Skip to main content

Correlation between private education costs and parental depression in South Korea

Abstract

Background

In Korea, higher education has rapidly grown influenced by sociocultural tradition. Parents invest a significant portion of their household income in their children’s education. Private education has been considered to greatly affect students’ psychology and behavior. However, past research has largely neglected to study parents who pay these costs. Since household income and education level are important determinants of socioeconomic status (SES), education expenditures are likely to cause depressive symptoms. Therefore, the study aimed to investigate the correlation between private education costs and parental depression in South Korea.

Methods

Data were collected from the Korean Welfare Panel Study (KoWePS, 2015, 2018). The sample analyzed consisted of 397 and 337 fathers and 403 and 370 mothers in 2015 and 2018, respectively. The independent variable in this study was the proportion of private education cost. This proportion was calculated by dividing each household’s private education costs by its equivalized household disposable income (EHDI) and multiplying this number by 100. The main dependent variable was parental responses to the Center for Epidemiologic Studies Depression Scale-11 (CESD-11). Using a generalized linear model, we investigated the effects of the proportion of private education cost on parental depression.

Results

The results showed that fathers with higher proportions of private education cost exhibited higher CESD-11 scores compared to fathers with lower proportions cost (moderate: β = 0.419, S. E = 0.164, p = 0.0105; high: β = 0.476, S. E = 0.178, p = 0.0076), indicating that a higher ratio of private education cost may negatively affect depression in fathers. However, there was no discernable correlation between mothers’ CESD-11 scores and the proportion of private education cost (moderate: β = − 0.078, S. E = 0.250, p = 0.7555; high: β = 0.003, S. E = 0.215, p = 0.9882).

Conclusions

These results may be explained by the tendency for fathers to experience greater economic burdens than mothers in patriarchal Korean society.

Peer Review reports

Background

Depression is a widespread mental disorder all over the world. Korea is no exception. In Korea, about 6.7% of the total population suffers from depression [1]. In addition, a significant number of suicide deaths are closely related to depressive disorder [2]. South Korea has a high suicide rate, as it ranks first among the Organization for Economic Cooperation and Development (OECD) countries [3]. Therefore, it is necessary to find and address the factors that lead to depression.

Socioeconomic status (SES) is associated with an increased likelihood of depressive symptoms. Among the components of SES, household income is related to depressive symptoms, in both adults and adolescents [4, 5]. Academic success is closely related to social status, as education levels play an important role in defining the social class in Korean society [6]. Education levels reflect an important aspect of SES and are closely related to prestigious jobs [7]. Since household income and education level are important determinants of SES, education expenditures are likely to cause depressive symptoms.

Especially in Korea, higher education has grown rapidly with socio-cultural tradition (Confucian tradition), western educational ideas, and rapid economic growth [8]. Marginson proposes four elements that have developed educational needs in East Asia in relation to Confucian traditions: (1) strong nation-state policy (2) tertiary education funded by households (3) ‘one-chance’ national exams (4) public investment in research universities. These characteristics show that Confucian traditions have systematically influenced the development of higher education [9]. Koreans’ enthusiasm for education was an important factor not only to develop the national economy but also to expand higher education in the country [10]. In a strong desire to educate their children, parents invest a significant portion of their household income in their children’s education These phenomena have led to the development of education, but there have also been problems such as excessive education and shadow education [11, 12].

In South Korea, there is a strong interest in private education. Korean parents make substantial investments in private education to increase their children’s academic achievement. Parental obsession and dedication for their children’s educational and social success have been widely discussed in academic articles and media reports both in and outside Korea [13]. According to a Private Education Expenditures Survey 2018 conducted by Statistics Korea, the average monthly private education expenses per student in Korea is 291,000 Won (about 249 dollars) and it is generally increasing every year. If the figure is adjusted to account for 73% of students, excluding those without private education costs, spending increases to 399,000 Won (about 342 dollars) per student. The total cost of private education in 2018 increased by 4.4% compared to last year. Private education costs in Korea are high enough to account for 7.7% of households’ total consumption expenditure [14]. Since households’ total consumption expenditure also includes households without children, the proportion of private education costs for households with children should be higher. While many students are receiving private education to improve their academic performance, private education costs differ by household income. According to a Private Education Expenditures Survey 2018, the higher the average monthly household income, the higher the private education costs and participation rate [14]. Since private education affects a student’s academic performance, parents could be concerned about private education and household income. Thus, it is crucial to understand how private education affects households. Affected targets are largely divided into children and parents.

