Evaluating a longitudinal multilevel mediation model of self-concept clarity,hope,and subjective well-being in adolescents

Abstract

This study examined the longitudinal relationships among self-concept clarity (SCC), hope, and subjective well-being (i.e., emotional well-being and cognitive well-being). Specifically, we tested both the between-person and within-person associations of SCC with subjective well-being among 2,001 Chinese adolescents (age range 11–24 years, 42.9% males) during the first year. In addition, we examined the longitudinal mediating role of hope. Results showed that SCC had positive correlations with hope and subjective well-being both at one time point and over time. Multilevel mediation analysis indicated that hope could serve as a mediator in the association between SCC and subjective well-being, at both the between-person and within-person levels. Moreover, the model of longitudinal multilevel mediation was found to be moderated by gender and age. Our results indicated that hope could be an underlying mechanism for the longitudinal relationship between SCC and subjective well-being among Chinese adolescents, which provides a potential intervention target for improving adolescents’ well-being.

Keywords

Self-concept clarity hope subjective well-being multilevel mediation analysis adolescents

Introduction

Subjective well-being (SWB) is a crucial psychological health indicator, encompassing evaluations of one’s life (i.e., perceived life satisfaction) and emotional responses (i.e., positive and negative affect; Diener, 2009; Ebert et al., 2020). A complete sense of SWB encompasses both high life satisfaction and positive affect, along with low negative affect (Ryan & Deci, 2001). This can be further broken down into two distinct components: cognitive well-being (CWB) and emotional well-being (EWB; Diener, 2009; Kong et al., 2015). Adolescents with high levels of SWB can be associated with several positive outcomes, such as better academic performance and mental health (Geng, 2016; Nie et al., 2019; Teng et al., 2020). Therefore, investigating the factors that influence the development of SWB is critical for adolescents.

Based on the self-discrepancy theory (Haemmerlie & Montgomery, 1982) and hope theory (Snyder, 2002), this study explores the associations of self-concept clarity (SCC), hope, and SWB. However, previous research has largely comprised cross-sectional designs (Xiang et al., 2020), and the longitudinal relationships between SCC, hope, and SWB (containing both CWB and EWB) have not been well defined. In addition, much of the existing studies focus on stable, between-person associations among SCC, hope, and SWB. Fewer studies have explored how these individual factors change at the within-person level, and moreover, how these changes may influence well-being outcomes (e.g., CWB and EWB). Thus, we conducted longitudinal multilevel model analyses to examine both intra-individual differences (i.e., within-person associations) and inter-individual differences (i.e., between-person associations) in the associations between SCC, hope, CWB, and EWB. Specifically, we examined whether the within-person change in SCC and hope predicted concomitant within-person change in CWB and EWB among adolescents. We also examined whether SCC and hope accounted for unique variance in CWB and EWB, or if SCC on EWB and CWB was better explained via mediation pathways (i.e., between- and within-person pathways) of hope.

Importance of SCC in SWB

SCC, an important part of self-concept structure, refers to the consistent and stable sense of self, which mainly reflects the extent to which the self-concept is clearly and confidently defined (Campbell et al., 1996; Crocetti et al., 2015; Lodi-Smith et al., 2017). According to the self-discrepancy theory, when there is an inconsistency between the current self and the ideal self, it will reduce an individual’s positive emotional experience and produce negative emotions (Haemmerlie & Montgomery, 1982). People with low levels of SCC are inclined to have inconsistent and unstable self-perceptions. Therefore, people’s well-being naturally depends greatly on their SCC (Barnett et al., 2017; Haemmerlie & Montgomery, 1982; Xiang et al., 2020). Studies suggest that SCC has an impact on individual psychosocial functions. High SCC is closely associated with increased levels of life satisfaction and positive emotions (Slotter & Walsh, 2017; Xiang et al., 2020) and decreased levels of anxiety and depressive symptoms (Wong et al., 2019). Using a regression model, some cross-sectional studies suggested that SCC positively predicted EWB and CWB (Parise et al., 2019; Xiang et al., 2020). For instance, Parise et al. (2019) found SCC was an effective predictor of emotion regulation when dealing with positive and negative emotions in a sample of 922 adolescents (ages 14–16 years). Xiang et al. (2020) conducted the study in 2,792 Chinese adolescents and found that SCC could be a mediator in the relationship between family cohesion and SWB. Furthermore, in a longitudinal study, van Dijk et al. (2014) found that SCC predicted lower anxiety and symptoms of depression in a sample of 323 adolescents at a 4-year follow-up. In light of the above evidence, it is not surprising that SCC could be a key promoter for the development of CWB and EWB in adolescents.

Few studies, however, have longitudinally examined this relationship. The benefit of a longitudinal design is that it allows us to examine both between-person association (cross-sectional at one point) and within-person association (longitudinal across different points; Curran & Bauer, 2011; Hoffman & Stawski, 2009) of the predictors. For example, the linkage between SCC and SWB, the between-person association examines the difference between a group of adolescents with high levels of SCC versus a group with low levels of SCC on SWB. In contrast, the within-person association demonstrates the difference in a specific adolescent’s reports with SWB, which is quantified by the scores of SCC at a given time. In longitudinal data, the within-person effect is always nested in the between-person association in multilevel perspectives. We, therefore, can use the multilevel models to examine the within- and between-person associations of SCC and SWB.

Importance of Hope in SWB

According to Snyder’s (1995) hope theory, hope is defined as a general disposition that helps individuals initiate and sustain action toward long-term goals, and it includes pathway thinking (i.e., the ability to create feasible routes toward goals) and agency thinking (i.e., the belief that one is motivated to initiate or maintain progress toward a goal). Hope can also be divided into trait hope (i.e., a relatively stable and durable personality) and state hope (i.e., a much more situational or context-complex dynamic form; Luthans & Jensen, 2002; Nie et al., 2019). In the present study, we treated hope as a relatively stable personality trait.

As an important aspect of positive psychological functioning, hope is correlated to various aspects of mental health and plays a protective role to buffer individuals from negative influences. For instance, individuals with high levels of hope tend to have higher levels of life satisfaction (Demirli et al., 2014; Du et al., 2015; Nie et al., 2019; Pleeging et al., 2021) and report less anxiety (Arnau et al., 2010) and depression symptoms (Li et al., 2018). Previous research indicates that hope can reduce negative emotional experiences and promote the development of positive emotions (Satici, 2016; Yip & Tse, 2018). For instance, Yip and Tse (2019) recruited 139 Chinese adults and found that their trait hope can effectively reduce the generation of their negative emotions. In addition, Satici (2016) found that college students’ psychological vulnerability and resilience could affect their negative emotions through trait hope. Moreover, in the longitudinal study, adolescents’ hope, self-esteem, and attribution styles can predict their EWB and academic achievement (Ciarrochi et al., 2007). Thus, hope might play a central role in the development of SWB.

