Bidirectional Associations Between Parental Work-Family Conflict and Early Adolescents’ Academic Adjustment: A Four-Wave Dyadic Longitudinal Study in China

Bidirectional Associations Between Parental Work-Family Conflict and Early Adolescents’ Academic Adjustment: A Four-Wave Dyadic Longitudinal Study in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Bidirectional Associations Between Parental Work-Family Conflict and Early Adolescents’ Academic Adjustment: A Four-Wave Dyadic Longitudinal Study in China Xiaoli Wang, Cui Wang, Zilal Yashengjiang, Hanjin Bao, Shibo Li, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8598251/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Work-family conflict (WFC) not only affects parents’ mental and physical health but may also directly or indirectly influence adolescents’ academic adjustment. Importantly, this relationship may be bidirectional: while parental WFC can disrupt adolescents’ academic adjustment, adolescents’ characteristics, such as behavioral problems and difficulties in academic functioning, may in turn undermine parents’ ability to manage work-family demands. To date, however, longitudinal research examining the dynamic, reciprocal relationship between parents’ WFC and adolescent academic adjustment, as well as the underlying mechanisms, remains limited. Therefore, the present study aims to investigate the bidirectional and developmental associations between parents’ WFC and early adolescents’ academic adjustment. Using a longitudinal dyadic design, this study followed 329 seventh-grade students and their dual-earner parents across four waves of data collection: the first and second semesters of seventh grade (T1, T2) and the first and second semesters of eighth grade (T3, T4). Self-report questionnaires were administered to assess fathers’ and mothers’ WFC and early adolescents’ academic adjustment. Structural equation modeling and cross-lagged panel models were employed to examine the bidirectional predictive effects between parental WFC and adolescent academic adjustment. In addition, parallel latent growth modeling was conducted to explore their synchronous developmental trajectories over time. The results indicated that adolescents’ academic adjustment exhibited a linear downward trend from seventh to eighth grade. A significant synchronous developmental relationship was observed between fathers’ WFC and adolescents’ academic adjustment during this transition period. Specifically, the initial level of fathers’ WFC predicted both the initial level and the rate of change in adolescents’ academic adjustment: higher initial levels of fathers’ WFC were associated with poorer academic adjustment and slower growth in adjustment over time, and vice versa. Conversely, adolescents’ academic adjustment also predicted fathers’ WFC. Higher levels of academic adjustment were associated with lower initial levels of fathers’ WFC and a slower rate of change in WFC, while improvements in adolescents’ academic adjustment occurred more rapidly, thereby contributing to a slower increase in fathers’ WFC over time. Overall, the findings provide robust evidence for a significant bidirectional relationship between parents’ WFC and early adolescents’ academic adjustment. On the one hand, parents’ experiences of WFC tend to accumulate over time and negatively affect adolescents’ academic adjustment. On the other hand, adolescents’ academic adjustment difficulties can, in turn, exacerbate parents’ WFC. This study highlights the influence of distal environmental factors, such as parents’ work experiences, on adolescent development and suggests that interventions aimed at improving parents’ work environments may play an important role in promoting adolescents’ academic adjustment. Health sciences/Health care Biological sciences/Psychology Social science/Psychology Work-Family Conflict Academic Adjustment Early adolescent Figures Figure 1 Figure 2 1. Introduction Work and family constitute the two central domains of adult life. Rather than functioning independently, these domains frequently influence one another through processes of spillover. Work-family conflict (WFC) is defined as a form of inter-role conflict in which participation in one role is made more difficult by participation in another, resulting in negative spillover between work and family domains. As originally articulated by Powell and Greenhaus ( 1985 ), the work-family relationship is inherently bidirectional: work demands may interfere with family life, while family responsibilities can, in turn, impede work performance. China's ongoing transition toward a market-oriented economy, together with rapid social modernization, has profoundly reshaped work arrangements and lifestyle patterns. These societal changes have transformed the interface between work and family life, confronting parents with a complex combination of new challenges and opportunities. Although the relationship between work and family can involve both conflict and mutual enrichment, the reality for most contemporary parents is the necessity of managing dual role demands. When the balance between these roles is difficult to maintain, the likelihood of experiencing WFC increases substantially (Frone et al., 1992 ; J. H. Greenhaus & Beutell, 1985 ; Powell & Greenhaus, 2006 ). Importantly, WFC may not only affect adults’ well-being but also have implications for their children’s mental health and development. To date, however, relatively few studies have examined the association between parental WFC and children’s mental health outcomes. Against the backdrop of the increasing prevalence of WFC among parents and the rising incidence of adjustment problems among adolescents in recent decades (Col- lishaw 2015; Collishaw et al. 2004), particularly difficulties in academic adjustment, it is critical to understand whether, and through what mechanisms, parental WFC influences adolescents’ academic adjustment (Bakker et al., 2009 , 2014 ; Cho & Coulton, 2016 ). Beyond the family context, the school environment represents another critical microsystem for adolescent development, whose influence becomes increasingly salient with age. Successful academic adjustment constitutes a core developmental task during adolescence and is particularly emphasized in Chinese families, where academic achievement is often regarded as a primary determinant of future educational and occupational success. Although previous research has highlighted the importance of family-related factors, such as parenting practices, parents’ mental health, and socioeconomic status, in shaping adolescents’ academic adjustment (Huang jie et al., 2019; Wang mingzhong et al., 2018), empirical evidence in the Chinese context that systematically examines the association between parents’ WFC and adolescents’ academic outcomes remains limited. Although work takes place outside the family setting, it profoundly structures parents’ daily routines, emotional resources, and patterns of interaction within the household. The demands and resources embedded in parents’ work roles jointly shape the family environment and, in turn, influence adolescents’ adjustment by modifying their developmental context. From a family systems perspective, mothers and fathers fulfill distinct yet equally indispensable roles, and family members are interconnected, such that interactions between spouses and between parents and children are mutually influential (Matias et al., 2017 ; Matias & Recharte, 2020 ). However, existing research has largely focused on unidirectional pathways, emphasizing how parental characteristics affect adolescents’ psychological and academic functioning, while often portraying adolescents as passive recipients of family influences. In contrast, adolescents’ characteristics and adjustment difficulties may also affect parents’ capacity to manage work-family demands. Therefore, it is essential to conceptualize the association between parents’ WFC and adolescent adjustment as a dynamic and potentially bidirectional process. 1.1 Developmental Characteristics of Adolescent Academic Adjustment Academic adjustment refers to an individual’s capacity to cope with academic demands and challenges and to achieve positive learning outcomes. It primarily encompasses multiple interrelated dimensions, including learning attitudes, study skills, learning environments, and physical and mental health, as well as academic self-efficacy, stress, burnout, and classroom performance experienced during the learning process (Guangzhen Zhang et al.,2013; Cuimin Zhou et al.,2016). Additionally, academic adjustment is reflected not only in adolescents’ perceived competence in achieving success at school but also in their motivation and desire to perform well academically (Wang & Cai, 2017 ). Adolescence represents a transitional period from childhood to adulthood, during which individuals experience substantial changes across multiple developmental contexts, including curriculum structure, parents’ educational expectations, school climate, class size, teacher-student relationships, and peer interactions (Eccles & Wigfield, 2002 ; Moilanen et al., 2015 ). Compared with elementary school, learning in middle school is generally more competitive, and both parents and teachers place greater emphasis on individual academic performance, often accompanied by heightened expectations for academic success. Within such an environment, adolescents are more susceptible to difficulties in academic adjustment. On the one hand, the increasing salience of academic demands leads to greater evaluative pressure and criticism in response to poor academic performance (Roisman et al., 2004 ). On the other hand, the rising complexity and difficulty of academic tasks in middle school can exceed adolescents’ coping capacities, thereby increasing academic stress. Early adolescence has been widely identified as a critical period marked by declines in academic engagement, learning motivation, and academic achievement. Following the transition to middle school, adolescents often exhibit reduced learning motivation and poorer academic adjustment (Eccles et al., 1999 ). Furthermore, gender differences have been observed in adolescents’ academic adjustment. Boys tend to experience more academic adjustment difficulties than girls, whereas differences across grade levels are generally less pronounced, with academic adjustment showing a slight decline as students progress through school (Maughan et al., 2004 ). Girls typically place greater importance on academic achievement, demonstrate higher levels of intrinsic academic motivation, and attain better academic outcomes (Brière et al., 2015 ; Veas et al., 2019 ). However, they also tend to be more concerned about their academic performance, which may contribute to higher levels of academic burnout compared with boys (Brière et al., 2015 ; Veas et al., 2019 ). Research evidence indicates that the factors influencing adolescents’ academic adjustment are multifaceted, involving not only individual psychological characteristics, such as perseverance, shyness, values, and emotional functioning (Baker, 2006 ; Birch & Ladd, 1997 ; Kiuru et al., 2009 ), but also the broader family environment. As adolescents mature, they become increasingly sensitive to their parents’ roles and experiences within both the work and family domains. In the Chinese cultural context, academic achievement is commonly regarded by parents as a key indicator of future success, leading to elevated educational expectations for their children. Such expectations may function as a double-edged sword: while they can promote academic engagement, they often entail substantial academic investment from adolescents, accompanied by heightened stress (Fan & Chen, 2001). Accordingly, it is essential to examine whether observed changes in adolescents’ academic adjustment primarily reflect normative developmental processes or are shaped by external contextual factors, such as parents’ work-family spillover. 1.2 WFC and Adolescent Academic Adjustment Academic adjustment represents one of the most critical developmental tasks during adolescence (Bouchey & Harter, 2005 ). The transition from childhood to adolescence, characterized by an expanded curriculum and heightened academic competition and pressure, renders adolescents particularly vulnerable to difficulties in academic adjustment (Abdollahi et al., 2020 ). Adolescents who experience poor academic adjustment are more likely to develop negative attitudes toward school, exhibit disengagement from school-related activities, and ultimately achieve lower academic performance. Furthermore, these adolescents face an increased risk of school dropout (Fortin et al., 2013 ). Substantial evidence indicates that parents’ WFC is an important predictor of adolescents’ academic difficulties. Adolescents raised in families characterized by frequent conflict are more likely to experience poor academic outcomes (Brown, 2014 ). Specifically, when parents’ work demands interfere with adolescents’ educational needs due to constraints on key resources such as time and energy, adolescents’ academic adjustment may be compromised, resulting in lower academic achievement and the emergence of maladaptive learning behaviors (Cho & Coulton, 2016 ). The mechanisms underlying this association are multifaceted. First, time-based WFC can constrain parents’ involvement in their children’s education, thereby depriving adolescents of critical resources that support learning motivation and engagement (Phillipson & Phillipson, 2007 ). Moreover, parents experiencing high levels of WFC often face additional challenges, such as limited career advancement opportunities and increased financial strain (Allen et al., 2019 ), which further reduce their available time, energy, and capacity to participate in their children’s education at home and at school. These parents are also more likely to adopt less effective academic supervision strategies, as cognitive and emotional depletion resulting from multiple role demands undermines their ability to respond sensitively, provide stimulation, and interact effectively with their children (Craig & Sawrikar, 2008 ). Additionally, the strain associated with balancing work and family responsibilities may disrupt parents’ daily routines (e.g., through overtime or night shifts), thereby limiting the time available to supervise adolescents’ homework and after-school learning activities (Cho & Coulton, 2016 ). Effective parental supervision and behavioral control are particularly important, as they not only promote greater investment of time in academic activities but also facilitate the development of adolescents’ self-regulation in academic emotions, cognition, and behavior, ultimately contributing to improved academic competence and achievement (Cho & Coulton, 2016 ; Shim & Finch, 2014 ; Tseng, 2004 ; Veas et al., 2019 ; Jiang & Dong, 2020 ). Finally, even when parents are able to allocate time to their children, work-related stress stemming from demanding schedules may manifest as fatigue, tension, and irritability. Such strain can impair parents’ physiological and emotional capacity to engage meaningfully in their adolescents’ education, thereby exacerbating academic stress and maladjustment among adolescents (Li et al., 2014 ). Conversely, family-related factors may also interfere with work functioning. For example, adolescents’ academic difficulties can substantially undermine parents’ mental health and reduce their ability to concentrate on work-related tasks (Matias et al., 2017 a; Vieira, Matias, Lopez, & Matos, 2016). Furthermore, adolescents differ considerably in their responses to parents’ WFC. While some adolescents exhibit developmental difficulties, such as declining academic performance, increased problem behaviors, and poorer social skills, others demonstrate relatively positive adaptation despite exposure to parental WFC. Prior research suggests that adolescents’ age and gender play important moderating roles in how parents’ work-family spillover affects individual development (Twenge & Nolen-Hoeksema, 2002 ). Changes in parents’ work and family environments may thus have differential implications for sons and daughters. For instance, girls may be more sensitive to the effects of parental WFC, as they tend to perceive and internalize negative emotions more acutely. When parents experience sudden financial strain, they may be more likely to interrupt girls’ educational trajectories (Borelli et al., 2017 ). According to the resource dilution model, increases in family size reduce the amount of available resources allocated to each child (Blake, 1981 ); however, the extent of this reduction may differ between sons and daughters. Western scholarship has suggested that under adverse family conditions, greater investment may be directed toward daughters (Trivers & Willard, 1973) . In contrast, research conducted in Eastern cultural contexts indicates that when family resources are limited, daughters do not receive preferential consideration or care (Fan & Chen, 2020), and their interests are more likely to be sacrificed (Li et al., 2014 ). As family socioeconomic status improves, this pattern of sacrificing girls’ interests gradually diminishes (Lee et al., 1994 ), highlighting cultural differences in family resource allocation mechanisms. Within the Chinese cultural context, patriarchal norms have historically contributed to a pronounced “son preference” (Baopei Wu et al., 2013). When family resources are scarce, parents are more likely to prioritize sons over daughters (Hannum et al., 2009 ; Parish & Willis, 1993). Similarly, in the intergenerational transmission of family resources, boys tend to receive greater investment and are more likely to inherit their parents’ social status (Chu & Yu, 2007). 1.3The present study The present study aims to investigate parents’ WFC and their relationships with academic adjustment from a dynamic developmental perspective during early adolescence in the Chinese context. The primary goals are three fold: First, it examines the developmental trajectories of academic adjustment among Chinese adolescents across middle school years. Based on existing literature, it is hypothesized that academic adjustment will increase during middle school years ( Hypothesis 1 ). Second, the study explores how these developmental trajectories of parents’ work-family are associated with the developmental trajectories of adolescent academic adjustment. It is assumed that trajectories of parents’ WFC will be negatively associated with the developmental trajectories of adolescent’ academic adjustment ( Hypothesis 2 ). Finally, the study employs cross-lagged panel models to investigate the direction of effects between parents’ WFC and adolescent academic adjustment. Drawing on literature regarding parents, it is hypothesized that parents’ WFC and adolescent academic adjustment will exhibit cumulative cycles, where WFC predict adolescent academic adjustment which in turn, influence sleep problems ( Hypothesis 3 ). 