Next Article in Journal
Platform Governance, Institutional Distance, and Seller Trust in Cross-Border E-Commerce
Previous Article in Journal
The Impact of Visual Elements of Packaging Design on Purchase Intention: Brand Experience as a Mediator in the Tea Bag Product Category
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Behavioral Sciences
Volume 15
Issue 2
10.3390/bs15020182
behavsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Longitudinal Relationship Between Self-Esteem, Life Satisfaction, and Depressive and Anxiety Symptoms Among Chinese Adolescents: Within- and Between-Person Effects

by
Zongqiao Han
1,
Shuai Chen
2,
Yan Zhou
1,
Yanling Liu
1 and
Cheng Guo
1,*
1
Research Center of Mental Health Education, Faculty of Psychology, Southwest University, Chongqing 400715, China
2
Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China
*
Author to whom correspondence should be addressed.
Behav. Sci. 2025, 15(2), 182; https://doi.org/10.3390/bs15020182
Submission received: 26 December 2024 / Revised: 4 February 2025 / Accepted: 6 February 2025 / Published: 10 February 2025
Browse Figures
Versions Notes

Abstract

:
Adolescents are especially vulnerable to experiencing depression and anxiety. This longitudinal study, from within- and between-person perspectives, explores how self-esteem relates to depressive and anxiety symptoms in Chinese adolescents and identifies the mediating factors impacting this relationship. Data were collected from 1025 junior and high school students in Southwestern China at three points over an 18-month period. This study utilized both traditional and random-intercept cross-lagged panel models to understand the dynamic developmental relationships. The general occurrence of depressive and anxiety symptoms increased longitudinally, with a more pronounced upward trend among female students. Between-person level analyses indicated bidirectional associations among self-esteem, life satisfaction, and depressive and anxiety symptoms. Moreover, life satisfaction emerged as a significant mediator. At the within-person level, self-esteem uniquely predicted both life satisfaction and subsequent depressive and anxiety symptoms. This study clarifies the longitudinal interplay between these constructs. Self-esteem, which denotes internal self-assessments, and life satisfaction, which denotes external evaluations of life, both significantly buffer the emergence of depressive and anxiety symptoms.

1. Introduction

Adolescence represents the critical developmental stage during which depressive and anxiety symptoms most frequently occur (Kessler et al., 2005; Merikangas et al., 2010), making adolescents a high-risk group for both conditions (WHO, 2024). Depression has emerged as a primary cause of disability and mortality among adolescents, while anxiety disorders typically develop during childhood or adolescence (WHO, 2023a, 2023b). Anxiety often coexists with depression. Adolescents with depression or anxiety have poorer social functioning (Copeland et al., 2021; Psychogiou et al., 2024), experience suicidal ideation (C. Kang et al., 2021), and exhibit lower prosocial tendencies (Yang et al., 2024) and life satisfaction (Essau et al., 2014). As competition intensifies, mental health issues among adolescents increase, with greater prevalence of depression and anxiety (Shorey et al., 2022). Consequently, it is essential to examine the factors and developmental processes associated with depressive and anxiety symptoms in adolescents.
The ongoing exploration of how self-esteem interacts with depressive and anxiety symptoms has been a major area of interest. During adolescence, the complex interplay between self-esteem and various social, cognitive, and emotional factors can significantly affect mental health (Costello & Maughan, 2015). These factors include not only the quality and quantity of peer and adult relationships but also broader ecological dimensions, such as school climate, sense of belonging, and perceived social support (de Arellano et al., 2023; Gaylord-Harden et al., 2007; B. X. Kang et al., 2024). Moreover, contemporary research underscores the importance of digital environments and online connectivity (Twenge et al., 2019), as hyper-connection can exacerbate stress, compare-based self-worth, and exposure to bullying or cyberbullying (Keles et al., 2020). Social pressures (e.g., social norms, social media use) related to culturally promoted aesthetic ideals contribute further to body dissatisfaction (Rajagopalan & Shejwal, 2014; Rodrigue et al., 2024). From the perspective of individuals’ self-perception, a longitudinal meta-analysis and an additional longitudinal study found that individuals possessing low self-esteem often experience increased depression and anxiety (Sowislo & Orth, 2013; Steiger et al., 2014). Although existing research has established a link between self-esteem and both depressive and anxiety symptoms, most studies have utilized cross-lagged panel models (CLPM) to investigate this relationship, yet only a few have examined and addressed the within-person and between-person effects involved. Meanwhile, adolescents’ self-esteem may influence their life satisfaction, while depressive and anxiety symptoms are often the outcomes of complex interactions between internal and external factors. Individuals’ evaluations of their lives are influenced by their objective life circumstances, indicating that life satisfaction plays a crucial mediating role in the association between self-esteem and depressive or anxiety symptoms. Accordingly, this study employs both the traditional CLPM and the random intercept cross-lagged panel model (RI-CLPM) across three waves of data to investigate the dynamic development of self-esteem and depressive or anxiety symptoms, including the mediating function of life satisfaction in this regard.

1.1. Self-Esteem, Depressive and Anxiety Symptoms

Self-esteem is an evaluative judgment based on self-perception, shaped by both cognitive and affective components, reflecting a person’s comprehensive evaluation and perception of their own worth (Leary & Baumeister, 2000). It is widely recognized as a fundamental indicator of psychological well-being (Rosenberg, 1965). Some researchers have distinguished between state self-esteem (Heatherton & Polivy, 1991) and trait self-esteem, with the former representing an individual’s subjective self-evaluation that fluctuates in response to emotional and contextual changes, while the latter reflects a relatively stable sense of self-worth. Existing research has consistently identified a significant negative relationship between self-esteem and depression (Bang et al., 2020). This relationship has been supported not only by cross-sectional studies (Nguyen et al., 2019) but also by longitudinal research (Gao et al., 2022). Given the frequent comorbidity between depressive and anxiety symptoms, scholars tend to discuss these conditions together. Self-esteem can impact both depressive and anxiety symptoms. According to Cognitive Theories of Depression (Beck, 1967), cognitive patterns, particularly self-perception, are critical contributors to depressive symptoms. Similarly, the Vulnerability Model (Ingram, 2003) posits that perceiving oneself as worthless predisposes individuals to depression. Derived from Terror Management Theory, the anxiety buffer hypothesis proposes that high self-esteem acts as a psychological defense against mental threats (e.g., negative life events or stress), protecting against anxiety and depressive symptoms (Solomon et al., 1991). Sowislo and Orth (2013) argued that low self-esteem heightens the risk of experiencing depression and anxiety, whereas high self-esteem supports a positive self-image and serves as a buffer against these emotional challenges. A longitudinal study using a traditional CLPM demonstrates that self-esteem uniquely predicts depression (Wouters et al., 2013). By contrast, the Scar Model advocates the reverse influence, suggesting that experiencing mental disorders can leave lasting “scars” on an individual’s personality, implying that self-esteem may adversely affected by these conditions (Lewinsohn et al., 1981).
Vulnerability and Scar Models should primarily be tested at the within-person level. This suggests that using traditional CLPMs may not be the most appropriate approach for exploring these relationships. Research employing RI-CLPMs to examine the association between self-esteem and depressive and anxiety symptoms has produced inconsistent findings concerning the direction of effects. At the within-person level, Jørgensen et al. (2023) found moderate vulnerability effects between the ages of 13 and 15 years, and small scar effects between the ages of 15 and 21 years. In exploring the above interplay within interpersonal relationships, Tran et al. (2023) found that depression predicts lower self-esteem, supporting the Scar Model. However, employing RI-CLPMs across three different data sets, Masselink et al. (2018) observed that self-esteem negatively influenced depressive symptoms but did not find evidence to support the scar effect. For anxiety symptoms, a longitudinal study employing an RI-CLPM revealed significant cross-lagged effects, in which self-esteem negatively predicts anxiety symptoms, but not vice versa (X. Q. Liu et al., 2022). However, another study reported bidirectional effects between self-esteem and anxiety symptoms (Li et al., 2023). In summary, there is substantial backing for the vulnerability model in most studies, but the Scar Model is only weakly supported (Orth & Robins, 2013).
Although previous studies employing RI-CLPM have yielded inconsistent results, these studies consistently indicate that low self-esteem is a significant risk factor for de- pression and anxiety. When considering contextual factors, some scholars have examined this relationship within specific interpersonal or sex contexts, while others have focused solely on the relationship between these variables. This difference in focus may have led to discrepancies in findings. From a methodological perspective, few studies have integrated both between- and within-person results to interpret the relationship among these constructs. This lack of integration may limit understanding of how these variables inter- act dynamically at different levels. Accordingly, this research aims to delineate the predictive relationship between self-esteem and both depressive and anxiety symptoms by formulating two main models—namely, one for depressive symptoms and one for anxiety—and examining the effects at both between- and within-person levels.