Hope as a Mediator in the Relationship Between SCC and SWB

As reviewed above, both SCC and hope are correlated with SWB (containing both CWB and EWB). However, we know less about how SCC, hope, and SWB are actually related. We can only speculate the relationship between these three variables according to a few theories and empirical studies. Based on hope theory, an individual will have a high level of hope when he or she has the motivation and multiple paths to achieve his goal (Snyder, 2002). People with the ability to unambiguously and consistently define beliefs about the self (i.e., SCC) might capture features of goal content and match the goal content to their own interests, which contributes to the increase of motivation in goal setting and achievement (i.e., agency thinking; Fite et al., 2017; Light et al., 2017). Moreover, people with a high level of SCC could actively seek matching solutions based on their abilities to increase the likelihood of success in achieving their goals (i.e., pathway thinking; Thomas & Gadbois, 2007). Evidence from existing research indicates that people experiencing self-uncertainty could reduce the accessibility of possible selves related to a goal (Smith et al., 2014), which in turn may undermine goal pursuit (Oyserman et al., 2015). Individuals with clear self-definition tend to have a strong sense of goal and set long-term goals related to their interests (Fite et al., 2017). In addition, previous cross-sectional studies indicated positive associations between hope and self-concept (JahangiriZadeh & Khodabakhshi Koolaee, 2016; Patrício et al., 2019; Teimouri et al., 2020) and between hope and metacognition (González et al., 2017). Moreover, Xiang et al. (2020) found that family cohesion could influence CWB and EWB through the chain-mediating effect of SCC and hope. Therefore, individuals with a clearer self-concept might have higher levels of hope. That is, SCC may promote the development of hope, which in turn contributes to the development of EWB and CWB. The above hope is considered as a mediator at the between-person level (i.e., compared with individuals with low-level hope, individuals with high-level hope are more likely to be positively affected by SCC, and are more likely to promote the improvement of happiness) and has attracted more attention in recent years. However, hope as a mediator at the within-person level (i.e., hope would mediate the relationship between SCC and SWB over time) has not been studied well.

Gender and Age as Moderators

Several studies have identified age and gender differences in SCC, hope, and SWB (Crocetti et al., 2015). For example, Crocetti et al. (2015) conducted a 6-year longitudinal study and found that compared to adolescent girls, adolescent boys show an increase in SCC during early teenage years, followed by a decline after turning 16. Xiang et al. (2021) also reported that boys and older adolescents had higher levels of SCC than girls and young adolescents in a sample of 2,792 adolescents. In addition, older adolescents reported higher levels of life satisfaction and positive emotions than younger adolescents. With regard to hope, Marques and Gallagher (2017) conducted a study with 1,453 participants and found moderate rank-order stability of hope over a 1-year interval in middle adolescent and early adult groups. Furthermore, Hendricks (2006) suggested that middle adolescents reported higher well-being than late adolescents, and girls reported higher hope and well-being than boys. Moreover, Xiang et al. (2022) found a gender-specific relationship between SCC and SWB in a longitudinal study using latent growth models. Considering that gender and age differences may exist in the relationship among SCC, hope, and SWB, the present study further examined age and gender differences as an exploratory analysis.

The Present Study

The present study examined relationships over time among SCC, hope, CWB, and EWB. Although previous research (e.g., Xiang et al., 2022, 2023) examined the development of SCC and the longitudinal associations of SCC and well-being in adolescents from ages 11–24 using the latent growth curve model, Cross-Lagged Panel Models (CLPMs), and Random Intercept Cross-Lagged Panel Models (RI-CLPMs), the present study has unique contributions. First, the present study addressed the research gaps related to potential mechanism (i.e., hope) in the longitudinal associations of SCC and SWB, which was not examined in previous research (Xiang et al., 2022, 2023).

Second, compared to previous studies, this study extends the analysis by disentangling within- and between-person associations in the longitudinal relationships among SCC, hope, and SWB using multilevel mediation models. Specifically, in terms of between-person associations, adolescents with higher levels of SCC could report higher levels of hope, which in turn would report higher levels of CWB and EWB, compared to adolescents who report lower levels of SCC. In addition, concerning within-person associations, an adolescent whose SCC increases over time should experience a subsequent increase in hope, and in turn in greater SWB. Third, we intended to investigate gender and age differences in both scores for SCC, hope, CWB, and EWB and the associations among the above main variables. We believe that based on our previous research results, this study can provide some new insights.

Method

Participants and Procedure

Participants were adolescents attending eight schools (containing three middle and high schools and five universities) in China. Recruitment of study participants occurred for 1 year across three waves (i.e., 6 months apart across three cohorts; henceforth labeled T1, T2, and T3). The present 2,001 adolescents ranged in age from 11 to 24 years (M = 16.01, SD = 2.68; 42.9% males) at the first wave of assessment. According to Sawyer et al. (2018), the contemporary perspective on the age range of adolescence posits it to be between 10 and 24 years. This aligns more accurately with both the physiological growth of adolescents and the broader societal perception of this developmental stage. At the commencement of the study, 32.9% of adolescents were junior high school students, with ages ranging from 11 to 15 years (M_age = 12.84 years, SD = 0.68; 46% males), 32.6% of adolescents were high school students, with ages ranging from 13 to 19 years (M_age = 15.99 years, SD = 0.80; 41.6% males), and 34.5% of adolescents were college students, with ages ranging from 17 to 24 years (M_age = 19.04 years, SD = 1.01). Only 1,608 adolescents participated in all three time point assessments for a year (M_age = 15.72 years, SD = 2.58; 42.5% males). The participants were the same as those in previous longitudinal studies (Xiang et al., 2022, 2023) that explored the longitudinal associations of SCC and well-being in adolescents ages 11–24 years.

Based on participants’ T1 characteristics, we compared participants who were included in the T3 assessments with those who were not. We created an indicator (0 = missing, 1 = complete) to examine whether the missing data influence the key variables of our research. Chi-square (χ²) tests for contingency and independent samples t-tests were used for gender, home location, only child status, age, SCC, hope, CWB, and EWB, respectively. The results revealed that data on adolescents from cities and towns (χ²_[1] = 5.73, p < .05) and only children (χ²_[1] = 3.94, p < .05) were significantly missing, as were those on SCC (t = 2.79, p < .01) and age (t = 9.83, p < .001), but other variables (gender, hope, CWB, and EWB) were not significant with missing data (ps > .05). Consequently, we used the full-information maximum-likelihood method to deal with the missing data via Mplus 7.0.

This study, approved by the educational and psychological research ethics committee of China Three Gorges University (No. H23001), adhered strictly to the guidelines outlined in the Declaration of Helsinki. Prior to commencing the survey, adolescents were furnished with written information about the research and sought to give their oral consent. Throughout each period of the study, trained researchers administered a self-report questionnaire to the participants within a 45-min class period, subsequently collecting the completed questionnaires.

Measures

SCC

The Self-Concept Clarity Scale (SCCS; Campbell et al., 1996) was used to measure the extent of clear and consistent self-view among adolescents; the scale comprises 12 items (e.g., I spend a lot of time wondering about what kind of person I really am), scored on a 7-point scale ranging from 1 (complete disagreement) to 7 (complete agreement). Except for Items 6 (e.g., I seldom experience conflict between the different aspects of my personality) and 11 (e.g., In general, I have a clear sense of who I am and what I am), all items were scored in reverse. Responses for all 12 items were averaged to produce a composite score, and higher scores indicate higher levels of SCC. Previous Chinese studies indicate that SCCS has good re-test, internal reliability, and high validity (Xiang et al., 2020). For scores in the present study, Cronbach’s α for the SCCS was 0.81 (T1), 0.85 (T2), and 0.86 (T3).