Private education in South Korea has adverse effects from excessive parental urgency, private education costs, and private tutoring methods [15]. There have been some studies on how private education has affected students. Private tutoring increase student’s academic stress and the increase in private education is likely to lead to depression in the children of the poor due to the burden of education costs, poor academic performance, academic achievement, and stress [16, 17]. The previous study has also shown that participation time in private education has an indirect impact on depression through academic stress and academic achievement [17]. The link between student depression and parental depression has also been analyzed in earlier research [18].

However, there are not enough amount of studies on how private education affects parents. Most extant studies exploring the relationship between private education and parents focus on parent’s participation in education [19,20,21]. In addition to the economic burden, private education is a burden for parents in the process of checking better private tutoring options and interacting with private tutors [20, 22]. As demonstrated before, household income and education level are important determinants of SES, so education expenditures are likely to cause depressive symptoms. Therefore, this study aimed to investigate the correlation between private education costs and parental depression in South Korea.

Methods

Design

We collected data from the 2015 and 2018 outcomes of the Korean Welfare Panel Study (KoWePS), which is a nationwide annual study that provides reliable data on Korean households. Approximately 50% of the KoWePS sample consisted of individuals in low-income brackets with less than 60% median income; thus, the survey was for low-income policy and poverty research. The survey investigated household information (general information, health, medical care, economic status, social insurance, retirement pension, housing, living conditions, living expenses, and income) and household member information (social insurance, labor, living conditions, private education, and mental health). Since a supplementary children’s survey was administered to the same respondents in a three-year cycle, we used data from 2015 and 2018 for families with children in elementary school 4th–6th grades in 2015 and middle school 1st–3rd grade in 2018 according to Korean education course. We built our dataset by linking parent survey responses with household income and children’s survey responses.

Participants

The KoWePS 2015 and 2018 surveyed 13,647 and 12,469 participants, respectively. The number of children surveyed in 2015 and 2018 with the Supplementary Children’s Survey was 471 and 402, respectively. We added parental response data to the children’s response data table and separated the fathers’ and mothers’ variables to test the hypothesis. Since men are usually financially responsible in Korea society, father and mother were studied separately [23]. Each child’s information was combined separately with their fathers’ and mothers’ information in two distinct analyses. The following participants’ data were excluded. First, children with only one parent were excluded, in order to eliminate the impact of differences in financial burdens. Second, participants who failed to complete the questionnaires were also excluded. The analyzed sample consisted of 292 and 254 fathers in 2015 and 2018 and 179 and 177 mothers in 2015 and 2018, respectively, as seen in Fig. 1.

Fig. 1
figure1

Flow diagram displaying the inclusion and exclusion of subjects

Variables

In this study, the independent variable was the proportion of private education cost, which was calculated by dividing household private education costs by the EHDI (Equivalized household disposable income) and multiplying this number by 100.

$$ The\ proportion\ of\ private\ education\ co\mathrm{s}t=\frac{Private\ education\ cost}{Equivalized\ household\ disposable\ income}\times 100 $$

Disposable income is one of the main indicators used to measure the overall economic status of households, and it is the widely used indicator of welfare level [24]. To calculate disposable income, market income and public transfer income were summed, and public transfer expenditure was subtracted [25, 26].

$$ Market\ income+ Public\ transfer\ income- Public\ transfer\ expenditure= Household\ disposable\ income. $$

EHDI was calculated using the following formula because changes in the number of household members can affect results. This formula provides an adequate comparison of disposable income between various members and households [25,26,27].

$$ \mathrm{E} quivalised\ Household\ disposable\ income=\frac{\ Household\ disposable\ income}{\sqrt{Number\ of\ household\ member(s)}} $$

After calculating the proportion of private education cost, we divided the sample into three groups (low, mid, or high) according to the tertiles.

