The Influencing Factors of Self-evaluation in Adolescents: A Structural Equation Modeling

doi:10.21203/rs.3.rs-89997/v3

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The Influencing Factors of Self-evaluation in Adolescents: A Structural Equation Modeling

https://doi.org/10.21203/rs.3.rs-89997/v3

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Background

Adolescents’ self-evaluation is an expressive form of their self-concept. Parental bonding, personality traits, and psychological status were the three main determining factors of adolescents’ self-evaluation; however, no study has tested the effects of the three variables simultaneously. We aimed to explore these effects by a systematic approach.

Methods

Data came from the Chinese Family Panel Studies (CFPS). The associations of parental bonding (measured by the Parental Bonding Instrument), personality traits (the Responsibility Scale), and psychological status (the Kessler Psychological Distress Scale, K6) with self-evaluation measured in three domains (the Rosenberg Self-Esteem Scale, the Nowicki- Strickland Locus of Control Scale for children and the Self-Discipline Scale) were tested by the structural equation modeling (SEM) analysis.

Results

A total of 892 Chinese adolescents were included. Significant positive correlations were found among self-evaluation, parental bonding, personality traits, and psychological status. The overall (direct and indirect) effect of parental bonding on adolescents’ self-evaluation was 0.49. Personality traits and psychological status were directly associated with adolescents’ self-evaluation.

Conclusions

The use of SEM offered a detailed analysis of the correlations between parental bonding, personality traits, and psychological status and a systematic approach to investigate their direct and indirect effects on adolescents’ self-evaluation. The three factors directly associated with adolescents’ self-evaluation and parental bonding indirectly affected adolescents’ self-evaluation that was mediated by both personality traits and psychological status.

Adolescents

Self-evaluation

Parental bonding

Personality traits

Under the influence of positive psychology, measuring positive indicators of adolescents’ mental health, such as self-evaluation, can provide a more comprehensive understanding of overall mental health. Adolescents’ self-evaluation is an expressive form of self-concept. Self-concepts are defined as self-perceptions related to specific domains, roles, or social contexts [1]. Although some specificity in self-concepts is developed earlier in childhood [2], these self-perceptions become increasingly complex and differentiated across adolescence [1, 3], presumably due to both the cognitive development and Changes in the living environment experienced during adolescence.

Recently, society from all social classes has attached more importance to self-evaluation issues among adolescents. A person with a positive self-assessment during adolescence will believe in his own abilities, appreciate his efforts, and may have confidence and hope for future life, encouraging him to strive to solve problems [4]. Conversely, negative self-evaluation is the primary source of self-destructive behaviors. Things such as drinking alcohol, excessive internet use, and smartphone addiction are exacerbated as people try to avoid negative self-evaluations of themselves. Study on adolescents has found that self-evaluation is strongly associated with physical, psychological, academic, emotional, and social variables [3, 5, 6]. In view of the important impact of self-evaluation on adolescent development, it is necessary to explore the factors that influence adolescents’ self-evaluation.

However, the factors influencing contemporary adolescent self-evaluation are multidimensional and complex. Here, we nominate three main groups of factors: first, factors related to the family of origin, such as the relationships between the family members [7]. Parents are the earliest social environment for children and play an important role in shaping Chinese adolescents' psychological status. [8, 9]. Parental bonding was identified as one of the crucial factors in children’s personality development. Growing up with parents who provide consistent and effective guidance about regulating emotional states may counteract the impact that heightened physiological and emotional reactivity would otherwise have on peer relationships and social competence, which helps teens develop more positive self-evaluations [10].

The second group of factors affecting adolescents’ self-evaluation is related to the personality traits that contributed to the initiative in personal, emotional, motivational, and social behaviors of adolescents [11, 12]. Personality growth initiatives may be intimately linked with psychological adjustment. At the same time, positive mental health and a well-adjusted personality may be fundamental characteristics of healthy, positive, and initiative self-evaluation [13, 14]. Furthermore, parental relationships can directly affect adolescents' self-evaluations. Abnormal parental relationships can also affect personality development, which may lead to certain problematic personality traits such as distress and emotional instability, which may indirectly reduce levels of self-evaluation [15]. Previous empirical studies have shown that personality traits mediate the relationship between parental bonding and adolescent self-evaluation [16, 17]. Therefore, the above evidence provides a concrete theoretical and empirical basis for the potential mediating effect of the personality traits in the relation between parental bonding and self-evaluation.

