Correlations Between Social Support and Loneliness, Self-Esteem, and Resilience Among Left-Behind Children in Mainland China: A Meta-Analysis

Background: Social support is frequently reported to be correlated with loneliness, self-esteem, and resilience among left-behind children in mainland China. However, to date, there is no consensus on the extent to which those factors are correlated with social support among left-behind children. We thus performed a meta-analysis to quantitatively synthesize the previous findings.

Methods: Two investigators systematically and independently searched PubMed, EMBASE, Web of Science, PsycINFO, Wan Fang, Chinese National Knowledge Infrastructure (CNKI) and China Science Technology Journal Database (VIP) on January 9, 2022. Pooled Pearson's correlation coefficients between social support and loneliness, self-esteem, and resilience were calculated by Stata 16.0 software using random effects model.

Results: Forty-seven studies involving a total of 30 212 left-behind children were identified. A large degree of negative correlation was found between social support and loneliness [summary r: −0.36 (95% CI: −0.42– −0.30), p < 0.001]. Large positive correlations were found between social support and self-esteem, and resilience [self-esteem: summary r: 0.33 (95% CI: 0.24–0.41), p < 0.001; resilience: summary r: 0.45 (95% CI: 0.38–0.50), p < 0.001]. The pooled correlations revealed some discrepancies when stratified by some moderators. Sensitivity analysis also revealed the robustness of the findings. The Egger regression and Duvall and Tweedle trim-and-fill procedure suggest the absence of publication bias.

Conclusion: The current meta-analysis provided solid evidence that social support has a high degree of negative correlation with loneliness and a high degree of positive correlation with self-esteem and resilience among left-behind children in mainland China. This indicated that left-behind children with high levels of social support tend to have lower levels of loneliness and higher levels of self-esteem and resilience. More studies, especially large prospective studies, are warranted to verify our findings.

Introduction

Since China's economic reform and opening up in the 1980's, with the rapid economic development and industrialization, a growing number of rural middle-aged and young labor force have migrated to work in the country's main cities in order to improve their family's economic conditions. China has experienced the largest internal migration in human history (1). Due to the high cost of living and education in cities, as well as the limitations of China's dual urban-rural household registration system, many migrant workers are forced to keep their children in the household registration area and entrust their care to family members (usually grandparents), resulting in the formation of a unique group of children known as “left behind children” (LBC). LBC refers to children under the age of 18 who have to stay in their hometown due to one or both parents going out to work, and are supervised by one parent and/or grandparents, relatives, neighbors for more than 6 months (2). In 2018, the Ministry of Civil Affairs of China conducted a survey on left-behind children, which revealed that China's total number of left-behind children had reached a staggering 6.97 million (3). The situation of LBC in China is a major social and health issue that has attracted widespread concern. Many studies show that LBC has more behavioral and psychological problems than non-left-behind children (NLBC) (4–7). Therefore, the study of this group is not only related to their own destiny, but also provides a Chinese perspective for the development of disadvantaged children around the world.

Social support refers to the respect, care and help that individual perceive from social relations around them (such as their family, friends, important others.), which can make individuals avoid or less affected by negative events of stress (8). For the LBC in the family environment with relatively lack of family affection, social support is their coping resources to adapt to the adverse environment (9). Social support has dual effects, namely main effect and buffer effect (10, 11). The first is to enhance the subjective self-evaluation of the individual and mobilize the positive qualities of the individual to improve the ability to adapt to adverse environments, such as improve self-esteem and resilience (12); the second is to directly buffer the impact of stress on the individual and play a protective role in maintaining individual mental health (10).

An increasing amount of evidence has shown that social support is closely related to many detrimental psychological problems of LBC such as loneliness, low levels of self-esteem, and low levels of resilience (13–15). However, there has been no consensus on the extent to which these factors are correlated with social support among LBC so far in mainland China. Specifically, first of all, as for the correlation between social support and loneliness among LBC in mainland China, some studies have found a relatively large negative correlation (14, 16), while others have found a small negative correlation (17, 18). Secondly, regarding the relationship between social support and self-esteem, some studies have found that there was a small positive correlation,while others have found a lager positive correlation (15, 19). Similarly, the strength of identified associations between social support and resilience among LBC in mainland China has varied considerably thus far, ranging from small (r = 0.22) (20) to large (r = 0.75) (21).

Using meta-analysis, the outcomes of several studies can be statistically combined to obtain an overall effect size. However, up to now, no meta-analysis has been conducted on the relationship between social support and loneliness, self-esteem, and resilience among LBC in mainland China. Therefore, the purpose of this study is to conducted 3 meta-analysis to explore the relationship between social support and loneliness, self-esteem, and resilience among LBC in mainland China. The potential existence of publication bias was addressed. Because journals may tend to publish studies with significant results and reject those with non-significant results, this may lead to publication bias; In addition, existing null results that have never been published may lead to overestimation of the relationship between variables (22). Furthermore, subgroup analysis was used to analyze the moderating effects of sampling strategy, sample size, gender, educational stage of children, published type, social support measurement instruments, and the measurement instruments for the three targeted variables in the included studies to evaluate whether the relationships between variables were moderated by demographics and study characteristics.

Materials and Methods

A systematic review and meta-analysis was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (23). Moreover, the review was registered in PROSPERO (registration number: CRD42022304140).

Searching Strategy

The databases PubMed, EMBASE, Web of Science, PsycINFO, Wan Fang database, Chinese National Knowledge Infrastructure (CNKI) and China Science Technology Journal Database (VIP) were searched on January 9, 2022 using the key words “left-behind,” “stay at home,” “child^*,” “adolescent^*” “child^*,” “student^*,” “support,” “social support,” “social network,” “social relation,” “social resource,” “social environment,” “Chinese” and “China.” Finally, appropriate Boolean operators are used to combine these search terms. In addition, Google Scholar and CNKI were used to conduct gray literature search for dissertations that met our inclusion criteria. A detailed search strategy is available in Supplementary File 1. Publication languages were limited to English and Chinese. Reference lists of retrieved studies were scanned for further possible articles.

