, Pollack JM, Finkel EJ. Mind-sets matter: a meta-analytic review of implicit theories and self-regulation. Psychological Bulletin. 2013;139(3):655.\u003c/li\u003e\n\u003cli\u003eQi W, Shi J, Cui L. A developmental system perspective to interpret the link between parental fixed mindset and youth mental health: A moderated mediation model. International Journal of Environmental Research and Public Health. 2022;19(20):13285.\u003c/li\u003e\n\u003cli\u003eDescartes CH, Ramesar M, Mills J. Global or domain specific self-esteem: Can it predict aggression among children and adolescents? Journal of Aggression, Maltreatment \u0026amp; Trauma. 2019;28(3):350\u0026ndash;368.\u003c/li\u003e\n\u003cli\u003eSun P, Sun Y, Fang D, Jiang H, Pan M. Cumulative ecological risk and problem behaviors among adolescents in secondary vocational schools: the mediating roles of Core self-evaluation and basic psychological need satisfaction. Frontiers in Public Health. 2021;9:591614.\u003c/li\u003e\n\u003cli\u003eValois RF, Zullig KJ, Revels AA. Aggressive and violent behavior and emotional self‐efficacy: Is there a relationship for adolescents? Journal of School Health. 2017;87(4):269\u0026ndash;277.\u003c/li\u003e\n\u003cli\u003eLi Y, Shen X, Wang J. Association between negative life events and suicidal behavior in adolescents: roles of core self-evaluation, depression and gender. Social Psychiatry and Psychiatric Epidemiology. 2024;60:673\u0026ndash;684.\u003c/li\u003e\n\u003cli\u003eWang Q, Tu R, Hu W, Luo X, Zhao F. Childhood psychological maltreatment and depression among Chinese adolescents: multiple mediating roles of perceived ostracism and core self-evaluation. International Journal of Environmental Research and Public Health. 2021;18(21):11283.\u003c/li\u003e\n\u003cli\u003eZhu L, Zhang Y, Wang H. Effects of core self-evaluation on tobacco and alcohol use among left-behind children: mediating role of fear of missing out and moderating role of parental migration category and gender. BMC Psychology. 2025;13(1):262.\u003c/li\u003e\n\u003cli\u003eGriggs S, Crawford SL. Hope, core self-evaluations, emotional well-being, health-risk behaviors, and academic performance in university freshmen. Journal of Psychosocial Nursing and Mental Health Services. 2017;55(9):33\u0026ndash;42.\u003c/li\u003e\n\u003cli\u003eMart\u0026iacute;nez-Casanova E, Molero-Jurado M, P\u0026eacute;rez-Fuentes M. Self-esteem and risk behaviours in adolescents: A systematic review. Behavioral Sciences. 2024;14(6):432.\u003c/li\u003e\n\u003cli\u003eDong W, Tang H, Wu S, Lu G, Shang Y, Chen C. The effect of social anxiety on teenagers\u0026rsquo; internet addiction: the mediating role of loneliness and coping styles. BMC Psychiatry. 2024;24(1):395.\u003c/li\u003e\n\u003cli\u003eDuan S, Duan Z, Li R, Wilson A, Wang Y, Jia Q, Yang Y, Xia M, Wang G, Jin T. Bullying victimization, bullying witnessing, bullying perpetration and suicide risk among adolescents: A serial mediation analysis. Journal of Affective Disorders. 2020;273:274\u0026ndash;279.\u003c/li\u003e\n\u003cli\u003eVillanueva-Blasco V, Villanueva-Silvestre V, V\u0026aacute;zquez-Mart\u0026iacute;nez A. Relationship between depression and risky alcohol consumption in women: the mediating role of coping styles and age. International Journal of Mental Health and Addiction. 2024;22(3):1376\u0026ndash;1393.\u003c/li\u003e\n\u003cli\u003eGarnefski N, Legerstee J, Kraaij V, van Den Kommer T, Teerds J. Cognitive coping strategies and symptoms of depression and anxiety: A comparison between adolescents and adults. Journal of Adolescence. 2002;25(6):603\u0026ndash;611.\u003c/li\u003e\n\u003cli\u003eSun P, Sun Y, Jiang H, Jia R, Li Z. Gratitude and problem behaviors in adolescents: The mediating roles of positive and negative coping styles. Frontiers in Psychology. 2019;10:1547.\u003c/li\u003e\n\u003cli\u003eLazarus RS, Folkman S. Transactional theory and research on emotions and coping. European Journal of Personality. 1987;1(3):141\u0026ndash;169.\u003c/li\u003e\n\u003cli\u003eZhang J, Li Y, Li J, Lyu M, Chen Y, Yang S, Tan C, Tao Y, Ye B, Zhang J. The effect of life events, resilience, self-esteem, and coping styles on aggressive behavior among left-behind adolescents: Structural equation modeling. Frontiers in Psychiatry. 2023;14:991608.\u003c/li\u003e\n\u003cli\u003eLin J, Su Y, Lv X, Liu Q, Wang G, Wei J, Zhu G, Chen Q, Tian H, Zhang K. Perceived stressfulness mediates the effects of subjective social support and negative coping style on suicide risk in Chinese patients with major depressive disorder. Journal of Affective Disorders. 2020;265:32\u0026ndash;38.\u003c/li\u003e\n\u003cli\u003eWang X, Ding T, Lai X, Yang C, Luo J. Negative life events, negative coping style, and internet addiction in middle school students: A large two-year follow-up study. International Journal of Mental Health and Addiction. 2024;22(5):3233\u0026ndash;3243.