1.2. Life Satisfaction as Mediator

Life satisfaction reflects an individual’s subjective evaluation of their overall satisfaction with life (Diener et al., 2010). Various psychological theories acknowledge the interconnection between self-esteem and life satisfaction, each emphasizing distinct evaluative perspectives (Çivitci & Çivitci, 2009). Previous research and perspectives from positive psychology have identified self-esteem as an important indicator of life satisfaction (Moksnes & Espnes, 2013; Seligman, 2004; Szcześniak et al., 2022). Individuals with low self-esteem frequently experience self-doubt and perceive a reduced sense of control over their lives, which subsequently diminishes their life satisfaction. According to the sociometer theory (Leary & Baumeister, 2000), fluctuations in self-esteem reflect an individual’s perceived social value and acceptance in interpersonal interactions. When self-esteem increases, individuals experience greater acceptance and support in social interactions, promoting higher life satisfaction. Conversely, individuals with low self-esteem may exhibit heightened sensitivity to social evaluations and rejection (Minihan et al., 2023), resulting in decreased life satisfaction (Xing et al., 2024). However, longitudinal research has drawn inconsistent conclusions regarding the relationship between self-esteem and life satisfaction. For instance, a study involving Swiss adolescents demonstrated that self-esteem unidirectionally influences life satisfaction over time (Marcionetti & Rossier, 2019), whereas research on Korean adolescents identified a bidirectional cross-lagged effect between the two constructs (Kim & Nho, 2020).
Satici et al. (2016) proposed a mediating model in which life satisfaction serves as a cognitive mediator that reduces psychological vulnerability, including depressive and anxiety symptoms. Extensive research has associated life satisfaction with mental health outcomes, including depressive and anxiety symptoms. Individuals free from generalized anxiety symptoms report significantly higher life satisfaction than those experiencing such symptoms (Peixoto et al., 2023). Life satisfaction has also been shown to significantly negatively predict both depressive and anxiety symptoms (Mei et al., 2021). Cross-sectional studies have identified the impact of depressive and anxiety symptoms on life satisfaction (Duong, 2021; Foroughi et al., 2021), suggesting the possibility of a bidirectional path between these variables. For instance, one longitudinal study found that life satisfaction among older adults increases over time, while depression gradually diminishes (Lee et al., 2020). Another longitudinal study at the between-person level revealed cross-lagged effects between life satisfaction and both emotional disorders (Tang et al., 2024).
The relationships among the above constructs overlap with one another. According to Beck’s cognitive triad hypothesis for depression (Allen, 2003), depression originates from negative perceptions of oneself, the world, and future prospects. These three negative cognitions intertwine, driving depression. Low self-esteem causes individuals to feel worthless and perceive the world negatively, leading to diminished life satisfaction, difficulty finding fulfillment, and the development of hopelessness, depressive, and anxiety symptoms. Through a CLPM-based longitudinal analysis, it was determined that rumination mediates the relationship between self-esteem and depressive symptoms (Kuster et al., 2012). For adolescents, life typically encompasses domains such as school and family, and negative events in these areas can lower life satisfaction (Jovanovic, 2019). For instance, a longitudinal study from China found that bullying victimization mediates the role of self-esteem on depressive symptoms at the trait level (X. Wang et al., 2024). Furthermore, a longitudinal analysis of subjective well-being trajectories in college students found that self-esteem correlates with different patterns of subjective well-being, where stable and elevated levels of well-being are connected to lower depression risks (X. Q. Liu et al., 2024).
Although previous researchers have examined these relationships, the majority have employed cross-sectional methodologies, with few adopting a longitudinal approach. The reliance on single analytical models, such as CLPM or latent growth models, further limits the comprehensive understanding of these relationships, thereby creating significant gaps in the literature. While direct evidence supporting life satisfaction as a mediator is currently limited, ample longitudinal data suggest its potential role in linking self-esteem with depressive and anxiety symptoms. Consequently, this study is designed to bridge these gaps by employing (RI)-CLPMs to investigate both within- and between-person effects.

1.3. Current Study

Although earlier work has identified strong links among self-esteem, life satisfaction, and both depressive and anxiety symptoms, much of this evidence derives from cross-sectional designs or emphasizes between-person effects. This approach fails to capture dynamic within-person relationships over time, leaving the longitudinal relationships among these variables unclear. To address these limitations, the current study employs a longitudinal design with Chinese adolescents aged 13–18, encompassing distinct educational stages within China’s education system: junior middle school (ages 13–15) and senior high school (ages 16–18). Notably, in the first year of senior high school, students undergo subject specialization, a unique feature of the Chinese education framework that tracks students into different academic streams based on their strengths and career aspirations. The study utilizes both a traditional CLPM and RI-CLPM to investigate the between- and within-person dynamics linking self-esteem with depressive and anxiety symptoms over time. In addition, it examines whether life satisfaction mediates these associations. In doing so, this study tests the following hypotheses:
H1: 
At both the between- and within-person levels, there is a bidirectional relationship between self-esteem and depressive (H1a) and anxiety (H1b) symptoms.
H2: 
At both the trait and state levels, there is a bidirectional relationship between self-esteem and life satisfaction.
H3: 
Life satisfaction mediates the relationship between self-esteem and depressive (H3a) and anxiety (H3b) symptoms.

2. Materials and Methods

2.1. Participants

This study utilized a longitudinal design over a period of 18 months, collecting data at three points at 6-month intervals. Participants were recruited from a secondary school that is representative of typical secondary education institutions in Sichuan Province, characterized by both middle and high school divisions, and a diverse student population. The selection was also based on the school’s accessibility and the existing collaborative relationship with its administration, which facilitated effective data collection. Taking into account the academic burdens faced by students and the logistical challenges of data collection, the students selected at Time 1 were from non-final year grades (9th grade and final-year high school). Ultimately, a total of 1025 students (34.8% male, 65.2% female; Mage = 15.33 years, SDage = 1.48; 26.83% middle school, 73.17% high school) participated in this study’s school-organized longitudinal survey. At Time 1, participants were asked whether they were only children (10.7% only children, 89.3% non-only children). A total of 906 (33.7% male and 66.3% female) and 940 (33.9% male and 66.1% female) students participated at Time 2 and Time 3, respectively. Data were missing for 204 participants (19.9% of the total sample) across all three waves.
Ethical approval for this research was granted by the Institutional Review Board of the Psychology Department at Southwest University (IRB: H23175). Before the survey began, all participants provided informed consent. A trained graduate student collected the data in a standard classroom setting, with each participant completing the survey in about 20 min. Participants were briefed on the study’s objectives and reassured that their information would remain confidential and be used solely for research purposes.

2.2. Measures

2.2.1. Self-Esteem

Self-esteem was measured using the Chinese version of the Self-Esteem Scale (Ji & Yu, 1999; Rosenberg, 1965). This 10-item instrument (e.g., “I feel that I have a number of good qualities”, “I take a positive attitude toward myself”) evaluates adolescents’ self-worth and acceptance. Each statement was evaluated on a 4-point Likert scale with anchors from 1 (“strongly disagree”) to 4 (“strongly agree”). Reverse scoring was utilized for Items 3, 5, 8, 9, and 10. Higher total scores correspond to greater self-esteem. Based on previous research (P. Wang et al., 1998), the scale has been suggested to present cultural differences, particularly regarding the expression of Item 8, which may not align well with the domestic context. To enhance the scale’s discriminative ability and psychometric properties, it is recommended that Item 8 be recoded as a positively scored item or deleted entirely. This study opted to remove Item 8. In this study, McDonald’s ω for the Self-Esteem Scale was 0.91 at T1, 0.92 at T2, and 0.94 at T3.

2.2.2. Life Satisfaction

The Satisfaction With Life Scale (SWLS), developed by Diener et al. (2010), measures individuals’ life satisfaction levels and comprises 5 items (e.g., “I am satisfied with my life”, “The conditions of my life are excellent”). This scale demonstrates cross-cultural applicability and strong psychometric properties, making it a reliable tool for measuring life satisfaction. This study used the Chinese version of SWLS revised by K. T. Wang et al. (2009), which reflects robust reliability and validity. The self-report questionnaire employs a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The mean score across all items indicated individuals’ level of life satisfaction, with higher averages signifying greater satisfaction. In this sample, McDonald’s ω values were 0.92 at T1, 0.93 at T2, and 0.93 at T3.

2.2.3. Depressive Symptoms

Depressive symptoms were evaluated using the Patient Health Questionnaire-9 (Kroenke et al., 2001), a 9-item self-report measure (e.g., “Little interest or pleasure in doing things”, “Feeling tired or having little energy”) that is aligned with the diagnostic criteria for major depressive disorders in the DSM-IV. Responses are recorded on a 4-point Likert scale from 0 (not at all) to 3 (nearly every day), with higher totals indicating more severe symptoms. Scores of 1–4 suggest minimal depression, 5–9 indicate mild depression, 10–14 represent moderate to moderately severe depression, and 20 or above signify severe depression. In this study, McDonald’s ω was 0.89 at T1, 0.92 at T2, and 0.94 at T3.