Hope

The Children’s Hope Scale (CHS; Snyder et al., 1997) has often been used to measure goal-related cognition. Students respond using a 6-point Likert-type scale (from 1 = none of the time to 6 = all of the time). A composite score was produced from the averaged responses for all six items. Higher scores indicated higher levels of hope. This scale has been evidenced to be suitable for both children (ages 6–13; Snyder et al., 1997) and adolescents (ages 11–24; Nie et al., 2019; Xiang et al., 2020). The Chinese version of the CHS (Nie et al., 2019) has been evidenced by good reliability and validity. For scores in the present study, Cronbach’s α for the SCCS was 0.85 (T1), 0.89 (T2), and 0.88 (T3).

CWB

The Satisfaction with Life Scale (SWLS; Diener et al., 1985) was used to measure the cognitive component of SWB (i.e., CWB), which consists of five items (e.g., “I am satisfied with my life”), using a 7-point scale (1 = totally disagree, 7 = totally agree) to measure overall satisfaction with one’s life. Items were averaged with higher scores indicating higher life satisfaction. Existing research indicates that the Chinese version of the SWLS has a reliable and valid measurement to assess the CWB of Chinese adolescents (Kong et al., 2015). In the present study, the internal consistency (Cronbach’s α) for the SWLS was 0.72 (T1), 0.80 (T2), and 0.79 (T3).

EWB

The Positive and Negative Affect Schedule (PANAS; Watson et al., 1988) was used to evaluate the emotional component of well-being (i.e., EWB). The PANAS contains 20 items describing two different affect states (10 positive and 10 negative words; e.g., “active” and “afraid”) using a 5-point Likert-type scale. The Positive Affect subscale (PAS) and Negative Affect subscale (NAS) scores were calculated separately, and the final EWB score was computed by subtracting the NAS score from the PAS score, with higher scores indicating higher levels of their current EWB (Kong et al., 2015; Wang et al., 2020). For scores in the present study, Cronbach’s α for the PAS were 0.83 (T1), 0.87 (T2), and 0.85 (T3), whereas for the NAS, they were 0.84 (T1), 0.88 (T2), and 0.86 (T3).

In addition, to assess the long-term internal consistency of the measures, we performed a longitudinal confirmatory factor analysis using three models. Initially, the configural invariance model (CIM) estimated all parameters across the three waves. Subsequently, a basic test of factorial invariance was conducted, employing a weak invariance model (WIM), which constrained factor loadings to be equal across T1, T2, and T3. Finally, a strong invariance model (SIM) was established to equate the factor loadings and intercepts across the time points. Differences in models were assessed by identifying changes in Comparative Fit Index (CFI; i.e., ΔCFI < 0.01 indicates a significant difference; Cheung & Rensvold, 2002).

The results of longitudinal measurement invariance analysis (Cheung & Rensvold, 2002) indicated that SCCS (ΔCFI = 0.003, ΔCFI = 0.006; root mean square error of approximation (ΔRMSEA) = 0.001, ΔRMSEA = 0.001) and CHS had strong invariance (ΔCFI = 0.003, ΔCFI = 0.004; ΔRMSEA = 0.001, ΔRMSEA = 0.001), while PAS (ΔCFI = 0.002, ΔCFI = 0.014; ΔRMSEA = 0.001, ΔRMSEA = 0.002) showed weak invariance, as did NAS (ΔCFI = 0.005, ΔCFI = 0.023; ΔRMSEA = 0.001, ΔRMSEA = 0.003) and SWLS (ΔCFI = 0.001, ΔCFI = 0.012; ΔRMSEA = 0.002, ΔRMSEA = 0.005). Regardless of whether it was weak or strong invariance, the results demonstrated no significant changes over time (Xiang et al., 2023). Additional details of the tests of measurement invariance can be found in Table A1 in Appendix 1. We also conducted measurement invariance assessments for gender (1 = boy, 2 = girl) and age groups (1 = younger adolescents, 2 = older adolescents). The results demonstrated the measurement invariance across both boys and girls (ΔCFIs = 0.001–0.009, ΔRMSEAs = 0.001–0.003), as well as between younger and older adolescents (ΔCFIs = 0.001–0.011, ΔRMSEAs = 0.001–0.005).

Statistical Analyses

Descriptive Statistics and Repeated Measures Analysis of Variance (ANOVA)

Before conducting longitudinal multilevel mediation model analyses, descriptive statistics for SCC, hope, CWB, and EWB were calculated for the three waves of data using SPSS 21.0 software. First, 3 (times: T1, T2, and T3) × 2 (gender: boys and girls) ANOVA was used to explore the influence of times and gender on SCC, hope, CWB, and EWB, respectively. Second, we used unconditional means models to partition the variance in outcomes (i.e., SCC, hope, EWB, and CWB) across both between- and within-person analyses. Specifically, the intra-class coefficient (ICC) was used to compute each of the above main variables. The ICC coefficient indicates the proportion of between-person-level variation in total variation (Hoffman, 2015; Nie et al., 2019) in multilevel models. If there was substantial variance at the within-person level (i.e., at least 10%) for each measure, multilevel models were conducted (Hamaker et al., 2015; Yang et al., 2022). Then, we conduct between-person and within-person correlations between SCC, hope, CWB, and EWB.

Longitudinal Multilevel Mediation Model Analyses

The previous between-person research cannot examine the impact of within-person change in SCC and hope on concomitant within-person change in CWB and EWB. Thus, in the present study, multilevel regression models (MLMs) were used to estimate models for hierarchical and repeated measures data (Kenny et al., 2003). We used Mplus 7.0 to implement a series of two-level multilevel models in which SCC, hope, CWB, and EWB were treated as time-varying variables, which were each measured at T1, T2, and T3. Then, we examined whether the effect of time-varying SCC on EWB and CWB could be better accounted for through the mediating effect of hope both at the between-person level and within-person level (Galla et al., 2014; Preacher et al., 2010). The use of time-varying covariates (TVCs) in longitudinal multilevel mediation model design allows disaggregation of the within- and between-person differences (Hoffman, 2015; Nie et al., 2019). To enhance understanding of the MLM, a sample two-level model is presented here (Galla et al., 2014):

Level 1 (within-person level):

CWB / {EWB}_{i j} = β_{0 j} + β_{1 j} + β_{2 j} (time) + β_{2 j} (TVC) + ε_{i j}

Level 2 (between-person level):

β_{0 j} = y_{00} + y_{01} (average TVC) + y_{0 n} (covariates) + u_{0 j}

β_{1 j} = y_{11} + y_{12} (average TVC) + y_{0 n} (covariates) + u_{1 j}

β_{2 j} = y_{20}

These models comprise the intercept of outcomes, slope (time), and TVC (either SCC or hope). To elucidate these variables, they were mean-centered (Galla et al., 2014; Nie et al., 2019). Intra-individual centralization involves subtracting the value at a specific time point from the individual’s average value across three measurements, that is intra-group centralization or individual neutralization. This process excludes inter-individual information from Level 1 variables, enabling the analysis of intra-individual variables. Simultaneously, Level 2 variables among individuals were also neutralized, resulting in a constant total mean value. Subsequently, all inter-individual and intra-individual variables were standardized. This approach facilitates the disentanglement of intra-individual and inter-individual effects on the outcomes (Hoffman & Stawski, 2009). It also allows for the simultaneous estimation of associations between within-person changes in SCC, hope, CWB, and EWB; the associations between mean between-person levels of SCC, hope, and baseline CWB and EWB; and rates of change in CWB and EWB. Moreover, the current study incorporates gender and age as moderators in both between- and within-person models.