2. Method 2.1. Participants This study employed a cluster sampling approach, randomly selecting five classes from each of three junior high schools in Nanchang City, resulting in a total of 15 participating classes. All first-year students from these classes and their parents were invited to participate. They were informed that their data would remain confidential and be used solely for research purposes. Both active written assent from adolescents and passive consent from parents were obtained prior to data collection. Trained research assistants, including postgraduate students in psychology and school psychological counselors, administered the surveys. The baseline assessment (T1) was conducted in September 2020. A total of 737 student-parent triads completed the questionnaires. Among the adolescents, 98.3% resided with both biological parents, with the remaining from single-parent households due to divorce, bereavement, or other reasons. Parents’ age was concentrated between 40 and 50 years. Over 93% of fathers and 92% of mothers had attained a senior high school education or above. Furthermore, 93.7% of fathers and 82.8% of mothers were employed full-time. The final valid sample at T1 comprised 587 complete families (i.e., 587 adolescents, 587 fathers, and 587 mothers).Three follow-up assessments were conducted using identical procedures at six-month intervals: T2 in April 2021, T3 in September 2021, and T4 in April 2022. While all initially recruited participants completed the T1 assessment, attrition occurred at subsequent waves due to student transfer, illness, or other reasons. The valid samples for T2, T3, and T4 consisted of 623, 465, and 437 families, respectively. For the primary longitudinal analyses requiring complete data across all four time points, the final analytic sample included 329 families (329 adolescents and both their parents). Adolescent demographic characteristics, including age, gender, and sibling status, were collected via self-report at T1. The adolescents had a mean age of 12.45 years (SD = 1.31) at baseline, and the sample included 175 girls. Independent-samples t-tests indicated no significant differences at T1 between participants retained in the final sample and those who dropped out on key study variables: fathers’ WFC (t(587) = − 0.24, p = 0 .81, 95% CI [–0.49, 0.38]), mothers’ WFC (t(587) = − 0.27, p = 0.89, 95% CI [–0.43, 0.51]), and academic adjustment (t(587) = − 0.55, p = 0.71, 95% CI [–4.30, 3.55]). These results suggest the absence of systematic attrition bias. Data collection procedure for adolescents: the baseline data were collected in September 2020. Adolescents completed the questionnaires during a 45-minute regular class session in a group-administered format. The survey administrators were postgraduate students in psychology and trained school counselors. Questionnaires were collected immediately upon completion to ensure data quality. All collected questionnaires were screened for validity; those with over 85% missing data or exhibiting patterned responses were excluded from analysis. 2.2 Procedure Data collection procedure for parents: Adolescents took sealed envelopes containing the parent questionnaires home. They were instructed to ask both their father and mother to complete the surveys separately and independently. Parents were asked to seal their completed questionnaires in the provided envelopes, which the students then returned to their homeroom teacher within one week. The parent questionnaires assessed their own WFC and collected basic demographic information. In families with more than one child within the target age range, parents were requested to report based on the participating adolescent only. All participating adolescents and their parents received an honorarium of 50 RMB for each completed wave of assessment. The study procedures were approved by the Institutional Review Board of the School of Psychology (Approval No: HR2018-10-002). 2.3Measures Parents’ Work-Family Conflict : This study assessed Work-Family Conflict (WFC) for both fathers and mothers using the conflict subscale of the Work-Family Spillover Scale (Wayne et al., 2004 ). The full scale contains two dimensions: work to family conflict and work to family enhancement, each comprising 8 items. This study utilized only the conflict subscale. Both parents reported on their own experiences using a Likert 5-point scale ( 1 = “Never”, 2 = “Rarely”, 3 = “Sometimes”, 4 = “Often”, 5 = “Always” ). Higher scores indicate a higher level of conflict experienced by the participant. Parents reported WFC using the Work-Family Spillover Scale (Wayne et al., 2004 ). This questionnaire consisted of 8 items, describing two aspects from WFC (8 items, e.g., “My job reduces the effort I can give to activities at home”). The Chinese version of this questionnaire has been validated (Ma et al., 2018) . Parents indicated how often they had experienced each during the last month on a five-point Likert scale ranging from 1 ( all the time )to 5 ( never ). Items were scored such that higher scores meant more conflict. Cronbach’s alpha coefficients ranged from 0.87–0.94across T1–T4 for both mothers and fathers, respectively. The confirmatory factor analysis indicated good structure validity of the scale. WFC for fathers: T1 : χ 2 /df = 2.87, CFI = 0.95, TLI = 0.92, RMSEA = 0.08; T2 : χ 2 /df = 2.54, CFI = 0.97, TLI = 0.95, RMSEA = 0.07; T3 : χ 2 /df = 1.98, CFI = 0.98, TLI = 0.97, RMSEA = 0.06; T4 : χ 2 /df = 2.14, CFI = 0.98, TLI = 0.96, RMSEA = 0.06);WFC for mothers༚ T1 : χ 2 /df = 2.0, CFI = 0.98, TLI = 0.96, RMSEA = 0.06; T2 : χ 2 /df = 2.58, CFI = 0.97, TLI = 0.95, RMSEA = 0.07; T3 : χ 2 /df = 1.75, CFI = 0.98, TLI = 0.97, RMSEA = 0.05; T4 : χ 2 /df = 2.58, CFI = 0.97, TLI = 0.95, RMSEA = 0.07. All factor loadings in the above tests were within above 0.40 ( p s < 0.001). Academic adjustment: This study used the 24-item Learning Adjustment Scales (Midgley et al., 2000) to assess the academic adjustment of adolescents. This scale included three subscales: academic pressure ( e.g., “Having to study things you do not understand” ), academic efficiency ( e.g., “Well behaved in school” ), and academic burnout ( e.g., “My study is so poor that I really want to give it up” ). For the above statements, responses ranged from 1 ( never true ) to 5 ( always true ), with items reverse-scored when necessary, and higher scores representing greater dysfunctional. The Cronbach’s alpha coefficients of each subscale ranged from 0.70 to 0.83 in this study. In the analytic sample the internal consistency was fair across four waves (α 1 = 0.70, α 2 = 0.72, α 3 = 0.74, α 4 = 0.75). The confirmatory factor analysis indicated good structure validity of the scale. ( T1 : χ 2 /df = 1.76, CFI = 0.99, TLI = 0.98, RMSEA = 0.05; T2 : χ 2 /df = 1.86, CFI = 0.99, TLI = 0.98, RMSEA = 0.05; T3 : χ 2 /df = 2.41, CFI = 0.97, TLI = 0.95, RMSEA = 0.07; T4 : χ 2 /df = 1.71, CFI = 0.99, TLI = 0.98, RMSEA = 0.05). 2.4 Data processing First, means, standard deviations and correlations for all study variables are presented in Table 1 . Polyserial correlation coefficients were calculated so as to allow estimation of the magnitude of bivariate relations between continuously measured indicators of WFC, academic adjustment. In the second step, to examine the developmental trends of adolescent academic adjustment, latent growth models (LGM) were fitted, including an unconditional linear LGM and an unconditional nonlinear LGM, to assess the trajectory of adolescent academic adjustment across middle school years. For the nonlinear LGM, the loadings on the slope factor were fixed at 0 and 1 for T1 and T4, respectively, and were freely estimated for the intermediate time points to optimally correspond to the unique characteristics of the data. Based on the growth shape determined by LGM, bivariate parallel process LGMs were employed to examine the relations between the developmental trajectories of parents’ WFC and academic adjustment, as indexed by intercept-intercept and slope-slope associations. We specified longitudinal cross-lagged panel models to determine whether father and mothers’ WFC predict academic adjustment or vice versa. Finally, We conducted a parallel process LGM models to examine the relationship between adolescent academic adjustment and parents’ WFC. All models were run using the robust maximum likelihood (MLR) estimator. The goodness of fit was assessed using convergence across multiple fit indices, including the root mean square error of approximation (RMSEA), Tucker–Lewis Index (TLI), and comparative fit index (CFI). The model fit is considered adequate if the CFI and TLI values are ≥ 0.90 and better if they are ≥ 0.95. The cutoff value for the RMSEA is ≤ 0.08, with a better fit indicated at ≤ 0.05 (Hu and Bentler, 1999). 3. Results 3.1. Preliminary analyses The data gathered in this study were based on self-reports, which can potentially introduce a typical methodological bias. After data collection, the common method bias across all four tests was evaluated using the Harman single-factor test (Harman'Single-Factor Test, Podsakoff et al., 2003 ). The first factor explains 17.23, 18.88, 18.11and 21.15% of the variance at T1, T2, T3, and T4, respectively. These values fall below the critical threshold of 40% (Dandan Tangn, Zhonglin Wen, 2020), indicating no significant common method bias in the four measurements. The longitudinal measurement invariance of the study variables over time was assessed by fitting and comparing a series of progressively more constrained models. Given the sensitivity of the Chi-square difference test to larger sample sizes, it is recommended to examine changes in the Tucker-Lewis Index (TLI) and comparative fit index (CFI), when sample sizes exceed 300 cases. Specifically, when ΔTLI and ΔCFI are ≤ 0.02, the conditions for different levels of measurement in variance are considered met (Chen, 2007). The results indicated that longitudinal scalar in variance was established for all variables (see Table 1 ). Table 1 Model Fit Indices for Testing Longitudinal Measurement Invariance Model Parameter Estimation Model Comparison Variable Model χ 2 df RMSEA CFI TLI ΔCFI ΔTLI Fathers’ WFC M1 886.92 404 0.060 0.932 0.917 M2 941.27 425 0.061 0.927 0.915 M2-M1 –0.005 –0.002 M3 986.25 443 0.061 0.924 0.914 M3-M2 –0.003 –0.001 M4 994.42 456 0.060 0.924 0.918 M4-M3 0.000 0.004 Mothers’ WFC M1 757.22 410 0.051 0.924 0.908 M2 791.23 431 0.050 0.921 0.910 M2-M1 –0.003 0.002 M3 820.86 447 0.050 0.918 0.909 M3-M2 –0.003 –0.001 M4 858.58 469 0.050 0.915 0.910 M4-M3 –0.003 0.001 Academic Adjustment M1 459.35 210 0.060 0.944 0.926 M2 479.59 225 0.059 0.942 0.929 M2-M1 –0.002 0.003 M3 520.34 235 0.061 0.936 0.924 M3-M2 –0.006 –0.005 M4 534.52 248 0.059 0.935 0.928 M4-M3 –0.001 0.004 Note. WFC = work family conflict 3.2.Descriptive statistics and correlation Descriptive statistics and bivariate correlations among academic adjustment, mothers’ and fathers’ WFC each time point are presented in Table 1 . Associations between consecutive time points showed medium stability over time for fathers’ WFC ( rs = 0.36–0.41, ps < 0.001), mothers’ WFC ( rs = 0.31–0.40, ps < 0.001), and adolescent academic adjustment ( rs = 0.37–0.49, ps < 0.001). Within-time associations between fathers’ WFC and academic adjustment indicated a relatively medium degree of co-occurrence ( rs = − 0.30 – − 0.54, ps < 0.001), whereas those between mothers’ WFC and academic adjustment showed a week degree of co-occurrence ( rs = − 0.10 – − 0.22, ps < 0.001). Table 2 Descriptive statistics and correlations for all study variables ( N = 329) Variables 1 2 3 4 5 6 7 8 9 10 11 12 1.WFC (F) -T1 – 2.WFC (F) -T2 0.41 ** − 3.WFC (F) -T3 0.35 ** 0.51 ** − 4.WFC (F) -T4 0.32 ** 0.40 ** 0.40 ** − 5.WFC (M) -T1 0.36 ** 0.18 ** 0.13 ** 0.08 * − 6.WFC (M) -T2 0.23 ** 0.28 ** 0.08 ** 0.06 * 0.35 ** − 7.WFC (M) -T3 0.13 ** 0.12 ** 0.23 ** 0.21 ** 0.40 ** 0.46 ** − 8.WFC (M) -T4 0.08 ** 0.08 ** 0.08 ** 0.17 ** 0.31 ** 0.43 ** 0.40 ** − 9.AcademicAdjustment-T1 –0.54 ** –0.34 ** –0.36 ** –0.38 ** –0.22 ** –0.15 ** –0.14 ** –0.12 ** − 10.Academic Adjustment-T2 –0.43 ** –0.45 ** –0.30 ** –0.32 ** –0.15 ** –0.17 ** –0.14 ** –0.13 ** 0.46 ** − 11.Academic Adjustment-T3 –0.33 ** –0.32 ** –0.42 ** –0.47 ** –0.11 ** –0.12 ** –0.18 * –0.14 ** 0.49 ** 0.53 ** − 12.Academic Adjustment-T4 –0.30 ** –0.31 ** –0.37 ** –0.53 ** –0.10 ** –0.13 ** –0.11 * –0.18 ** 0.37 ** 0.44 ** 0.56 ** M 2.52 2.33 2.60 2.72 2.21 2.39 2.21 2.57 2.51 2.31 2.24 1.88 SD 0.47 0.46 0.54 0.45 0.30 0.52 0.60 0.47 0.45 0.33 0.40 0.38 Note. p * < 0.05, p ** < 0.001 3.3 Development trajectory of adolescent academic adjustment To investigate the general developmental trends of early adolescent academic adjustment, linear unconditional latent growth models (LGM) and quadratic unconditional LGMs of the aforementioned variables were constructed. From the model fit indices of early adolescent academic adjustment, the fit indices of the linear unconditional LGM were significantly better than those of the quadratic unconditional academic adjustment model: ( χ 2 = 13.00, df = 5, CFI = 0.977, TLI = 0.973, RMSEA = 0.070). This indicates that adolescent academic adjustment shows a linear trend of development over the two-year period, with an initial level of academic adjustment quantified at 2.51, which is significantly greater than 0. Over four measurements, a declining trend was observed (slope = − 0.19, p < 0.001). Furthermore, the variance of the intercept for academic adjustment (σ 2 = 0.38, p < 0.00) and the variance of the slope (σ 2 = 0.02, p = 0.04) were both significantly greater than 0, suggesting that there are significant individual differences in both the initial level and rate of development in academic adjustment. However, there was no significant correlation between the intercept and slope ( r = 0.02, SE = 0.02, p > 0.05), indicating that the initial level of academic adjustment does not affect its rate of change. The results show that adolescent academic adjustment exhibits a linear decline, and there are individual differences in both the initial level and development speed (see Fig. 1). Fig. 1. Development trajectory of academic adjustment 3.4 Direction of effects between parents’ WFC and adolescent academic adjustment A longitudinal panel model with auto-regressive and cross-lagged paths was estimated to test for the directionality of effects between parents’ WFC and academic adjustment. The initial auto-regressive model included all continuity paths across time for each construct and the cross-sectional correlations among constructs. This model demonstrated a good fit to the data ( χ 2 = 2501.507, df = 1465, RMSEA = 0.046, CFI = 0.920, TLI = 0.932). The results indicated that relative standing on all variables was stable (i.e., all auto-regressive paths were statistically significant ( p < 0.001, βs ranged from 0.36 to 0.40). Cross-sectional correlations among the constructs indicated negative correlations between fathers’ WFC and academic adjustment at each time point, suggesting that fathers’ WFC were associated with descend concurrent adolescent academic adjustment at all time points. The CLMP of fathers’ and mothers’ WFC and adolescent academic adjustment demonstrated a good fit to the data ( χ 2 = 2501.507, df = 1465, RMSEA = 0.046, CFI = 0.920, TLI = 0.932). The results showed a reciprocal relationship between fathers’ WFC and academic adjustment from Time 1 to Time 4, but not mothers. More specifically, the structural equation model showed that greater fathers’ WFC were associated with worse and academic adjustment vice versa. In contrast, mothers’ WFC not significantly predicting adolescent academic adjustment, and the reverse association was not significant also (see Fig. 2 ). The CLMP model just only be capable of uncovering the mutual predictive relationship among variables; however, it is unable to account for the directionality of covariation. Consequently, in the subsequent stage, a parallel latent variable analysis will be carried out separately regarding the father’s WFC and adolescent academic adjustment. 3.5 Co-development associations between parents’ WFC and adolescent academic adjustment To examine the co-development associations between fathers’ WFC and academic adjustment, parallel process LGMs were fitted ( χ 2 = 86.25, df = 43, CFI = 0.93, TLI = 0.89, RMSEA = 0.03), and the initial level of fathers’ WFC significantly predicting the intercept(β = − 0.85, SE = 0.12, p < 0.001) and slope (β = − 0.16, SE = 0.06, p = 0.03) of academic adjustment. Then another parallel process LGMs were construct to test whether academic adjustment could inversely predict the fathers’ WFC, This model fit the data well ( χ 2 = 90.30, df = 43, CFI = 0.93, TLI = 0.90, RMSEA = 0.06), suggesting intercept of academic adjustment negatively and significantly predicting the intercept (β = − 0.94, SE = 0.14, p < 0.001)and slope (β = − 0.23, SE = 0.60, p = 0.04) of father’s WFC, and the slope of academic adjustment also predicting the slope of father’s WFC also (β = − 0.46, SE = 0.22, p = 0 .03). The results suggesting that the higher initial level of fathers’ WFC, the worse of the academic adjustment will be, the slower the improvement of their academic adjustment will be. Additionally, the higher the initial level of academic adjustment were associated with lower baseline fathers’ WFC and the slower the growth rate of fathers’ WFC, and the growth rate of academic adjustment is faster, and the change rate of fathe’s WFC is also slower. Mothers’ WFC not significantly predict adolescent academic adjustment at any of the time included in the current study, and so the model construction was not carried out. 4. Discussion Across societies, parents are required to simultaneously manage the demands of work and family roles. Difficulties in balancing these responsibilities may undermine family functioning and compromise the effective fulfillment of parental roles, thereby adversely affecting adolescents’ healthy development. Building on this perspective, the present study examined the longitudinal associations between parents’ WFC and early adolescents’ academic adjustment. 