The main dependent variable was parental responses to the Center for Epidemiologic Studies Depression Scale-11 (CESD-11). The Center for Epidemiological Studies Depression Scale (CESD) developed by Radloff was originally a 20-item self-report index of depressive symptoms designed for the use in large-scale surveys. CESD is a reliable and well-validated instrument for screening depression signs and symptoms in the elderly of all kinds of linguistic, racial, aging, and health status cohort of the population [28, 29]. CESD has four relatively invariant factors that are readily interpretable as Depressed Affect (being blues, depressed, lonely, failure, fearful, cry, or sad); Positive Affect (as good as others, felt hopeful, happy, or enjoyed life); Somatic Problems (having been bothered, appetite, trouble, effort, sleep, talked less, or could not get going); and Interpersonal Problems (feeling unfriendly, or dislike) [30].

Parental depression was measured using the CESD-11, a shortened version of the 20-item CESD. The factor structure of CESD-11 has the same four factors as those in the original CESD [31]. According to a survey conducted by KoWePS, Depressed Affect includes item 3, 6, and 9; Positive Affect includes item 2 and 7; Somatic Problems includes item 1, 4, 5, and 11; and Interpersonal Problems includes item 8 and 10. Response categories were ‘ Rarely or none of the time (Less than 1 day in last week) ‘, ‘ Some of the time (1–2 days in last week) ‘, ‘ Much of the time (3–4 days in last week)’, and ‘ Most or all the time (5-7 days in last week). The score was constructed following the guidelines of KoWePS. The number of the response became the score of each item. For Positive Affect (item 2, 7), the score was converted into ‘5-number’ (scores: 1 → 4, 2 → 3, 3 → 2, 4 → 1). The total score was calculated by adding the scores for all questions and multiplying the value by 20/11. Depression was diagnosed in individuals who reported CESD-11 scores above 16 [32]. The values of Cronbach’s α are 0.81 for CESD-11 compare to 0.86 for CESD [33]. Supplementary Table 1 provides basic statistics for participants’ CESD-11. Statistics show that the father’s depression has a positive correlation with the proportion of private education cost, and the father’s depression in 2018 is slightly higher than in 2015.

Other factors affecting parental depression were also assessed. Parents’ socio-demographic factors included age, private educational level (no high school private education or high school academic background), and residence (suburban, urban). Economic variables included household income (low, mid, or high, according to the tertiles) and economic activity (employed and unemployed). Health-related factors included chronic disease (none, diagnosed) and alcohol usage disorder identification test (AUDIT) score (WHO). Psychological factors included the Rosenberg Self-Esteem Scale (RSS) score, cost satisfaction (very low, low, normal, high, and very high), family satisfaction (very low, low, normal, high, and very high), and child satisfaction (very low, low, normal, high, and very high). Factors related to children included children’s grade point average (GPA) (very low or low, normal, and high or very high), children’s study stress (adding the scores of 4 questions with 4 point scale and grouping the points according to the tertiles into low, mid, or high), and children’s Korean Child Behavior Checklist (K-CBCL) scores (low, mid, or high, according to the tertiles) (Rosenberg, 1965; Oh, Lee, Hong, & Ha, 1997). For Table 3, parent’s age grouping was decided according to the tertiles (low, mid, or high) of each year (the dividing point of 2018 is calculated by adding 3 to the dividing point of 2015).

Statistical analysis

To analyze the association between parental depression and the proportion of private education cost, we performed a multiple regression analysis after controlling for covariates. These covariates included the household income, parental age, private education level, working status, residence, RSS scores, AUDIT scores, chronic disease, cost satisfaction, family satisfaction, child satisfaction, children’s GPA, children’s study stress, and children’s K-CBCL scores. Finally, we performed subgroup analyses for the association between the proportion of private education cost and other listed factors, according to parental depression, after adjusting for covariates. Data were analyzed using a log-linear Poisson regression model (SAS Genmod procedure, version 8.1) with generalized linear models. P-values less than 0.05 were considered statistically significant.