Results

Primary Analysis

Table 1 shows the means and other descriptive statistics for SCC, hope, EWB, and CWB for boys and girls, across three waves. The results of ANOVA (see Figure 1) showed that for SCC, the main effect of time was significant, F(2, 2,646) = 18.08, p < .001, η_p² = .01, and the scores for SCC decreased from T1 to T2 but increased from T2 to T3. The main effect of gender was also significant, F(1, 1,323) = 6.50, p < .05, η_p² = .01, and the scores for SCC were higher for boys than girls. The interaction between time and gender was found to be significant, F(2, 2,646) = 7.14, p < .001, η_p² = .01. Simple effect analysis showed that for boys, the scores for SCC at T2 were significantly lower than at T3, F(2, 2,202) = 3.66, p < .05). However, for girls, there were no significant differences among the three times (T1, T2, and T3).

Table 1.

Means and Other Descriptive Statistics for SCC, Hope, CWB, and EWB for Boys and Girls.

Variables	Boys (three waves)				Girls (three waves)
Variables	M	SD	Skewness	Kurtosis	M	SD	Skewness	Kurtosis
T1 (N = 2,001)
SCC	4.18	1.00	0.12	−0.29	4.05	0.96	0.07	−0.24
Hope	3.56	0.89	0.48	0.10	3.30	0.87	0.54	0.28
CWB	3.93	1.06	0.13	−0.01	3.92	1.05	0.13	−0.19
EWB	0.76	0.95	−0.06	0.33	0.54	0.95	−0.21	0.15
T2 (N = 1,703)
SCC	4.10	1.00	0.25	0.14	3.99	1.00	0.10	−0.07
Hope	3.52	0.83	0.51	0.76	3.43	0.84	0.56	0.63
CWB	4.05	0.98	0.15	0.74	3.97	1.04	0.01	0.37
EWB	0.55	1.02	0.27	0.74	0.37	1.00	−0.01	0.51
T3 (N = 1,608)
SCC	4.25	1.05	−0.01	−0.50	4.00	0.99	0.06	−0.28
Hope	3.45	0.90	0.60	0.11	3.26	0.86	0.58	0.55
CWB	3.92	1.11	0.03	−0.18	3.80	1.08	−0.02	−0.27
EWB	0.67	0.98	0.17	−0.21	0.40	0.93	−0.15	0.35

Note. SCC: self-concept clarity; CWB: cognitive well-being; EWB: emotional well-being. The range of scales for SCC, Hope, CWB, and EWB is 1–7, 1–6, 1–7, and 1–5, respectively.

Figure 1.

Differences Between Boys and Girls in Scores for (a) SCC, (b) Hope, (c) CWB, and (d) EWB Across Three Waves. SCC: self-concept clarity; CWB: cognitive well-being; EWB: emotional well-being. The range of scales for SCC, Hope, CWB, and EWB is 1–7, 1–6, 1–7, and 1–5, respectively. N_T1 = 2,001, N_T2 = 1,703, and N_T3 = 1,608.

For hope, there was a main effect of time, F(2, 2,646) = 5.65, p < .001, η_p² = .01, and gender, F(1, 1,323) = 25.10, p < .001, η_p² = .02. Specifically, the scores for hope at T1 and T2 were larger than at T3, and the scores were higher for boys than girls. In addition, the interaction between time and gender was significant, F(2, 2,646) = 9.23, p < .01, η_p² = .01. Simple effect analysis showed that for boys, the scores for hope at T1 were significantly higher than at T3, F(2, 2,202) = 3.47, p < .05. In addition, for girls, the scores for hope at T1 and T3 were significantly lower than at T2, F(2, 3,099) = 10.99, p < .001.

For CWB, there was a main effect of time, F(2, 2,642) = 5.19, p < .001, η_p² = .01, and gender, F(1, 1,321) = 3.97, p = .046, η_p² = .01. Specifically, the scores for CWB at T2 were larger than at T3, and the scores were higher for boys than girls. In addition, the interaction between time and gender was significant, F(2, 2,642) = 3.20, p = .046, η_p² = .01. Simple effect analysis showed that for boys, the scores for CWB at T2 were significantly higher than at T1 and T3, F(2, 2,200) = 3.56, p < .05. However, for girls, the scores for CWB at T1 and T2 were significantly higher than at T3, F(2, 3,099) = 7.27, p < .001.

For EWB, there was a main effect of time, F(2, 2,646) = 34.44, p < .001, η_p² = .03, and gender, F(1, 1,323) = 28.41, p < .001, η_p² = .02. The scores for EWB at T1 were higher than at T2 and T3, but the scores for EWB at T3 were higher than at T2. In addition, the scores for EWB were higher for boys than girls.

Common Methods Bias Analyses

Because the data were obtained through questionnaires, potential common method deviation could have arisen. To address and assess this, we employed Harman’s single-factor test using confirmatory factor analysis (Ma & Zhang, 2020). Specifically, factor analysis was applied to all items of SCCS, CHS, SWLS, and PANAS, and extracted a common factor from these items. The findings indicated that the interpretation rate of the first factor was 21.06%, less than 40%, suggesting no common method bias in the questionnaires used in this study.

Correlation Analyses

Correlations Among SCC, Hope, CWB, and EWB

Table A2 indicates that SCC, hope, CWB, and EWB scores were moderately stable over time (r = 0.23–0.60, ps < .01). In addition, we found that age had a positive association with SCC (r = 0.18, p < .01) and a negative correlation with CWB (r = −0.16, p < .01) at T1. At T2, age had positive associations with SCC (r = 0.17, p < .01), hope (r = 0.14, p < .01), and EWB (r = 0.10, p < .01). At T3, age had positive correlations with SCC (r = 0.13, p < .01) and hope (r = 0.08, p < .01) and had a negative association with CWB (r = −0.13, p < .01). Therefore, we would consider age as a moderator in the within- and between-person models among SCC, hope, CWB, and EWB.

Between- and Within-Person Correlations

Table 2 shows the between- and within-person correlations for SCC, hope, CWB, and EWB. The results indicate that both for the between-person level and within-person level, all variables had significantly positive relationships (r = 0.27–0.66, ps < .01). In addition, ICC for SCC, hope, CWB, and EWB were 0.56, 0.53, 0.48, and 0.56, respectively.

Table 2.

Between- and Within-Person Correlations Among Main Variables (N_T1 = 2,001, N_T2 = 1,703, and N_T3 = 1,608).

	ICC	Between-person association				Within-person association
	ICC	1	2	3	4	1	2	3	4
1. SCC	0.56	—				—
2. Hope	0.53	0.44**	—			0.36**	—
3. CWB	0.48	0.33**	0.55**	—		0.27**	0.49**	—
4. EWB	0.56	0.61**	0.66**	0.53**	—	0.54**	0.56**	0.45**	—

Note. ICC: intra-class coefficient; SCC: self-concept clarity; CWB: cognitive well-being; EWB: emotional well-being.

p < .01.