4.1 Development of Adolescent Academic Adjustment During early adolescence, adolescents’ academic adjustment generally exhibits a declining trend as they grow older. This pattern has been supported by numerous studies conducted in China, which have shown that first-year middle school students demonstrate significantly better academic adjustment than students in the second year (Wendao Li et al., 2003), and that academic adjustment abilities tend to decrease with age among middle school students (Aifen Song et al., 2007). Similarly, longitudinal research in Western contexts has documented a clear linear decline in academic adjustment among American middle school students from sixth to eighth grade, accompanied by decreases in learning motivation and academic performance (Weeks et al., 2016 ). Consistent with these findings, the present study reveals that early adolescents’ academic adjustment deteriorates across the two-year observation period. In addition, substantial individual differences were observed in both the initial levels and rates of change in academic adjustment, indicating that adolescents enter middle school with varying levels of academic adjustment and exhibit heterogeneous developmental trajectories over time. Moreover, the initial level of academic adjustment was not significantly associated with its slope, suggesting that the rate of change in academic adjustment remains relatively independent of adolescents’ starting levels (Mund & Nestler, 2019 ). Specifically, adolescents enter school with distinct personality characteristics shaped by diverse family backgrounds, resulting in variability in academic performance at school entry. Although many characteristics and behavioral patterns related to academic adjustment show continuity during early adolescence, significant academic difficulties tend to emerge gradually over time among middle school students (McLaughlin &King, 2015). Consistent with the present findings, previous research has reported a declining trend in academic adjustment across adolescence (Vanhalst et al., 2013 ) or a stabilization of academic adjustment during later stages of adolescence (Danneel et al., 2020 ). Moreover, a recent meta-analysis demonstrated a general decline in academic motivation and adjustment during early adolescence, followed by relative stabilization during middle to late adolescence ( Mund et al. 2020). 4.2 Changes in Parents’ WFC and the Development of Adolescent Academic Adjustment The findings of the present study indicate a bidirectional association between parents’ WFC and adolescents’ academic adjustment, consistent with prior research (Dinh et al., 2017 ; Jeffrey H. Greenhaus & Foley, 2007 ; Rahman & Ali, 2020 ; Zou et al., 2021 ). An increase in parents’ WFC is associated with greater levels of academic maladjustment among adolescents, including behaviors such as school avoidance and dropout (Chai & Schieman, 2021). Parents’ irregular work schedules, such as overtime or night shifts, may limit their opportunities to engage fully in their adolescents’ academic activities and educational supervision (J. Li et al., 2014 ). This lack of parental planning and monitoring is particularly consequential during early adolescence, a developmental period in which insufficient academic guidance may foster negative attitudes toward learning and contribute to declines in academic performance (Carlo et al., 2018). At the same time, adolescents’ academic maladjustment may also exacerbate parents’ WFC. The psychological strain associated with raising an adolescent who struggles academically can deplete parents’ cognitive and emotional resources, increase interparental conflict, and generate a negative feedback loop. When combined with other family responsibilities, this resource depletion may intensify parents’ experience of WFC and contribute to its accumulation over time (Chee et al., 2009 ). From a family systems perspective, the family functions as an interconnected unit in which changes in one member inevitably influence others and the broader family environment. Accordingly, WFC may disrupt family relationships and functioning, while adolescents’ characteristics and adjustment difficulties may, in turn, interfere with parents’ capacity to manage work-family demands. The findings of the present study further support this theoretical perspective. Notably, the interaction patterns between fathers’ and mothers’ WFC and early adolescents’ academic adjustment exhibit temporal differences and subtle distinctions. These patterns can be better understood in light of changes in family environments and family relationships across different stages of adolescent development. Specifically, a bidirectional relationship was observed between fathers’ work–family conflict and adolescents’ academic adjustment, suggesting a reciprocal pathway between fathers’ experiences at the work-family interface and adolescents’ developmental outcomes. In contrast, this bidirectional association was not evident in the relationship between mothers’ WFC and adolescents’ academic adjustment. Moreover, the initial level of fathers’ WFC not only predicted subsequent levels of adolescents’ academic adjustment but also forecasted the trajectory of change in academic adjustment over time. This finding indicates that early adolescents’ academic adjustment is particularly sensitive to fathers’ WFC. As children grow older, especially during the transition into early adolescence, fathers’ supervisory and regulatory roles become increasingly salient. Adolescents who report higher levels of paternal supervision tend to demonstrate stronger academic achievement compared with those who report lower levels of paternal supervision (Criss et al., 2015; Dishion, Bullock, & Kiesner, 2008; Hill & Tyson, 2009; Véronneau & Dishion, 2012), and the inverse pattern is observed when paternal supervision is limited. In other words, the association between fathers’ WFC and adolescents’ academic adjustment appears to be more proximal, and the dynamic linkage between the developmental trajectories of fathers’ WFC and early adolescents’ academic adjustment is stronger, with the two processes showing near-synchronous change over time. Notably, both the initial level and the developmental course of fathers’ WFC were negatively predicted by changes in adolescents’ academic adjustment. This pattern is consistent with prior research suggesting that fathers are more sensitive to adolescents’ academic performance (Collins & Russell, 1991 ). Such sensitivity may reflect developmental shifts in children’s needs for paternal involvement as they grow older, as well as differences in parental beliefs regarding appropriate forms of involvement in adolescents’ lives. For example, mothers may place greater emphasis on adolescents’ independence in daily functioning and emotional well-being (Hays, 1998), whereas fathers may be less focused on the emotional aspects of parent-child relationships and more oriented toward discipline, preparation for future roles, and the attainment of social status. Since the reinstatement of China’s National College Entrance Examination (Gaokao) in the 1970s, education and academic achievement have become central societal concerns, widely regarded as the primary pathways to admission into prestigious universities and subsequent access to upward social mobility. As a result, Chinese parents tend to hold high educational expectations for their children and are often willing to invest substantial time, energy, and resources to support their adolescents’ academic success. Within this cultural context, both parents commonly reach a shared understanding of the importance of academic performance. This emphasis is particularly pronounced among fathers, who traditionally bear responsibility for the continuation and honor of the family lineage (Fuligni & Zhang, 2017 ; L. Li et al., 2020 ). Historically, individual competence in China has been closely evaluated through academic achievement. Consequently, adolescents’ academic performance is not only viewed as a determinant of their future personal success but also as a reflection of family status and honor, rendering academic success a particularly salient concern for fathers. 4.3 Limitations and Future Directions Although the present study extends the literature by examining the relationship between parents’ WFC and early adolescents’ academic adjustment from a dynamic developmental perspective, several limitations should be acknowledged. First, the developmental trajectories analyzed in this study were confined to the junior high school period. Future research should adopt a longer developmental time frame and include additional stages, such as late elementary school and high school, to determine whether the association between parents’ WFC and adolescents’ academic adjustment follows a universal developmental pattern. Second, the data primarily relied on self-reports from adolescents and their parents. Although self-report measures are effective for capturing subjective perceptions, future studies would benefit from incorporating multiple sources of information, such as teacher reports and official school records, as well as objective indicators, including parents’ actual working hours and standardized measures of adolescents’ academic performance. Such multi-informant and multi-method approaches would provide more robust evidence and help reduce potential common method bias. Third, data were collected at six-month intervals in the present study. Future research employing shorter assessment intervals, such as monthly or quarterly measurements within intensive longitudinal designs, may more precisely capture the dynamic and reciprocal processes linking parents’ WFC and adolescents’ academic adjustment. In addition, this study primarily focused on direct associations between parents’ work–family conflict and adolescents’ academic adjustment. Future investigations should further explore potential mediating mechanisms, such as parents’ psychological stress and the quality of parent-child relationships, as well as moderating factors, including family socioeconomic status, adolescent gender, and school support. Finally, the sample was drawn from three middle schools in Nanchang, China, which may limit the generalizability of the findings. The conclusions may not directly extend to adolescents in other regions of China (e.g., rural areas) or to populations in different cultural contexts. Future studies should examine the universality of these relationships using more diverse and representative samples. 5. Conclusions The following results can be drawn from the study: (1)Based on the latent variable growth model, adolescent academic adjustment shows a linear declining trend from the end of seventh grade to the end of eighth grade, suggestion that with the increase in age and academic tasks, academic adjustment becomes increasingly poor. (2)According to the results of cross-lagged analysis, fathers’ WFC and academic adjustment exhibit a bidirectional predictive relationship, whereas the direct influence of mother WFC on adolescent academic adjustment is not significant. (3)The parallel latent growth model results of parents’ WFC and early adolescent academic adjustment indicate that fathers’ WFC and adolescent academic adjustment demonstrating a synchronous development pattern. Furthermore, the initial level of fathers’ WFC can predict not only the initial level of adolescent academic adjustment but also the rate of development; the higher the initial level of fathers’ WFC, the poorer the adolescent academic adjustment and the slower the growth in adjustment ability, and vice versa. Conversely, adolescent academic adjustment can predict fathers’ WFC; the higher the level of academic adjustment, the lower the fathers’ WFC, with a slower rate of change, while the improvement in academic adjustment occurs at a faster rate, leading to a slower development of fathers’ WFC. Declarations Funding This research received no external funding. Author Contribution Xiaoli Wang: Contributed to Conceptualization, Formal Analysis, and Writing – Original Draft.Cui Wang: Contributed to Investigation, Data Curation, and Writing – Review & Editing.Zilalai Yashengjiang: Contributed to Writing – Review & Editing and MethodologyHanjin Bao (Corresponding author. E-mail: [email protected] ): Contributed toWriting – Review & Editing and SoftwareShibo Li: Contributed to Supervision, Validation, Writing – review & editing.Shuo Liu: Contributed to Validation, Data Curation. Data Availability All data generated or analysed during this study are included in this published article. All methods were performed in accordance with the relevant guidelines and regulations Additional Information (including a Competing Interests Statement) No potential conflict of interest was reported by the authors. References Abdollahi, A., Panahipour, S., Akhavan Tafti, M., & Allen, K. A. (2020). Academic hardiness as a mediator for the relationship between school belonging and academic stress. Psychology in the Schools, 57(5), 823–832. https://doi.org/10.1002/pits.22339 Allen, T. D., French, K. A., Braun, M. T., & Fletcher, K. (2019). The passage of time in work-family research: Toward a more dynamic perspective. Journal of Vocational Behavior, 110(December 2018), 245–257. https://doi.org/10.1016/j.jvb.2018.11.013 Baker, J. A. (2006). Contributions of teacher-child relationships to positive academic adjustment during elementary school. Journal of School Psychology, 44(3), 211–229. https://doi.org/10.1016/j.jsp.2006.02.002 Bakker, A. B., Demerouti, E., & Burke, R. (2009). Workaholism and Relationship Quality: A Spillover-Crossover Perspective. Journal of Occupational Health Psychology, 14(1), 23–33. https://doi.org/10.1037/a0013290 Bakker, A. B., Shimazu, A., Demerouti, E., Shimada, K., & Kawakami, N. (2014). Work engagement versus workaholism: A test of the spillover-crossover model. Journal of Managerial Psychology, 29(1), 63–80. https://doi.org/10.1108/JMP-05-2013-0148 Birch, S. H., & Ladd, G. W. (1997). The teacher-child relationship andadolescents early academic adjustment. Journal of School Psychology, 35(1), 61–79. https://doi.org/10.1016/S0022-4405(96)00029-5 Blake, J. (1981). Family size and the quality of children. Demography, 18(4), 421–442. https://doi.org/10.2307/2060941 Borelli, J. L., Nelson, S. K., River, L. M., Birken, S. A., & Moss-Racusin, C. (2017). Gender Differences in Work-Family Guilt in Parents of Young Children. Sex Roles, 76(5–6), 356–368. https://doi.org/10.1007/s11199-016-0579-0 Bouchey, H. A., & Harter, S. (2005). Reflected appraisals, academic self-perceptions, and math/science performance during early adolescence. Journal of Educational Psychology, 97(4), 673–686. https://doi.org/10.1037/0022-0663.97.4.673 Brière, F. N., Janosz, M., Fallu, J. S., & Morizot, J. (2015). Adolescent Trajectories of Depressive Symptoms: Codevelopment of Behavioral and Academic Problems. Journal of Adolescent Health, 57(3), 313–319. https://doi.org/10.1016/j.jadohealth.2015.05.012 Brown, T. J. (2014). Work Family Conflict Among Parents of Atypically Developing Children: Exploring the Impact of Worker, Work, and Child Factors. Journal of Child and Family Studies, 23(5), 854–862. https://doi.org/10.1007/s10826-013-9739-9 Cenk, D. S., & Demir, A. (2016). The Relationship Between Parenting Style, Gender and Academic Achievement with Optimism Among Turkish Adolescents. Current Psychology, 35(4), 720–728. https://doi.org/10.1007/s12144-015-9375-1 Chee, K. H., Conger, R. D., & Elder, G. H. (2009). Mother'S Employment Demands, Work-Family Conflict, and Adolescent Development. International Journal of Sociology of the Family, 35(2), 189–202. http://www.ncbi.nlm.nih.gov/pubmed/20927198%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2949071 Cho, Y., & Coulton, C. J. (2016). The Effects of parental Nonstandard Work Schedules on Adolescents' Academic Achievement in Dual-Earner Households in South Korea. Child Indicators Research, 9(1), 193–212. https://doi.org/10.1007/s12187-015-9308-4 Collins, W. A., & Russell, G. (1991). Mother-child and father-child relationships in middle childhood and adolescence: A developmental analysis. Developmental Review, 11(2), 99–136. https://doi.org/10.1016/0273-2297(91)90004-8 Craig, L., & Sawrikar, P. (2008). Satisfaction with work-family balance for parents of early adolescents compared to parents of younger children. Journal of Family Studies, 14(1), 91–106. https://doi.org/10.5172/jfs.327.14.1.91 Danneel, S., Geukens, F., Maes, M., Bastin, M., Bijttebier, P., Colpin, H., Verschueren, K., & Goossens, L. (2020). Loneliness, Social Anxiety Symptoms, and Depressive Symptoms in Adolescence: Longitudinal Distinctiveness and Correlated Change. Journal of Youth and Adolescence, 49(11), 2246–2264. https://doi.org/10.1007/s10964-020-01315-w Dinh, H., Cooklin, A. R., Leach, L. S., Westrupp, E. M., Nicholson, J. M., & Strazdins, L. (2017). Parents' transitions into and out of work-family conflict andadolescents mental health: Longitudinal influence via family functioning. Social Science and Medicine, 194(October), 42–50. https://doi.org/10.1016/j.socscimed.2017.10.017 Eccles, J. S., Roeser, R. W., Wigfield, A., & Freedman-Doan, C. (1999). Academic and motivational pathways through middle childhood. Child Psychology: A Handbook of Contemporary Issues, January 2014, 287–317. Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(February), 109–132. https://doi.org/10.1146/annurev.psych.53.100901.135153 Fan, J., & Chen, B. Bin. (2020). Parenting styles and coparenting in China: The role of parents andadolescents sibling status. Current Psychology, 39(5), 1505–1512. https://doi.org/10.1007/s12144-019-00379-7 Fortin, L., Marcotte, D., Diallo, T., Potvin, P., & Royer, É. (2013). A multidimensional model of school dropout from an 8-year longitudinal study in a general high school population. European Journal of Psychology of Education, 28(2), 563–583. https://doi.org/10.1007/s10212-012-0129-2 Frone, M. R., Russell, M., & Cooper, M. L. (1992). Antecedents and outcomes of work^family conflict: Testing a model of the work^family interface. In Journal of Applied Psychology (Vol. 77, Issue 1, pp. 65–78). https://doi.org/10.1037//0021-9010.77.1.65 Fuligni, A. J., & Zhang, W. (2017). Attitudes toward family obligation among adolescents in contemporary Urban and rural China.adolescents Services in the Developing World, 74(1), 135–148. https://doi.org/10.4324/9781315260495-22 Greenhaus, J. H., & Beutell, N. J. (1985). Sources of Conflict Between Work and Family Roles. Academy of Management Review, 10(1), 76–88. https://doi.org/10.5465/amr.1985.4277352 Greenhaus, Jeffrey H., & Foley, S. (2007). The intersection of work and family lives. Handbook of Career Studies, January 2007, 131–152. https://doi.org/10.4135/9781412976107.n8 Hannum, E., Kong, P., & Zhang, Y. (2009). Family sources of educational gender inequality in rural China: A critical assessment. International Journal of Educational Development, 29(5), 474–486. https://doi.org/10.1016/j.ijedudev.2009.04.007 Jiang, S., & Dong, L. (2020). Association between deprivation and cognitive ability among Chinese adolescents: Examining the mechanisms of parents’ involvement in a rural–urban dual system. Current Psychology. https://doi.org/10.1007/s12144-020-00981-0 Kiuru, N., Nurmi, J. E., Aunola, K., & Salmela-Aro, K. (2009). Peer group homogeneity in adolescents' academic adjustment varies according to peer group type and gender. International Journal of Behavioral Development, 33(1), 65–76. https://doi.org/10.1177/0165025408098014 Lee, Y., Parish, W. L., & Willis, R. J. (1994). Support in Taiwan '. 