Compared to parental bonding and personality traits, little study has been done on the impact of the third group of factors; the psychological status of adolescents [18, 19]. Adolescents with negative beliefs, attachment anxiety, or low self-esteem, influenced by environmental factors, especially parental rearing, were described as exhibiting behaviors that reflect a negative self-evaluation and then compensate for that. It implies that they act in accord with negative self-patterns [20, 21]. In addition to personal growth [22], positive self-evaluation shows an important moderating role in life, work, and learning [23, 24, 25]. Studies have shown that close parental bonding is significantly and positively associated with adolescents' overall health evaluations, and this relationship may be partially explained by adolescent psychological states [26]. Similarly, we can infer that perceived psychological status is a mediator between adolescents' parental bonding and self-evaluation.

Although studies have respectively investigated the associations of parental bonding, personality traits, and psychological status on adolescents’ self-evaluation [27, 28], no studies have combined all the three factors or examined their relations so far. The present study aimed to examine the relationships between parental bonding, personality traits, psychological status, and self-evaluation among Chinese adolescents. We hypothesized that parental bonding, personality traits, psychological status, and self-evaluation would be significantly positively correlated (H1). Moreover, we hypothesized that personality traits would mediate the relationship between parental bonding and self-evaluation (H2) and that psychological status would mediate the relationship between parental bonding and self-evaluation (H3).

Data Sources

The data for this study were obtained from the Chinese Family Panel Studies (CFPS) by implementing the China Social Science Survey Center, Peking University. CFPS conducted initial investigations in Beijing, Shanghai, and Guangdong in 2008 and 2009, and samples were collected from all over China in 2010. CFPS is a national, large-scale, and multidisciplinary social follow-up survey project that includes four main questionnaire types: community questionnaire, family questionnaire, adult questionnaire, and children questionnaire. CFPS had collected data over four rounds. The data analyzed in this study was from a single-round collection in 2014 by children questionnaire. The study protocol and sampling method details can be found elsewhere [29,30].

Adolescents in this study were students aged 10 to 15 years old in the east, north, south, central, northeast, northwest, and southwest regions of China, including 25 provinces, cities and autonomous regions. The representativeness of the sample is very good. A total of 892 adolescents from 871 families were included in the study with complete and significant study questionnaires.

Participants

A total of 892 adolescents from east (15.1%), north (11.3%), south (14.0%), central (19.7%), northeast (10.2%), northwest (16.0%) and southwest (13.6%) China, included 485 (54.4%) boys and 407 (45.6%) girls were included in the current study. The sample was composed of 365 (40.9%) adolescents living in urban areas and 527 (59.1%) adolescents from rural areas. The average age of total boys and girls adolescents was 10.72 (SD=0.89), 10.71 (SD=0.83), and 10.72 (SD=0.96) years, respectively.

Measures Questionnaire design

This research conducted a preliminary survey of 783 adolescents in Beijing, Shanghai, and Guangdong provinces in 2008 and 2009, to improve the operability of the questionnaire survey. Those 783 adolescents were excluded from the formal study because the final questionnaire had been modified according to their feedback. The study is based on the CFPS self-administered questionnaire for adolescents aged 10 to 15 years that covered basic information on age, gender, living condition, educational level, type of residence, self-evaluation, parental bonding instrument, personality traits, and psychological status.

Self-evaluation

Adolescents’ self-evaluation consists of three scales: the Rosenberg Self-Esteem Scale [31], the Nowicki-Strickland Locus of Control Scale for children (NLCS-C) [32], and the Self-Discipline Scale [33]. The Rosenberg Self-Esteem Scale consisted of 10 questions such as “On the whole, I am satisfied with myself,” which was a 4 -point Likert scale (1) “totally disagree” (2) “disagree” (3) “agree” and (4) “totally agree”, with some questions were reverse scored. A higher final sum score for all the ten items indicated higher self-esteem. The NLCS-C scale consisted of 40 yes/no answered questions with a low score indicating internal locus of control and a high score indicating external locus of control. Such as “Do you believe that most problems will solve themselves if you just don’t fool with them?” The Self-Discipline Scale is based on a 5 -point Likert scale (1) “Disagree strongly” (2) “Disagree a little” (3) “Neither agree nor disagree” (4) “Agree a little” and (5) “Agree Strongly”. Of the 12 questions such as “I am good at resisting temptation”, a higher score indicates optimism and higher perceived self-efficacy. However, after the existing and mature scales abroad were introduced to China, researchers also faced the problems of measuring validity and reliability. Because Chinese people tend to be conservative in their responses to the scale, they tend to choose neutral answers rather than the most suitable ones, which leads to inaccurate measurement results. In dealing with this problem, the researchers of CFPS have added or deleted items and modified their scoring to include (1) “totally disagree” (2) “disagree” (3) "neither agree nor disagree” (4) “agree” and (5) “totally agree” to reduce the probability that respondents improperly choose the middle option [34]. The Cronbach's alphas for the respective three scales were 0.88, 0.82, and 0.70.