Selection Criteria

Two investigators independently screened the retrieved literature according to the following inclusion and exclusion criteria: (1) LBC living in China; (2) cross-sectional studies offering Pearson's correlation coefficients for the associations between social support and loneliness, self-esteem, and resilience; (3) social support measurement instruments were limited to the Social Support Rating Scale (SSRS), Social Support Questionnaire (SSQ), Multi-dimensional Scale of Perceived Social Support (MSPSS) and Chinese version Perceived Social Support Scale (PSSS); (4) loneliness measurement instruments were limited to Children Loneliness Scale (CLS), University of California Los Angeles Loneliness Scale (ULS), Mental Health Diagnostic Test (MHT) and Adolescents' loneliness scale (ALS); (5) self-esteem measurement instruments were limited to Self-Esteem Scale (SES) and Collective Self-esteem Scale (CSES); (6) there was no restriction on resilience scales; and (7) published in English or Chinese; The exclusion criteria are as follows: (1) “special” left-behind children, such as orphans or children from single-parent families; (2) conference abstracts and review articles. If more than one paper were published based on the same dataset, we only included the articles using more completed information; and (3) literature with poor quality or apparent data mistakes were also excluded.

Study Selection and Data Extraction

Two researchers (HTH and XW) systematically and independently evaluated the eligibility of the study and extracted data. In case of disagreement during the process, it will be resolved through discussion or consultation with a third researcher (YMD). The following information was extracted: first author, year of publication, geographical area, sampling strategy, sample size, number of males and females, mean age, measurement tool of social support level, instruments used to measure levels of loneliness, self-esteem, and resilience and Pearson's correlation coefficients between social support and the above three variables.

Assessment of the Study Quality

Nine-item Joanna Briggs Institution Critical Appraisal Checklist for Studies Reporting Prevalence Data is used as a quality assessment tool (24). A minor adjustment has been made to the third item of the scale. That is, the appropriate sample size was judged based on Pearson's correlation study design rather than the prevalence study design. The answers to each item include “yes,” “no,” “unclear” and “not applicable.” If the answer is “yes,” the item will receive one point; otherwise, it will receive zero points. The higher the score, the better the quality of the method. The methodological quality of all studies included was independently assessed by two researchers (HTH and YMD). A third author was available for resolving differences (CRC). The results showed that all the included studies were of medium or high quality (total score ≥ 6). See Supplementary File 2 for the specific quality evaluation results.

Statistical Analysis

Stata 16.0 was used for statistical analysis (STATA Corp, College Station, TX). The Pearson product-moment correlation coefficient (r) is used as the effect size of this study. Since the variance is strongly dependent on the correlation, the r coefficient is transformed by the formula into Fisher 'z (25). The sample correlation r is converted into Fisher's Z by formula (1), and the standard error is calculated by formula (2), where n is the sample size. Fisher z statistics are assumed to be normally distributed data, and their 95% confidence intervals are calculated by formula (3). In the end, an inverse transformation was performed to report the results on the scale of the r-coefficient by formula (4). Moreover, since the reference standard for the interpretation of the correlation coefficient suggested by Cohen (26) (r = 0.1 is low correlation, r = 0.3 is moderate correlation and r = 0.5 is strong correlation) is based on qualitative analysis, which is relatively subjective, so this study adopts the suggestions of Gignac and Szodorai, and r = 0.1, r = 0.2 and r = 0.3 represent relatively small, typical, and relatively large correlation (27).

• $Fishe{r}^{{}^{\prime }}sZ=0.5ln\frac{1+r}{1-r}$

• $S_E=\sqrt{1/(n-3)}$

• 95%CI = Z± 1.96(SEz)

• $Summaryr=\frac{e^{2z}-1}{e^{2z}+1}$ (Z=summary Fisher′s Z).

The random-effects model was used for data analysis because it does not assume a common potential effect size for all included studies, making it more suitable than fixed-effects models for meta-analyses based on existing literature (22). The meta-analysis was performed with the Der-Simonian and Laird's method (28), where the weighting of sample size was introduced into the model as the inverse of variance. Heterogeneity was tested by Q statistics and I², which measure whether there are differences between the included studies. In addition, we further tested the probable variables that could moderate the correlations between social support and loneliness, self-esteem, and resilience among LBC by subgroup analysis. Studies were grouped by a few available study characteristics, including sampling strategy, sample size, gender, educational stage of children, published type, social support measurement instruments, and the measurement instruments for the three targeted variables. The Q statistic was also used to test the differences between and within groups of studies.

To assess the impact of individual studies on the summary correlation coefficients and evaluate the robustness of the correlations between social support and loneliness, self-esteem, and resilience, sensitivity analyses were conducted by sequentially omitting one study each turn. Lastly, visual inspection of funnel plots, Egger's linear regression test (29) and Duval and Tweedie's trim-and-fill (30) analysis were performed to help us assess publication bias.

Results

Study Selection and Study Characteristics

Our search strategy identified 1 205 studies without duplicates (Figure 1). There were 975 studies excluded after title and abstract screening. Finally, the full texts of 230 articles were reviewed. We excluded 183 studies for the following reasons: irrelevant purposes (n = 108), conference abstracts or reviews (n = 37), poor quality (n = 7), had insufficient data or not correlation studies (n = 20), had apparent data mistakes (n = 5), or duplicate publications (n = 6). As shown in Table 1, 47 studies ultimately met the inclusion criteria, involving a total of 30 212 LBC in China. Of these 47 studies, 20 reported Pearson's correlation coefficients between social support and loneliness, 14 reported Pearson's correlation coefficients between social support and self-esteem, and 20 reported Pearson's correlation coefficients between social support and resilience.

FIGURE 1

Figure 1. The flow chart of the study selection process.

TABLE 1

Table 1. Characteristics of studies included in the meta-analysis.

The number of LBC involved in the correlations between social support and loneliness, self-esteem, and resilience was 10 305, 8 615, and 11 292, respectively. The results of meta-analysis show that the social support of the LBC in mainland China has a relatively large negative correlation with loneliness (summary r: −0.36 [95% CI: −0.42– −0.30], p < 0.001), and a relatively large positive correlation with self-esteem [summary r: 0.33 (95% CI: 0.24– −0.41), p < 0.001] and resilience [summary r: 0.45 (95% CI: 0.38– −0.50), p < 0.001] (Figures 2–4).

FIGURE 2

Figure 2. Forest plots for the correlation between social support and loneliness. Weights are from random-effects model.

FIGURE 3

Figure 3. Forest plots for the correlation between social support and self-esteem. Weights are from random-effects model.

FIGURE 4

Figure 4. Forest plots for the correlation between social support and resilience. Weights are from random-effects model.

Subgroup Analysis

As shown in Table 2, the summary correlation coefficient between social support and loneliness did not reveal any significant difference when stratified by sample size, gender, education, published type, and social support measurement instrument (all with p > 0.05). However, we found that the summary correlation coefficient for loneliness in studies using random sample were higher than that in studies using non-random sample (random: summary r = −0.44, 95% CI: −0.51– −0.36, p < 0.001; non-random: summary r = −0.32, 95% CI: −0.39– −0.24, p < 0.001; Q_B = 4.81, p < 0.05). Similarly, studies using the ULS-8 measurement tool yielded higher negative correlation than studies using the CLS, MHT, and ALS measurement tools (ULS-8: summary r = −0.45, 95% CI: −0.64– −0.22, p < 0.001; CLS: summary r = −0.38, 95% CI: −0.46– −0.29, p < 0.001; MHT: summary r = −0.33, 95% CI: −0.43–−0.23, p < 0.001; ALS: summary r = −0.19, 95% CI: −0.26– −0.11, p < 0.001; Q_B = 15.08, p < 0.05).

TABLE 2

Table 2. Subgroup analyses of the summary correlation between social support and loneliness among LBC.

As shown in Table 3, subgroup analysis showed that sampling method, sample size, gender, education, publication type, social support measurement tool, and self-esteem measurement tool did not significantly affect the relationship between social support and self-esteem (all with p > 0.05).

TABLE 3

Table 3. Subgroup analyses of the summary correlation between social support and self-esteem among LBC.

The summary correlation coefficient between social support and resilience was substantially changed when stratified by the sample size and measurement instrument for resilience (all with p < 0.05). No difference was observed in subgroup analyses by sampling strategy, gender, education, published type or instrument for social support (all with p > 0.05) (Table 4).

TABLE 4

Table 4. Subgroup analyses of the summary correlation between social support and resilience among LBC.

Sensitivity Analyses

Stability of results was assessed by sequentially excluding one study and then recalculating the pooled correlation coefficient. Sensitivity analyses for summary correlation coefficients between social support and loneliness, self-esteem, and resilience revealed minor changes, indicating that our results were stable (Supplementary File 3).

Publication Bias

Judging subjectively, it was difficult to determine whether the funnel plots for the summary correlation coefficients between social support and loneliness, self-esteem, and relisience were symmetric or not (Supplementary File 4). The Egger linear regression test showed insignificant results (Loneliness: t = −0.51, p = 0.62; Self-esteem:t = 0.23, p = 0.82;Resilience:t = 1.62, p = 0.12). Duval and Tweedle trim-and-fill procedure suggested that no additional research is needed for all three meta-analyses (Supplementary File 5). Taken together, it suggests the absence of publication bias for these meta-analyses.

Discussion

To the best of our knowledge, this was the first meta-analysis exploring the pooled correlation coefficients of social support with loneliness, self-esteem, and resilience among LBC in mainland China. Our results indicated that the social support of the LBC in mainland China has a relatively large negative correlation with loneliness, and a relatively large positive correlation with self-esteem and resilience, with a series of summary Pearson's correlation coefficients of −0.36, 0.33 and 0.45, respectively. The sensitivity analysis results are robust, which indicates that the pooled analysis of correlation coefficients is reliable and convincing. Egger linear regression and Duval and Tweedie's trim-and-fill analysis also show that there is no publication bias in our research results.

According to interactionist theory, loneliness is a response to the lack of satisfactory social networks (68). Social support can fill the gap between social network and social contact needs, thus reducing loneliness (69). Research by Ayalon, Shiovitz-Ezra and Palgi suggests that the frequency, content and meaning of social interactions have a significant impact on loneliness (70). The effect of social support on loneliness is also likely to be mediated by other variables, not just directly. Evidence has shown that the association between social support and loneliness could be mediated by gratitude (71). According to the broaden-and-build theory of positive emotions, gratitude as a positive emotion helps individuals to expand their cognitive schema, enhance the flexibility of activities, construct personal psychological and social resources, and eliminate the negative effects of negative emotions (72). Individuals with higher social support levels have more positive emotional experiences such as gratitude, which reduces their loneliness. Interestingly, there is also evidence that psychopathology in turn affects social support (73). The social selection model believes that healthy individuals are more likely to obtain good social relationships, experience more social support, and have more positive evaluations of themselves, others, and the world (74), which may increase individuals' gratitude to others and stimulate others' willingness and behavior to further support individuals (75), thus enabling individuals to experience more social support. Adolescence is a transitional stage from children to adults, when individuals face more psychological conflicts and pressures (32). On the one hand, the psychological sense of adulthood caused by teenagers' physiological maturity coexists with naivety in reality, which makes it easy for teenagers to experience psychological conflicts; On the other hand, adolescent individuals begin to assume some adult roles and obligations (32). This change of social role makes them pay attention to the practical problems of future development, such as further education and employment, and bear great pressure from family, school and society. For LBC who are in the background of relative lack of parental affection, the psychological conflicts and pressures they experience may be more serious than those of ordinary teenagers, so they are more likely to have psychological problems (76). LBC is more prone than NLBC to experience psychological difficulties such as loneliness, according to studies (76). Our findings suggest that there is a substantial negative relationship between social support and loneliness among LBC, and that enhancing social support for these children can help them feel less lonely. As a result, establishing a proper social support system for the mental health development of the LBC is critical.

Consistent with previous literature, self-esteem was positively correlated with social support. Adela's research found that social support is beneficial to improve an individual's self-esteem (77). Rosenberg also put forward a similar point of view, he believed that self-esteem is the result of social support, in adolescence, a harmonious social environment has a very important role in the maintenance of self-esteem (78). Yarcheski's study of 165 adolescents aged 15–17 found that the correlation between social support and self-esteem was 0.30 (79); in 1997, they reported a correlation of 0.38 (80). For LBC in an unfavorable growing environment, they may not be able to receive timely support and affirmation from their parents like NLBC. This kind of support is not satisfied for a long time, which will lead to the LBC often denying themselves, having a low evaluation of self-worth and developing a low self-esteem personality (44). Studies have shown that compared with NLBC, LBC show lower self-esteem (81). The positive correlation between social support and self-esteem reveals that for the LBC who lack parental care, increasing social support may be an effective strategy to help LBC enhance their positive self-identity and improve their self-esteem.

The results of the meta-analysis show that social support is positively correlated with resilience, which is consistent with the results of previous study (82). The resilience is the psychological function that an individual can keep or return to normal after experiencing adversity or trauma (83). It is a successful “self-adjustment mechanism” response and an important protective element against emotional and behavioral issues in adolescents (84). The main effect model of social support believes that social support has a general positive effect, no matter what the current level of social support is, as long as social support increases, it will inevitably lead to the improvement of individual health status (85). In addition, the positive correlation between the two is also consistent with the prediction of the protective-protective model, that one protective factor enhances the effect of another protective factor (86). Research shows that the ability of LBC to adapt to the difficulties such as lack of parental affection, insufficient family education and limitation of intergenerational rearing is related to psychological resilience (87). This suggests that we should provide a good social support environment for the children who have been left behind. LBC can gain problem-solving skills and experience from family, friends, schools and other outsiders by establishing a safe and friendly relationship with others, which will have a positive effect on their psychological resilience, thus effectively buffering the influence of external harmful factors.

Moderating effect analysis showed that sampling methods and loneliness measurement tools may moderate the relationship between social support and loneliness. The former suggests that the quality of research design may affect the relationship between the two, and more accurate conclusions may be obtained by using random sampling methods. The latter may be due to the lack of included literature in some subgroups (e.g., the ULS-8 and ALS groups included only 2 and 1 articles, respectively). Subgroup analysis by sample size showed that the summary social support-resilience correlation coefficients were higher in smaller sample size studies than in larger sample size studies (summary r: 0.51 vs. 0.39, p <0.01) (Table 3). Studies with larger sample sizes may be more representative and more likely to yield reliable results. Resilience measurement tools may also regulate the relationship between social support and resilience, which may also be related to the lack of literature in some groups (for example, CYRM-28 group only contains one literature).

Limitations and Future Implications

When interpreting the results of the current study, several limitations must be kept in mind. First, to reduce the potential source of heterogeneity, social support measurement tool was restricted to the SSRS, SSQ, MSPSS, and PSSS. Similarly, measurement tool for loneliness was restricted to the CLS, ULS, MHT and ALS; the measurement instrument for self-esteem was restricted to the SES and CSES. As a result, the article included in this meta-analysis was limited. In the future, after the paper is further enriched, it is necessary to further explore the research using other measurement tools. Second, in our search strategy, only a few commonly used databases were searched, which may lead to certain publication bias. Future research can increase the number of retrieval databases, such as Scopus, EBSCO, Springer link, The Cochrane library, to minimize the risk of bias in research results. Third, in view of the limited number of studies included, subgroup analysis based on some moderators should be carefully interpreted to some extent. In addition, even after subgroup analysis, the aggregate correlation coefficient still has substantial heterogeneity. Other possible influencing factors such as pre-existing illness, personality, comorbidity, lifestyle, and living conditions might also account for this correlation. Unfortunately, because the effect size is Pearson correlation coefficient rather than partial correlation coefficient, the correlation between social support and the three clinical variables is calculated without adjusting the related variables. Few studies conducted stratified Pearson's correlation analysis according to these variables. Future research can further focus on other variables (such as personality, living conditions.) that may directly affect social support and loneliness, self-esteem, and resilience in Chinese LBC, so as to provide clearer intervention ideas for future mental health research. Finally, the articles included in this study are all cross-sectional studies, and no judgment can be made on the causal relationship between variables. Therefore, more longitudinal studies are still needed in the future to test the causal relationship between social support and loneliness, self-esteem, and resilience.

Conclusion

Despite the limitations mentioned above, all available evidence supports that the social support of the LBC in mainland China has a relatively large negative correlation with loneliness, and a relatively large positive correlation with self-esteem and resilience. Their summary Pearson's correlation coefficients were −0.36, 0.33 and 0.45, respectively. This means that left-behind children in mainland China with high levels of social support are more likely to have lower levels of loneliness and higher levels of self-esteem and resilience. More studies, especially large prospective studies with long follow-up periods, are warranted to verify our findings.

Data Availability Statement

The data analyzed in this study is subject to the following licenses/restrictions: The datasets presented in this study are available from the authors upon reasonable request. Requests to access these datasets should be directed to HH, huangtaomiss@163.com.

Author Contributions

HH and XW: study design, critical revision of the manuscript, and drafting of the manuscript. YL, YZ, QP, YD, GL, and CC: analysis and interpretation of data. All authors approval of the final version for submission.

Funding

This research was sponsored by Graduate Education Reform and Quality Improvement Project of Henan Province (Grant Number: YJS2021AL074), Graduate Education Innovation and Quality Improvement Project of Henan University (Grant Number: SYL19060141), and Planning and Decision Consultation Project of Henan Province (Grant Number: 2018JC38).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2022.874905/full#supplementary-material

Supplementary File 1. Search strategy.

Supplementary File 2. Quality assessment form for included studies.

Supplementary File 3. Sensitivity analyses of correlations between social support and loneliness, self-esteem, and resilience.

Supplementary File 4. Funnel plot of correlations between social support and loneliness, self-esteem, and resilience.

Supplementary File 5. Duval and Tweedle trim-and-fill procedure of correlations between social support and loneliness, self-esteem, and resilience.

Supplementary File 6. PRISMA Checklist.

References

1. Wen YJ, Hou WP, Zheng W, Zhao XX, Wang XQ, Bo QJ, et al. The neglect of left-behind children in china: a meta-analysis. Trauma Violence Abus. (2021) 22:1326–38. doi: 10.1177/1524838020916837

PubMed Abstract | CrossRef Full Text | Google Scholar

2. Duan CR, Zhou FL. A study on children left behind (in Chinese). Popul Res. (2005) 01:29–36.

PubMed Abstract | Google Scholar

3. Ministry of Civil Affairs of the People's Republic of China. Chart: Data of Left-Behind Children in Rural Areas in 2018. (2018). Available online at: http://www.mca.gov.cn/article/gk/tjtb/201809/20180900010882.shtml (accessed February 10, 2022).

Google Scholar

4. Fellmeth G, Rose-Clarke K, Zhao C, Busert LK, Zheng Y, Massazza A, et al. Health impacts of parental migration on left-behind children and adolescents: a systematic review and meta-analysis. Lancet. (2018) 392:2567–82. doi: 10.1016/S0140-6736(18)32558-3

PubMed Abstract | CrossRef Full Text | Google Scholar

5. Adhikari R, Jampaklay A, Chamratrithirong A, Richter K, Pattaravanich U, Vapattanawong P. The impact of parental migration on the mental health of children left behind. J Immigr Minor Healt. (2014) 16:781–9. doi: 10.1007/s10903-013-9809-5

PubMed Abstract | CrossRef Full Text | Google Scholar

6. Cheng J, Sun YH. Depression and anxiety among left-behind children in China: a systematic review. Child Care Health Dev. (2015) 41:515–23. doi: 10.1111/cch.12221

PubMed Abstract | CrossRef Full Text | Google Scholar

7. Tomsa R, Jenaro C. Children left behind in romania: anxiety and predictor variables. Psychol Rep. (2015) 116:485–512. doi: 10.2466/10.17.PR0.116k19w1

PubMed Abstract | CrossRef Full Text | Google Scholar

8. Alloway R, Bebbington P. The buffer theory of social support–a review of the literature. Psychol Med. (1987) 17:91–108. doi: 10.1017/S0033291700013015

PubMed Abstract | CrossRef Full Text | Google Scholar

9. Chen ZX, Wang H, Feng YX, Liu X. The effect of peer victimization on left-behind adolescents subjective well-being: the role of self-esteem and social support (in Chinese). Psychol Dev Educ. (2020) 05:605–14.

Google Scholar

10. Callaghan P, Morrissey J. Social support and health: a review. J Adv Nurs. (1993) 18:203–10. doi: 10.1046/j.1365-2648.1993.18020203.x

PubMed Abstract | CrossRef Full Text | Google Scholar

11. Zelkowitz P. Social support and aggressive behavior in young children. Fam Relat. (1987) 16:129–34. doi: 10.2307/583941

CrossRef Full Text | Google Scholar

12. Liu DW, Zhou YQ, Li GH. Social support and schizophrenia disability: the chain mediating role of self esteem and resilience (in Chinese). Chin J Clin Psychol. (2019) 27:78–82.

Google Scholar

13. Wu WC, Chen C, When KS, Luo L. Relationship between loneliness and social support of the rural left-behind children in chaoshan area (in Chinese). Health Psychol. (2010) 18:1220–1122.

Google Scholar

14. Ai H, Hu J. Psychological resilience moderates the impact of social support on loneliness of “left-behind” children. J Health Psychol. (2016) 21:1066–73. doi: 10.1177/1359105314544992

PubMed Abstract | CrossRef Full Text | Google Scholar

15. Cheng FS, Zhou XQ, Xiang R, Zhang L, Li J. Effect of social support as medium in the process of attachment styles and self-esteem on Chinese left-behind children (in Chinese). China J Health Psychol. (2020) 28:733–6.

Google Scholar

16. Kong XJ, Liu Y, Zhang J. Intermediary role of social supports between loneliness and deliberate self-harm in rural left-home children (in Chinese). Chin J Sch Doct. (2016) 12:134–8.

Google Scholar

17. Chen YH, Qi JL, Zhang Y. The characteristics of mental health and social support of rural left-behind children in middle school (in Chinese). J Qiqihar Med University. (2014) 35:1350–4.

Google Scholar

18. Zeng R. A study on the relationship between mental health and social support among left-behind junior high school students (in Chinese). J Henan Institute of Education. (2011) 30:44–7.

Google Scholar

19. Ma WY, Gao P, Huang DW. The relationship between perceived social support and subjective well being of left behind adolescents: the chain mediating effect of self-esteem and resilience (in Chinese). J Guizhou Educ University. (2021) 37:14–22. doi: 10.13391/j.cnki.issn.1674-7798.2021.06.003

CrossRef Full Text | Google Scholar

20. Lin SX, Bai S. A study on the relationship between psychological resilience and social support of left-behind children and non-left-behind children (in Chinese). Modern Vocat Educ. (2016) 28:5–7.

Google Scholar

21. Niu Y. A Study on the Relationship Between Psychological Resilience and Perceived Social Support in Left-Behind Children and an Intervention Study(in Chinese). Nanjing: Nanjing Normal University (2014).

Google Scholar

22. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to Meta-Analysis. New Jersey: John Wiley & Sons (2021).

Google Scholar

23. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. (2009) 6:e1000097. doi: 10.1371/journal.pmed.1000097

PubMed Abstract | CrossRef Full Text | Google Scholar

24. Munn Z, Moola S, Lisy K, Riitano D, Tufanaru C. Methodological guidance for systematic reviews of observational epidemiological studies reporting prevalence and cumulative incidence data. Int J Evid Based Healthc. (2015) 13:147–53. doi: 10.1097/XEB.0000000000000054

PubMed Abstract | CrossRef Full Text | Google Scholar

25. Ruiz-Cárdenas JD, Rodríguez-Juan JJ, Ríos-Díaz J. Relationship between jumping abilities and skeletal muscle architecture of lower limbs in humans: systematic review and meta-analysis. Hum Mov Sci. (2018) 58:10–20. doi: 10.1016/j.humov.2018.01.005

PubMed Abstract | CrossRef Full Text | Google Scholar

26. Cohen J. Statistical Power Analysis for the Behavioral Sciences. London: Routledge. (2013).

PubMed Abstract | Google Scholar

27. Gignac GE, Szodorai ET. Effect size guidelines for individual differences researchers. Pers Indiv Differ. (2016) 102:74–8. doi: 10.1016/j.paid.2016.06.069

CrossRef Full Text | Google Scholar

28. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. (1986) 7:177–88. doi: 10.1016/0197-2456(86)90046-2

PubMed Abstract | CrossRef Full Text | Google Scholar

29. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ. (1997) 315:629–34. doi: 10.1136/bmj.315.7109.629

PubMed Abstract | CrossRef Full Text | Google Scholar

30. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. (2000) 56:455–63. doi: 10.1111/j.0006-341X.2000.00455.x

PubMed Abstract | CrossRef Full Text | Google Scholar

31. Liu X, Hu XX, Shen JL. The influence of different sources of social support on the loneliness of rural left-behind children (in Chinese). J Henan University. (2008) 01:18–22. doi: 10.15991/j.cnki.411028.2008.01.017

CrossRef Full Text | Google Scholar

32. Zhao J X, Liu X, Shen JL. The relationship between the social support network of left-behind adolescents and their depression and loneliness——based on the perspective of variable center and individual center (in Chinese). Psychol Dev Educ. (2008) 01:36–42.

Google Scholar

33. Du X. A study on the relationship between social support, life satisfaction and mental health of rural left-behind junior high school students (in Chinese). Sci Educ Article Collects. (2009) 12:234–7.

Google Scholar

34. Li YX, Luo PC, Nie GH. The impact of personality characteristics and social support on resilience of left-behind children. J Henan University. (2009) 46:127–30. doi: 10.15991/j.cnki.411028.2009.06.016

CrossRef Full Text | Google Scholar

35. Li ZK. The relationship between mental resilience and social support of left-behind children (in Chinese). China J Health Psyc. (2009) 17:442–6.

Google Scholar

36. Liu M. Research on Perceived Social Support Affecting the Social Adaptation of Left-Behind Junior High School Students (in Chinese). Chongqing: Southwest University (2009).

Google Scholar

37. Chen HH, Liu QL, Huang BS. Study on the social -support and peer relationships impact on psychological resilirnce among the left -behind children in rural area (in Chinese). Modern Prev Med. (2011) 38:3219–24.

Google Scholar

38. Wu WC, Chen C, Fu RJ. A study on relationship between children's self-esteem and social support of the rural left-behind children in chaoshan area. J Hanshan Normal University. (2012) 33:04–7.

Google Scholar

39. Wang S. A Study on the Relationship Between Loneliness, Personality Characteristics and Social Support of Left-Behind Children (in Chinese). Qinghai: Qinghai Normal University (2012).

Google Scholar

40. Li ZZ, Guo Y. Study of relationship between social support and mental health of left-behind children in rural area (in Chinese). J Taiyuan Normal University. (2013) 12:131–3.

PubMed Abstract | Google Scholar

41. Zhou YH, Lv CF, Xu FG. On the relationship between left-at-home rural children's resilience and mental Health (in Chinese). Chinese J Special Educ. (2013) 10:52–9.

Google Scholar

42. Chen MF, Chen DY, Yan DJ. Resarch on relationship between social support and mental health on overseas left–behind children (in Chinese). Psychol Res. (2014) 07:63–7.