2.2.4. Anxiety Symptoms

The Generalized Anxiety Disorder 7-item Scale (Spitzer et al., 2006), created by Spitzer and Kroenke, is a self-report measure evaluating the severity of generalized anxiety disorder, suitable for screening and as a diagnostic adjunct. Each of the seven items (e.g., “Feeling nervous, anxious, or on edge”, “Worrying too much about different things”) is rated from 0 (not at all) to 3 (nearly every day), producing a total score reflecting overall anxiety levels. Scores of 0–4 indicate no clinically significant anxiety, 5–9 suggest mild anxiety, 10–18 represent moderate anxiety, and 19 or above denote severe anxiety. In this sample, McDonald’s ω values were 0.95 at T1, 0.96 at T2, and 0.97 at T3.

Covariates

As sex and educational stage may influence the relationships among the variables in this study, they were included as control variables in the research model. During data collection, sex was coded as 1 for male and 2 for female. Additionally, participants’ educational stage was recorded, with middle school (Grades 1–3) coded as 1 and high school (Grades 4–6) coded as 2.

2.3. Data Analysis

2.3.1. Missing Data

Using SPSS v29.0.1.0, Little’s MCAR (Little, 1988) test was conducted to examine the patterns of missing data. Results suggested that the missing variables followed MAR (χ2 = 70.75, df = 19, p < 0.001). A series of t-tests revealed that age (t = 8.64, p < 0.001), self-esteem (t = −1.98, p < 0.05), depressive symptoms (t = 3.89, p < 0.001), and anxiety symptoms (t = 3.18, p < 0.001) were MAR, whereas life satisfaction (t = −0.88, p = 0.378) was MCAR. Missing data were primarily owing to participant classes not completing the questionnaire or students transferring schools. Consequently, to address missing data in subsequent analyses, Mplus 8.3 applied the full information maximum likelihood approach.

2.3.2. Descriptive Analysis

To advance understanding of adolescent mental health, it is essential to quantify the prevalence of depressive and anxiety symptoms within middle- and high-school cohorts. Accordingly, this study utilized SPSS v29 to conduct descriptive analyses of these symptoms, followed by Pearson correlation analyses to explore relationships among the key study variables.

2.3.3. Measurement Invariance

As this study involved repeated measurements of participants across three time points, assessing measurement invariance was necessary. To this end, this study developed and analyzed configural, metric, and scalar invariance models. The nested longitudinal invariance models were assessed based on the recommendations of Chen (2007) that metric invariance is supported when changes in the Comparative Fit Index (ΔCFI ≤ 0.01), Root Mean Square Error of Approximation (ΔRMSEA ≤ 0.015), and Standardized Root Mean Square Residual (ΔSRMR ≤ 0.030) remain within these specified thresholds. For scalar and strict invariance, ΔCFI ≤ 0.01, ΔRMSEA ≤ 0.015, or ΔSRMR ≤ 0.010 are indicative of invariance across time (Stenling et al., 2018). As illustrated in Supplementary Table S1, the measurement model established scalar invariance, indicating that the observed changes over time were meaningful.

2.3.4. Between-Person Effect (CLPM) and Within-Person Effect (RI-CLPM)

CLPM is frequently employed in longitudinal research because it assesses how variability between individuals in one construct influences subsequent changes in another. In doing so, it focuses on between-person effects without separating out within-person dynamics. Building on the CLPM, the RI-CLPM incorporates a random intercept that represents an individual’s initial status at the trait level, reflecting between-person differences, while the cross-lagged effects demonstrate how temporary deviations in one variable at a given time affect subsequent deviations in another variable for the same individual.
Utilizing Mplus 8.3, this study modeled two relational pathways—“self-esteem–life satisfaction–depressive/anxiety symptoms”—and investigated longitudinal associations at both trait and state levels using CLPM and RI-CLPM. This study used maximum likelihood estimation to analyze the models and then compared the two models to identify differences. A robust model requires evaluation using multiple indicators, including metrics such as CFI and Tucker–Lewis Index (TLI) above 0.90, and RMSEA and SRMR below 0.08. This study implemented a series of constraints in model construction (Orth et al., 2021). In the CLPM, the analysis began with an unconstrained model (CLPM1), followed by restrictions on autoregressive paths (CLPM2) and cross-lagged paths (CLPM3), ultimately applying constraints to both autoregressive and cross-lagged paths (CLPM4). For the RI-CLPM analysis, the process started with an unconstrained model (RI-CLPM1), followed by the gradual restriction of autoregressive paths (RI-CLPM2), addition of restrictions on cross-lagged paths (RI-CLPM3), and finally setting the within-person correlations to be equal (RI-CLPM4). ΔCFI ≤ 0.01 and ΔRMSEA ≤ 0.015 indicate no significant differences in fit between the compared models (Chen, 2008; Cheung & Rensvold, 2002). Finally, this study tested for mediation effects in the models using the Bootstrap method with the sample size set to 5000.

3. Results

3.1. Descriptive Analysis

As illustrated in Table 1, the proportion of middle school students displaying both depressive and anxiety symptoms increased over time, with female students demonstrating consistently higher prevalence rates than their male counterparts. At the high-school level, the number of female students experiencing depressive and anxiety symptoms exceeded that of their male peers at all three time points, with the lowest prevalence of both conditions observed at T2.
Table 2 displays the Pearson correlation coefficients for each time point. All variables were significantly correlated both within and across waves. In general, at every measurement occasion, higher levels of self-esteem and life satisfaction were associated with fewer depressive and anxiety symptoms. Moreover, self-esteem and life satisfaction exhibited a positive association, while depressive and anxiety symptoms were positively interrelated.

3.2. CLPM Results

Table 3 displays the fit indices for the CLPM and RI-CLPM, assessing the target variables while controlling for sex and educational stage. The fit indices for CLPM4 indicate a good fit, and there were no significant differences in model comparisons.
Figure 1 illustrates CLPM4 for depressive symptoms. T1 self-esteem positively predicts T2 life satisfaction (β = 0.18, p < 0.001), while T2 life satisfaction negatively predicts T3 depressive symptoms (β = −0.09, p < 0.001). Moreover, T2 life satisfaction significantly mediates the effect of T1 self-esteem on T3 depressive symptoms (β = −0.017, 95% CI [−0.027, −0.007]), thereby supporting H1a and H3a at the between-person level.
Figure 2 presents CLPM4 for anxiety symptoms. T1 self-esteem positively predicts T2 life satisfaction (β = 0.18, p < 0.001), while T2 life satisfaction negatively predicts T3 anxiety symptoms (β = −0.08, p < 0.01). Additionally, the indirect effect of T1 self-esteem on T3 anxiety symptom through T2 life satisfaction is significant (β = −0.014, 95% CI = [−0.024, −0.004]), which supports H1b and H3b at the between-person level, but in both the depressive and anxiety symptoms models only a unidirectional effect path from self-esteem to life satisfaction was found, partially supporting H2.
This study also identified other mediating pathways, which are detailed in Supplementary Table S2. Overall, the results indicate that the positive pathway from self-esteem to life satisfaction negatively predicts both depressive and anxiety symptoms and exhibits a significant mediating effect. However, the reverse pathways do not demonstrate the same level of significance in either case.

3.3. RI-CLPM Results

This study used an RI-CLPM to conduct separate analyses of the relationship between self-esteem, life satisfaction, and depressive symptoms and that between self-esteem, life satisfaction, and anxiety symptoms. Sex and education stage were controlled for at the between-person level in the RI-CLPM. Table 3 presents the comparison indices for both models after applying constraints and reports the results for RI-CLPM4 for both the depressive and anxiety symptom models.
Figure 3 and Figure 4 illustrate the RI-CLPM4 results for depressive and anxiety symptoms, respectively, revealing similar patterns. At the between-person level, self-esteem is positively correlated with life satisfaction (r = 0.75, p < 0.001), while both self-esteem and life satisfaction are negatively correlated with depressive (r = −0.68 and −0.90, p < 0.001) and anxiety symptoms (r = −0.75 and −0.54, p < 0.001). At the within-person level, self-esteem at an earlier time point positively predicts life satisfaction later point (β = 0.19 and 0.17 for the depressive symptoms model and β = 0.18 and 0.16 for the anxiety symptoms model, p < 0.05) and negatively predicts both depressive (β = −0.22 and −0.20, p < 0.001) and anxiety symptoms (β = −0.22 and −0.21, p < 0.01). However, no significant within-person cross-lagged relationships were observed between life satisfaction and either depressive or anxiety symptoms. These results partially support H1a and H1b, as well as H2, at the within-person level, revealing only a unidirectional effect path from self-esteem to life satisfaction, depressive and anxiety symptoms, without finding a mediating role for life satisfaction.