99(4), 1010–1041. Li, J., Johnson, S. E., Han, W. J., Andrews, S., Kendall, G., Strazdins, L., & Dockery, A. (2014). Parents' nonstandard work schedules and child well-being: A critical review of the literature. Journal of Primary Prevention, 35(1), 53–73. https://doi.org/10.1007/s10935-013-0318-z Li, L., Shi, J., Wu, D., & Li, H. (2020). Only child, parental educational expectation, self-expectation and science literacy in Zhuang adolescents in China: A serial mediation model. Children and Youth Services Review, 115(May), 105084. https://doi.org/10.1016/j.childyouth.2020.105084 Matias, M., Ferreira, T., Vieira, J., Cadima, J., Leal, T., & M. Matos, P. (2017). Work–family conflict, psychological availability, and child emotion regulation: Spillover and crossover in dual-earner families. Existing Measures of Emotion Dysregulation Typically Assess Dispositional Tendencies and Are Therefore Not Well Suited for Study Designs That Require Repeated Assessments over Brief Intervals. The Aim of This Study Was to Develop and Validate a State-Base, 24(3), 623–639. https://doi.org/10.1111/pere.12198 Matias, M., & Recharte, J. (2020). Links Between Work–Family Conflict, Enrichment, and Adolescent Well-Being: Parents' andadolescents Perspectives. Family Relations. https://doi.org/10.1111/fare.12453 Maughan, B., Rowe, R., Messer, J., Goodman, R., & Meltzer, H. (2004). Conduct Disorder and Oppositional Defiant Disorder in a national sample: Developmental epidemiology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 45(3), 609–621. https://doi.org/10.1111/j.1469-7610.2004.00250.x Moilanen, K. L., Rasmussen, K. E., & Padilla-Walker, L. M. (2015). Bidirectional Associations Between Self-Regulation and Parenting Styles in Early Adolescence. Journal of Research on Adolescence, 25(2), 246–262. https://doi.org/10.1111/jora.12125 Mund, M., & Nestler, S. (2019). Beyond the Cross-Lagged Panel Model: Next-generation statistical tools for analyzing interdependencies across the life course. Advances in Life Course Research, 41. https://doi.org/10.1016/j.alcr.2018.10.002 Phillipson, S., & Phillipson, S. N. (2007). Academic expectations, belief of ability, and involvement by parents as predictors of child achievement: A cross-cultural comparison. Educational Psychology, 27(3), 329–348. https://doi.org/10.1080/01443410601104130 Podsakoff, P. M., MacKenzie, S. B., Podsakoff, N. P., & Lee, J. Y. (2003). The mismeasure of man(agement) and its implications for leadership research. Leadership Quarterly, 14(6), 615–656. https://doi.org/10.1016/j.leaqua.2003.08.002 Powell, G. N., & Greenhaus, J. H. (2006). Managing incidents of work-family conflict: A decision-making perspective. In Human Relations (Vol. 59, Issue 9). https://doi.org/10.1177/0018726706069765 Rahman, M. M., & Ali, N. A. (2020). Does work–family balance mediate the relationship between work–family conflicts and job satisfaction of academicians? Journal of Community Psychology, October, 1–14. https://doi.org/10.1002/jcop.22464 Roisman, G. I., Aguilar, B., & Egeland, B. (2004). Antisocial behavior in the transition to adulthood: The independent and interactive roles of developmental history and emerging developmental tasks. Development and Psychopathology, 16(4), 857–871. https://doi.org/10.1017/S0954579404040040 Shim, S. S., & Finch, W. H. (2014). Academic and social achievement goals and early adolescents' adjustment: A latent class approach. Learning and Individual Differences, 30, 98–105. https://doi.org/10.1016/j.lindif.2013.10.015 Tseng, V. (2004). Family interdependence and academic adjustment in college: Youth from immigrant and U.S.-born families. Child Development, 75(3), 966–983. https://doi.org/10.1111/j.1467-8624.2004.00717.x Twenge, J. M., & Nolen-Hoeksema, S. (2002). Age, gender, race, socioeconomic status, and birth cohort differences on theadolescents Depression Inventory: A meta-analysis. Journal of Abnormal Psychology, 111(4), 578–588. https://doi.org/10.1037/0021-843X.111.4.578 Vanhalst, J., Luyckx, K., Scholte, R. H. J., Engels, R. C. M. E., & Goossens, L. (2013). Low self-esteem as a risk factor for loneliness in adolescence: Perceived - But not actual - Social acceptance as an underlying mechanism. Journal of Abnormal Child Psychology, 41(7), 1067–1081. https://doi.org/10.1007/s10802-013-9751-y Veas, A., Castejón, J.-L., Miñano, P., & Gilar-Corbí, R. (2019). Early Adolescents' Attitudes and Academic Achievement: The Mediating Role of Academic Self-concept. Revista de Psicodidáctica (English Ed.), 24(1), 71–77. https://doi.org/10.1016/j.psicoe.2018.11.002 Wang, H., & Cai, T. (2017). parental involvement, adolescents' self-determined learning and academic achievement in Urban China. International Journal of Psychology, 52(1), 58–66. https://doi.org/10.1002/ijop.12188 Wayne, J. H., Musisca, N., & Fleeson, W. (2004). Considering the role of personality in the work-family experience: Relationships of the big five to work-family conflict and facilitation. Journal of Vocational Behavior, 64(1), 108–130. https://doi.org/10.1016/S0001-8791(03)00035-6 Weeks, M., Ploubidis, G. B., Cairney, J., Wild, T. C., Naicker, K., & Colman, I. (2016). Developmental pathways linking childhood and adolescent internalizing, externalizing, academic competence, and adolescent depression. Journal of Adolescence, 51, 30–40. https://doi.org/10.1016/j.adolescence.2016.05.009 Zahed Zahedani, Z., Rezaee, R., Yazdani, Z., Bagheri, S., & Nabeiei, P. (2016). The influence of parenting style on academic achievement and career path. Journal of Advances in Medical Education & Professionalism, 4(3), 130–134. http://www.ncbi.nlm.nih.gov/pubmed/27382580%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4927255 Zou, S., Wu, X., Ren, Y., & Wang, X. (2021). Actor–partner association of work–family conflict and parental depressive symptoms during COVID-19 in China: Does coparenting matter? Applied Psychology: Health and Well-Being, September, 1–19. https://doi.org/10.1111/aphw.12312 Tang Dandan,Wen Zhonglin. (2020). Common Method Bias Test: Problem Suggestions. 31771245, 215–223. https://doi.org/10.16719/j.cnki.1671-6981.20200130 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8598251","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":592783149,"identity":"31b4819a-915b-4fdd-9b5c-13e2c0ed5b1b","order_by":0,"name":"Xiaoli Wang","email":"","orcid":"","institution":"Changji University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Wang","suffix":""},{"id":592783150,"identity":"4306b686-3e61-41b1-8ac6-53f147747cbb","order_by":1,"name":"Cui Wang","email":"","orcid":"","institution":"Changji University","correspondingAuthor":false,"prefix":"","firstName":"Cui","middleName":"","lastName":"Wang","suffix":""},{"id":592783153,"identity":"3f8abcfd-ea24-4cb6-960f-87763babfc3c","order_by":2,"name":"Zilal Yashengjiang","email":"","orcid":"","institution":"Changji University","correspondingAuthor":false,"prefix":"","firstName":"Zilal","middleName":"","lastName":"Yashengjiang","suffix":""},{"id":592783155,"identity":"cce56722-6b40-4f49-addb-08e71bc9130c","order_by":3,"name":"Hanjin Bao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYPACCTn7ZobEBwkVNcRrMTZgb3hs8ODMMeKtSdzAc/CZ5MMWZsJKDY6fPfziZ5sF43aJ5LSKxAY2Bv727gT8Ws7kpVn2tkkwW85IS7uRuEOGQeLM2Q14tZgdyDEzZmyTYGO4kQPUcoaNwUAil4CW82/AWngYbuR/K0hsYyZCy40c48dALRIGZw6kMRClxf7GGzPGnnMSBpLtDckSCWeO8RD0i2R/jvGHH2V19f3MDIkff1TUyPG39+LXAgRsEsg8HkLKQYD5AzGqRsEoGAWjYAQDAA7oS9QNg82xAAAAAElFTkSuQmCC","orcid":"","institution":"Changji University","correspondingAuthor":true,"prefix":"","firstName":"Hanjin","middleName":"","lastName":"Bao","suffix":""},{"id":592783157,"identity":"cf38c272-f6b6-47c8-8960-e18b1ffb6a73","order_by":4,"name":"Shibo Li","email":"","orcid":"","institution":"Changji University","correspondingAuthor":false,"prefix":"","firstName":"Shibo","middleName":"","lastName":"Li","suffix":""},{"id":592783159,"identity":"f2d1aa09-4cb9-4056-a18f-3c6e1a885b00","order_by":5,"name":"Shuo Liu","email":"","orcid":"","institution":"Changji University","correspondingAuthor":false,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2026-01-14 06:38:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8598251/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8598251/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103000510,"identity":"13e4ffb9-75c9-4db4-90bb-5c1779356770","added_by":"auto","created_at":"2026-02-19 13:24:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":32047,"visible":true,"origin":"","legend":"\u003cp\u003eDevelopment trajectory of academic adjustment\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8598251/v1/c49c4ae3e20bd5405bd7630f.png"},{"id":103000634,"identity":"5cc457ee-ec34-4d79-9b53-8d640d14d9e8","added_by":"auto","created_at":"2026-02-19 13:24:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":134194,"visible":true,"origin":"","legend":"\u003cp\u003eThe cross-lagged associations between WFC and academic adjustment\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8598251/v1/f5d609d3553bc96b0f8a5c18.png"},{"id":105903304,"identity":"9e55f88d-f8be-4b62-bf1b-7a98830a9d3d","added_by":"auto","created_at":"2026-04-01 09:43:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1210771,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8598251/v1/d19fd281-22a5-4f5d-af1f-26ce4fd771a4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bidirectional Associations Between Parental Work-Family Conflict and Early Adolescents’ Academic Adjustment: A Four-Wave Dyadic Longitudinal Study in China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWork and family constitute the two central domains of adult life. Rather than functioning independently, these domains frequently influence one another through processes of spillover. Work-family conflict (WFC) is defined as a form of inter-role conflict in which participation in one role is made more difficult by participation in another, resulting in negative spillover between work and family domains. As originally articulated by Powell and Greenhaus (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1985\u003c/span\u003e), the work-family relationship is inherently bidirectional: work demands may interfere with family life, while family responsibilities can, in turn, impede work performance. China's ongoing transition toward a market-oriented economy, together with rapid social modernization, has profoundly reshaped work arrangements and lifestyle patterns. These societal changes have transformed the interface between work and family life, confronting parents with a complex combination of new challenges and opportunities. Although the relationship between work and family can involve both conflict and mutual enrichment, the reality for most contemporary parents is the necessity of managing dual role demands. When the balance between these roles is difficult to maintain, the likelihood of experiencing WFC increases substantially (Frone et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; J. H. Greenhaus \u0026amp; Beutell, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1985\u003c/span\u003e; Powell \u0026amp; Greenhaus, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Importantly, WFC may not only affect adults\u0026rsquo; well-being but also have implications for their children\u0026rsquo;s mental health and development. To date, however, relatively few studies have examined the association between parental WFC and children\u0026rsquo;s mental health outcomes. Against the backdrop of the increasing prevalence of WFC among parents and the rising incidence of adjustment problems among adolescents in recent decades (Col- lishaw 2015; Collishaw et al. 2004), particularly difficulties in academic adjustment, it is critical to understand whether, and through what mechanisms, parental WFC influences adolescents\u0026rsquo; academic adjustment (Bakker et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Cho \u0026amp; Coulton, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeyond the family context, the school environment represents another critical microsystem for adolescent development, whose influence becomes increasingly salient with age. Successful academic adjustment constitutes a core developmental task during adolescence and is particularly emphasized in Chinese families, where academic achievement is often regarded as a primary determinant of future educational and occupational success. Although previous research has highlighted the importance of family-related factors, such as parenting practices, parents\u0026rsquo; mental health, and socioeconomic status, in shaping adolescents\u0026rsquo; academic adjustment (Huang jie et al., 2019; Wang mingzhong et al., 2018), empirical evidence in the Chinese context that systematically examines the association between parents\u0026rsquo; WFC and adolescents\u0026rsquo; academic outcomes remains limited. Although work takes place outside the family setting, it profoundly structures parents\u0026rsquo; daily routines, emotional resources, and patterns of interaction within the household. The demands and resources embedded in parents\u0026rsquo; work roles jointly shape the family environment and, in turn, influence adolescents\u0026rsquo; adjustment by modifying their developmental context. From a family systems perspective, mothers and fathers fulfill distinct yet equally indispensable roles, and family members are interconnected, such that interactions between spouses and between parents and children are mutually influential (Matias et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Matias \u0026amp; Recharte, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, existing research has largely focused on unidirectional pathways, emphasizing how parental characteristics affect adolescents\u0026rsquo; psychological and academic functioning, while often portraying adolescents as passive recipients of family influences. In contrast, adolescents\u0026rsquo; characteristics and adjustment difficulties may also affect parents\u0026rsquo; capacity to manage work-family demands. Therefore, it is essential to conceptualize the association between parents\u0026rsquo; WFC and adolescent adjustment as a dynamic and potentially bidirectional process.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 Developmental Characteristics of Adolescent Academic Adjustment\u003c/h2\u003e \u003cp\u003eAcademic adjustment refers to an individual\u0026rsquo;s capacity to cope with academic demands and challenges and to achieve positive learning outcomes. It primarily encompasses multiple interrelated dimensions, including learning attitudes, study skills, learning environments, and physical and mental health, as well as academic self-efficacy, stress, burnout, and classroom performance experienced during the learning process (Guangzhen Zhang et al.,2013; Cuimin Zhou et al.,2016). Additionally, academic adjustment is reflected not only in adolescents\u0026rsquo; perceived competence in achieving success at school but also in their motivation and desire to perform well academically (Wang \u0026amp; Cai, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdolescence represents a transitional period from childhood to adulthood, during which individuals experience substantial changes across multiple developmental contexts, including curriculum structure, parents\u0026rsquo; educational expectations, school climate, class size, teacher-student relationships, and peer interactions (Eccles \u0026amp; Wigfield, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Moilanen et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Compared with elementary school, learning in middle school is generally more competitive, and both parents and teachers place greater emphasis on individual academic performance, often accompanied by heightened expectations for academic success. Within such an environment, adolescents are more susceptible to difficulties in academic adjustment. On the one hand, the increasing salience of academic demands leads to greater evaluative pressure and criticism in response to poor academic performance (Roisman et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). On the other hand, the rising complexity and difficulty of academic tasks in middle school can exceed adolescents\u0026rsquo; coping capacities, thereby increasing academic stress. Early adolescence has been widely identified as a critical period marked by declines in academic engagement, learning motivation, and academic achievement. Following the transition to middle school, adolescents often exhibit reduced learning motivation and poorer academic adjustment (Eccles et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). Furthermore, gender differences have been observed in adolescents\u0026rsquo; academic adjustment. Boys tend to experience more academic adjustment difficulties than girls, whereas differences across grade levels are generally less pronounced, with academic adjustment showing a slight decline as students progress through school (Maughan et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Girls typically place greater importance on academic achievement, demonstrate higher levels of intrinsic academic motivation, and attain better academic outcomes (Bri\u0026egrave;re et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Veas et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, they also tend to be more concerned about their academic performance, which may contribute to higher levels of academic burnout compared with boys (Bri\u0026egrave;re et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Veas et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResearch evidence indicates that the factors influencing adolescents\u0026rsquo; academic adjustment are multifaceted, involving not only individual psychological characteristics, such as perseverance, shyness, values, and emotional functioning (Baker, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Birch \u0026amp; Ladd, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Kiuru et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), but also the broader family environment. As adolescents mature, they become increasingly sensitive to their parents\u0026rsquo; roles and experiences within both the work and family domains. In the Chinese cultural context, academic achievement is commonly regarded by parents as a key indicator of future success, leading to elevated educational expectations for their children. Such expectations may function as a double-edged sword: while they can promote academic engagement, they often entail substantial academic investment from adolescents, accompanied by heightened stress (Fan \u0026amp; Chen, 2001). Accordingly, it is essential to examine whether observed changes in adolescents\u0026rsquo; academic adjustment primarily reflect normative developmental processes or are shaped by external contextual factors, such as parents\u0026rsquo; work-family spillover.