Multilevel Mediation Analyses

The longitudinal results of multilevel mediation analyses are shown in Table 3 and Figure 2. First, for CWB, the between-person (i.e., cross-sectional at one point) mediation effect was significant. Specifically, the mediation association between SCC and CWB, through hope, was significant (a × b = 0.22, SE = 0.02, p < .001, 95% confidence interval [CI] = [0.200, 0.251]). The direct effect of SCC on CWB was also significant (c′ = 0.11, SE = 0.02, p < .001). In addition, the within-person (i.e., longitudinal across different points) mediation effect was also significant. In specific, the mediation effect of SCC on CWB, through hope, was significant (a × b = 0.06, SE = 0.01, p < .001, 95% CI = [0.045, 0.076]). The direct effect of SCC on CWB was also significant (c′ = 0.07, SE = 0.02, p < .001).

Table 3.

Multilevel Mediation Models of Hope (N_T1 = 2,001, N_T2 = 1,703, and N_T3 = 1,608).

Mediation type	a	B	c′	a × b [95% CI]	c
Outcome: CWB
Between-person level	0.38***	0.59***	0.11***	0.22 [0.200, 0.251]	0.33***
Within-person level	0.13***	0.45***	0.07***	0.06 [0.045, 0.076]	0.13***
Outcome: EWB
Between-person level	0.38***	0.54***	0.39***	0.21 [0.185, 0.228]	0.60***
Within-person level	0.13***	0.29***	0.28***	0.04 [0.028, 0.051]	0.32***

Note. CWB: cognitive well-being; EWB: emotional well-being; CI: confidence interval.

***

p < .001.

Figure 2.

Multilevel Mediation Model of Hope on Association Between (a) SCC and CWB and (b) Between SCC and EWB. SCC: self-concept clarity; CWB: cognitive well-being; EWB: emotional well-being. N_T1 = 2,001, N_T2 = 1,703, and N_T3 = 1,608.

In addition, for EWB, the between-person (i.e., cross-sectional at one point) mediation effect was significant. The mediation effect of SCC on EWB, through hope, was significant (a × b = 0.21, SE = 0.01, p < .001, 95% CI = [0.185, 0.228]), and the direct effect of SCC on EWB was also significant (c′ = 0.39, SE = 0.02, p < .001). Moreover, the within-person (i.e., longitudinal across different points) mediation effect was also significant. The mediation effect of SCC on EWB, through hope, was significant (a × b = 0.04, SE = 0.01, p < .001, 95% CI = [0.028, 0.051]). Meanwhile, the direct effect of SCC on EWB was also significant (c′ = 0.28, SE = 0.02, p < .001).

To examine whether gender (1 = boy, 2 = girl) and age moderated the within- and between-person models, we carried out a series of slope tests. At the within-person level, gender and age were found to moderate the effect of SCC on EWB (b_gender = 0.08, p = .034; b_age = −0.01, p = .040). Specifically, the association between SCC and EWB was stronger for girls than for boys, and this association strength decreased with age over time. In addition, the moderation effect of age in the path of hope on EWB was also significant (b_age = −0.02, p = .018), with the association being stronger for young adolescents than older adolescents over time. However, at the between-person level, the moderation effect of age in hope on CWB was found to be significant (b_age = 0.03, p = .001), with the association being stronger for older adolescents compared to younger adolescents.

Discussion

Previous research has emphasized the between-person associations between SCC, hope, and SWB, and has not considered whether SCC and hope change within the person and correspondingly, whether such change affects SWB. The present study extended prior research and aimed to explore the longitudinal links between SCC, hope, and SWB at both the between-person level and within-person level. Of particular interest was the mediating role of hope in the associations between SCC and CWB and between SCC and EWB. As expected, we found that SCC had a positive correlation between hope, CWB, and EWB. In addition, multilevel mediation analyses indicated that hope could be a mediator in the association between SCC and SWB (containing both CWB and EWB) at both the between-person and within-person levels. Furthermore, we found that the associations between SCC, hope, and SWB were dynamic relationships that differed with age and gender at between-person and within-person levels.

First, in accordance with our hypothesis, this study found that SCC positively correlated with CWB and EWB no matter at the within-person level or between-person level. At the between-person level, adolescents with high levels of SCC reported greater life satisfaction and more positive emotions than those with low levels of SCC, which helps confirm a large body of previous studies (Slotter & Walsh, 2017). In addition, we found that an individual student with high levels of SCC could predict greater CWB and EWB over time. That is, as adolescents changed (relative to their own mean levels) in their levels of SCC, so too did their life satisfaction and emotional quality. This finding is consistent with previous longitudinal research and contributes to understanding the malleability of SCC (Crocetti et al., 2016; Schwartz et al., 2012), which could contribute to the development of CWB and EWB. The finding of such a within-person effect reveals the relationship between SCC and SWB from the perspective of individual development and extends the previous direct between-person association to a within-person association, which to some extent makes up for the gaps in previous studies.

Second, the mediating effect of hope in the relationship between SCC and SWB has not been simultaneously reported at the between- and within-person levels. In the present study, as predicted, we found longitudinal mediation effects of hope in the associations between SCC and well-being outcomes (e.g., CWB and EWB) among adolescents at both between- and within-person levels. At the between-person level, adolescents with higher levels of SCC were found to be more hopeful than those with lower levels of SCC, which in turn was correlated with higher CWB and EWB. Several studies have reported similar results to our research. For instance, Poulsen et al. (2006) found that goal orientations (i.e., a form of hope) could mediate the association of self-concept and life satisfaction. Cotton et al. (2009) showed that hope mediated the relationship between purpose and life satisfaction in adolescents, emerging adults, and adults. More similar to this study, Xiang et al. (2020) demonstrated that family cohesion could be associated with EWB and CWB indirectly through the chain mediation effect of SCC and hope. Above all, these findings suggest that adolescents’ perceptions about themselves (e.g., SCC) play a central role in their goal setting and attaining (e.g., hope), which in turn promote their emotional quality and life satisfaction.

What is unique about the present finding is that the associations among SCC, hope, and SWB also exist at the within-person level. More specifically, an adolescent’s SCC level at a point in time significantly predicted that adolescent’s hope, which in turn predicted EWB and CWB at that particular point in time. In addition, individual adolescents who reported a rapid increase in SCC reported a rapid increase in hope, and in turn, predicted higher levels of SWB (relative to themselves). These findings lend empirical support to the theories that have consistently asserted that having a coherent self-understanding should be critical for hope (Barnett et al., 2017; Snyder, 2002). Thus, our findings provide direct empirical evidence for the mediating role of hope in the relationship between SCC and SWB at the within-person level, which helps to understand the above three variables at the individual level.