Results

Table 1 includes the general characteristics of the study sample after excluding the missing values. Of the sample comprising 292 fathers, the mean CESD score for a low proportion of private education cost (32.2%) was 2.71. The mean CESD score for a moderate proportion of private education cost (34.6%) was 3.46. The mean CESD score for a high proportion of private education cost (33.2%) was 3.66. Of the 179-person mother sample, the mean CESD score for a low proportion of private education cost (31.8%) was 3.03. The mean CESD score for a moderate proportion of private education cost (31.8%) was 3.03. The mean CESD score for a high proportion of private education cost (36.3%) was 3.02.

Table 1 General characteristics of study subjects at 2015 baseline year

Table 2 presents the results of the multiple regression model used to analyze the factors associated with parent’s depression as measured by the CESD. Fathers with higher proportions of private education cost reported higher CESD scores when compared to those with lower proportions of private education cost (moderate: β = 0.419, S. E = 0.164, 95%CI = 0.098 ~ 0.740, p = 0.0105; high: β = 0.476, S. E = 0.178, 95%CI = 0.126 ~ 0.825, p = 0.0076). For mothers, however, the results revealed that there was no correlation between CESD scores and the proportions of private education cost (moderate: β = − 0.078, S. E = 0.250, 95%CI = − 0.568 ~ 0.412, p = 0.7555; high: β = 0.003, S. E = 0.215, 95%CI = − 0.418 ~ 0.425, p = 0.9882).

Table 2 Association between proportion of private education cost to EHDI and depression among parents

Table 3 presents the results of the subgroup multiple regression analyzing the association between parent’s depression and proportions of private education cost according to EHDI. Higher proportions of private education cost significantly increased depression among fathers who lived in households with low EHDI (moderate: β = 1.172, S. E = 0.365, 95%CI = 0.457 ~ 1.887, p = 0.0013; high: β = 1.437, S. E = 0.313, 95%CI = 0.823 ~ 2.051, p < 0.001). There is a blank space in the table because the model did not converge.

Table 3 Results of subgroup analysis by proportion of private education cost to CESD scores according to EHDI

Discussion

This study revealed that as the proportion of private education cost changes, it affects the fathers’ depression levels but not that of the mothers. This suggests that fathers are mostly concerned about their children’s private education costs. Family roles in Korea often dictate fathers to offer financial resources thus they experience greater economic burdens than mothers. Although gender roles are changing, men have historically been expected to earn money while women are expected to perform childcare and housekeeping activities. This patriarchal system remains in Korea [34]. According to research participants, while only 2.1% of the total number of fathers were unemployed, as many as 36.3% of the total number of mothers were unemployed. This demonstrates that fathers bear a greater responsibility to earn money. In South Korea, under the Confucian tradition, father-children relationships are highly valued. Traditional fatherhood is based on the use of discipline and guidance in children’s education and not on warmth or care [35]. However, these traditional family ideals are challenged as society changes. New paternal expectations demand parents spend more time with their kids [36]. Nevertheless, it is likely that many working-class fathers are still after the Confucian ideals. Those fathers do not spend time with their children but only care about their child’s academic performance [37]. As our research data was collected from KoWePS, the participants were mostly working-class families. Participants would mostly follow Confucian ideals and care about a child’s academic performance. In Korea, the responsibility for children’s education is largely left to the mother, so the mother can be stressed from private education [38]. But the stress comes from educating children, not spending on private tuition. While the mother decides how to use private education, it is a father who feels burdened with the spending. However, as Confucianism is gradually disappearing in Korea, dual-income families are increasing [39]. The economic burden, which has traditionally belonged to men, will gradually become a burden to both parents.