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 WFC and Adolescent Academic Adjustment\u003c/h2\u003e \u003cp\u003eAcademic adjustment represents one of the most critical developmental tasks during adolescence (Bouchey \u0026amp; Harter, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The transition from childhood to adolescence, characterized by an expanded curriculum and heightened academic competition and pressure, renders adolescents particularly vulnerable to difficulties in academic adjustment (Abdollahi et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Adolescents who experience poor academic adjustment are more likely to develop negative attitudes toward school, exhibit disengagement from school-related activities, and ultimately achieve lower academic performance. Furthermore, these adolescents face an increased risk of school dropout (Fortin et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Substantial evidence indicates that parents\u0026rsquo; WFC is an important predictor of adolescents\u0026rsquo; academic difficulties. Adolescents raised in families characterized by frequent conflict are more likely to experience poor academic outcomes (Brown, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Specifically, when parents\u0026rsquo; work demands interfere with adolescents\u0026rsquo; educational needs due to constraints on key resources such as time and energy, adolescents\u0026rsquo; academic adjustment may be compromised, resulting in lower academic achievement and the emergence of maladaptive learning behaviors (Cho \u0026amp; Coulton, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe mechanisms underlying this association are multifaceted. First, time-based WFC can constrain parents\u0026rsquo; involvement in their children\u0026rsquo;s education, thereby depriving adolescents of critical resources that support learning motivation and engagement (Phillipson \u0026amp; Phillipson, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Moreover, parents experiencing high levels of WFC often face additional challenges, such as limited career advancement opportunities and increased financial strain (Allen et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which further reduce their available time, energy, and capacity to participate in their children\u0026rsquo;s education at home and at school. These parents are also more likely to adopt less effective academic supervision strategies, as cognitive and emotional depletion resulting from multiple role demands undermines their ability to respond sensitively, provide stimulation, and interact effectively with their children (Craig \u0026amp; Sawrikar, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Additionally, the strain associated with balancing work and family responsibilities may disrupt parents\u0026rsquo; daily routines (e.g., through overtime or night shifts), thereby limiting the time available to supervise adolescents\u0026rsquo; homework and after-school learning activities (Cho \u0026amp; Coulton, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Effective parental supervision and behavioral control are particularly important, as they not only promote greater investment of time in academic activities but also facilitate the development of adolescents\u0026rsquo; self-regulation in academic emotions, cognition, and behavior, ultimately contributing to improved academic competence and achievement (Cho \u0026amp; Coulton, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shim \u0026amp; Finch, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Tseng, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Veas et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jiang \u0026amp; Dong, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Finally, even when parents are able to allocate time to their children, work-related stress stemming from demanding schedules may manifest as fatigue, tension, and irritability. Such strain can impair parents\u0026rsquo; physiological and emotional capacity to engage meaningfully in their adolescents\u0026rsquo; education, thereby exacerbating academic stress and maladjustment among adolescents (Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Conversely, family-related factors may also interfere with work functioning. For example, adolescents\u0026rsquo; academic difficulties can substantially undermine parents\u0026rsquo; mental health and reduce their ability to concentrate on work-related tasks (Matias et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003ea; Vieira, Matias, Lopez, \u0026amp; Matos, 2016).\u003c/p\u003e \u003cp\u003e Furthermore, adolescents differ considerably in their responses to parents\u0026rsquo; WFC. While some adolescents exhibit developmental difficulties, such as declining academic performance, increased problem behaviors, and poorer social skills, others demonstrate relatively positive adaptation despite exposure to parental WFC. Prior research suggests that adolescents\u0026rsquo; age and gender play important moderating roles in how parents\u0026rsquo; work-family spillover affects individual development (Twenge \u0026amp; Nolen-Hoeksema, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Changes in parents\u0026rsquo; work and family environments may thus have differential implications for sons and daughters. For instance, girls may be more sensitive to the effects of parental WFC, as they tend to perceive and internalize negative emotions more acutely. When parents experience sudden financial strain, they may be more likely to interrupt girls\u0026rsquo; educational trajectories (Borelli et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to the resource dilution model, increases in family size reduce the amount of available resources allocated to each child (Blake, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1981\u003c/span\u003e); however, the extent of this reduction may differ between sons and daughters. Western scholarship has suggested that under adverse family conditions, greater investment may be directed toward daughters \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(Trivers \u0026amp; Willard, 1973)\u003c/span\u003e. In contrast, research conducted in Eastern cultural contexts indicates that when family resources are limited, daughters do not receive preferential consideration or care (Fan \u0026amp; Chen, 2020), and their interests are more likely to be sacrificed (Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). As family socioeconomic status improves, this pattern of sacrificing girls\u0026rsquo; interests gradually diminishes (Lee et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1994\u003c/span\u003e), highlighting cultural differences in family resource allocation mechanisms. Within the Chinese cultural context, patriarchal norms have historically contributed to a pronounced \u0026ldquo;son preference\u0026rdquo; (Baopei Wu et al., 2013). When family resources are scarce, parents are more likely to prioritize sons over daughters (Hannum et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Parish \u0026amp; Willis, 1993). Similarly, in the intergenerational transmission of family resources, boys tend to receive greater investment and are more likely to inherit their parents\u0026rsquo; social status (Chu \u0026amp; Yu, 2007).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3The present study\u003c/h2\u003e \u003cp\u003eThe present study aims to investigate parents\u0026rsquo; WFC and their relationships with academic adjustment from a dynamic developmental perspective during early adolescence in the Chinese context.\u003c/p\u003e \u003cp\u003eThe primary goals are three fold: First, it examines the developmental trajectories of academic adjustment among Chinese adolescents across middle school years. Based on existing literature, it is hypothesized that academic adjustment will increase during middle school years (\u003cem\u003eHypothesis 1\u003c/em\u003e). Second, the study explores how these developmental trajectories of parents\u0026rsquo; work-family are associated with the developmental trajectories of adolescent academic adjustment. It is assumed that trajectories of parents\u0026rsquo; WFC will be negatively associated with the developmental trajectories of adolescent\u0026rsquo; academic adjustment (\u003cem\u003eHypothesis 2\u003c/em\u003e). Finally, the study employs cross-lagged panel models to investigate the direction of effects between parents\u0026rsquo; WFC and adolescent academic adjustment. Drawing on literature regarding parents, it is hypothesized that parents\u0026rsquo; WFC and adolescent academic adjustment will exhibit cumulative cycles, where WFC predict adolescent academic adjustment which in turn, influence sleep problems (\u003cem\u003eHypothesis 3\u003c/em\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants\u003c/h2\u003e \u003cp\u003eThis study employed a cluster sampling approach, randomly selecting five classes from each of three junior high schools in Nanchang City, resulting in a total of 15 participating classes. All first-year students from these classes and their parents were invited to participate. They were informed that their data would remain confidential and be used solely for research purposes. Both active written assent from adolescents and passive consent from parents were obtained prior to data collection. Trained research assistants, including postgraduate students in psychology and school psychological counselors, administered the surveys.\u003c/p\u003e \u003cp\u003eThe baseline assessment (T1) was conducted in September 2020. A total of 737 student-parent triads completed the questionnaires. Among the adolescents, 98.3% resided with both biological parents, with the remaining from single-parent households due to divorce, bereavement, or other reasons. Parents\u0026rsquo; age was concentrated between 40 and 50 years. Over 93% of fathers and 92% of mothers had attained a senior high school education or above. Furthermore, 93.7% of fathers and 82.8% of mothers were employed full-time. The final valid sample at T1 comprised 587 complete families (i.e., 587 adolescents, 587 fathers, and 587 mothers).Three follow-up assessments were conducted using identical procedures at six-month intervals: T2 in April 2021, T3 in September 2021, and T4 in April 2022. While all initially recruited participants completed the T1 assessment, attrition occurred at subsequent waves due to student transfer, illness, or other reasons. The valid samples for T2, T3, and T4 consisted of 623, 465, and 437 families, respectively. For the primary longitudinal analyses requiring complete data across all four time points, the final analytic sample included 329 families (329 adolescents and both their parents). Adolescent demographic characteristics, including age, gender, and sibling status, were collected via self-report at T1. The adolescents had a mean age of 12.45 years (SD\u0026thinsp;=\u0026thinsp;1.31) at baseline, and the sample included 175 girls. Independent-samples t-tests indicated no significant differences at T1 between participants retained in the final sample and those who dropped out on key study variables: fathers\u0026rsquo; WFC (t(587) = \u0026minus;\u0026thinsp;0.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0 .81, 95% CI [\u0026ndash;0.49, 0.38]), mothers\u0026rsquo; WFC (t(587) = \u0026minus;\u0026thinsp;0.27, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.89, 95% CI [\u0026ndash;0.43, 0.51]), and academic adjustment (t(587) = \u0026minus;\u0026thinsp;0.55, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.71, 95% CI [\u0026ndash;4.30, 3.55]). These results suggest the absence of systematic attrition bias.\u003c/p\u003e \u003cp\u003eData collection procedure for adolescents: the baseline data were collected in September 2020. Adolescents completed the questionnaires during a 45-minute regular class session in a group-administered format. The survey administrators were postgraduate students in psychology and trained school counselors. Questionnaires were collected immediately upon completion to ensure data quality. All collected questionnaires were screened for validity; those with over 85% missing data or exhibiting patterned responses were excluded from analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Procedure\u003c/h2\u003e \u003cp\u003e Data collection procedure for parents: Adolescents took sealed envelopes containing the parent questionnaires home. They were instructed to ask both their father and mother to complete the surveys separately and independently. Parents were asked to seal their completed questionnaires in the provided envelopes, which the students then returned to their homeroom teacher within one week. The parent questionnaires assessed their own WFC and collected basic demographic information. In families with more than one child within the target age range, parents were requested to report based on the participating adolescent only. All participating adolescents and their parents received an honorarium of 50 RMB for each completed wave of assessment. The study procedures were approved by the Institutional Review Board of the School of Psychology (Approval No: HR2018-10-002).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.3Measures\u003c/h2\u003e \u003cp\u003e \u003cb\u003eParents\u0026rsquo; Work-Family Conflict\u003c/b\u003e: This study assessed Work-Family Conflict (WFC) for both fathers and mothers using the conflict subscale of the Work-Family Spillover Scale (Wayne et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The full scale contains two dimensions: work to family conflict and work to family enhancement, each comprising 8 items. This study utilized only the conflict subscale. Both parents reported on their own experiences using a Likert 5-point scale (\u003cem\u003e1 = \u0026ldquo;Never\u0026rdquo;, 2 = \u0026ldquo;Rarely\u0026rdquo;, 3 = \u0026ldquo;Sometimes\u0026rdquo;, 4 = \u0026ldquo;Often\u0026rdquo;, 5 = \u0026ldquo;Always\u0026rdquo;\u003c/em\u003e). Higher scores indicate a higher level of conflict experienced by the participant.\u003c/p\u003e \u003cp\u003eParents reported WFC using the Work-Family Spillover Scale (Wayne et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). This questionnaire consisted of 8 items, describing two aspects from WFC (8 items, e.g., \u0026ldquo;My job reduces the effort I can give to activities at home\u0026rdquo;). The Chinese version of this questionnaire has been validated \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(Ma et al., 2018)\u003c/span\u003e. Parents indicated how often they had experienced each during the last month on a five-point Likert scale ranging from 1 (\u003cem\u003eall the time\u003c/em\u003e)to 5 (\u003cem\u003enever\u003c/em\u003e). Items were scored such that higher scores meant more conflict. Cronbach\u0026rsquo;s alpha coefficients ranged from 0.87\u0026ndash;0.94across T1\u0026ndash;T4 for both mothers and fathers, respectively. The confirmatory factor analysis indicated good structure validity of the scale. WFC for fathers: \u003cb\u003eT1\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.87, CFI\u0026thinsp;=\u0026thinsp;0.95, TLI\u0026thinsp;=\u0026thinsp;0.92, RMSEA\u0026thinsp;=\u0026thinsp;0.08; \u003cb\u003eT2\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.54, CFI\u0026thinsp;=\u0026thinsp;0.97, TLI\u0026thinsp;=\u0026thinsp;0.95, RMSEA\u0026thinsp;=\u0026thinsp;0.07; \u003cb\u003eT3\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.98, CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.97, RMSEA\u0026thinsp;=\u0026thinsp;0.06; \u003cb\u003eT4\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.14, CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.96, RMSEA\u0026thinsp;=\u0026thinsp;0.06);WFC for mothers༚\u003cb\u003eT1\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.0, CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.96, RMSEA\u0026thinsp;=\u0026thinsp;0.06; \u003cb\u003eT2\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.58, CFI\u0026thinsp;=\u0026thinsp;0.97, TLI\u0026thinsp;=\u0026thinsp;0.95, RMSEA\u0026thinsp;=\u0026thinsp;0.07; \u003cb\u003eT3\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.75, CFI\u0026thinsp;=\u0026thinsp;0.98, TLI\u0026thinsp;=\u0026thinsp;0.97, RMSEA\u0026thinsp;=\u0026thinsp;0.05;\u003cb\u003eT4\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.58, CFI\u0026thinsp;=\u0026thinsp;0.97, TLI\u0026thinsp;=\u0026thinsp;0.95, RMSEA\u0026thinsp;=\u0026thinsp;0.07. All factor loadings in the above tests were within above 0.40 (\u003cem\u003ep\u003c/em\u003es\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAcademic adjustment: This study used the 24-item Learning Adjustment Scales (Midgley et al., 2000) to assess the academic adjustment of adolescents. This scale included three subscales: academic pressure (\u003cem\u003ee.g., \u0026ldquo;Having to study things you do not understand\u0026rdquo;\u003c/em\u003e), academic efficiency (\u003cem\u003ee.g., \u0026ldquo;Well behaved in school\u0026rdquo;\u003c/em\u003e), and academic burnout (\u003cem\u003ee.g., \u0026ldquo;My study is so poor that I really want to give it up\u0026rdquo;\u003c/em\u003e). For the above statements, responses ranged from 1 (\u003cem\u003enever true\u003c/em\u003e) to 5 (\u003cem\u003ealways true\u003c/em\u003e), with items reverse-scored when necessary, and higher scores representing greater dysfunctional. The Cronbach\u0026rsquo;s alpha coefficients of each subscale ranged from 0.70 to 0.83 in this study. In the analytic sample the internal consistency was fair across four waves (α\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.70, α\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.72, α\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.74, α\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.75). The confirmatory factor analysis indicated good structure validity of the scale. (\u003cb\u003eT1\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.76, CFI\u0026thinsp;=\u0026thinsp;0.99, TLI\u0026thinsp;=\u0026thinsp;0.98, RMSEA\u0026thinsp;=\u0026thinsp;0.05; \u003cb\u003eT2\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.86, CFI\u0026thinsp;=\u0026thinsp;0.99, TLI\u0026thinsp;=\u0026thinsp;0.98, RMSEA\u0026thinsp;=\u0026thinsp;0.05; \u003cb\u003eT3\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.41, CFI\u0026thinsp;=\u0026thinsp;0.97, TLI\u0026thinsp;=\u0026thinsp;0.95, RMSEA\u0026thinsp;=\u0026thinsp;0.07; \u003cb\u003eT4\u003c/b\u003e: \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/df\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.71, CFI\u0026thinsp;=\u0026thinsp;0.99, TLI\u0026thinsp;=\u0026thinsp;0.98, RMSEA\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data processing\u003c/h2\u003e \u003cp\u003eFirst, means, standard deviations and correlations for all study variables are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Polyserial correlation coefficients were calculated so as to allow estimation of the magnitude of bivariate relations between continuously measured indicators of WFC, academic adjustment.