Finally, we found gender and age differences in the associations between SCC, hope, CWB, and EWB. The results of moderate effects of gender and age in the longitudinal multilevel mediation models demonstrated that at the within-person level, the association between SCC and EWB was stronger for girls than for boys, and this association strength was decreased with age over time. According to the attachment promotion hypothesis and internal working models, females might have a stronger ability to disclose positive/negative feelings (Pinquart & Sorensen, 2001), recognize emotional responses, and better metacognitive ability to interpret information, which may account for the gender difference in the association between SCC (i.e., a metacognitive process) and EWB. In addition, based on previous research, adolescent girls are found to suffer from more emotional problems than adolescent boys (Bouma et al., 2008), and the interaction effect of gender by self-esteem (i.e., a component of self-concept) is found on depression, with the association being stronger for girls than for boys (Moksnes & Espnes, 2012). However, this was found at the between-person level, not at the within-person level. Our study could provide supplementary support for the above finding demonstrating that SCC (i.e., a construct of self-concept) was more likely to be a somewhat stronger variable for girls than for boys’ EWB over time. In addition, the association between SCC and EWB decreased with age over time. The developmental change in the relationship between SCC and EWB could support the hypothesis that self-beliefs, achievement, and emotion gradually become a coherent self-stabilizing system with age (Wu et al., 2021). According to the longitudinal research of van Dijk et al. (2014), over time, the links between SCC and later anxiety symptoms only existed in early to middle adolescents rather than older adolescents, which could partly support the coherent stabilizing system within the self with age over time. Furthermore, at the within-person level, the moderation effect of age in the path of hope on EWB was also significant, with the association being stronger for young adolescents than older adolescents over time. However, at the between-person level, the association between hope and CWB was stronger for older adolescents than for young adolescents. Due to the lack of guiding theory and empirical research support for this finding, we would not speculate on differences in the relationship between hope and CWB and between hope and EWB at the between- and within-person level.

Limitations

Although the present study has several unique strengths, including its longitudinal design and the application of multilevel mediation analyses to distinguish between-person associations from within-person associations, it is imperative to acknowledge its limitations. First, the non-experimental nature of this study may constrain our capacity to draw causal inferences regarding the influence of SCC and hope on CWB and EWB. In future research, the employment of experimental methodologies would facilitate the elucidation of causal relationships among the principal variables. Second, the data were collected with only a self-reported scale, which does not capture the perspective of the parents, teachers, and experts about adolescents’ SCC and hope. Consequently, the robustness of our findings may be compromised. Future studies could enhance comprehensiveness and objectivity by integrating data from diverse sources, such as peer and teacher evaluations. Third, both the number of waves and the longitudinal sampling interval could impact the results. The utilization of only a 12-month longitudinal design with intervals of merely 6 months between data collection waves might be deemed too brief, constituting a potential limitation. Future research endeavors could incorporate additional waves of data over an extended temporal span, thereby bolstering the persuasiveness of predictions and allowing for analysis through diverse methodologies, such as latent variable growth curve models.

Conclusion

The results indicated that hope could be a mediator in the association between SCC and SWB (containing both CWB and EWB) at both the between-person and within-person levels. The findings of the present study suggest that SCC and hope could be critical factors in the development of EWB and CWB among adolescents. More importantly, our results indicate that hope, as an explanatory mechanism for the relationship between SCC and SWB among adolescents, provides a potential intervention target for improving adolescents’ well-being.

Footnotes

Appendix 1

Table A2.

Correlations Between Model Variables.

Variables	1	2	3	4	5	M	SD	Skewness	Kurtosis
T1
1. Age	—					16.01	2.68	0.06	–1.14
2. Gender	–0.01	—				—	—	—	—
3. SCC	0.18**	–0.06**	—			4.11	0.98	0.19	–0.25
4. Hope	0.01	–0.15**	0.32**	—		3.41	0.89	0.51	0.19
5. CWB	–0.16**	–0.01	0.23**	0.46**	—	3.92	1.05	0.13	–0.11
6. EWB	0.02	–0.11**	0.50**	0.54**	0.41**	0.64	0.95	–0.15	0.25
T2
1. Age	—					16.61	2.76	0.07	–1.23
2. Gender	–0.01	—				—	—	—	—
3. SCC	0.17**	–0.05*	—			4.03	1.00	0.16	0.02
4. Hope	0.14**	–0.06*	0.38**	—		3.47	0.84	0.54	0.66
5. CWB	–0.01	–0.04	0.31**	0.54**	—	4.00	1.01	0.05	0.51
6. EWB	0.10**	–0.09**	0.57**	0.60**	0.50**	0.44	1.01	0.11	0.64
T3
1. Age	—					16.66	2.55	0.18	–0.96
2. Gender	–0.01	—				—	—	—	—
3. SCC	0.13**	–0.12**	—			4.11	1.02	0.05	–0.39
4. Hope	0.08**	–0.11**	0.40**	—		3.34	0.88	0.59	0.36
5. CWB	–0.13**	–0.05*	0.28**	0.48**	—	3.85	1.09	0.01	–0.22
6. EWB	0.04	–0.14**	0.53**	0.57**	0.45**	0.51	0.96	0.06	0.17

Note. SCC: self-concept clarity; CWB: cognitive well-being; EWB: emotional well-being.

p < .05; **p < .01.

Availability of Data and Materials

Data are available upon reasonable request.

Credit Authorship Contribution Statement

Guangcan Xiang: Conceptualization, Formal analysis, Writing-original draft, Writing-review & editing, Project administration. Zhaojun Teng: Conceptualization, Formal analysis. Yiru Du: Formal analysis. Linchuan Yang: Writing-original draft. Yanyan He: Conceptualization.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was funded by the Projects of the National Social Science Foundation of China (grant no. 18CSH051), Philosophy and Social Science Research Project of Education Department of Hubei Province, China (grant no. 22Q029), and Social Science Research Project in Yichang, China (grant no. ysk23kt076).

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

ORCID iD

Guangcan Xiang

References

Arnau

R. C.

Rosen

D. H.

Finch

J. F.

Rhudy

J. L.

Fortunato

V. J.

(2010). Longitudinal effects of hope on depression and anxiety: A latent variable analysis. Journal of Personality, 75(1), 43–64. https://doi.org/10.1111/j.1467-6494.2006.00432.x

Barnett

M. D.

Moore

J. M.

Harp

A. R.

(2017). Who we are and how we feel: Self-discrepancy theory and specific affective states. Personality and Individual Differences, 111, 232–237. https://doi.org/10.1016/j.paid.2017.02.024

Bouma

E. M. C.

Ormel

Verhulst

F. C.

Oldehinkel

A. J.

(2008). Stressful life events and depressive problems in early adolescent boys and girls: The influence of parental depression, temperament and family environment. Journal of Affective Disorders, 105(1–3), 185–193. https://doi.org/10.1016/j.jad.2007.05.007

Campbell

J. D.

Trapnell

P. D.

Heine

S. J.

Katz

I. M.

Lavallee

L. F.

Lehman

D. R.

(1996). Self-concept clarity: Measurement, personality correlates, and cultural boundaries. Journal of Personality and Social Psychology, 70(1), 141–156. https://doi.org/10.1037/0022-3514.70.1.141

Cheung

G. W.

Rensvold

R. B.

(2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5

Ciarrochi

Heaven

P. C.

Davies

(2007). The impact of hope, self-esteem, and attributional style on adolescents’ school grades and emotional well-being: A longitudinal study. Journal of Research in Personality, 41(6), 1161–1178. https://doi.org/10.1016/j.jrp.2007.02.001

Cotton

B. K.

Hill

P. L.

Lapsley

D. K.

Talib

T. L.

Finch

(2009). Purpose, hope, and life satisfaction in three age groups. The Journal of Positive Psychology, 4(6), 500–510. https://doi.org/10.1080/17439760903271439

Crocetti

Moscatelli

Van der Graaff

Rubini

Meeus

Branje

(2016). The interplay of self-certainty and prosocial development in the transition from late adolescence to emerging adulthood. European Journal of Personality, 30(6), 594–607. https://doi.org/10.1002/per.2084

Crocetti

Rubini

Branje

Koot

H. M.

Meeus

(2015). Self-concept clarity in adolescents and parents: A six-wave longitudinal and multi-informant study on development and intergenerational transmission. Journal of Personality, 84(5), 580–593. https://doi.org/10.1111/jopy.12181

10.