4. Discussion

Although numerous studies have linked self-esteem, life satisfaction, and depressive and anxiety symptoms, only a limited number have explored their longitudinal dynamics. Addressing this gap, this study analyzed the prevalence of depressive and anxiety symptoms in adolescents, using advanced statistical models to explore the dynamic relationships between these variables. The findings can be summarized as follows. First, descriptive analysis showed that female students had higher prevalence rates of depression and anxiety than male students in both the middle- and high-school educational stages, with overall rates of both conditions increasing over time, especially for female students. Second, CLPM results revealed a bidirectional relationship between self-esteem, life satisfaction, and both emotional disorders, with life satisfaction strongly mediating this relationship. However, no reverse pathway from self-esteem to life satisfaction was identified. Third, RI-CLPM results showed significant correlations between self-esteem, life satisfaction, and both emotional disorders at the trait level. At the within-person level, self-esteem predicted life satisfaction and depressive and anxiety symptoms, but life satisfaction did not exert cross-lagged effects on these symptoms.
The results indicate that female students exhibit higher rates of depressive and anxiety symptoms compared to their male peers. Except for the anxiety detection rates in high school, the overall prevalence across the three time points shows a consistent upward trend, with female students experiencing a more rapid increase in depressive and anxiety symptoms than their male peers. Previous research on adolescent mental disorders has found that girls are particularly susceptible to socialization pressures and internalized emotions, which can significantly impact their mental health. When faced with emotional and social stressors, girls tend to exhibit different coping strategies than boys, often leading to greater emotional turmoil (Hyde et al., 2008). During adolescence, the pressures associated with gender role socialization intensify, exacerbating emotional distress among girls and increasing their vulnerability to emotional disorders (Nolenhoeksema & Girgus, 1994). Furthermore, in the Chinese context, the prevalence of depressive and anxiety symptoms among girls presents a more pronounced upward trend with age (X. Liu et al., 2024), suggesting that the challenges they face may become more complex and demanding as they mature.
The between-person results revealed a robust bidirectional relationship between self-esteem and both symptoms. Consistent with a recent study (Son et al., 2024), self-esteem and depressive symptoms had the strongest negative correlation during early adolescence at the one-year follow-up mark. A possible explanation is that individuals with higher self-esteem tend to experience fewer depressive and anxiety symptoms, as they are more likely to sustain positive self-evaluations and adopt adaptive attribution styles when encountering failure or challenges, reducing their vulnerability to depressive symptoms (Baumeister et al., 2003; Heimpel et al., 2002). Conversely, individuals with higher levels of depression or anxiety often experience declining self-esteem due to emotional distress and low confidence in the face of uncertainty (Brown & Marshall, 2013).
After controlling for trait-level effects, changes in self-esteem significantly and negatively predict subsequent changes in depressive and anxiety symptoms; this study provides empirical support for cognitive theories of depression, vulnerability theories, and the anxiety buffer hypothesis, which aligns with longitudinal research (Henriksen et al., 2017; Masselink et al., 2018). This study does not fully support the Scar Model, which suggests that depression negatively affects self-esteem. Notably, the CLPM indicated a bidirectional relationship between self-esteem and depressive and anxiety symptoms, whereas the RI-CLPM only identified a unidirectional path from self-esteem to both symptoms. This finding may be due to the limitations of the CLPM, which does not distinguish between trait and state effects. Self-esteem, depression, and anxiety are relatively trait-like constructs, potentially resulting in variations in the strength and direction of their relationship (Hamaker et al., 2015). A reasonable explanation is that, at trait level, self-esteem can form a long-term feedback loop with depressive and anxiety symptoms. However, at the state level, short-term boosts or drops in self-esteem trigger quick emotional responses before any reciprocal influence can register. In other words, while momentary increases or decreases in self-esteem may directly shape how one feels in the short run, the reverse pathway is overshadowed by broader, enduring vulnerabilities—such as stable cognitive styles or longstanding interpersonal stressors—that do not fluctuate as rapidly.
This study also found a bidirectional relationship between self-esteem and life satisfaction at the between-person level, aligning with previous research. Numerous studies have reliably demonstrated that higher self-esteem is associated with greater life satisfaction across diverse cultural backgrounds and age ranges (Diener & Diener, 1995). Similarly, people who experience greater life satisfaction tend to attribute positive experiences in their lives to their own efforts and value, thus enhancing their self-esteem (Kong et al., 2012).
Consistent with perspectives from positive psychology, this study found that, at the within-person level, changes in self-esteem positively predicted changes in life satisfaction, partially supporting H2. This aligns with previous findings suggesting that high self-esteem can prospectively predict success and satisfaction across various life domains (Orth & Robins, 2014). According to the sociometer theory, individuals whose self-esteem increases may receive positive feedback in social interactions, reinforcing their sense of self-worth and, in turn, enhancing life satisfaction. However, this study only found a unidirectional relationship at the within-person level, with no significant reverse prediction from life satisfaction to self-esteem. One possible explanation is that life satisfaction’s impact on self-esteem primarily occurs at the trait level, whereas self-esteem’s influence on life satisfaction operates at both the trait and state levels. Because life satisfaction reflects an individual’s overall evaluation of their life, and adolescence involves multiple spheres, such as school, peer relationships, and family life, contextual or situational factors may drive uncertain effects that, in turn, dilute any bidirectional relationship at the state level. Although self-esteem can fluctuate on a short-term basis and immediately shape how adolescents feel about their daily experiences, life satisfaction may require a longer timeframe to exert its influence, becoming evident only when considering more specific patterns of well-being.
The results also indicate a bidirectional association between life satisfaction and depressive and anxiety symptoms at the between-person level. This finding is consistent with previous research suggesting that individuals with lower life satisfaction are more likely to experience depression or anxiety and, conversely, that depression or anxiety can negatively impact life satisfaction (Martins et al., 2022). This may stem from individuals’ attribution styles (Diener & Chan, 2011), wherein they attribute unfortunate events in their lives to personal shortcomings and incompetence. Further, it could be related to individuals’ sense of efficacy (Hashemabady et al., 2022), wherein those with low levels of efficacy may lack confidence in their ability to cope with life events, leading to feelings of despair. Individuals with higher levels of depressive or anxiety symptoms tend to adopt negative cognitive processing styles (Lin et al., 2021), which may cause them to perceive their lives as unsatisfactory. However, at the state level, life satisfaction did not show any significant predictive pathways with depressive and anxiety symptoms, failing to support the notion of a dynamic relationship between life satisfaction and these emotional disorders. This suggests that the relationship between life satisfaction and depressive or anxiety symptoms may only exist at the trait level without a longitudinal connection over time.
The CLPM results demonstrated the expected effects, indicating that life satisfaction plays a strong mediating role in the longitudinal relationship between self-esteem and depressive and anxiety symptoms. This supports self-determination theory, which posits that emotional disorders are influenced by the fulfillment of three basic needs and complex mechanisms of well-being. Individuals with higher self-esteem may perceive more social support (Dündar & Yildiz, 2023), enhancing their life satisfaction. Furthermore, adolescents with diminished life satisfaction are at a higher risk of experiencing depression or anxiety (S. Wang et al., 2023), potentially due to their discontent and frustration with life. This may lead to the buildup of negative emotions, ultimately resulting in feelings of hopelessness and helplessness. In this study, when employing the RI-CLPM to differentiate between trait and state levels, the mediating role of life satisfaction did not remain significant.