Parental Bonding Instrument, Personality Traits and Psychological Status

In order to make the scales conform to Chinese people's answering habits and thinking mode and reduce the inaccurate measurement results, the researchers of CFPS have modified these scoring scales a little and re-measured the validity and reliability of the scales [34]. The Parental Bonding Instrument introduced by Parker et al. was used with a 25-items measure of differences in parental bonding. Responses were scored on a 5-point Likert scale ranging from (1) “never” (2) “rarely” (3) “sometimes” (4) “often” and (5) “always”; Cronbach's alpha for the scale was 0.80 [35]. The Personality Scale that was used to assess the personality traits [34] was derived from a sub-scale of the Big Five Questionnaire-Children produced by Barbaranelli et al. [36], with a 12- self-reported items rated from (1) “totally disagree” to (5) “totally agree” and its Cronbach's alpha was 0.77. Kessler measured the psychological status using the Kessler 6 Psychological Distress Scale (K6) [37]. The scale consisted of 6 items scored on a 5- point Likert scale ranging from (1) “always” (2) “often” (3) “sometimes” (4) “rarely” and (5) “never”. Some of the items were reversely scored so that the high total score indicates positive psychological status. The Cronbach's alpha for this scale was 0.649.

Procedure

In brief, the CFPS sample was a multi-stage probability sample extracted by the implicit stratification method. The samples of the subsampling frame were extracted in three stages. The first-stage sampling (primary sampling units, PSUs) were counties (or county-level cities/districts) listed in descending order by a socioeconomic indicator. The second-stage sampling (Secondary sampling units, SSUs) were resident committees and administrative villages from counties (or county-level cities/districts). The third and final stage of sampling (Tertiary sampling units, TSUs) were households from resident committees and administrative villages. In the first two stages of the sampling process, official administrative entities were used. The administrative structure in China has two important features: first, it is strictly hierarchical; and second, at least in theory, it covers the entire population of China exhaustively, without exception. Moreover, to minimize sampling frame errors, it was the random starting point of the circular isometric sampling method that was used to extract sample households in the third stage. The study was designed to include interviews and consider all members over the age of 9 years in a sampled household as core members of the CFPS.

Statistical analysis

SPSS-25.0 and AMOS-24.0 were used for data analyses. The participants’ characteristics were presented as numbers and frequencies. In order to examine the theoretical model which contained the targeted factors, a type of multivariate analysis method, structural equation modeling (SEM), was applied. Initially, a model containing the final scores of the parental bonding instrument, personality traits scale, and psychological status scale with the adolescents’ self-evaluation domains was designed. Then the estimated value and significance level of each parameter were obtained. In addition, in order to explore the heterogeneity caused by demographic characteristics, and tests for heterogeneity for age (<11 and ≥11 years), sex (boy and girl), and living environment (urban and rural) by multigroup analyses of the structural equation modeling considering subgroup sample size³200 [38].

After that, the bivariate correlation analysis (BCA) was used to observe the correlation among the included factors. After the analysis results were confirmed, the proposed hypothesis model was verified and fitted with the structural equation modeling (SEM) analysis of AMOS. The proposed model was confirmed by examining the goodness of fit statistics, which indicted a ratio of the chi-square (χ2) to the degree of freedom (df), a goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI), and root mean square error of approximation (RMSEA). The definition of satisfactory goodness of fit was χ2/df < 2.0, GFI > 0.95, AGFI > 0.90, CFI > 0.97, and RMSEA < 0.05, while the standard of acceptable goodness of fit was χ2/df < 3.0, GFI > 0.90, AGFI > 0.85, CFI > 0.95, and RMSEA < 0.08 [39]. The chi-square difference test was used to check the nested models and if the complex model fitted a higher degree of the data when compared to the simpler model [40]. By comparing the Akaike information criterion (AIC) value of the models, a nested model is proved to be a significant well-fitting model if it was associated with at least 50 units reduction in the measurement [41,42,43].