Numerous studies have investigated the impact of family resources on educational performance [40]. While parents invest in their children’s education, these investments incur opportunity costs for other investments that parents or their families want [41]. Private education is a potential investment for children. Therefore, parents should evaluate this investment against other important expenditures [42]. Becker provides the intrafamily decision-making model, in which the household acts as one economic agent that optimizes a multiperiod utility function. Investment in the child comes at the opportunity cost of present-period consumption by the parent [43]. Numerous researchers have applied the Becker model to their studies to investigate the economics of parenting [40, 44]. Studies suggest that there are intergenerational conflict and moral risks in the household which leads to an intrahousehold dilemma. These financial worries may be deeply associated with depression and anxiety [45]. It is obvious that lower-income households are more sensitive to the proportion of private education costs than those with higher levels of income. (see Table 3).

A previous study of private education revealed that private education negatively affects children’s academic stress [46]. In Korea’s contemporary education-obsessed society, private education costs significantly affect not only children but families as a whole. High private education costs not only affect the mental health of the family but also low birth rates and educational inequality. When parents decide how many children to raise, they consider the cost of raising children and their economic strength so that all their children have a good capacity [47]. Inequality of educational opportunity due to the socioeconomic status of parents makes a difference in the educational attainment of the children’s generation [48].

Private education refers to supplementary education in addition to public education. Therefore, it poses a risk of educational inequality. Korean students study hard to attend highly reputed tertiary schools [49]. In 2018, 69.7% of high school graduates entered higher education institutions, which is 65.5% of the population of the same age [50]. It could be a positive social phenomenon in that many people receive higher education, but this leads to excessive private education spending. Parents do not want their children to fall behind, so they rely heavily on private education. Parents aware that future income depends on the education level. According to the Korea Statistics 2018, education level and hourly wages are highly correlated [50]. Parents make their children study, hoping that they will be richer than they are, but the level of education already depends on their financial level. Inequality drives parents into an endless competition, but this competition only results in intensified inequality [51]. Educational inequality is one of the fundamental causes of private educational use.

This study focused on parental depression caused by private education, while many other studies focused on children’s mood. Also, using the socio-cultural contexts of Korea, the reasons why fathers are more likely to be affected by higher proportions of private education cost, and why private education is highly activated are explained. Our findings argue that the impact of private education on parents should be highly considered. Recently, there has been much discussion about parenting in economics [52]. Parenting is affected by sociocultural contexts, economics, and thus affects parent mental health. Therefore, the proportions of private education cost could serve as an important variable in familial economic decision-making. Also, research on private education costs may give a deeper understanding of parenting. However, this study has some limitations. By using the given data from KoWePS, only researched variables were available. If the number of panels was bigger, a better understanding of the findings could be possible. CESD assesses short-term depressive mood, so it may not reflect the long-term associations which lead to clinical depression. Since the children in the study group included only students aged 11–16, the generalization of the results may be limited. In addition, the survey was conducted by KoWePS, which is suitable for low-income policies and poverty studies, so the generalization of different social statuses may be limited. However, since it was investigated by the government, the data is reliable.

Conclusions

The results of this study show an association between the proportion of private education cost and fathers’ depression levels in Korea. Korean traditional Confucian ideologies affect fathers to burden private education costs. As private education cost comes from the opportunity cost of consumption for household, raising private education costs, and lowering household incomes lead to parental depression. Since high private education costs affect families as a whole, the government should attempt to address private education problems. The government announced measures to reduce private education and normalize public education in 2014 [53]. However, these efforts were not enough, and the issue remains prevalent. In response, the government should attempt to address more fundamental problems. A social policy that guarantees employment opportunities through compulsory education will be the fundamental solution to these private education cost problems. A society that can provide quality jobs through vocational training after compulsory education will reduce private education for compulsory education. Education inequality will be alleviated if the government strengthens public education and provides educational subsidies to reduce the cost of private education [54]. The process may be challenging, but it can ease the burden on low-income families.

Availability of data and materials

The dataset analyzed during the current study are available in the Korea Welfare Panel Study, https://www.koweps.re.kr:442/.

Abbreviations

KoWePS:

Korea Welfare Panel Study

CESD:

The Center for Epidemiologic Studies Depression Scale

EHDI:

Equivalized Household Disposable Income

AUDIT:

Alcohol Usage Disorder Identification Test

RSS:

Rosenberg Self-Esteem Scale

K-CBCL:

Korean Child Behavior Checklist

References

  1. 1.