Curran

P. J.

Bauer

D. J.

(2011). The disaggregation of within-person and between-person effects in longitudinal models of change. Annual Review of Psychology, 62, 583–619. https://doi.org/10.1146/annurev.psych.093008.100356

11.

Demirli

Türkmen

Arik

R. S.

(2014). Investigation of dispositional and state hope levels’ relations with student subjective well-being. Social Indicators Research, 120(2), 601–613. https://doi.org/10.1007/s11205-014-0607-9

12.

Diener

(2009). Assessing subjective well-being: Progress and opportunities. Social Indicators Research, 39, 25–65. https://doi.org/10.1007/978-90-481-2354-4_3

13.

Diener

E. D.

Emmons

R. A.

Larsen

R. J.

Griffin

(1985). The satisfaction with life scale. Journal of Personality Assessment, 49, 71–75. https://doi.org/10.1207/s15327752jpa4901_13

14.

Bernardo

A. B. I.

Yeung

S. S.

(2015). Locus-of-hope and life satisfaction: The mediating roles of personal self-esteem and relational self-esteem. Personality and Individual Differences, 83, 228–233. https://doi.org/10.1016/j.paid.2015.04.026

15.

Ebert

A. R.

Bernstein

L. E.

Carney

A. K.

Patrick

J. H.

(2020). Emotional well-being during the first four months of COVID-19 in the United States. Journal of Adult Development, 27, 1–8. https://doi.org/10.1007/s10804-020-09365-x

16.

Fite

R. E.

Lindeman

M. I. H.

Rogers

A. P.

Voyles

Durik

A. M.

(2017). Knowing oneself and long-term goal pursuit: Relations among self-concept clarity, conscientiousness, and grit. Personality and Individual Differences, 108, 191–194. https://doi.org/10.1016/j.paid.2016.12.008

17.

Galla

B. M.

Wood

J. J.

Tsukayama

Har

Chiu

A. W.

Langer

D. A.

(2014). A longitudinal multilevel model analysis of the within-person and between-person effect of effortful engagement and academic self-efficacy on academic performance. Journal of School Psychology, 52(3), 295–308. https://doi.org/10.1016/j.jsp.2014.04.001

18.

Geng

(2016). Gratitude mediates the effect of emotional intelligence on subjective well-being: A structural equation modeling analysis. Journal of Health Psychology, 23(10), 1378–1386. https://doi.org/10.1177/1359105316677295

19.

González

Fernández

M. V. C.

Paoloni

P. V.

(2017). Hope and anxiety in physics class: Exploring their motivational antecedents and influence on metacognition and performance. Journal of Research in Science Teaching, 54(5), 558–585. https://doi.org/10.1002/tea.21377

20.

Haemmerlie

F. M.

Montgomery

R. L.

(1982). Self-perception theory and unobtrusively biased interactions: A treatment for heterosocial anxiety. Journal of Counseling Psychology, 29(4), 362–370. https://doi.org/10.1037/0022-0167.29.4.362

21.

Hamaker

E. L.

Kuiper

R. M.

Grasman

R. P. P. P

. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. https://doi.org/10.1037/a0038889

22.

Hendricks

F. V.

(2006). Relationships of age and gender to hope and spiritual well-being among adolescents with cancer. Journal of Pediatric Oncology Nursing, 23(4), 189–199. https://doi.org/10.1177/1043454206289757

23.

Hoffman

(2015). Longitudinal analysis: Modeling within-person fluctuation and change. Routledge. https://doi.org/10.3102/1076998616679361

24.

Hoffman

Stawski

R. S.

(2009). Persons as contexts: Evaluating between-person and within-person effects in longitudinal analysis. Research in Human Development, 6(2–3), 97–120. https://doi.org/10.1080/15427600902911189

25.

JahangiriZadeh

Khodabakhshi Koolaee

(2016). The relationship between self-concept, life satisfaction and hope among retired and housewife older adults’ women. Journal of Gerontology, 1(1), 19–28.

26.

Kenny

D. A.

Korchmaros

J. D.

Bolger

(2003). Lower level mediation in multilevel models. Psychological Methods, 8(2), 115–128. https://doi.org/10.1037/1082-989X.8.2.115

27.

Kong

S. Y.

Wang

Song

Y. Y.

Liu

(2015). Neural correlates of the happy life: The amplitude of spontaneous low frequency fluctuations predicts subjective well-being. Neuroimage, 107, 136–145. https://doi.org/10.1016/j.neuroimage.2014.11.033

28.

Wang

Mao

Yin

(2018). Relationship between hope and depression in college students: A cross-lagged regression analysis. Personality and Mental Health, 12(2), 170–176. https://doi.org/10.1002/pmh.1412

29.

Light

A. E.

Rios

DeMarree

K. G.

(2017). Self-uncertainty and the influence of alternative goals on self-regulation. Personality and Social Psychology Bulletin, 44(1), 24–36. https://doi.org/10.1177/0146167217730368

30.

Lodi-Smith

Spain

S. M.

Cologgi

Roberts

B. W.

(2017). Development of identity clarity and content in adulthood. Journal of Personality and Social Psychology, 112(5), 755–768. https://doi.org10.1037/pspp0000091

31.

Luthans

Jensen

S. M.

(2002). Hope: A new positive strength for human resource development. Human Resource Development Review, 1(3), 304–322. https://doi.org/10.1177/1534484302013003

32.

Q. Z.

Zhang

Z. J.

(2020). Meaning in life and parent-child attachment of high school students: The mediation of peer attachment and time perspective. Psychological Development and Education, 36(2), 168–174.

33.

Marques

S. C.

Gallagher

M. W.

(2017). Age differences and short-term stability in hope: Results from a sample aged 15 to 80. Journal of Applied Developmental Psychology, 53, 120–126. https://doi.org/10.1016/j.appdev.2017.10.002

34.

Moksnes

U. K.

Espnes

G. A.

(2012). Self-esteem and emotional health in adolescents-gender and age as potential moderators. Scandinavian Journal of Psychology, 53(6), 483–489. https://doi.org/10.1111/sjop.12021

35.

Nie

Teng

Bear

G. G.

Guo

Liu

Zhang

(2019). Hope as mediator between teacher–student relationships and life satisfaction among Chinese adolescents: A between-and within-person effects analysis. Journal of Happiness Studies, 20, 2367–2383. https://doi.org/10.1007/s10902018-0052-6

36.

Oyserman

Destin

Novin

(2015). The context-sensitive future self: Possible selves motivate in context not otherwise. Self and Identit, 14(2), 173–188. https://doi.org/10.1080/15298868.2014.965733

37.

Parise

Canzi

Olivari

M. G.

Ferrari

(2019). Self-concept clarity and psychological adjustment in adolescence: The mediating role of emotion regulation. Personality and Individual Differences, 138, 363–365. https://doi.org/10.1016/j.paid.2018.10.023

38.