Baseline characteristics

Our analytic sample includes 892 children and youth, of which 485 are boys (54.4%) and 407 are girls (45.6%). The mean age of the sample was 10.7 (SD=0.89) years. The baseline characteristics of study participants are shown in Table 1 (see Table 1).

Correlations

The results show that the score of the parental bonding instrument correlated with scores of the self-evaluation domains, including self-esteem, self-discipline, and NLCS-C (r from 0.119 to 0.265, P<0.01). It meant that adolescents’ self-evaluation might rise with high levels of parental bonding instruments. The parental bonding instrument score was associated with the K6 score of psychological status and personality traits score (r = 0.185 and 0.157, P<0.01, respectively). Different parental bonding instrument might have different psychological states and personality traits for adolescents. At the same time, the personality traits score was correlated with all self-evaluation domains’ scores (r from 0.156 to 0.364, P<0.01), with the strongest correlation observed with self-esteem (r=0.364). Meanwhile, the K6 score (psychological status) was moderately correlated with some self-evaluation domains, which were the self-esteem score (r = 0.250, p<0.01) and NLCS-C score (r = 0.126, p<0.01) specifically (see Table 2).

Structural equation model

The initial model assumed that self-evaluation was affected by the scores of parental bonding instrument, personality traits and psychological status. The unsatisfactory fit of the initial model was revealed by the measures of model fit (χ 2 /df = 12.214, GFI = 0.961, AGFI = 0.908, CFI = 0.793, RMSEA = 0.112), especially whose AIC was 133.929 (see Fig. 1).

Several significant paths were added to optimize the model, and a revised structural equation model was specified. The measures of the revised model fit (χ 2 /df = 2.876, GFI = 0.994, AGFI = 0.977, CFI = 0.977, RMSEA = 0.046) indicates that the revised model has a satisfactory fit. Furthermore, given that the AIC for the revised model (47.255) was lower than that of the initial model (133.929); thus, the revised model was more suitable for the data than the initial one (see Fig. 2).

Significant relationships between observed variables

As the path diagram with the standardized coefficients for each factor was provided (see Fig. 2). Results presented the direct, indirect, and total effects of the scores of parental bonding instrument, personality traits, and K6 (psychological status) on the self-evaluation scores calculated with both unstandardized and standardized coefficients. The path coefficients of variables measured at different scales within the same model can be directly compared using the standardized coefficients. In the revised SEM, the parental bonding instrument has a great direct and indirect influence on self-evaluation (direct β=0.28; mediated by personality traits and K6 β=0.21, and total effect β =0.49), while K6 was directly related to self-evaluation (β=0.39). Additionally, personality traits have the strongest positive total (direct) effect on self-evaluation (β=0.78) (see Table 3).

Multigroup analyses

Pre-specified multi-group analyses were presented for age (<11 and ≥11 years) (see Additional file 1), for sex (boys and girls) (see Additional file 2), and for the living environment (urban and rural) (see Additional file 3) in Supplemental File. The associations of parental bonding instrument, personality traits, and K6 with a self-evaluation did not vary by the levels of the subgroup factors, with similar results to those among the whole sample population. Parental bonding instrument, personality traits, and K6 had direct effects on self-evaluation. In addition, the Parental bonding instrument had indirect effects on self-evaluation by mediation personality traits and K6.

This study is the first empirical study to use the SEM systematic approach to investigate the influence of parental bonding, personality traits, and psychological status on the self-evaluation of Chinese adolescents (self-esteem, self-discipline, and locus of control for children). It presented a comprehensive study of mechanisms for the parental, personal, and psychological impacts on adolescents’ self-concept. The SEM analysis has demonstrated that parental bonding, personality traits, and psychological status played significant positive roles in the self-evaluation of Chinese adolescents.

The current study findings indicated that parental bonding was a determining factor in Chinese adolescents’ self-evaluation. It had become a consensus that parents were the earliest social environment for children and played a unique and significant role in the development of adolescents. The score of the parental bonding instrument was not only directly associated with self-evaluation but also had an indirect association with self-evaluation mediated by personality traits and the K6 score. During adolescence, adolescents are vulnerable to the harm of adverse stimuli, which would cause some learning and psychological problems and reduce their self-evaluation. In such situations, there is no doubt that the parental effects will not only limit their role in their children's growth and development but will also extend to the ways by which the adolescents interact with these harmful stimuli. A recent study [44] indicated that adolescents who perceived no parental support were 4-times more likely to have mental health problems than those who perceived strong support from their parents’ personality traits. Moreover, the K6-measured psychological status mediated the association between parental bonding and self-evaluation of adolescents, besides their direct influencing effects on self-evaluation. It affirms the previous study findings that pointed to concrete psychological mechanisms in terms of mentality and personality for parental bonding affecting adolescent self-evaluation [13,45].

The study found that parental bonding had significant effects on self-evaluation among Chinese adolescents. What’s more, those adolescents with higher scores on the personality traits scale were more likely to have higher self-evaluation. Personality traits are persistent and universal positive or negative attitudes towards people or things [46]. Adolescents with high personality trait scores usually have constant affirmation and the ability to complete daily tasks [47,48]. Thus, personality traits are a crucial factor in improving adolescents’ self-evaluation, which was consistent with previous studies’ findings [13,45]. To a certain extent, this provides ideas for us to carry out intervention work from the aspect of personality traits.

As indicated by the results, psychological status, measured by the K6 scale, was also associated with the self-evaluation in Chinese adolescents. Psychological status is a major internal motive for improving psychological and physical health [49,50]. A few previous studies also had found that adolescents with poor psychological status were prone to a negative self-evaluation, considering themselves inferior to others [51,52]. Consequently, those adolescents with distressing psychological status were vulnerable to losing their courage and determination to surmount difficulties and experienced greater emotional instability (higher neuroticism), which can reduce individual self-evaluation [53]. Previous studies indicated that anxiety affected axis activity (the awakening response, diurnal cortisol slope, and cortisol levels over the day) in the hypothalamic hazard-Adrenal cortex (HPA). Individuals with a flatter diurnal cortisol slope had a shorter sleep, poorer sleep quality, and even suicide. Therefore, not coincidentally was the positive correlation between self-evaluation and K6 scores observed in this study. Given this, it is essential to ameliorate the psychological status of adolescents to improve their self-evaluation.

From the view of practical significance, to raise the level of self-evaluation among Chinese adolescents, compared to interventional measures that target a single variable of either parental bonding, personality traits, or psychological status of the adolescents. We should formulate and conduct simultaneous interventions that take into consideration the mentioned three variables.

Limitations

The causal associations between variables cannot be deduced because of the cross-sectional nature of this study. Besides, the associations between the variables may be overestimated or underestimated since the study was conducted by self-reports from only one source in 2014, which may lead to bias to some extent. Last, about 60% of the interviewed adolescents did not submit a relatively complete research questionnaire, especially the question about self-evaluations, so they were excluded from the study in the process of selecting the population. Although those participants probably did not have a clear self-concept of themselves, their characteristics did not differ from those of the included adolescents in terms of sociodemographic data, health status, and scores for parental bonding instrument, personality traits, and psychological status scales.

Poor self-evaluation in adolescents can have significant long-term implications for mental health disorders, including further episodes of depression as an adult and an increased risk of suicidal ideation [54, 55]. Negative self-evaluation, including worthlessness, are one of the most common mental health disorders in adolescent. This novel study supported the importance and complexity of self-evaluation in adolescent development. Adolescents with mental health disorders could impair self-evaluation, which can change over time and improve with intervention.

This study expounds on the internal relationship among adolescents' self-evaluation (self-esteem, self-discipline, and locus of control for children), individual factors, and family environment factors, which provides a potentially direct and indirect intervention perspective for further improving adolescents' self-evaluation.

CFPS

the Chinese Family Panel Studies.

the Kessler Psychological Distress Scale.

SEM

the structural equation modeling.

PSUs

primary sampling units.

SSUs

Secondary sampling units.

TSUs

Tertiary sampling units.

NLCS-C

the Nowicki-Strickland Locus of Control Scale.

BCA

the bivariate correlation analysis.

χ2

the chi-square; df:the degree of freedom.

GFI

goodness of fit index.

AGFI

adjusted goodness of fit index.

CFI

comparative fit index.

RMSEA

root mean square error of approximation.