4.1. Strengths, Limitations, and Future Directions

This study presents several key contributions to the field of adolescent mental health research within the Chinese context. First, it provides a comprehensive analysis of the prevalence rates of depressive and anxiety symptoms among Chinese adolescents, thereby offering an updated and culturally specific understanding of the current mental health landscape. Second, by employing a longitudinal design, the study investigates the dynamic and temporal relationships among self-esteem, life satisfaction, and depressive and anxiety symptoms, contributing to a more nuanced understanding of these interactions over time. Third, by advancing methodological rigor, this research distinguishes between within-person and between-person effects through the application of both CLPM and RI-CLPM. This dual-model approach elucidates the importance of separating trait-like and state-like variations when analyzing the interplay between psychological constructs. Furthermore, the study explores the mediating role of life satisfaction, identifying its significant influence on the relationship between self-esteem and depressive and anxiety symptoms over time. These findings underscore the critical role of life satisfaction as a mediator, highlighting its potential as a target for interventions aimed at enhancing psychological well-being. Collectively, these methodological and analytical advancements address previous inconsistencies in the literature and enhance our understanding of the complex interplay between self-esteem, life satisfaction, and emotional disorders during adolescence. Importantly, conducting this research within the Chinese cultural framework provides insights into factors such as collectivist family dynamics, high academic expectations, and societal stigma surrounding mental health, thereby informing the development of tailored mental health strategies and interventions that address these specific cultural and societal influences on adolescent well-being in China.
Notwithstanding these advantages, several limitations are as follows. Initially, although this study’s data analysis is feasible, the sample of adolescent participants is imbalanced in terms of educational stages and sex, which may limit the generalizability of the findings. Future research should aim for more balanced and diverse samples to prevent skewed outcomes and enhance representativeness. Second, from a methodological perspective, this study relied on self-report questionnaires for data collection. While questionnaires have historically proven to be robust and effective in psychology, the fast-paced nature of modern life may lead adolescents to respond less seriously, potentially compromising the authenticity of the data. Future research could employ innovative analytical approaches, such as analyzing adolescents’ daily-life (e.g., essays, diaries, or electronic device usage) using text analysis and machine learning to explore the relationships between self-esteem, depressive and anxiety symptoms, life satisfaction, and other potential variables. Third, as the data were collected from schools in a specific region of China, results may not generalize to other areas or cultures. Future investigations should gather data from more regions and cultural contexts to bolster external validity and build a more comprehensive understanding of adolescent well-being. Fourth, at the state level, this study identified only a unidirectional predictive relationship from self-esteem to life satisfaction, depressive and anxiety symptoms, implying that certain situational variables may have been overlooked. Future research should consider incorporating more context-specific factors into the analysis. Additionally, adopting more intensive data collection methods, such as experience sampling, could capture the nuanced day-to-day interplay between self-esteem, life satisfaction, and internalizing symptoms, thereby clarifying state-level effects. Finally, from a disciplinary standpoint, the variables, methods, and theories employed in this study remain predominantly within a psychological framework. However, adolescent life also requires insights from other academic fields to address mental health issues more comprehensively. Future research should thus consider additional interdisciplinary factors, integrating various elements not only at discrete time intervals but also through more intensive data collection. Such an approach would help identify important risk factors for adolescents within specific cultural contexts and illuminate the dynamic developmental changes and contextual differences underlying internalizing symptoms.

4.2. Implications

According to this study, the prevalence of depressive and anxiety symptoms is generally higher among female students than that among male students, with females exhibiting a more significant increase. This suggests that mental health interventions should place greater emphasis on the psychological well-being of female adolescents and develop targeted strategies to enhance their ability to cope with these challenges. Findings underscore the crucial role of self-esteem in relation to depressive and anxiety symptoms. Enhancing self-esteem can significantly improve mental health, especially as adolescents spend more time at school than at home. Therefore, school-level efforts are essential. Teachers can provide positive feedback to help students recognize their abilities and boost their confidence. Encouraging participation and self-expression in the classroom can aid in developing self-identity and enhancing self-esteem. Additionally, schools should create an inclusive and supportive environment wherein students feel safe and respected. The results also highlight the role of life satisfaction in the relationship between self-esteem and emotional disorders. Educators should focus on both academic performance and promoting social interaction by organizing activities that enhance social support. As some students may face familial challenges, fostering collaboration among families, schools, and communities is vital for ensuring students’ life satisfaction. Teachers can also incorporate mindfulness and gratitude exercises to cultivate positive emotions, thereby increasing life satisfaction and psychological resilience. Furthermore, a multi-tiered mental health support system should be established, integrating individual counseling, group therapy, and other support mechanisms to better assist students. At the state level, self-esteem and life satisfaction significantly predicted depressive and anxiety symptoms, while no reverse effects were observed. Interventions should therefore focus on enhancing state-level self-esteem and life satisfaction to more promptly prevent or alleviate depressive and anxiety symptoms. The absence of reverse effects also suggests that the influence of emotional states on self-esteem and life satisfaction may require a longer-term cumulative effect or may depend on the modulation of other contextual variables. Consequently, teachers should regularly monitor students’ changes and maintain close communication, while parents need to strike a reasonable work–family balance by devoting more time to their children and paying attention to the challenges and life events that adolescents face.

5. Conclusions

This study investigated the longitudinal dynamic relationships among self-esteem, life satisfaction, and depressive and anxiety symptoms. It expands existing research by distinguishing between the between- and within-person levels and interpreting the longitudinal relationships among these variables. The findings confirmed the existence of a bidirectional relationship between self-esteem, life satisfaction, and depressive and anxiety symptoms at the between-person level, with life satisfaction playing a significant mediating role in these longitudinal relationships. At the state level, fluctuations in self-esteem significantly impact changes in life satisfaction and depressive and anxiety symptoms, although no reciprocal pathways were observed. Additionally, when life satisfaction is considered at the within-person level, its mediating effect becomes non-significant. By providing fresh insights into the pathways linking self-esteem, life satisfaction, and mental health outcomes, this study advances the existing literature and aims to inspire further research in this domain.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/bs15020182/s1, Table S1: Fit statistics for measurement model and tests of measurement invariance; Table S2: Indirect effect in CLPM.

Author Contributions

Z.H. conceived the study, conducted data collection and statistical analyses, and drafted the manuscript; S.C. participated in data collection and analysis and helped write and revise the draft of the manuscript; Y.Z. assisted in data collection and analysis; Y.L. supervised this study, organized the data collection, and revised the manuscript; C.G. supervised this study, organized the data collection, and revised the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Major Project of the National Social Science Fund of China, grant number 19ZDA357. The APC was funded by the Major Project of the National Social Science Fund of China.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Faculty of Psychology, Southwest University of China (IRB protocol number: H23175, Date: 22 September 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The datasets generated and analyzed during the current study are not publicly available but are available from the corresponding author upon reasonable request.