\u003c/li\u003e\n\u003cli\u003eLi Y, Wang Z, You W, Liu X. Core self-evaluation, mental health and mobile phone dependence in Chinese high school students: why should we care. Italian Journal of Pediatrics. 2022;48(1):28.\u003c/li\u003e\n\u003cli\u003eShi J, Kim HK. Integrating risk perception attitude framework and the theory of planned behavior to predict mental health promotion behaviors among young adults. Health Communication. 2020;35(5):597\u0026ndash;606.\u003c/li\u003e\n\u003cli\u003eKammeyer-Mueller JD, Judge TA, Scott BA. The role of core self-evaluations in the coping process. Journal of Applied Psychology. 2009;94(1):177.\u003c/li\u003e\n\u003cli\u003eWang X, Shi L, Ding Y, Liu B, Chen H, Zhou W, Yu R, Zhang P, Huang X, Yang Y. School bullying, bystander behavior, and mental health among adolescents: The mediating roles of self-efficacy and coping styles. Healthcare. 2024;12(17):1738.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"growth mindset, core self-evaluation, coping style, health risk behaviors, adolescents","lastPublishedDoi":"10.21203/rs.3.rs-8204472/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8204472/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e Health risk behaviors pose serious threats to adolescents’ physical and psychological well-being as well as their long-term development. Previous studies suggest that a growth mindset can serve as a positive cognitive resource influencing such behaviors, but the underlying mechanisms remain underexplored, especially over time. Guided by the transactional model of stress and coping, this study aimed to examine a longitudinal model linking growth mindset to later health risk behaviors via core self-evaluation and coping style.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e A three-wave longitudinal study was conducted using cluster sampling to recruit middle school students in eastern China. Assessments occurred at three-month intervals: growth mindset was measured at Time\u0026nbsp;1 (T1), core self-evaluation and coping style at Time\u0026nbsp;2 (T2), and health risk behaviors at Time\u0026nbsp;3 (T3). In total, 534 students (\u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e = 12.40, 50.2% male) completed all three waves.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e Findings indicated that growth mindset at T1 negatively predicted health risk behaviors at T3. Core self-evaluation and positive coping style at T2 independently mediated this relationship and also operated sequentially as a chain mediation pathway, highlighting the longitudinal mechanism linking cognitive beliefs to behavioral outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e Growth mindset functions as a protective cognitive factor against adolescents’ health risk behaviors by fostering positive self-evaluation and adaptive coping strategies. These findings extend cognitive-behavioral accounts of health risk behaviors and support multicomponent interventions targeting adolescents’ mindsets, core self-evaluation, and coping skills.\u003c/p\u003e","manuscriptTitle":"The impact of growth mindset on adolescents’ health risk behaviors: the chain mediating roles of core self-evaluation and coping styles","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 14:07:53","doi":"10.21203/rs.3.rs-8204472/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-16T05:39:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T22:20:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-26T15:53:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"11885946772174963329930173448583618917","date":"2025-12-26T09:03:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"202033979163974304204495426375801819065","date":"2025-12-18T07:07:03+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-18T05:54:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-18T02:27:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T10:06:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-06T17:39:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychology","date":"2025-12-01T10:55:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"psyo","sideBox":"Learn more about [BMC Psychology](http://bmcpsychology.biomedcentral.com/)","snPcode":"","submissionUrl":"","title":"BMC Psychology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fd1818b4-8c3d-4f93-af14-ebc2e4bc7c68","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-02T16:07:17+00:00","versionOfRecord":{"articleIdentity":"rs-8204472","link":"https://doi.org/10.1186/s40359-026-04211-3","journal":{"identity":"bmc-psychology","isVorOnly":false,"title":"BMC Psychology"},"publishedOn":"2026-02-28 15:59:00","publishedOnDateReadable":"February 28th, 2026"},"versionCreatedAt":"2025-12-22 14:07:53","video":"","vorDoi":"10.1186/s40359-026-04211-3","vorDoiUrl":"https://doi.org/10.1186/s40359-026-04211-3","workflowStages":[]},"version":"v1","identity":"rs-8204472","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8204472","identity":"rs-8204472","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}