\u003c/p\u003e \u003cp\u003eIn the second step, to examine the developmental trends of adolescent academic adjustment, latent growth models (LGM) were fitted, including an unconditional linear LGM and an unconditional nonlinear LGM, to assess the trajectory of adolescent academic adjustment across middle school years. For the nonlinear LGM, the loadings on the slope factor were fixed at 0 and 1 for T1 and T4, respectively, and were freely estimated for the intermediate time points to optimally correspond to the unique characteristics of the data. Based on the growth shape determined by LGM, bivariate parallel process LGMs were employed to examine the relations between the developmental trajectories of parents\u0026rsquo; WFC and academic adjustment, as indexed by intercept-intercept and slope-slope associations. We specified longitudinal cross-lagged panel models to determine whether father and mothers\u0026rsquo; WFC predict academic adjustment or vice versa. Finally, We conducted a parallel process LGM models to examine the relationship between adolescent academic adjustment and parents\u0026rsquo; WFC.\u003c/p\u003e \u003cp\u003eAll models were run using the robust maximum likelihood (MLR) estimator. The goodness of fit was assessed using convergence across multiple fit indices, including the root mean square error of approximation (RMSEA), Tucker\u0026ndash;Lewis Index (TLI), and comparative fit index (CFI). The model fit is considered adequate if the CFI and TLI values are \u0026ge;\u0026thinsp;0.90 and better if they are \u0026ge;\u0026thinsp;0.95. The cutoff value for the RMSEA is \u0026le;\u0026thinsp;0.08, with a better fit indicated at \u0026le;\u0026thinsp;0.05 (Hu and Bentler, 1999).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Preliminary analyses\u003c/h2\u003e \u003cp\u003eThe data gathered in this study were based on self-reports, which can potentially introduce a typical methodological bias. After data collection, the common method bias across all four tests was evaluated using the Harman single-factor test (Harman'Single-Factor Test, Podsakoff et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The first factor explains 17.23, 18.88, 18.11and 21.15% of the variance at T1, T2, T3, and T4, respectively. These values fall below the critical threshold of 40% (Dandan Tangn, Zhonglin Wen, 2020), indicating no significant common method bias in the four measurements.\u003c/p\u003e \u003cp\u003eThe longitudinal measurement invariance of the study variables over time was assessed by fitting and comparing a series of progressively more constrained models. Given the sensitivity of the Chi-square difference test to larger sample sizes, it is recommended to examine changes in the Tucker-Lewis Index (TLI) and comparative fit index (CFI), when sample sizes exceed 300 cases. Specifically, when ΔTLI and ΔCFI are \u0026le;\u0026thinsp;0.02, the conditions for different levels of measurement in variance are considered met (Chen, 2007). The results indicated that longitudinal scalar in variance was established for all variables (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Fit Indices for Testing Longitudinal Measurement Invariance\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eModel Parameter Estimation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003eModel Comparison\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003edf\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRMSEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTLI\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 \u003cp\u003eΔCFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eΔTLI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFathers\u0026rsquo; WFC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e886.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.917\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e941.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM2-M1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026ndash;0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e986.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM3-M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026ndash;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e994.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM4-M3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eMothers\u0026rsquo; WFC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e757.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.908\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e791.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.921\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM2-M1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e820.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM3-M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026ndash;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e858.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM4-M3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAcademic Adjustment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e459.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.944\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.926\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e479.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM2-M1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e520.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM3-M2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026ndash;0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e534.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.928\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eM4-M3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026ndash;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNote. WFC\u0026thinsp;=\u0026thinsp;work family conflict\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.2.Descriptive statistics and correlation\u003c/h2\u003e \u003cp\u003eDescriptive statistics and bivariate correlations among academic adjustment, mothers\u0026rsquo; and fathers\u0026rsquo; WFC each time point are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Associations between consecutive time points showed medium stability over time for fathers\u0026rsquo; WFC (\u003cem\u003ers\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.36\u0026ndash;0.41, \u003cem\u003eps\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), mothers\u0026rsquo; WFC (\u003cem\u003ers\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.31\u0026ndash;0.40, \u003cem\u003eps\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and adolescent academic adjustment (\u003cem\u003ers\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37\u0026ndash;0.49, \u003cem\u003eps\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Within-time associations between fathers\u0026rsquo; WFC and academic adjustment indicated a relatively medium degree of co-occurrence (\u003cem\u003ers\u003c/em\u003e = \u0026minus;\u0026thinsp;0.30 \u0026ndash; \u0026minus;\u0026thinsp;0.54, \u003cem\u003eps\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas those between mothers\u0026rsquo; WFC and academic adjustment showed a week degree of co-occurrence (\u003cem\u003ers\u003c/em\u003e = \u0026minus;\u0026thinsp;0.10 \u0026ndash; \u0026minus;\u0026thinsp;0.22, \u003cem\u003eps\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"13\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"12\" nameend=\"c12\" namest=\"c1\"\u003e \u003cp\u003eTable\u0026nbsp;2 Descriptive statistics and correlations for all study variables (\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;329)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\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 \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1.WFC\u003csub\u003e(F)\u003c/sub\u003e-T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.WFC\u003csub\u003e(F)\u003c/sub\u003e-T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.41\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3.WFC\u003csub\u003e(F)\u003c/sub\u003e-T3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.35\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4.WFC\u003csub\u003e(F)\u003c/sub\u003e-T4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.32\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5.WFC\u003csub\u003e(M)\u003c/sub\u003e-T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.36\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6.WFC\u003csub\u003e(M)\u003c/sub\u003e-T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.28\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.06\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\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7.WFC\u003csub\u003e(M)\u003c/sub\u003e-T3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026minus;\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 \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8.WFC\u003csub\u003e(M)\u003c/sub\u003e-T4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.43\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.40\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026minus;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9.AcademicAdjustment-T1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.54\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.34\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.36\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.38\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.22\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;0.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;0.12\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u0026minus;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10.Academic Adjustment-T2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.43\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.45\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.32\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.15\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;0.17\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.46\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026minus;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11.Academic Adjustment-T3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.33\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.32\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.42\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.47\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.11\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;0.12\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.18\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;0.14\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.49\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026minus;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12.Academic Adjustment-T4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ndash;0.30\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ndash;0.31\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026ndash;0.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;0.53\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;0.10\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026ndash;0.13\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026ndash;0.11\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026ndash;0.18\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.37\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.44\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.56\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e2.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eNote. \u003cem\u003ep\u003c/em\u003e\u003csup\u003e*\u003c/sup\u003e\u0026lt; 0.05, \u003cem\u003ep\u003c/em\u003e\u003csup\u003e**\u003c/sup\u003e\u0026lt; 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=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Development trajectory of adolescent academic adjustment\u003c/h2\u003e \u003cp\u003eTo investigate the general developmental trends of early adolescent academic adjustment, linear unconditional latent growth models (LGM) and quadratic unconditional LGMs of the aforementioned variables were constructed.\u003c/p\u003e \u003cp\u003eFrom the model fit indices of early adolescent academic adjustment, the fit indices of the linear unconditional LGM were significantly better than those of the quadratic unconditional academic adjustment model: (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;13.00, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5, CFI\u0026thinsp;=\u0026thinsp;0.977, TLI\u0026thinsp;=\u0026thinsp;0.973, RMSEA\u0026thinsp;=\u0026thinsp;0.070). This indicates that adolescent academic adjustment shows a linear trend of development over the two-year period, with an initial level of academic adjustment quantified at 2.51, which is significantly greater than 0. Over four measurements, a declining trend was observed (slope = \u0026minus;\u0026thinsp;0.19, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, the variance of the intercept for academic adjustment (σ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.38, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.00) and the variance of the slope (σ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) were both significantly greater than 0, suggesting that there are significant individual differences in both the initial level and rate of development in academic adjustment. However, there was no significant correlation between the intercept and slope (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that the initial level of academic adjustment does not affect its rate of change. The results show that adolescent academic adjustment exhibits a linear decline, and there are individual differences in both the initial level and development speed (see Fig. 1).\u003c/p\u003e \u003cp\u003e Fig. 1. Development trajectory of academic adjustment\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Direction of effects between parents\u0026rsquo; WFC and adolescent academic adjustment\u003c/h2\u003e \u003cp\u003eA longitudinal panel model with auto-regressive and cross-lagged paths was estimated to test for the directionality of effects between parents\u0026rsquo; WFC and academic adjustment. The initial auto-regressive model included all continuity paths across time for each construct and the cross-sectional correlations among constructs. This model demonstrated a good fit to the data ( \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2501.507, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1465, RMSEA\u0026thinsp;=\u0026thinsp;0.046, CFI\u0026thinsp;=\u0026thinsp;0.920, TLI\u0026thinsp;=\u0026thinsp;0.932). The results indicated that relative standing on all variables was stable (i.e., all auto-regressive paths were statistically significant ( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, \u003cem\u003eβs\u003c/em\u003e ranged from 0.36 to 0.40).\u003c/p\u003e \u003cp\u003eCross-sectional correlations among the constructs indicated negative correlations between fathers\u0026rsquo; WFC and academic adjustment at each time point, suggesting that fathers\u0026rsquo; WFC were associated with descend concurrent adolescent academic adjustment at all time points.\u003c/p\u003e \u003cp\u003eThe CLMP of fathers\u0026rsquo; and mothers\u0026rsquo; WFC and adolescent academic adjustment demonstrated a good fit to the data ( \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2501.507, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1465, RMSEA\u0026thinsp;=\u0026thinsp;0.046, CFI\u0026thinsp;=\u0026thinsp;0.920, TLI\u0026thinsp;=\u0026thinsp;0.932). The results showed a reciprocal relationship between fathers\u0026rsquo; WFC and academic adjustment from Time 1 to Time 4, but not mothers. More specifically, the structural equation model showed that greater fathers\u0026rsquo; WFC were associated with worse and academic adjustment vice versa. In contrast, mothers\u0026rsquo; WFC not significantly predicting adolescent academic adjustment, and the reverse association was not significant also (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe CLMP model just only be capable of uncovering the mutual predictive relationship among variables; however, it is unable to account for the directionality of covariation. Consequently, in the subsequent stage, a parallel latent variable analysis will be carried out separately regarding the father\u0026rsquo;s WFC and adolescent academic adjustment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Co-development associations between parents\u0026rsquo; WFC and adolescent academic adjustment\u003c/h2\u003e \u003cp\u003eTo examine the co-development associations between fathers\u0026rsquo; WFC and academic adjustment, parallel process LGMs were fitted (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;86.25, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;43, CFI\u0026thinsp;=\u0026thinsp;0.93, TLI\u0026thinsp;=\u0026thinsp;0.89, RMSEA\u0026thinsp;=\u0026thinsp;0.03), and the initial level of fathers\u0026rsquo; WFC significantly predicting the intercept(β = \u0026minus;\u0026thinsp;0.85, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.12, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and slope (β = \u0026minus;\u0026thinsp;0.16, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.06, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) of academic adjustment. Then another parallel process LGMs were construct to test whether academic adjustment could inversely predict the fathers\u0026rsquo; WFC, This model fit the data well (\u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;90.30, \u003cem\u003edf\u0026thinsp;=\u003c/em\u003e\u0026thinsp;43, CFI\u0026thinsp;=\u0026thinsp;0.93, TLI\u0026thinsp;=\u0026thinsp;0.90, RMSEA\u0026thinsp;=\u0026thinsp;0.06), suggesting intercept of academic adjustment negatively and significantly predicting the intercept (β = \u0026minus;\u0026thinsp;0.94, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.14, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)and slope (β = \u0026minus;\u0026thinsp;0.23, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) of father\u0026rsquo;s WFC, and the slope of academic adjustment also predicting the slope of father\u0026rsquo;s WFC also (β = \u0026minus;\u0026thinsp;0.46, \u003cem\u003eSE\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.22, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0 .03).\u003c/p\u003e \u003cp\u003eThe results suggesting that the higher initial level of fathers\u0026rsquo; WFC, the worse of the academic adjustment will be, the slower the improvement of their academic adjustment will be. Additionally, the higher the initial level of academic adjustment were associated with lower baseline fathers\u0026rsquo; WFC and the slower the growth rate of fathers\u0026rsquo; WFC, and the growth rate of academic adjustment is faster, and the change rate of fathe\u0026rsquo;s WFC is also slower. Mothers\u0026rsquo; WFC not significantly predict adolescent academic adjustment at any of the time included in the current study, and so the model construction was not carried out.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e Across societies, parents are required to simultaneously manage the demands of work and family roles. Difficulties in balancing these responsibilities may undermine family functioning and compromise the effective fulfillment of parental roles, thereby adversely affecting adolescents\u0026rsquo; healthy development. Building on this perspective, the present study examined the longitudinal associations between parents\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Development of Adolescent Academic Adjustment\u003c/h2\u003e \u003cp\u003eDuring early adolescence, adolescents\u0026rsquo; academic adjustment generally exhibits a declining trend as they grow older. This pattern has been supported by numerous studies conducted in China, which have shown that first-year middle school students demonstrate significantly better academic adjustment than students in the second year (Wendao Li et al., 2003), and that academic adjustment abilities tend to decrease with age among middle school students (Aifen Song et al., 2007). Similarly, longitudinal research in Western contexts has documented a clear linear decline in academic adjustment among American middle school students from sixth to eighth grade, accompanied by decreases in learning motivation and academic performance (Weeks et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consistent with these findings, the present study reveals that early adolescents\u0026rsquo; academic adjustment deteriorates across the two-year observation period.\u003c/p\u003e \u003cp\u003eIn addition, substantial individual differences were observed in both the initial levels and rates of change in academic adjustment, indicating that adolescents enter middle school with varying levels of academic adjustment and exhibit heterogeneous developmental trajectories over time. Moreover, the initial level of academic adjustment was not significantly associated with its slope, suggesting that the rate of change in academic adjustment remains relatively independent of adolescents\u0026rsquo; starting levels (Mund \u0026amp; Nestler, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Specifically, adolescents enter school with distinct personality characteristics shaped by diverse family backgrounds, resulting in variability in academic performance at school entry. Although many characteristics and behavioral patterns related to academic adjustment show continuity during early adolescence, significant academic difficulties tend to emerge gradually over time among middle school students (McLaughlin \u0026amp;King, 2015). Consistent with the present findings, previous research has reported a declining trend in academic adjustment across adolescence (Vanhalst et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) or a stabilization of academic adjustment during later stages of adolescence (Danneel et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, a recent meta-analysis demonstrated a general decline in academic motivation and adjustment during early adolescence, followed by relative stabilization during middle to late adolescence \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e(\u003c/span\u003eMund et al. 2020).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Changes in Parents\u0026rsquo; WFC and the Development of Adolescent Academic Adjustment\u003c/h2\u003e \u003cp\u003eThe findings of the present study indicate a bidirectional association between parents\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment, consistent with prior research (Dinh et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jeffrey H. Greenhaus \u0026amp; Foley, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Rahman \u0026amp; Ali, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zou et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). An increase in parents\u0026rsquo; WFC is associated with greater levels of academic maladjustment among adolescents, including behaviors such as school avoidance and dropout (Chai \u0026amp; Schieman, 2021). Parents\u0026rsquo; irregular work schedules, such as overtime or night shifts, may limit their opportunities to engage fully in their adolescents\u0026rsquo; academic activities and educational supervision (J. Li et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This lack of parental planning and monitoring is particularly consequential during early adolescence, a developmental period in which insufficient academic guidance may foster negative attitudes toward learning and contribute to declines in academic performance (Carlo et al., 2018). At the same time, adolescents\u0026rsquo; academic maladjustment may also exacerbate parents\u0026rsquo; WFC. The psychological strain associated with raising an adolescent who struggles academically can deplete parents\u0026rsquo; cognitive and emotional resources, increase interparental conflict, and generate a negative feedback loop. When combined with other family responsibilities, this resource depletion may intensify parents\u0026rsquo; experience of WFC and contribute to its accumulation over time (Chee et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). From a family systems perspective, the family functions as an interconnected unit in which changes in one member inevitably influence others and the broader family environment. Accordingly, WFC may disrupt family relationships and functioning, while adolescents\u0026rsquo; characteristics and adjustment difficulties may, in turn, interfere with parents\u0026rsquo; capacity to manage work-family demands.\u003c/p\u003e \u003cp\u003eThe findings of the present study further support this theoretical perspective. Notably, the interaction patterns between fathers\u0026rsquo; and mothers\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment exhibit temporal differences and subtle distinctions. These patterns can be better understood in light of changes in family environments and family relationships across different stages of adolescent development. Specifically, a bidirectional relationship was observed between fathers\u0026rsquo; work\u0026ndash;family conflict and adolescents\u0026rsquo; academic adjustment, suggesting a reciprocal pathway between fathers\u0026rsquo; experiences at the work-family interface and adolescents\u0026rsquo; developmental outcomes. In contrast, this bidirectional association was not evident in the relationship between mothers\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment. Moreover, the initial level of fathers\u0026rsquo; WFC not only predicted subsequent levels of adolescents\u0026rsquo; academic adjustment but also forecasted the trajectory of change in academic adjustment over time. This finding indicates that early adolescents\u0026rsquo; academic adjustment is particularly sensitive to fathers\u0026rsquo; WFC. As children grow older, especially during the transition into early adolescence, fathers\u0026rsquo; supervisory and regulatory roles become increasingly salient. Adolescents who report higher levels of paternal supervision tend to demonstrate stronger academic achievement compared with those who report lower levels of paternal supervision (Criss et al., 2015; Dishion, Bullock, \u0026amp; Kiesner, 2008; Hill \u0026amp; Tyson, 2009; V\u0026eacute;ronneau \u0026amp; Dishion, 2012), and the inverse pattern is observed when paternal supervision is limited.\u003c/p\u003e \u003cp\u003eIn other words, the association between fathers\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment appears to be more proximal, and the dynamic linkage between the developmental trajectories of fathers\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment is stronger, with the two processes showing near-synchronous change over time. Notably, both the initial level and the developmental course of fathers\u0026rsquo; WFC were negatively predicted by changes in adolescents\u0026rsquo; academic adjustment. This pattern is consistent with prior research suggesting that fathers are more sensitive to adolescents\u0026rsquo; academic performance (Collins \u0026amp; Russell, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Such sensitivity may reflect developmental shifts in children\u0026rsquo;s needs for paternal involvement as they grow older, as well as differences in parental beliefs regarding appropriate forms of involvement in adolescents\u0026rsquo; lives. For example, mothers may place greater emphasis on adolescents\u0026rsquo; independence in daily functioning and emotional well-being (Hays, 1998), whereas fathers may be less focused on the emotional aspects of parent-child relationships and more oriented toward discipline, preparation for future roles, and the attainment of social status.\u003c/p\u003e \u003cp\u003eSince the reinstatement of China\u0026rsquo;s National College Entrance Examination (Gaokao) in the 1970s, education and academic achievement have become central societal concerns, widely regarded as the primary pathways to admission into prestigious universities and subsequent access to upward social mobility. As a result, Chinese parents tend to hold high educational expectations for their children and are often willing to invest substantial time, energy, and resources to support their adolescents\u0026rsquo; academic success. Within this cultural context, both parents commonly reach a shared understanding of the importance of academic performance. This emphasis is particularly pronounced among fathers, who traditionally bear responsibility for the continuation and honor of the family lineage (Fuligni \u0026amp; Zhang, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; L. Li et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Historically, individual competence in China has been closely evaluated through academic achievement. Consequently, adolescents\u0026rsquo; academic performance is not only viewed as a determinant of their future personal success but also as a reflection of family status and honor, rendering academic success a particularly salient concern for fathers.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Limitations and Future Directions\u003c/h2\u003e \u003cp\u003eAlthough the present study extends the literature by examining the relationship between parents\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment from a dynamic developmental perspective, several limitations should be acknowledged. First, the developmental trajectories analyzed in this study were confined to the junior high school period. Future research should adopt a longer developmental time frame and include additional stages, such as late elementary school and high school, to determine whether the association between parents\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment follows a universal developmental pattern. Second, the data primarily relied on self-reports from adolescents and their parents. Although self-report measures are effective for capturing subjective perceptions, future studies would benefit from incorporating multiple sources of information, such as teacher reports and official school records, as well as objective indicators, including parents\u0026rsquo; actual working hours and standardized measures of adolescents\u0026rsquo; academic performance. Such multi-informant and multi-method approaches would provide more robust evidence and help reduce potential common method bias.\u003c/p\u003e \u003cp\u003eThird, data were collected at six-month intervals in the present study. Future research employing shorter assessment intervals, such as monthly or quarterly measurements within intensive longitudinal designs, may more precisely capture the dynamic and reciprocal processes linking parents\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment. In addition, this study primarily focused on direct associations between parents\u0026rsquo; work\u0026ndash;family conflict and adolescents\u0026rsquo; academic adjustment. Future investigations should further explore potential mediating mechanisms, such as parents\u0026rsquo; psychological stress and the quality of parent-child relationships, as well as moderating factors, including family socioeconomic status, adolescent gender, and school support. Finally, the sample was drawn from three middle schools in Nanchang, China, which may limit the generalizability of the findings. The conclusions may not directly extend to adolescents in other regions of China (e.g., rural areas) or to populations in different cultural contexts. Future studies should examine the universality of these relationships using more diverse and representative samples.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe following results can be drawn from the study:\u003c/p\u003e \u003cp\u003e(1)Based on the latent variable growth model, adolescent academic adjustment shows a linear declining trend from the end of seventh grade to the end of eighth grade, suggestion that with the increase in age and academic tasks, academic adjustment becomes increasingly poor.\u003c/p\u003e \u003cp\u003e(2)According to the results of cross-lagged analysis, fathers\u0026rsquo; WFC and academic adjustment exhibit a bidirectional predictive relationship, whereas the direct influence of mother WFC on adolescent academic adjustment is not significant.\u003c/p\u003e \u003cp\u003e(3)The parallel latent growth model results of parents\u0026rsquo; WFC and early adolescent academic adjustment indicate that fathers\u0026rsquo; WFC and adolescent academic adjustment demonstrating a synchronous development pattern. Furthermore, the initial level of fathers\u0026rsquo; WFC can predict not only the initial level of adolescent academic adjustment but also the rate of development; the higher the initial level of fathers\u0026rsquo; WFC, the poorer the adolescent academic adjustment and the slower the growth in adjustment ability, and vice versa. Conversely, adolescent academic adjustment can predict fathers\u0026rsquo; WFC; the higher the level of academic adjustment, the lower the fathers\u0026rsquo; WFC, with a slower rate of change, while the improvement in academic adjustment occurs at a faster rate, leading to a slower development of fathers\u0026rsquo; WFC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eXiaoli Wang: Contributed to Conceptualization, Formal Analysis, and Writing \u0026ndash; Original Draft.Cui Wang: Contributed to Investigation, Data Curation, and Writing \u0026ndash; Review \u0026amp; Editing.Zilalai Yashengjiang: Contributed to Writing \u0026ndash; Review \u0026amp; Editing and MethodologyHanjin Bao (Corresponding author. E-mail: [email protected]): Contributed toWriting \u0026ndash; Review \u0026amp; Editing and SoftwareShibo Li: Contributed to Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.Shuo Liu: Contributed to Validation, Data Curation.