Acknowledgments

We would like to thank the students who participated in this study and the teachers for their efforts in collecting data. We sincerely appreciate the editor and anonymous reviewers for their valuable comments and feedback.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Allen, J. P. (2003). An overview of Beck’s cognitive theory of depression in contemporary literature. Available online: http://www.personalityresearch.org/papers/allen.html (accessed on 25 October 2024).
  2. Bang, H., Won, D., & Park, S. (2020). School engagement, self-esteem, and depression of adolescents: The role of sport participation and volunteering activity and gender differences. Children and Youth Services Review, 113, 105012. [Google Scholar] [CrossRef]
  3. Baumeister, R. F., Campbell, J. D., Krueger, J. I., & Vohs, K. D. (2003). Does high self-esteem cause better performance, interpersonal success, happiness, or healthier lifestyles? Psychological Science, 4, 1–44. [Google Scholar] [CrossRef] [PubMed]
  4. Beck, A. (1967). Depression. Clinical, experimental and theoretical aspects. Harper & Row. [Google Scholar]
  5. Brown, J. D., & Marshall, M. A. (2013). The three faces of self-esteem. In Self-esteem issues and answers (pp. 4–9). Psychology Press. [Google Scholar]
  6. Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464–504. [Google Scholar] [CrossRef]
  7. Chen, F. F. (2008). What happens if we compare chopsticks with forks? The impact of making inappropriate comparisons in cross-cultural research. Journal of Personality and Social Psychology, 95(5), 1005–1018. [Google Scholar] [CrossRef]
  8. Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. [Google Scholar] [CrossRef]
  9. Copeland, W. E., Alaie, I., Jonsson, U., & Shanahan, L. (2021). Associations of childhood and adolescent depression with adult psychiatric and functional outcomes. Journal of the American Academy of Child and Adolescent Psychiatry, 60(5), 604–611. [Google Scholar] [CrossRef] [PubMed]
  10. Costello, E. J., & Maughan, B. (2015). Annual research review: Optimal outcomes of child and adolescent mental illness. Journal of Child Psychology and Psychiatry, 56(3), 324–341. [Google Scholar] [CrossRef] [PubMed]
  11. Çivitci, N., & Çivitci, A. (2009). Self-esteem as mediator and moderator of the relationship between loneliness and life satisfaction in adolescents. Personality and Individual Differences, 47(8), 954–958. [Google Scholar] [CrossRef]
  12. de Arellano, A., Neger, E. N., Rother, Y., Bodalski, E., Shi, D. X., & Flory, K. (2023). Students’ ratings of school climate as a moderator between self-esteem and internalizing symptoms in a community-based high school population. Psychology in the Schools, 60(11), 4701–4720. [Google Scholar] [CrossRef]
  13. Diener, E., & Chan, M. Y. (2011). Happy people live longer: Subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being, 3(1), 1–43. [Google Scholar] [CrossRef]
  14. Diener, E., & Diener, M. (1995). Cross-cultural correlates of life satisfaction and self-esteem. Journal of Personality and Social Psychology, 68(4), 653. [Google Scholar] [CrossRef] [PubMed]
  15. Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (2010). The satisfaction with life scale. Journal of Personality Assessment, 49(1), 71–75. [Google Scholar] [CrossRef]
  16. Duong, C. D. (2021). The impact of fear and anxiety of COVID-19 on life satisfaction: Psychological distress and sleep disturbance as mediators. Personality and Individual Differences, 178, 110869. [Google Scholar] [CrossRef]
  17. Dündar, A., & Yildiz, M. A. (2023). Multiple mediating role of perceived social support in the relationship between self-esteem and positivity. Journal of Educational Sciences & Psychology, 13(2), 215–226. [Google Scholar] [CrossRef]
  18. Essau, C. A., Lewinsohn, P. M., Olaya, B., & Seeley, J. R. (2014). Anxiety disorders in adolescents and psychosocial outcomes at age 30. Journal of Affective Disorders, 163, 125–132. [Google Scholar] [CrossRef]
  19. Foroughi, B., Griffiths, M. D., Iranmanesh, M., & Salamzadeh, Y. (2021). Associations between instagram addiction, academic performance, social anxiety, depression, and life satisfaction among university students. International Journal of Mental Health and Addiction, 20(4), 2221–2242. [Google Scholar] [CrossRef]
  20. Gao, W. J., Luo, Y. F., Cao, X. J., & Liu, X. Q. (2022). Gender differences in the relationship between self-esteem and depression among college students: A cross-lagged study from China. Journal of Research in Personality, 97, 104202. [Google Scholar] [CrossRef]
  21. Gaylord-Harden, N. K., Ragsdale, B. L., Mandara, J., Richards, M. H., & Petersen, A. C. (2007). Perceived support and internalizing symptoms in African American adolescents: Self-esteem and ethnic identity as mediators. Journal of Youth and Adolescence, 36(1), 77–88. [Google Scholar] [CrossRef]
  22. Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. [Google Scholar] [CrossRef] [PubMed]
  23. Hashemabady, B. G., Tavousi, A. Z., Mazloomzadeh, M., & Kazemi, S. M. (2022). The relationship between self-efficacy and life satisfaction: Mediating role of emotion dysregulation. Journal of Fundamentals of Mental Health, 24(4), 231–240. [Google Scholar] [CrossRef]
  24. Heatherton, T. F., & Polivy, J. (1991). Development and validation of a scale for measuring state self-esteem. Journal of Personality and Social Psychology, 60(6), 895–910. [Google Scholar] [CrossRef]
  25. Heimpel, S. A., Wood, J. V., Marshall, M. A., & Brown, J. D. (2002). Do people with low self-esteem really want to feel better? Self-esteem differences in motivation to repair negative moods. Journal of Personality and Social Psychology, 82(1), 128–147. [Google Scholar] [CrossRef]
  26. Henriksen, I. O., Ranoyen, I., Indredavik, M. S., & Stenseng, F. (2017). The role of self-esteem in the development of psychiatric problems: A three-year prospective study in a clinical sample of adolescents. Child and Adolescent Psychiatry and Mental Health, 11, 68. [Google Scholar] [CrossRef] [PubMed]
  27. Hyde, J. S., Mezulis, A. H., & Abramson, L. Y. (2008). The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychological Review, 115(2), 291–313. [Google Scholar] [CrossRef] [PubMed]
  28. Ingram, R. E. (2003). Origins of cognitive vulnerability to depression. Cognitive Therapy and Research, 27(1), 77–88. [Google Scholar] [CrossRef]
  29. Ji, Y., & Yu, X. (1999). Self-esteem scale (SES). Rating scale for mental health. Chinese Mental Health Journal, Supplement, 318–320. [Google Scholar]
  30. Jovanovic, V. (2019). Adolescent life satisfaction: The role of negative life events and the Big Five personality traits. Personality and Individual Differences, 151, 109548. [Google Scholar] [CrossRef]
  31. Jørgensen, M., Kristensen, S. M., & Breivik, K. (2023). Scar, vulnerability, or both? A longitudinal study of the association between depressive tendencies and global negative self-esteem from early adolescence to young adulthood with gender as a moderating factor. Personality and Individual Differences, 214, 112349. [Google Scholar] [CrossRef]
  32. Kang, B. X., Li, Y. Z., Zhao, X. Y., Cui, X. A., Qin, X. X., Fang, S., Chen, J., & Liu, X. Y. (2024). Negative parenting style and depression in adolescents: A moderated mediation of self-esteem and perceived social support. Journal of Affective Disorders, 345, 149–156. [Google Scholar] [CrossRef] [PubMed]
  33. Kang, C., Zheng, Y., Yang, L., Wang, X., Zhao, N., Guan, T. F., Qiu, S., Shi, J., & Hu, J. (2021). Prevalence, risk factors and clinical correlates of suicidal ideation in adolescent patients with depression in a large sample of Chinese. Journal of Affective Disorders, 290, 272–278. [Google Scholar] [CrossRef] [PubMed]
  34. Keles, B., McCrae, N., & Grealish, A. (2020). A systematic review: The influence of social media on depression, anxiety and psychological distress in adolescents. International Journal of Adolescence and Youth, 25(1), 79–93. [Google Scholar] [CrossRef]
  35. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Archives of General Psychiatry, 62(6), 593–602. [Google Scholar] [CrossRef] [PubMed]
  36. Kim, E. H., & Nho, C. R. (2020). Longitudinal reciprocal relationships between self-esteem, family support, and life satisfaction in Korean multicultural adolescents. Asian Social Work and Policy Review, 14(3), 184–196. [Google Scholar] [CrossRef]
  37. Kong, F., Zhao, J., & You, X. (2012). Emotional intelligence and life satisfaction in Chinese university students: The mediating role of self-esteem and social support. Personality and Individual Differences, 53(8), 1039–1043. [Google Scholar] [CrossRef]
  38. Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. [Google Scholar] [CrossRef] [PubMed]
  39. Kuster, F., Orth, U., & Meier, L. L. (2012). Rumination mediates the prospective effect of low self-esteem on depression: A five-wave longitudinal study. Personality and Social Psychology Bulletin, 38(6), 747–759. [Google Scholar] [CrossRef]