Google Scholar

43. Zhao JX, Liang J, Liu X. Left-at-home-adolescents' perception of social support networks and their relevance to individual self-esteem and social initiative: variable-centered and person-centered perspectives (in Chinese). Psyc Sci. (2008) 4:827–31 doi: 10.16719/j.cnki.1671-6981.2008.04.053

CrossRef Full Text | Google Scholar

44. Chen A, Zhao ZZ. The correlation between self-esteem and social support of left -behind children (in Chinese). China J Health Psychol. (2015) 23:993–6. doi: 10.13342/j.cnki.cjhp.2015.07.011

CrossRef Full Text | Google Scholar

45. Yue SH, Lu X J. Comparison of social support and loneliness among left-behind children in eastern and western China (in Chinese). Chin J School Health. (2015) 36:1662–4. doi: 10.16835/j.cnki.1000-9817.2015.11.023

CrossRef Full Text | Google Scholar

46. Zhao Y. The relationship between social support and mental health of left-behind children: the mediating effect of mental toughness (in Chinese). Educ Meas Eval. (2015) 12:53–7.

Google Scholar

47. Xiao F, Zhang Q. Research on the relationship between social support and loneliness of left-behind children in rural areas——taking Jiangxi Province as an example (in Chinese). J Pingxiang University. (2015) 32:110–3.

Google Scholar

48. Xiao M. The Research on the Situation and Relationship Among Social Support, Resilience and Social Adjustment of Left-Behind Children (in Chinese). Guangxi: Guangxi Normal University (2015).

Google Scholar

49. Ma WX, Yu Y. The relationship between social support and psychological resilience among rural left-behind middle school students: the mediating effect of self-esteem (in Chinese). J Guizhou Education University. (2016) 32:116–20.

Google Scholar

50. Fu WQ. The influence of discrimination perception of left behind children in junior high school on the problem behavior: the chain mediating effect of self-esteem and social support (in Chinese). J Schooling Stud. (2017) 14:96–103.

Google Scholar

51. Ji YY, Zhang Y, Yin F, Yang SJ, Yang Y. Liu QL. The prevalence of depressive symptoms and the relationships between depressive symptoms, self-esteem and social support among rural left-behind children in Sichuan province (in Chinese). Modern Prev Med. (2017) 2:239–42.

Google Scholar

52. Liu X. A study on the relationship between self concept of social support and mental health of left behind junior high school students (in Chinese). Contemporary Educ Res Teach Practice. (2017) 12:342–5.

Google Scholar

53. Man Y, Mengmeng L, Lezhi L, Ting M, Jingping Z. The psychological problems and related influential factors of left-behind adolescents (LBA) in Hunan, China: a cross sectional study. Int J Equity Health. (2017)16:163–7. doi: 10.1186/s12939-017-0639-2

PubMed Abstract | CrossRef Full Text | Google Scholar

54. Qiao Y. A Study on the Influence of Social Support on the Psychological Elasticity of Left - Behind High School Student (in Chinese). Yunnan; Yunnan Normal University. (2017).

Google Scholar

55. Liu S J, Chen F. Investigation on the status quo of self-esteem and social support of left behind children in Guizhou (in China). Education Forum. (2018) 11:63–7.

Google Scholar

56. Shen J. A Study on the Loneliness and Its Social Support of the Left-behind Children in Senior Grade of Primary School (in Chinese). Liaoning: Liaoning Normal University (2018).

Google Scholar

57. Fan X, Lu M. Testing the effect of perceived social support on left-behind children's mental well-being in mainland China: the mediation role of resilience. Child Youth Serv Rev. (2020) 109:104695. doi: 10.1016/j.childyouth.2019.104695

CrossRef Full Text | Google Scholar

58. Yu L, Xiang BA. Relationship of social support, resilience and general self-efficacy of left-behind children (in Chinese). J Wuhan Eng Inst. (2019) 31:69–72.

Google Scholar

59. Fang H. Study on the Relationship Between Mental Health, Psychological Resiliency and Social Support of Left-Behind Children (in Chinese). Shenzhen: Shenzhen University (2019).

Google Scholar

60. Fan X. Comparative Analysis of Social Support and Self-Esteem of Left-Behind Children (in Chinese). Guizhou: Guizhou Normal University (2020).

Google Scholar

61. Hua R, Liu X, Zhang H, Liu Y, Zhu ZQ. A study on loneliness and related research of 2188 left-behind children in the Midwest (in Chinese). Psychol Monthly. (2020) 15:27–8. doi: 10.19738/j.cnki.psy.2020.15.010

CrossRef Full Text | Google Scholar

62. Li M, Ren Y, Sun H. Social anxiety status of left-behind children in rural areas of hunan province and its relationship with loneliness. Child Psychiatry Hum Dev. (2020) 51:1016–24. doi: 10.1007/s10578-020-01045-x

PubMed Abstract | CrossRef Full Text | Google Scholar

63. Yang D. Study on the Psyehological Resilience and Influencing Factors of Left-Behind Children” in Longyang District,Baoshan City (in Chinese). Yunnan: Yunnan Normal University (2020).

Google Scholar

64. Wang CH. A Study on the Relationship and Intervention Between Social Support, School Belonging and Resilience of Left-Behind Children in Higher Grade of Primary School (in Chinese). Hebei: Hebei University (2020).

Google Scholar

65. Ge AR, Liu Q. The relationship between children's resilience to study and social support (in Chinese). J Zunyi Normal University. (2020) 22:157–60.

Google Scholar

66. Huang H, Chen J, Wang Q. The relationship between social support and social adaptation of rural left-behind children: the mediating role of self-esteem (in Chinese). China J Health Psychol. (2021) 36:151–6.