    Shin C, Kim Y, Park S, et al. Prevalence and associated factors of depression in general population of Korea: results from the Korea National Health and nutrition examination survey, 2014. J Korean Med Sci. 2017;32:1861–9.

    PubMed  PubMed Central  Google Scholar 

  2. 2.

    Jeon HJ. Depression and suicide. J Korean Med Assoc. 2011;54:370–5.

    Google Scholar 

  3. 3.

    Korea National Statistical Office. 2010 death and cause of death in Korea. Daejeon: Korea National Statistical Office; 2011.

    Google Scholar 

  4. 4.

    Lee J-H, Park K-S, Kim R-B, et al. The influence of individual-level social capital on depression. J Agric Med Community Health. 2011;36:73–86.

    Google Scholar 

  5. 5.

    Melchior M, Chastang JF, Walburg V, et al. Family income and youths’ symptoms of depression and anxiety: a longitudinal study of the French GAZEL youth cohort. Depress Anxiety. 2010;27:1095–103.

    PubMed  Google Scholar 

  6. 6.

    Robinson J. Social status and academic success in South Korea. Comp Educ Rev. 1994;38:506–30.

    Google Scholar 

  7. 7.

    Son M. Commentary: why the educational effect is so strong in differentials of mortality in Korea? Int J Epidemiol. 2004;33:308–10.

    PubMed  Google Scholar 

  8. 8.

    Shin JC. Higher education development in Korea: western university ideas, Confucian tradition, and economic development. High Educ. 2012;64:59–72.

    Google Scholar 

  9. 9.

    Marginson S. Higher education in East Asia and Singapore: rise of the Confucian model. High Educ. 2011;61:587–611.

    Google Scholar 

  10. 10.

    Lee J. Korean higher education: a Confucian perspective. Seoul: Jimoondang Publishing Company; 2002. p. 59.

    Google Scholar 

  11. 11.

    Dawson W. Private tutoring and mass schooling in East Asia: reflections of inequality in Japan, South Korea, and Cambodia. Asia Pac Educ Rev. 2010;11(1):14–24.

    Google Scholar 

  12. 12.

    Lee J, Lee H, Jang H. The history of policy responses to shadow education in South Korea: implications for the next cycle of policy responses. Asia Pac Educ Rev. 2010;11(1):97–108.

    Google Scholar 

  13. 13.

    Seth MJ. Education fever: society, politics, and the pursuit of schooling in South Korea. Honolulu: University of Hawaii Press; 2002.

    Google Scholar 

  14. 14.

    Statistics K. Private education expenditures survey 2018; 2019.

    Google Scholar 

  15. 15.

    Kim YC, Yang SS, Kim YH, et al. A study on the solution of private education: focused on the overheated tutoring. J Educ Adm. 2001;19(3):149–80.

    Google Scholar 

  16. 16.

    Byeon S. The effect of private tutoring participation and time on middle school students academic stress. Asian J Educ. 2018;17(4):913–44.

    Google Scholar 

  17. 17.

    Hwang J-H, Lee J-R. Exploring the pathways of depression in children's participation in private tutoring. Proceedings of the KMHA Conference; 2012. p. 372. (Korean: 황진홍, 이주리. 아동의 사교육 참여 시간이 우울에 영향을 미치는 경로탐색. 한국가정관리학회 학술발표대회 자료집. 2012;372–372).

    Google Scholar 

  18. 18.

    Jang EJ, Seo MJ, Jung CH. The study of relation to variables related to children’s depression and parents’ depression. J Korean Acad Child Adolesc Psychiatry. 2001;12(2):245–55.

    Google Scholar 

  19. 19.

    Otto B& Karbach J. The effects of private tutoring on students’ perception of their parents’ academic involvement and the quality of their parent-child relationship. Educ Psychol. 2019;39:923–40.

    Google Scholar 

  20. 20.

    Park H, Byun S-Y, Kim K-K. Parental involvement and Students' cognitive outcomes in Korea: focusing on private tutoring. Sociol Educ. 2011;84(1):3–22.

    Google Scholar 

  21. 21.

    Kowen M-R, Jang M, Lee N-K. Transforming in awareness of relationship problems due to excessive private education in Korea. Int J Qual Stud Health Well Being. 2019;14(1).

  22. 22.

    Jones RS. Education Reform in Korea. OECD: Economics Department Working Papers; 2013. Report No. p. 1067.

    Google Scholar 

  23. 23.

    Kendler KS, Gardner CO. Sex Differences in the Pathways to Major Depression: A Study of Opposite-Sex Twin Pairs. Am J Psychiatry. 2014;171(4):426–35.

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Milanovic B. True world income distribution, 1988 and 1993: first calculations, Based on Household Surveys Alone: The World Bank; 1999.

  25. 25.

    Korea Statistics. Korean statistical information service. 2018.

    Google Scholar 

  26. 26.

    OECD. Household disposable income (indicator); 2020. https://doi.org/10.1787/dd50eddd-en. (Accessed on 15 March 2020).

    Google Scholar 

  27. 27.

    OECD Project on Income Distribution and Poverty. What are equivalence scales?. 2005.

    Google Scholar 

  28. 28.

    Kim G, Decoster J, Huang CH, et al. Race/ethnicity and the factor structure of the Center for Epidemiologic Studies Depression Scale: a meta-analysis. Cult Divers Ethn Minor Psychol. 2011;17(4):381–96.

    Google Scholar 

  29. 29.

    Morin AJ, Moullec G, Maïano C, et al. Psychometric properties of the Center for Epidemiologic Studies Depression Scale (CES-D) in French clinical and nonclinical adults. Rev Epidemiol Sante Publique. 2011;59(5):327–40.

    CAS  PubMed  Google Scholar 

  30. 30.

    Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385–401.

    Google Scholar 

  31. 31.

    Yin Y-W, Chang C-W, Hung W-C, et al. Factor Structure of the 11-item Version of the Center for Epidemiological Studies Depression Scale (CES-D) among Community Dwelling Older Adults in Taiwan. Taiwan J Psychiatr. 2013;27(2):148–155+.

    Google Scholar 

  32. 32.

    Korea Welfare Panel Study. (유저가이드)13차년도 조사자료 유저가이드.pdf.pdf [Internet]: Koweps; 2019. p. 169–71. Available from: https://www.koweps.re.kr:442/data/guide/list.do.

  33. 33.

    Kohout FJ, Berkman LF, Evans DA, et al. Two shorter forms of the CES-D depression symptoms index. J Aging Health. 1993;5(2):179–93.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Lee K. Korean family and kinship. Seoul: Jimoondang Publishing Company; 1997.

    Google Scholar 

  35. 35.

    Park I, Cho L. Confucianism and the Korean family. J Comp Fam Stud. 1995;26:117–34.

    Google Scholar 

  36. 36.

    Han K. Men’s transition to parenthood: time of transition. J Korean Home Manage Assoc. 1997;34:231–44.

    Google Scholar 

  37. 37.

    Kwon Y, Roy K. Changing social expectations for work and family involvement among Korean fathers. J Comp Fam Stud. 2007;38(2):285–305.

    Google Scholar 

  38. 38.

    Park J. A study on the expenditure on the private education of junior and senior high school students, the stress from private education, and the role conflicts of their mothers. J Korean Home Manage Assoc. 2014;32(4):41–56.

    Google Scholar 

  39. 39.

    Han E-K, Yoo JS. Changes in gender-role attitudes of 20002015. Adv Dent Res. 2019;120:49–79.

    Google Scholar 

  40. 40.

    Acemoglu D, Pischke J-S. Changes in the wage structure, family income, and Children’s education. Eur Econ Rev. 2001;45(4):890–904.

    Google Scholar 

  41. 41.

    Lee S-L. The burden of private educational expenditure and consumption expenditure. J Korean Home Manage Assoc. 2005;23(3):63–76.