  40. Leary, M. R., & Baumeister, R. F. (2000). The nature and function of self-esteem: Sociometer theory. In M. P. Zanna (Ed.), Advances in experimental social psychology (Vol. 32, pp. 1–62). Academic Press. [Google Scholar] [CrossRef]
  41. Lee, S. W., Choi, J. S., & Lee, M. (2020). Life satisfaction and depression in the oldest old: A longitudinal study. The International Journal of Aging and Human Development, 91(1), 37–59. [Google Scholar] [CrossRef] [PubMed]
  42. Lewinsohn, P. M., Steinmetz, J. L., Larson, D. W., & Franklin, J. (1981). Depression-related cognitions—Antecedent or consequence. Journal of Abnormal Psychology, 90(3), 213–219. [Google Scholar] [CrossRef]
  43. Li, W., Guo, Y., Lai, W., Wang, W., Li, X., Zhu, L., Shi, J., Guo, L., & Lu, C. (2023). Reciprocal relationships between self-esteem, coping styles and anxiety symptoms among adolescents: Between-person and within-person effects. Child and Adolescent Psychiatry and Mental Health, 17(1), 21. [Google Scholar] [CrossRef] [PubMed]
  44. Lin, C.-Y., Lopes, A. R., & Nihei, O. K. (2021). Depression, anxiety and stress symptoms in Brazilian university students during the COVID-19 pandemic: Predictors and association with life satisfaction, psychological well-being and coping strategies. PLoS ONE, 16(10), e0258493. [Google Scholar] [CrossRef]
  45. Little, R. J. A. (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83(404), 1198–1202. [Google Scholar] [CrossRef]
  46. Liu, X., Yang, F., Huang, N., Zhang, S., & Guo, J. (2024). Thirty-year trends of anxiety disorders among adolescents based on the 2019 global burden of disease study. General Psychiatry, 37(2), e101288. [Google Scholar] [CrossRef] [PubMed]
  47. Liu, X. Q., Cao, X. J., & Gao, W. J. (2022). Does low self-esteem predict anxiety among chinese college students? Psychology Research and Behavior Management, 15, 1481–1487. [Google Scholar] [CrossRef] [PubMed]
  48. Liu, X. Q., Li, Y., & Gao, W. J. (2024). Subjective well-being of college students: Developmental trajectories, predictors, and risk for depression. Journal of Psychology in Africa. [Google Scholar] [CrossRef]
  49. Marcionetti, J., & Rossier, J. (2019). A longitudinal study of relations among adolescents’ self-esteem, general self-efficacy, career adaptability, and life satisfaction. Journal of Career Development, 48(4), 475–490. [Google Scholar] [CrossRef]
  50. Martins, V., Serrao, C., Teixeira, A., Castro, L., & Duarte, I. (2022). The mediating role of life satisfaction in the relationship between depression, anxiety, stress and burnout among Portuguese nurses during COVID-19 pandemic. BMC Nursing, 21(1), 188. [Google Scholar] [CrossRef] [PubMed]
  51. Masselink, M., Van Roekel, E., Hankin, B. L., Keijsers, L., Lodder, G. M. A., Vanhalst, J., Verhagen, M., Young, J. F., & Oldehinkel, A. J. (2018). The longitudinal association between self-esteem and depressive symptoms in adolescents: Separating between-person effects from within-person effects. European Journal of Personality, 32(6), 653–671. [Google Scholar] [CrossRef] [PubMed]
  52. Mei, S., Qin, Z., Yang, Y., Gao, T., Ren, H., Hu, Y., Cao, R., Liang, L., Li, C., & Tong, Q. (2021). Influence of life satisfaction on quality of life: Mediating roles of depression and anxiety among cardiovascular disease patients. Clinical Nursing Research, 30(2), 215–224. [Google Scholar] [CrossRef] [PubMed]
  53. Merikangas, K. R., He, J.-P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., Benjet, C., Georgiades, K., & Swendsen, J. (2010). Lifetime prevalence of mental disorders in US adolescents: Results from the national comorbidity survey replication–adolescent supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49(10), 980–989. [Google Scholar] [CrossRef]
  54. Minihan, S., Kwok, C., & Schweizer, S. (2023). Social rejection sensitivity and its role in adolescent emotional disorder symptomatology. Child and Adolescent Psychiatry and Mental Health, 17(1), 8. [Google Scholar] [CrossRef]
  55. Moksnes, U. K., & Espnes, G. A. (2013). Self-esteem and life satisfaction in adolescents-gender and age as potential moderators. Quality of Life Research, 22(10), 2921–2928. [Google Scholar] [CrossRef] [PubMed]
  56. Nguyen, D. T., Wright, E. P., Dedding, C., Pham, T. T., & Bunders, J. (2019). Low self-esteem and its association with anxiety, depression, and suicidal ideation in vietnamese secondary school students: A cross-sectional study. Frontiers in Psychiatry, 10, 698. [Google Scholar] [CrossRef] [PubMed]
  57. Nolenhoeksema, S., & Girgus, J. S. (1994). The emergence of gender differences in depression during adolescence. Psychological Bulletin, 115(3), 424–443. [Google Scholar] [CrossRef] [PubMed]
  58. Orth, U., Clark, D. A., Donnellan, M. B., & Robins, R. W. (2021). Testing prospective effects in longitudinal research: Comparing seven competing cross-lagged models. Journal of Personality and Social Psychology, 120(4), 1013–1034. [Google Scholar] [CrossRef] [PubMed]
  59. Orth, U., & Robins, R. W. (2013). Understanding the link between low self-esteem and depression. Current Directions in Psychological Science, 22(6), 455–460. [Google Scholar] [CrossRef]
  60. Orth, U., & Robins, R. W. (2014). The development of self-esteem. Current Directions in Psychological Science, 23(5), 381–387. [Google Scholar] [CrossRef]
  61. Peixoto, M. M., Ribeiro, V., & Cunha, O. (2023). Generalized anxiety symptoms and life satisfaction. Psychologica, 66, e066005. [Google Scholar] [CrossRef]
  62. Psychogiou, L., Navarro, M. C., Orri, M., Cote, S. M., & Ahun, M. N. (2024). Childhood and Adolescent Depression Symptoms and Young Adult Mental Health and Psychosocial Outcomes. JAMA Network Open, 7(8), e2425987. [Google Scholar] [CrossRef] [PubMed]
  63. Rajagopalan, J., & Shejwal, B. (2014). Influence of sociocultural pressures on body image dissatisfaction. Psychological Studies, 59(4), 357–364. [Google Scholar] [CrossRef]
  64. Rodrigue, C., Rodgers, R. F., Carbonneau, N., Bégin, C., & Dion, J. (2024). COVID-19-related distress, body image, and eating behaviors: A cross-sectional explanatory model. BMC Psychology, 12(1), 117. [Google Scholar] [CrossRef] [PubMed]
  65. Rosenberg, M. (1965). Society and the adolescent self-image. Princeton University Press. [Google Scholar]
  66. Satici, S. A., Uysal, R., Yilmaz, M. F., & Deniz, M. E. (2016). Social safeness and psychological vulnerability in Turkish youth: The mediating role of life satisfaction. Current Psychology, 35, 22–28. [Google Scholar] [CrossRef]
  67. Seligman, M. E. (2004). Authentic happiness: Using the new positive psychology to realize your potential for lasting fulfillment. Simon and Schuster. [Google Scholar]
  68. Shorey, S., Ng, E. D., & Wong, C. H. J. (2022). Global prevalence of depression and elevated depressive symptoms among adolescents: A systematic review and meta-analysis. British Journal of Clinical Psychology, 61(2), 287–305. [Google Scholar] [CrossRef]
  69. Solomon, S., Greenberg, J., & Pyszczynski, T. (1991). A terror management theory of self-esteem and its role in social behavior. Advances in Experimental Social Psychology, 24, 93–159. [Google Scholar]
  70. Son, S., Jang, Y., & Lee, H. (2024). Age-dependent relationship between self-esteem and depressive symptoms in Korean adolescents: A meta-analysis of longitudinal studies. Journal of Youth and Adolescence. [Google Scholar] [CrossRef] [PubMed]
  71. Sowislo, J. F., & Orth, U. (2013). Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies. Psychological Bulletin, 139(1), 213–240. [Google Scholar] [CrossRef]
  72. Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097. [Google Scholar] [CrossRef] [PubMed]
  73. Steiger, A. E., Allemand, M., Robins, R. W., & Fend, H. A. (2014). Low and decreasing self-esteem during adolescence predict adult depression two decades later. Journal of Personality And Social Psychology, 106(2), 325–338. [Google Scholar] [CrossRef]
  74. Stenling, A., Ivarsson, A., Lindwall, M., & Gucciardi, D. F. (2018). Exploring longitudinal measurement invariance and the continuum hypothesis in the swedish version of the behavioral regulation in sport questionnaire (BRSQ): An exploratory structural equation modeling approach. Psychology of Sport and Exercise, 36, 187–196. [Google Scholar] [CrossRef]
  75. Szcześniak, M., Bajkowska, I., Czaprowska, A., & Sileńska, A. (2022). Adolescents’ self-esteem and life satisfaction: Communication with peers as a mediator. International Journal of Environmental Research and Public Health, 19(7), 3777. [Google Scholar] [CrossRef]
  76. Tang, Q., Zou, X., Wang, S., Zhang, L., Liu, X., Shi, C., Tao, Y., & Li, Y. (2024). Longitudinal associations between capacity to be alone, life satisfaction, self-compassion, anxiety, and depression among Chinese college students. PsyCh Journal, 13(6), 979–992. [Google Scholar] [CrossRef]