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003eAll methods were performed in accordance with the relevant guidelines and regulations\u003c/p\u003e\n\u003ch2\u003eAdditional Information (including a Competing Interests Statement)\u003c/h2\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbdollahi, A., Panahipour, S., Akhavan Tafti, M., \u0026amp; Allen, K. A. (2020). Academic hardiness as a mediator for the relationship between school belonging and academic stress. Psychology in the Schools, 57(5), 823\u0026ndash;832. https://doi.org/10.1002/pits.22339\u003c/li\u003e\n \u003cli\u003eAllen, T. D., French, K. A., Braun, M. T., \u0026amp; Fletcher, K. (2019). The passage of time in work-family research: Toward a more dynamic perspective. Journal of Vocational Behavior, 110(December 2018), 245\u0026ndash;257. https://doi.org/10.1016/j.jvb.2018.11.013\u003c/li\u003e\n \u003cli\u003eBaker, J. A. (2006). Contributions of teacher-child relationships to positive academic adjustment during elementary school. Journal of School Psychology, 44(3), 211\u0026ndash;229. https://doi.org/10.1016/j.jsp.2006.02.002\u003c/li\u003e\n \u003cli\u003eBakker, A. B., Demerouti, E., \u0026amp; Burke, R. (2009). Workaholism and Relationship Quality: A Spillover-Crossover Perspective. Journal of Occupational Health Psychology, 14(1), 23\u0026ndash;33. https://doi.org/10.1037/a0013290\u003c/li\u003e\n \u003cli\u003eBakker, A. B., Shimazu, A., Demerouti, E., Shimada, K., \u0026amp; Kawakami, N. (2014). Work engagement versus workaholism: A test of the spillover-crossover model. Journal of Managerial Psychology, 29(1), 63\u0026ndash;80. https://doi.org/10.1108/JMP-05-2013-0148\u003c/li\u003e\n \u003cli\u003eBirch, S. H., \u0026amp; Ladd, G. W. (1997). The teacher-child relationship andadolescents early academic adjustment. Journal of School Psychology, 35(1), 61\u0026ndash;79. https://doi.org/10.1016/S0022-4405(96)00029-5\u003c/li\u003e\n \u003cli\u003eBlake, J. (1981). Family size and the quality of children. Demography, 18(4), 421\u0026ndash;442. https://doi.org/10.2307/2060941\u003c/li\u003e\n \u003cli\u003eBorelli, J. L., Nelson, S. K., River, L. M., Birken, S. A., \u0026amp; Moss-Racusin, C. (2017). Gender Differences in Work-Family Guilt in Parents of Young Children. Sex Roles, 76(5\u0026ndash;6), 356\u0026ndash;368. https://doi.org/10.1007/s11199-016-0579-0\u003c/li\u003e\n \u003cli\u003eBouchey, H. A., \u0026amp; Harter, S. (2005). Reflected appraisals, academic self-perceptions, and math/science performance during early adolescence. Journal of Educational Psychology, 97(4), 673\u0026ndash;686. https://doi.org/10.1037/0022-0663.97.4.673\u003c/li\u003e\n \u003cli\u003eBri\u0026egrave;re, F. N., Janosz, M., Fallu, J. S., \u0026amp; Morizot, J. (2015). Adolescent Trajectories of Depressive Symptoms: Codevelopment of Behavioral and Academic Problems. Journal of Adolescent Health, 57(3), 313\u0026ndash;319. https://doi.org/10.1016/j.jadohealth.2015.05.012\u003c/li\u003e\n \u003cli\u003eBrown, T. J. (2014). Work Family Conflict Among Parents of Atypically Developing Children: Exploring the Impact of Worker, Work, and Child Factors. Journal of Child and Family Studies, 23(5), 854\u0026ndash;862. https://doi.org/10.1007/s10826-013-9739-9\u003c/li\u003e\n \u003cli\u003eCenk, D. S., \u0026amp; Demir, A. (2016). The Relationship Between Parenting Style, Gender and Academic Achievement with Optimism Among Turkish Adolescents. Current Psychology, 35(4), 720\u0026ndash;728. https://doi.org/10.1007/s12144-015-9375-1\u003c/li\u003e\n \u003cli\u003eChee, K. H., Conger, R. D., \u0026amp; Elder, G. H. (2009). Mother\u0026apos;S Employment Demands, Work-Family Conflict, and Adolescent Development. International Journal of Sociology of the Family, 35(2), 189\u0026ndash;202. http://www.ncbi.nlm.nih.gov/pubmed/20927198%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC2949071\u003c/li\u003e\n \u003cli\u003eCho, Y., \u0026amp; Coulton, C. J. (2016). The Effects of parental \u0026nbsp;Nonstandard Work Schedules on Adolescents\u0026apos; Academic Achievement in Dual-Earner Households in South Korea. Child Indicators Research, 9(1), 193\u0026ndash;212. https://doi.org/10.1007/s12187-015-9308-4\u003c/li\u003e\n \u003cli\u003eCollins, W. A., \u0026amp; Russell, G. (1991). Mother-child and father-child relationships in middle childhood and adolescence: A developmental analysis. Developmental Review, 11(2), 99\u0026ndash;136. https://doi.org/10.1016/0273-2297(91)90004-8\u003c/li\u003e\n \u003cli\u003eCraig, L., \u0026amp; Sawrikar, P. (2008). Satisfaction with work-family balance for parents of early adolescents compared to parents of younger children. Journal of Family Studies, 14(1), 91\u0026ndash;106. https://doi.org/10.5172/jfs.327.14.1.91\u003c/li\u003e\n \u003cli\u003eDanneel, S., Geukens, F., Maes, M., Bastin, M., Bijttebier, P., Colpin, H., Verschueren, K., \u0026amp; Goossens, L. (2020). Loneliness, Social Anxiety Symptoms, and Depressive Symptoms in Adolescence: Longitudinal Distinctiveness and Correlated Change. Journal of Youth and Adolescence, 49(11), 2246\u0026ndash;2264. https://doi.org/10.1007/s10964-020-01315-w\u003c/li\u003e\n \u003cli\u003eDinh, H., Cooklin, A. R., Leach, L. S., Westrupp, E. M., Nicholson, J. M., \u0026amp; Strazdins, L. (2017). Parents\u0026apos; transitions into and out of work-family conflict andadolescents mental health: Longitudinal influence via family functioning. Social Science and Medicine, 194(October), 42\u0026ndash;50. https://doi.org/10.1016/j.socscimed.2017.10.017\u003c/li\u003e\n \u003cli\u003eEccles, J. S., Roeser, R. W., Wigfield, A., \u0026amp; Freedman-Doan, C. (1999). Academic and motivational pathways through middle childhood. Child Psychology: A Handbook of Contemporary Issues, January 2014, 287\u0026ndash;317.\u003c/li\u003e\n \u003cli\u003eEccles, J. S., \u0026amp; Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of Psychology, 53(February), 109\u0026ndash;132. https://doi.org/10.1146/annurev.psych.53.100901.135153\u003c/li\u003e\n \u003cli\u003eFan, J., \u0026amp; Chen, B. Bin. (2020). Parenting styles and coparenting in China: The role of parents andadolescents sibling status. Current Psychology, 39(5), 1505\u0026ndash;1512. https://doi.org/10.1007/s12144-019-00379-7\u003c/li\u003e\n \u003cli\u003eFortin, L., Marcotte, D., Diallo, T., Potvin, P., \u0026amp; Royer, \u0026Eacute;. (2013). A multidimensional model of school dropout from an 8-year longitudinal study in a general high school population. European Journal of Psychology of Education, 28(2), 563\u0026ndash;583. https://doi.org/10.1007/s10212-012-0129-2\u003c/li\u003e\n \u003cli\u003eFrone, M. R., Russell, M., \u0026amp; Cooper, M. L. (1992). Antecedents and outcomes of work^family conflict: Testing a model of the work^family interface. In Journal of Applied Psychology (Vol. 77, Issue 1, pp. 65\u0026ndash;78). https://doi.org/10.1037//0021-9010.77.1.65\u003c/li\u003e\n \u003cli\u003eFuligni, A. J., \u0026amp; Zhang, W. (2017). Attitudes toward family obligation among adolescents in contemporary Urban and rural China.adolescents Services in the Developing World, 74(1), 135\u0026ndash;148. https://doi.org/10.4324/9781315260495-22\u003c/li\u003e\n \u003cli\u003eGreenhaus, J. H., \u0026amp; Beutell, N. J. (1985). Sources of Conflict Between Work and Family Roles. Academy of Management Review, 10(1), 76\u0026ndash;88. https://doi.org/10.5465/amr.1985.4277352\u003c/li\u003e\n \u003cli\u003eGreenhaus, Jeffrey H., \u0026amp; Foley, S. (2007). The intersection of work and family lives. Handbook of Career Studies, January 2007, 131\u0026ndash;152. https://doi.org/10.4135/9781412976107.n8\u003c/li\u003e\n \u003cli\u003eHannum, E., Kong, P., \u0026amp; Zhang, Y. (2009). Family sources of educational gender inequality in rural China: A critical assessment. International Journal of Educational Development, 29(5), 474\u0026ndash;486. https://doi.org/10.1016/j.ijedudev.2009.04.007\u003c/li\u003e\n \u003cli\u003eJiang, S., \u0026amp; Dong, L. (2020). Association between deprivation and cognitive ability among Chinese adolescents: Examining the mechanisms of parents\u0026rsquo;\u0026nbsp; involvement in a rural\u0026ndash;urban dual system. Current Psychology. https://doi.org/10.1007/s12144-020-00981-0\u003c/li\u003e\n \u003cli\u003eKiuru, N., Nurmi, J. E., Aunola, K., \u0026amp; Salmela-Aro, K. (2009). Peer group homogeneity in adolescents\u0026apos; academic adjustment varies according to peer group type and gender. International Journal of Behavioral Development, 33(1), 65\u0026ndash;76. https://doi.org/10.1177/0165025408098014\u003c/li\u003e\n \u003cli\u003eLee, Y., Parish, W. L., \u0026amp; Willis, R. J. (1994). Support in Taiwan \u0026apos;. 99(4), 1010\u0026ndash;1041.\u003c/li\u003e\n \u003cli\u003eLi, J., Johnson, S. E., Han, W. J., Andrews, S., Kendall, G., Strazdins, L., \u0026amp; Dockery, A. (2014). Parents\u0026apos; nonstandard work schedules and child well-being: A critical review of the literature. Journal of Primary Prevention, 35(1), 53\u0026ndash;73. https://doi.org/10.1007/s10935-013-0318-z\u003c/li\u003e\n \u003cli\u003eLi, L., Shi, J., Wu, D., \u0026amp; Li, H. (2020). Only child, parental educational expectation, self-expectation and science literacy in Zhuang adolescents in China: A serial mediation model. Children and Youth Services Review, 115(May), 105084. https://doi.org/10.1016/j.childyouth.2020.105084\u003c/li\u003e\n \u003cli\u003eMatias, M., Ferreira, T., Vieira, J., Cadima, J., Leal, T., \u0026amp; M. Matos, P. (2017). Work\u0026ndash;family conflict, psychological availability, and child emotion regulation: Spillover and crossover in dual-earner families. Existing Measures of Emotion Dysregulation Typically Assess Dispositional Tendencies and Are Therefore Not Well Suited for Study Designs That Require Repeated Assessments over Brief Intervals. The Aim of This Study Was to Develop and Validate a State-Base, 24(3), 623\u0026ndash;639. https://doi.org/10.1111/pere.12198\u003c/li\u003e\n \u003cli\u003eMatias, M., \u0026amp; Recharte, J. (2020). Links Between Work\u0026ndash;Family Conflict, Enrichment, and Adolescent Well-Being: Parents\u0026apos; andadolescents Perspectives. Family Relations. https://doi.org/10.1111/fare.12453\u003c/li\u003e\n \u003cli\u003eMaughan, B., Rowe, R., Messer, J., Goodman, R., \u0026amp; Meltzer, H. (2004). Conduct Disorder and Oppositional Defiant Disorder in a national sample: Developmental epidemiology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 45(3), 609\u0026ndash;621. https://doi.org/10.1111/j.1469-7610.2004.00250.x\u003c/li\u003e\n \u003cli\u003eMoilanen, K. L., Rasmussen, K. E., \u0026amp; Padilla-Walker, L. M. (2015). Bidirectional Associations Between Self-Regulation and Parenting Styles in Early Adolescence. Journal of Research on Adolescence, 25(2), 246\u0026ndash;262. https://doi.org/10.1111/jora.12125\u003c/li\u003e\n \u003cli\u003eMund, M., \u0026amp; Nestler, S. (2019). Beyond the Cross-Lagged Panel Model: Next-generation statistical tools for analyzing interdependencies across the life course. Advances in Life Course Research, 41. https://doi.org/10.1016/j.alcr.2018.10.002\u003c/li\u003e\n \u003cli\u003ePhillipson, S., \u0026amp; Phillipson, S. N. (2007). Academic expectations, belief of ability, and involvement by parents as predictors of child achievement: A cross-cultural comparison. Educational Psychology, 27(3), 329\u0026ndash;348. https://doi.org/10.1080/01443410601104130\u003c/li\u003e\n \u003cli\u003ePodsakoff, P. M., MacKenzie, S. B., Podsakoff, N. P., \u0026amp; Lee, J. Y. (2003). The mismeasure of man(agement) and its implications for leadership research. Leadership Quarterly, 14(6), 615\u0026ndash;656. https://doi.org/10.1016/j.leaqua.2003.08.002\u003c/li\u003e\n \u003cli\u003ePowell, G. N., \u0026amp; Greenhaus, J. H. (2006). Managing incidents of work-family conflict: A decision-making perspective. In Human Relations (Vol. 59, Issue 9). https://doi.org/10.1177/0018726706069765\u003c/li\u003e\n \u003cli\u003eRahman, M. M., \u0026amp; Ali, N. A. (2020). Does work\u0026ndash;family balance mediate the relationship between work\u0026ndash;family conflicts and job satisfaction of academicians? Journal of Community Psychology, October, 1\u0026ndash;14. https://doi.org/10.1002/jcop.22464\u003c/li\u003e\n \u003cli\u003eRoisman, G. I., Aguilar, B., \u0026amp; Egeland, B. (2004). Antisocial behavior in the transition to adulthood: The independent and interactive roles of developmental history and emerging developmental tasks. Development and Psychopathology, 16(4), 857\u0026ndash;871. https://doi.org/10.1017/S0954579404040040\u003c/li\u003e\n \u003cli\u003eShim, S. S., \u0026amp; Finch, W. H. (2014). Academic and social achievement goals and early adolescents\u0026apos; adjustment: A latent class approach. Learning and Individual Differences, 30, 98\u0026ndash;105. https://doi.org/10.1016/j.lindif.2013.10.015\u003c/li\u003e\n \u003cli\u003eTseng, V. (2004). Family interdependence and academic adjustment in college: Youth from immigrant and U.S.-born families. Child Development, 75(3), 966\u0026ndash;983. https://doi.org/10.1111/j.1467-8624.2004.00717.x\u003c/li\u003e\n \u003cli\u003eTwenge, J. M., \u0026amp; Nolen-Hoeksema, S. (2002). Age, gender, race, socioeconomic status, and birth cohort differences on theadolescents Depression Inventory: A meta-analysis. Journal of Abnormal Psychology, 111(4), 578\u0026ndash;588. https://doi.org/10.1037/0021-843X.111.4.578\u003c/li\u003e\n \u003cli\u003eVanhalst, J., Luyckx, K., Scholte, R. H. J., Engels, R. C. M. E., \u0026amp; Goossens, L. (2013). Low self-esteem as a risk factor for loneliness in adolescence: Perceived - But not actual - Social acceptance as an underlying mechanism. Journal of Abnormal Child Psychology, 41(7), 1067\u0026ndash;1081. https://doi.org/10.1007/s10802-013-9751-y\u003c/li\u003e\n \u003cli\u003eVeas, A., Castej\u0026oacute;n, J.-L., Mi\u0026ntilde;ano, P., \u0026amp; Gilar-Corb\u0026iacute;, R. (2019). Early Adolescents\u0026apos; Attitudes and Academic Achievement: The Mediating Role of Academic Self-concept. Revista de Psicodid\u0026aacute;ctica (English Ed.), 24(1), 71\u0026ndash;77. https://doi.org/10.1016/j.psicoe.2018.11.002\u003c/li\u003e\n \u003cli\u003eWang, H., \u0026amp; Cai, T. (2017). parental involvement, adolescents\u0026apos; self-determined learning and academic achievement in Urban China. International Journal of Psychology, 52(1), 58\u0026ndash;66. https://doi.org/10.1002/ijop.12188\u003c/li\u003e\n \u003cli\u003eWayne, J. H., Musisca, N., \u0026amp; Fleeson, W. (2004). Considering the role of personality in the work-family experience: Relationships of the big five to work-family conflict and facilitation. Journal of Vocational Behavior, 64(1), 108\u0026ndash;130. https://doi.org/10.1016/S0001-8791(03)00035-6\u003c/li\u003e\n \u003cli\u003eWeeks, M., Ploubidis, G. B., Cairney, J., Wild, T. C., Naicker, K., \u0026amp; Colman, I. (2016). Developmental pathways linking childhood and adolescent internalizing, externalizing, academic competence, and adolescent depression. Journal of Adolescence, 51, 30\u0026ndash;40. https://doi.org/10.1016/j.adolescence.2016.05.009\u003c/li\u003e\n \u003cli\u003eZahed Zahedani, Z., Rezaee, R., Yazdani, Z., Bagheri, S., \u0026amp; Nabeiei, P. (2016). The influence of parenting style on academic achievement and career path. Journal of Advances in Medical Education \u0026amp; Professionalism, 4(3), 130\u0026ndash;134. http://www.ncbi.nlm.nih.gov/pubmed/27382580%0Ahttp://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=PMC4927255\u003c/li\u003e\n \u003cli\u003eZou, S., Wu, X., Ren, Y., \u0026amp; Wang, X. (2021). Actor\u0026ndash;partner association of work\u0026ndash;family conflict and parental depressive symptoms during COVID-19 in China: Does coparenting matter? Applied Psychology: Health and Well-Being, September, 1\u0026ndash;19. https://doi.org/10.1111/aphw.12312\u003c/li\u003e\n \u003cli\u003eTang Dandan,Wen Zhonglin. (2020). Common Method Bias Test: Problem Suggestions. 31771245, 215\u0026ndash;223. https://doi.org/10.16719/j.cnki.1671-6981.20200130\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Work-Family Conflict, Academic Adjustment, Early adolescent","lastPublishedDoi":"10.21203/rs.3.rs-8598251/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8598251/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWork-family conflict (WFC) not only affects parents\u0026rsquo; mental and physical health but may also directly or indirectly influence adolescents\u0026rsquo; academic adjustment. Importantly, this relationship may be bidirectional: while parental WFC can disrupt adolescents\u0026rsquo; academic adjustment, adolescents\u0026rsquo; characteristics, such as behavioral problems and difficulties in academic functioning, may in turn undermine parents\u0026rsquo; ability to manage work-family demands. To date, however, longitudinal research examining the dynamic, reciprocal relationship between parents\u0026rsquo; WFC and adolescent academic adjustment, as well as the underlying mechanisms, remains limited. Therefore, the present study aims to investigate the bidirectional and developmental associations between parents\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment.\u003c/p\u003e \u003cp\u003eUsing a longitudinal dyadic design, this study followed 329 seventh-grade students and their dual-earner parents across four waves of data collection: the first and second semesters of seventh grade (T1, T2) and the first and second semesters of eighth grade (T3, T4). Self-report questionnaires were administered to assess fathers\u0026rsquo; and mothers\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment. Structural equation modeling and cross-lagged panel models were employed to examine the bidirectional predictive effects between parental WFC and adolescent academic adjustment. In addition, parallel latent growth modeling was conducted to explore their synchronous developmental trajectories over time.\u003c/p\u003e \u003cp\u003eThe results indicated that adolescents\u0026rsquo; academic adjustment exhibited a linear downward trend from seventh to eighth grade. A significant synchronous developmental relationship was observed between fathers\u0026rsquo; WFC and adolescents\u0026rsquo; academic adjustment during this transition period. Specifically, the initial level of fathers\u0026rsquo; WFC predicted both the initial level and the rate of change in adolescents\u0026rsquo; academic adjustment: higher initial levels of fathers\u0026rsquo; WFC were associated with poorer academic adjustment and slower growth in adjustment over time, and vice versa. Conversely, adolescents\u0026rsquo; academic adjustment also predicted fathers\u0026rsquo; WFC. Higher levels of academic adjustment were associated with lower initial levels of fathers\u0026rsquo; WFC and a slower rate of change in WFC, while improvements in adolescents\u0026rsquo; academic adjustment occurred more rapidly, thereby contributing to a slower increase in fathers\u0026rsquo; WFC over time.\u003c/p\u003e \u003cp\u003eOverall, the findings provide robust evidence for a significant bidirectional relationship between parents\u0026rsquo; WFC and early adolescents\u0026rsquo; academic adjustment. On the one hand, parents\u0026rsquo; experiences of WFC tend to accumulate over time and negatively affect adolescents\u0026rsquo; academic adjustment. On the other hand, adolescents\u0026rsquo; academic adjustment difficulties can, in turn, exacerbate parents\u0026rsquo; WFC. This study highlights the influence of distal environmental factors, such as parents\u0026rsquo; work experiences, on adolescent development and suggests that interventions aimed at improving parents\u0026rsquo; work environments may play an important role in promoting adolescents\u0026rsquo; academic adjustment.\u003c/p\u003e","manuscriptTitle":"Bidirectional Associations Between Parental Work-Family Conflict and Early Adolescents’ Academic Adjustment: A Four-Wave Dyadic Longitudinal Study in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 13:23:56","doi":"10.21203/rs.3.rs-8598251/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"38b054e6-dc33-421e-a75f-f7ec9934c87d","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":63075154,"name":"Health sciences/Health care"},{"id":63075155,"name":"Biological sciences/Psychology"},{"id":63075156,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-04-01T09:40:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 13:23:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8598251","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8598251","identity":"rs-8598251","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}