Acknowledgments

The authors of this study were incredibly grateful to the staff of the China Institute of Social Science Survey and Center for Social Research of Peking University, as well as other relevant institutions. The dedication of all the participants of the China Family Panel Studies (CFPS) was also appreciated.

Author contributions

YNZ conceived the study design, XBZ did statistical analyses, XBZ and YNZ drafted the manuscript. YNZ, XBZ, FZ, CJ, MY, JZ, JHC, and BX revised the final manuscript. BX and JHC act as the guarantors for the paper. All authors have read and agree to publish the final manuscript.

Funding

This study was supported by the National Social Science Fund of China in 2015 (grant number: 15BSH057).

Availability of data and materials

The public data used to support the findings of this study are available from the Peking University Open Research Data. https://opendata.pku.edu.cn/dataset.xhtml?persistentId=doi:10.18170/D VN/45LCSO. (Accessed on 9 Aug 2021)

Ethics approval and consent to participate

Participants had received the explanation before signing the consent to participate. They were given the right to withdraw from the study whenever they were reluctant to continue, and the analysis was entirely anonymous. The study protocol was approved by the Wuhan University of Science and Technology Medical Ethics Review Form (No.2022082).

Competing Interest

The primary authors declare no potential conficts of interest with respect to the research, authorship, and/or publication of this article.

Consent for publication

Participants (or legal parents or guardians of adolescents) agree that researchers may report their personal data.

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Table 1 Baseline characteristics of the study participants

Characteristics	N	%
Age, years	10.72	0.89
Geographic Location
East China	135	15.1
North China	101	11.3
South China	125	14.0
Central China	176	19.7
Northeast China	91	10.2
Northwest China	143	16.0
Southwest China	121	13.6
Sex
Boy	485	54.4
Girl	407	45.6
Living Environment
Urban	365	40.9
Rural	527	59.1
Health Status
Excellent	311	34.9
Very good	275	30.8
Good	238	26.7
Fair	56	6.3
Poor	12	1.3
Whether have pocket money
Yes	685	76.8
No	207	23.2
Whether participated in student organizations
Yes	89	10.0
No	613	68.7
No student organization in school	190	21.3

Table 2 Descriptive statistics and Pearson correlations of variables

Variables		Minimum	Maximum	Mean	SD	Parental bonding Instrument	Personality Traits	K6 (Psychological status)	Self-evaluation
Variables		Minimum	Maximum	Mean	SD	Parental bonding Instrument	Personality Traits	K6 (Psychological status)	Self-esteem	Self-discipline	NLCS-C
Parental bonding instrument		21	65	45.22	7.73	1
Personality traits		20	59	43.57	6.4	.185**	1
K6 (Psychological status)		12	30	26.70	3.87	.157**	.002	1
Self-evaluation	Self-esteem	34	66	50.32	4.84	.265**	.364**	.250**	1
	Self-discipline	21	46	34.36	3.38	.119**	.350**	0.088	.165**	1
	NLCS-C	26	47	37.24	3.41	.133**	.156**	.126**	.314**	.084*	1

*, **, represents a significance level of p<0.05 and p<0.01, respectively.

Table 3 Total, direct and indirect effects of the independent variables on the dependent variable.

Dependent variables (self-evaluation and its domains)	Effect	Independent variables
		Parental bonding Personality traits K6			Parental bonding Personality traits K6
		β^a			B^b
Self-evaluation	Total	0.49	0.78	0.39	0.05	0.09	0.08
	Direct	0.28	0.78	0.39	0.03	0.09	0.08
	Indirect	0.21	0	0	0.02	0	0
Self-esteem	Total	0.23	0.37	0.19	0.15	0.28	0.24
	Direct	0	0	0	0	0	0
	Indirect	0.23	0.37	0.19	0.15	0.28	0.24
Self-discipline	Total	0.17	0.28	0.14	0.08	0.15	0.12
	Direct	0	0	0	0	0	0
	Indirect	0.17	0.28	0.14	0.08	0.15	0.12
NLCS-C	Total	0.11	0.17	0.09	0.05	0.09	0.08
	Direct	0	0	0	0	0	0
	Indirect	0.11	0.17	0.09	0.05	0.17	0.08

^a Standardized regression weight (β); ^b Unstandardized regression weight (B)

No competing interests reported.

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The Influencing Factors of Self-evaluation in Adolescents: A Structural Equation Modeling

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