Patrício

A. C. F. D. A.

Silva

I. B. D. N.

Ferreira

M. A. M.

Rodrigues

B. F. L.

Silva

R. F. D.

Nascimento

J. A. D.

Silva

R. A. R. D

. (2019). Depression, self-concept, future expectations and hope of people with HIV. Revista Brasileira de Enfermagem, 72, 1288–1294. https://doi.org/10.1590/0034-7167-2018-0730

39.

Pinquart

Sorensen

(2001). Gender difference in self-concept and psychological well-being in old age: A meta-analysis. The Journal of Gerontology Series B: Psychological Sciences and Social Sciences, 56(4), 195–213. https://doi.org/10.1093/geronb/56.4.P195

40.

Pleeging

Burger

van Exel

(2021). The relations between hope and subjective well-being: A literature overview and empirical analysis. Applied Research in Quality of Life, 16(3), 1019–1041.

41.

Poulsen

A. A.

Ziviani

J. M.

Cuskelly

(2006). General self-concept and life satisfaction for boys with differing levels of physical coordination: The role of goal orientations and leisure participation. Human Movement Science, 25(6), 839–860. https://doi.org/10.1016/j.humov.2006.05.003

42.

Preacher

K. J.

Zyphur

M. J.

Zhang

(2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods, 15, 209–233. https://doi.org/10.1037/a0020141

43.

Ryan

R. M.

Deci

E. L.

(2001). On happiness and human potentials: A review of research on hedonic and eudaimonic well-being. Annual Review of Psychology, 52(1), 141–166. https://doi.org/10.1146/annurev.psych.52.1.141

44.

Satici

S. A.

(2016). Psychological vulnerability, resilience and subjective well-being: The mediating role of hope. Personality and Individual Difference, 102, 68–73. https://doi.org/10.1016/paid.2016.06.057

45.

Sawyer

S. M.

Azzopardi

P. S.

Wickremarathne

Patton

G. C.

(2018). The age of adolescence. The Lancet Child & Adolescent Health, 2(3), 223–228. https://doi.org/10.1016/S2352-4642(18)30022-1

46.

Schwartz

S. J.

Klimstra

T. A.

Luyckx

Hale

W. W.

Meeus

W. H. J.

(2012). Characterizing the self-system over time in adolescence: Internal structure and associations with internalizing symptoms. Journal of Youth and Adolescence, 41(9), 1208–1225. https://doi.org/10.1007/s10964-012-9751-1

47.

Slotter

E. B.

Walsh

C. M.

(2017). All role transitions are not experienced equally: Associations among self-change, emotional reactions, and self-concept clarity. Self and Identity, 16(5), 531–556. https://doi.org/10.1080/15298868.2017.1280528

48.

Smith

G. C.

James

L. E.

Varnum

M. E. W.

Oyserman

(2014). Give up or get going? Productive uncertainty in uncertain times. Self and Identity, 13, 681–700. https://doi.org/10.1080/15298868.2014.919958

49.

Snyder

C. R.

(1995). Conceptualizing, measuring, and nurturing hope. Journal of Counseling and Development, 73(3), 355–360. https://doi.org/10.1002/j.1556-6676.1995.tb01764.x

50.

Snyder

C. R.

(2002). Hope theory, rainbows of the mind. Psychological Inquiry, 13(4), 249–275.

51.

Snyder

C. R.

Cheavens

Sympson

S. C.

(1997). Hope: An individual motive for social commerce. Group Dynamics: Theory, Research, and Practice, 1(2), 107–118. https://doi.org/10.1037/1089-2699.1.2.107

52.

Teimouri

Rezaei

Mohammadzadeh

(2020). A comparative study of hope, academic achievement motivation, and academic self-concept among students with and without learning disabilities. Journal of Learning Disabilities, 9(2), 7–35.

53.

Teng

Z. J.

Pontes

H. M.

Nie

Xiang

G. C.

Griffiths

M. D.

Guo

(2020). Internet gaming disorder and psychosocial well-being: A Longitudinal study of older-aged adolescents and emerging adults. Addictive Behaviors, 110, 106530. https://doi.org/10.1016/j.addbeh.2020.106530

54.

Thomas

C. R.

Gadbios

S. A.

(2007). Academic self-handicapping: The role of self-concept clarity and students’ learning strategies. British Journal of Educational Psychology, 77(1), 101–119. https://doi.org/10.1348/000709905X79644/

55.

van Dijk

M. P.

Branje

Keijsers

Hawk

S. T.

Hale

W. W.

Meeus

. (2014). Self-concept clarity across adolescence: Longitudinal associations with open communication with parents internalizing symptoms. Journal of Youth Adolescence, 43(11), 1861–1876. https://doi.org/10.1007/s10964-013-0055-x

56.

Wang

Zhao

Lai

Qiu

Pan

Gong

(2020). Neurostructural correlates of hope: Dispositional hope mediates the impact of the SMA gray matter volume on subjective well-being in late adolescence. Social Cognitive and Affective Neuroscience, 15(4), 195–404. https://doi.org/10.1093/scan/nsaa046

57.

Watson

Clark

L. A.

Tellegen

(1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063

58.

Wong

A. E.

Dirghangi

S. R.

Hart

S. R.

(2019). Self-concept clarity mediates the effects of adverse childhood experiences on adult suicide behavior, depression, loneliness, perceived stress, and life distress. Self and Identity, 18(3), 247–266. https://doi.org/10.1080/15298868.2018.1439096

59.

Guo

Yang

Zhao

Guo

(2021). A meta-analysis of the longitudinal relationship between academic self-concept and academic achievement. Educational Psychology Review, 33, 1749–1778. https://doi.org/10.1007/s10648-021-09600-1

60.

Xiang

Teng

Chen

(2023). Self-concept clarity and subjective well-being: Disentangling within-and between-person associations. Journal of Happiness Studies, 24(4), 1439–1461. https://doi.org/10.1007/s10902-023-00646-2

61.

Xiang

G. C.

Chen

Wang

Y. L.

Q. Q.

(2021). Self-concept clarity associated with subjective well-being in adolescents: A latent profile analysis. Journal of Southwest University (Social Sciences Edition), 47(2), 153–160+229.

62.

Xiang

G. C.

Q. Q.

X. L.

Liu

X. Y.

Xiao

M. Y.

Chen

(2020). Links between family-cohesion and subjective well-being in adolescents and early adults: The mediating role of self-concept clarity and hope. Current Psychology, 41(1), 76–85. https://doi.org/10.1007/s12144-020-00795-0

63.

Xiang

G. C.

Q. Q.

X. B.

Chen

(2022). Development of self-concept clarity from ages 11 to 24: Latent growth models of Chinese adolescents. Self and Identity, 22(1), 42–57.

64.

Yang

Huebner

E. S.

Tian

(2022). Transactional processes among childhood maltreatment, self-control and aggression in early adolescence: Disentangling between-and within-person associations. Research on Child and Adolescent Psychopathology, 50(3), 321–334. https://doi.org/10.1007/s10802-021-00863-4

65.

Yip

T. H. J.

Tse

W. S.

(2019). Why hope can reduce negative emotion? Could psychosocial resource be the mediator? Psychology, Health & Medicine, 24, 193–206. https://doi.org/10.1080/13548506.2018.1493207