    Google Scholar 

  42. 42.

    Benjamin LC, Francis XM, William LS. Marching across generations? Education benefits and Intrahousehold decision-making. J Hum Cap. 2019;13(3):410–33.

    Google Scholar 

  43. 43.

    Becker GS. A theory of social interactions. J Polit Econ. 1974;82(6):1063–93.

    Google Scholar 

  44. 44.

    Bursztyn L, Coffman LC. The schooling decision: family preferences, intergenerational conflict, and moral Hazard in the Brazilian favelas. J Polit Econ. 2012;120(3):359–97.

    Google Scholar 

  45. 45.

    Diefenbach GJ, McCarthy-Larzelere ME, Williamson DA, et al. Anxiety, depression, and the content of worries. Depress Anxiety. 2001;14:247–50.

    CAS  PubMed  Google Scholar 

  46. 46.

    Kim K. Longitudinal analysis of the use and effectiveness of youth private education. National Youth Policy Institute Research Report; 2007. p. 1–101. (Korean: 김기헌. 청소년 사교육 이용실태 및 효과에 대한 종단분석. 한국청소년정책연구원 연구보고서. 2007;1–101.).

    Google Scholar 

  47. 47.

    Song H, Shin W. The analysis of the relationship between childbirth, private education spending and household income. J Labour Econ. 2017;40(4):33–59.

    Google Scholar 

  48. 48.

    Kim H, Seo E. Trend in private tuition expenditure gaps. Korean J Educ Res. 2018;56(1):133–53.

    Google Scholar 

  49. 49.

    Kwon SK, Lee M, Shin D. Educational assessment in the Republic of Korea: lights and shadows of high-stake exam-based education system. Assess Educ. 2017;24(1):60–77.

    Google Scholar 

  50. 50.

    Statistics K. Korean social indicators; 2018.

    Google Scholar 

  51. 51.

    Mathias D, Zilibotti F. Love, money, and parenting: how economics explains the way we raise our kids. Princeton: Princeton University Press; 2019.

    Google Scholar 

  52. 52.

    Matthias D, Sorrenti G, Zilibotti F. The economics of parenting. Annu Rev Econom. 2019;11:55–84.

    Google Scholar 

  53. 53.

    Korean Ministry of Education. Measures to reduce private education and normalize public education. 2014. (Korean: 교육부. 사교육 경감 및 공교육 정상화 대책. 2014).

    Google Scholar 

  54. 54.

    Kim JY, Chun YJ, Choi BJ. University entrance competition and private tutoring: the effects of public education enhancement and education subsidy. Korean J Econ Stud. 2016;64(2):5–31.

    Google Scholar 

Download references

Acknowledgements

We would like to thank the reviewers for their helpful comments and suggestions on the manuscript.

Funding

This study did not receive any funding.

Author information

Affiliations

Authors

Contributions

BCO, JYY, HSL, and DWL designed the study, conducted the statistical analyses. BCO, JYY, and HSL drafted the manuscript, and interpreted the results. BCO, JYY, HSL, DWL, and ECP contributed to the discussion. All authors have read and approved the manuscript.

Corresponding authors

Correspondence to Doo Woong Lee or Eun-Cheol Park.

Ethics declarations

Ethics approval and consent to participate

The dataset was conducted by the Korea Welfare Panel Study, which the Korean government provides for the research study. Thus, no formal ethics approval was required for the current study.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Additional file 1: Table S1.

Comparison of CESD according to year and proportion of private education cost. Abbreviations: CESD (The Center for Epidemiologic Studies Depression Scale). 1Proportion of private education cost is defined as: (private education cost/equivalized household disposable income)*100. Value in the parentheses is the actual data range.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Oh, B., Yeon, J., Lee, H. et al. Correlation between private education costs and parental depression in South Korea. BMC Public Health 20, 972 (2020). https://doi.org/10.1186/s12889-020-09058-w

Download citation

Keywords

  • Private education cost
  • Parental depression
  • Age
  • Equivalized household disposable income
  • Korea welfare panel study
  • Education-obsessed Korean society