Google Scholar

67. Fan ZY, Fan XH. Effect of social support on the psychological adjustment of chinese left-behind rural children: a moderated mediation model. Front Psychol. (2020) 11:604397. doi: 10.3389/fpsyg.2020.604397

PubMed Abstract | CrossRef Full Text | Google Scholar

68. Liu D, Brown BB. Self-disclosure on social networking sites, positive feedback, and social capital among Chinese college students. Comput Hum Behav. (2014) 38:213–9. doi: 10.1016/j.chb.2014.06.003

CrossRef Full Text | Google Scholar

69. Kuhirunyaratn P Pongpanich S Somrongthong R Love EJ Chapman RS. Social support among elderly in Khon Kean Province, Thailand. Southeast Asian J Trop Med Public Health. (2007) 38:936–46.

Google Scholar

70. Ayalon L, Shiovitz-Ezra S, Palgi Y. Associations of loneliness in older married men and women. Aging Ment Health. (2013) 17:33–9. doi: 10.1080/13607863.2012.702725

PubMed Abstract | CrossRef Full Text | Google Scholar

71. He AM, Hui QH, Liu H. Relationship between social support and loneliness in undergraduates: the mediating role of gratitude. Chin J Clin Psychol. (2015) 23:150–3. doi: 10.16128/j.cnki.1005-3611.2015.01.034

CrossRef Full Text | Google Scholar

72. Fredrickson BL. The role of positive emotions in positive psychology. The broaden-and-build theory of positive emotions. Am Psychol. (2001) 56:218–26. doi: 10.1037/0003-066X.56.3.218

PubMed Abstract | CrossRef Full Text | Google Scholar

73. Kaniasty K, Norris FH. Longitudinal linkages between perceived social support and posttraumatic stress symptoms: sequential roles of social causation and social selection. J Trauma Stress. (2008) 21:274–81. doi: 10.1002/jts.20334

PubMed Abstract | CrossRef Full Text | Google Scholar

74. Zhou X, Wu X, Chen J. Longitudinal linkages between posttraumatic stress disorder and posttraumatic growth in adolescent survivors following the Wenchuan earthquake in China: a three-wave, cross-lagged study. Psychiatry Res. (2015) 228:107–11. doi: 10.1016/j.psychres.2015.04.024

PubMed Abstract | CrossRef Full Text | Google Scholar

75. Bartlett MY, DeSteno D. Gratitude and prosocial behavior: helping when it costs you. Psychol Sci. (2006) 17:319–25. doi: 10.1111/j.1467-9280.2006.01705.x

PubMed Abstract | CrossRef Full Text | Google Scholar

76. Fang F, Biao S. Absence of parental upbringing and liushou children's personality, academic achievements as well as behavior problems (in Chinese). Psychol Sci. (2005) 28:855–7.

Google Scholar

77. Yarcheski A, Mahon NE, Yarcheski TJ. Social support and well-being in early adolescents: The role of mediating variables. Clin Nurs Res. (2001) 10:163–81. doi: 10.1177/C10N2R6

PubMed Abstract | CrossRef Full Text | Google Scholar

78. Rosenberg M, Schooler C, Schoenbach C, Rosenberg F. Global self-esteem and specific self-esteem: Different concepts, different outcomes. Am Sociol Rev. (1995) 12:141–56. doi: 10.2307/2096350

CrossRef Full Text | Google Scholar

79. Yarcheski A, Mahon NE. A causal model of positive health practices: the relationship between approach and replication. Nurs Res. (1989) 38:88–93. doi: 10.1097/00006199-198903000-00003

PubMed Abstract | CrossRef Full Text | Google Scholar

80. Yarcheski A, Mahon NE. Yarcheski TJ. Alternate models of positive health practices in adolescents. Nurs Res. (1997) 46:85–9. doi: 10.1097/00006199-199703000-00005

PubMed Abstract | CrossRef Full Text | Google Scholar

81. Fan XH, Fang XY, Zhang SY, Chen FJ, Huang YS. Mediation of extroversion and self-esteem on relationship between family atmosphere and loneliness in rural parent-absent children (in Chinese). Chin J Clin Psychol. (2014) 22:680–3. doi: 10.16128/j.cnki.1005-3611.2014.04.025

CrossRef Full Text | Google Scholar

82. Ozbay F, Fitterling H, Charney D, Southwick S. Social support and resilience to stress across the life span: a neurobiologic framework. Curr Psychiatry Rep. (2008) 10:304–10. doi: 10.1007/s11920-008-0049-7

PubMed Abstract | CrossRef Full Text | Google Scholar

83. Luthar SS, Cicchetti D, Becker B. The construct of resilience: a critical evaluation and guidelines for future work. Child Dev. (2000) 71:543–62. doi: 10.1111/1467-8624.00164

PubMed Abstract | CrossRef Full Text | Google Scholar

84. Richardson GE. The metatheory of resilience and resiliency. J Clin Psychol. (2002) 58:307–21. doi: 10.1002/jclp.10020

PubMed Abstract | CrossRef Full Text | Google Scholar

85. House JS, Umberson D, Landis KR. Structures and processes of social support. Annu Rev Sociol. (2003) 6:293–318. doi: 10.1146/annurev.so.14.080188.001453

CrossRef Full Text | Google Scholar

86. Fergus S, Zimmerman MA. Adolescent resilience: a framework for understanding healthy development in the face of risk. Annu Rev Public Health. (2005) 26:399–419. doi: 10.1146/annurev.publhealth.26.021304.144357

PubMed Abstract | CrossRef Full Text | Google Scholar

87. He F, Liu QL, Zhou H, Yang Y, Zhang S. Influencing factors of psychological resilience among rural left-behind junior school students in southern Sichuan (in Chinese). Chin J Sch Health. (2011) 32:164–5. doi: 10.16835/j.cnki.1000-9817.2011.02.016

CrossRef Full Text | Google Scholar