  77. Tran, T., Liu, Q., & Cole, D. A. (2023). Prospective and contemporaneous relations of self-esteem and depressed affect in the context of parent-child closeness during adolescence: A random-intercept cross-lagged panel model. Journal of Youth and Adolescence, 52(3), 506–518. [Google Scholar] [CrossRef] [PubMed]
  78. Twenge, J. M., Martin, G. N., & Spitzberg, B. H. (2019). Trends in US Adolescents’ media use, 1976–2016: The rise of digital media, the decline of TV, and the (near) demise of print. Psychology of Popular Media Culture, 8(4), 329–345. [Google Scholar] [CrossRef]
  79. Wang, K. T., Yuen, M., & Slaney, R. B. (2009). Perfectionism, depression, loneliness, and life satisfaction a study of high school students in Hong Kong. Counseling Psychologist, 37(2), 249–274. [Google Scholar] [CrossRef]
  80. Wang, P., Gao, H., Xu, J., Huang, J., & Wang, C. (1998). The reliability and validity of the self-esteem scale. Journal of Psychiatry, 11(4), 31–32. [Google Scholar]
  81. Wang, S., Li, H., Chen, X., Yan, N., & Wen, D. (2023). The mediating role of psychological capital in the association between life satisfaction and depressive and anxiety symptoms among Chinese medical students during the COVID-19 pandemic: A cross-sectional study. BMC Psychiatry, 23(1), 398. [Google Scholar] [CrossRef] [PubMed]
  82. Wang, X., Wang, H., & Wang, W. (2024). Longitudinal associations among bullying victimization, self-esteem, and adolescents’ depressive symptoms. Psychology of Violence, 14(1), 56–65. [Google Scholar] [CrossRef]
  83. WHO. (2023a). Anxiety disorders. World Health Organization. Available online: https://www.who.int/news-room/fact-sheets/detail/anxiety-disorders (accessed on 25 October 2024).
  84. WHO. (2023b). Depressive disorder (depression). Available online: https://www.who.int/news-room/fact-sheets/detail/depression (accessed on 25 October 2024).
  85. WHO. (2024). Mental health of adolescents. Available online: https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health (accessed on 25 October 2024).
  86. Wouters, S., Duriez, B., Luyckx, K., Klimstra, T., Colpin, H., Soenens, B., & Verschueren, K. (2013). Depressive symptoms in university freshmen: Longitudinal relations with contingent self-esteem and level of self-esteem. Journal of Research in Personality, 47(4), 356–363. [Google Scholar] [CrossRef]
  87. Xing, H. L., Zhang, Y. Q., Yao, M. L., Zhu, W. L., & Liu, H. R. (2024). How perceived parenting qualities link to the reciprocal relationship between adolescents’ self-concept and life satisfaction. Journal of Social and Personal Relationships, 41(11), 3480–3502. [Google Scholar] [CrossRef]
  88. Yang, Z. X., Peng, H. Y., & Xin, S. F. (2024). A longitudinal study on depression and anxiety among Chinese adolescents in the late phase of the COVID-19 pandemic: The trajectories, antecedents, and outcomes. Acta Psychologica Sinica, 56(4), 482–496. [Google Scholar] [CrossRef]
Behavsci 15 00182 g001
Figure 1. CLPM illustrating the relationships among self-esteem, life satisfaction, and depressive symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. Correlations within each time point and residuals are excluded for clarity. ** p < 0.01, and *** p < 0.001.
Figure 1. CLPM illustrating the relationships among self-esteem, life satisfaction, and depressive symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. Correlations within each time point and residuals are excluded for clarity. ** p < 0.01, and *** p < 0.001.
Behavsci 15 00182 g001
Behavsci 15 00182 g002
Figure 2. CLPM illustrating the relationships among self-esteem, life satisfaction, and anxiety symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. Correlations within each time point and residuals are excluded for clarity. ** p < 0.01, and *** p < 0.001.
Figure 2. CLPM illustrating the relationships among self-esteem, life satisfaction, and anxiety symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. Correlations within each time point and residuals are excluded for clarity. ** p < 0.01, and *** p < 0.001.
Behavsci 15 00182 g002
Behavsci 15 00182 g003
Figure 3. RI-CLPM illustrating the relationships among self-esteem, life satisfaction, and depressive symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. To enhance clarity, within-person level correlations are not displayed. ** p < 0.01, and *** p < 0.001.
Figure 3. RI-CLPM illustrating the relationships among self-esteem, life satisfaction, and depressive symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. To enhance clarity, within-person level correlations are not displayed. ** p < 0.01, and *** p < 0.001.
Behavsci 15 00182 g003
Behavsci 15 00182 g004
Figure 4. RI-CLPM illustrating the relationships among self-esteem, life satisfaction, and anxiety symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. To enhance clarity, within-person level correlations are not displayed. * p < 0.05, ** p < 0.01, and *** p < 0.001.
Figure 4. RI-CLPM illustrating the relationships among self-esteem, life satisfaction, and anxiety symptoms. All path coefficients are standardized, and gray dashed lines indicate non-significant pathways. To enhance clarity, within-person level correlations are not displayed. * p < 0.05, ** p < 0.01, and *** p < 0.001.
Behavsci 15 00182 g004
Table 1. Descriptive Analysis of the Prevalence of Depressive and Anxiety Symptoms.
Table 1. Descriptive Analysis of the Prevalence of Depressive and Anxiety Symptoms.
Depressive SymptomsAnxiety Symptoms
MiddleHighMiddleHigh
MaleFemaleMaleFemaleMaleFemaleMaleFemale
T17 (2.55%)27 (9.82%)62 (8.27%)104 (13.87%)7 (2.55%)15 (5.45%)40 (5.33%)77 (10.27%)
T212 (4.46%)35 (13.01%)49 (7.66%)90 (14.06%)9 (3.35%)21 (7.81%)31 (4.84%)52 (8.13%)
T313 (4.74%)43 (15.69%)67 (10.06%)99 (14.86%)12 (4.38%)30 (10.95%)42 (6.31%)63 (9.46%)
Table 2. Correlation Analysis of Main Variables.
Table 2. Correlation Analysis of Main Variables.
M ± SD123456789101112
T1
 1. Self-esteem2.89 ± 0.52-
 2. Life satisfaction4.69 ± 1.150.51 **-
 3. Depressive symptoms0.62 ± 0.59−0.51 **−0.34 **-
 4. Anxiety symptoms0.60 ± 0.68−0.51 **−0.36 **0.83 **-
T2
 5. Self-esteem2.87 ± 0.500.58 **0.32 **−0.36 **−0.33 **-
 6. Life satisfaction4.56 ± 1.160.41 **0.47 **−0.32 **−0.29 **0.49 **-
 7. Depressive symptoms0.65 ± 0.60−0.40 **−0.33 **0.43 **0.45 **−0.53 **−0.33 **-
 8. Anxiety symptoms0.57 ± 0.67−0.35 **−0.28 **0.41 **0.44 **−0.50 **−0.29 **0.85 **-
T3
 9. Self-esteem2.84 ± 0.480.47 **0.29 **−0.32 **−0.29 **0.58 **0.31 **−0.36 **−0.34 **-
 10. Life satisfaction4.70 ± 1.160.30 **0.39 **−0.25 **−0.23 **0.35 **0.44 **−0.24 **−0.23 **0.40 **-
 11. Depressive symptoms0.74 ± 0.63−0.29 **−0.25 **0.37 **0.35 **−0.40 **−0.24 **0.44 **0.41 **−0.49 **−0.35 **-
 12. Anxiety symptoms0.69 ± 0.73−0.29 **−0.25 **0.36 **0.39 **−0.42 **−0.26 **0.45 **0.48 **−0.48 **−0.34 **0.86 **-
Note: ** p < 0.01.
Table 3. Model Comparison Test of the CLPM and RI-CLPM.
Table 3. Model Comparison Test of the CLPM and RI-CLPM.
Dependent Variableχ2dfRMSEACFITLISRMRΔRMSEAΔCFIΔSRMR
Depressive symptoms
 CLPM1111.324210.0650.9690.9210.033
 CLPM2111.525240.0600.9700.9330.0330.0050.0010.000
 CLPM3121.616270.0580.9680.9360.0340.002 0.002 0.001
 CLPM4122.088300.0550.9690.9440.0350.0030.0010.001
 RI-CLPM125.65760.0570.9930.9400.017
 RI-CLPM225.65790.0420.9940.9660.0170.0150.0010.000
 RI-CLPM326.943150.0280.9960.9850.0180.0140.0020.001
 RI-CLPM454.573210.0390.9890.9710.0230.0110.0070.005
Anxiety symptoms
 CLPM1120.210210.0680.9660.9130.032
 CLPM2121.016240.0630.9670.9260.0330.0050.0010.001
 CLPM3127.910270.0600.9660.9310.0340.0030.0010.001
 CLPM4133.027300.0580.9650.9370.0360.0020.0010.002
 RI-CLPM125.33360.0560.9930.9410.017
 RI-CLPM225.33390.0420.9940.9670.0170.0140.0010.000
 RI-CLPM327.751150.0290.9960.9840.0180.0130.0020.001
 RI-CLPM451.300210.0380.9900.9730.0250.0090.0060.007
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Han, Z.; Chen, S.; Zhou, Y.; Liu, Y.; Guo, C. The Longitudinal Relationship Between Self-Esteem, Life Satisfaction, and Depressive and Anxiety Symptoms Among Chinese Adolescents: Within- and Between-Person Effects. Behav. Sci. 2025, 15, 182. https://doi.org/10.3390/bs15020182

AMA Style

Han Z, Chen S, Zhou Y, Liu Y, Guo C. The Longitudinal Relationship Between Self-Esteem, Life Satisfaction, and Depressive and Anxiety Symptoms Among Chinese Adolescents: Within- and Between-Person Effects. Behavioral Sciences. 2025; 15(2):182. https://doi.org/10.3390/bs15020182

Chicago/Turabian Style

Han, Zongqiao, Shuai Chen, Yan Zhou, Yanling Liu, and Cheng Guo. 2025. "The Longitudinal Relationship Between Self-Esteem, Life Satisfaction, and Depressive and Anxiety Symptoms Among Chinese Adolescents: Within- and Between-Person Effects" Behavioral Sciences 15, no. 2: 182. https://doi.org/10.3390/bs15020182

APA Style

Han, Z., Chen, S., Zhou, Y., Liu, Y., & Guo, C. (2025). The Longitudinal Relationship Between Self-Esteem, Life Satisfaction, and Depressive and Anxiety Symptoms Among Chinese Adolescents: Within- and Between-Person Effects. Behavioral Sciences, 15(2), 182. https://doi.org/10.3390/bs15020182

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop