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. 2023 Sep 3;9:23779608231196841. doi: 10.1177/23779608231196841

Work–Family Conflict and Depressive Symptoms of Married Working Women in Korea: The Role of Marriage Satisfaction and Organizational Gender Discrimination Climate

Ji-Young Kim 1, Gye-Hyun Jung 2, Ji-Hye Kim 3,✉
PMCID: PMC10478552  PMID: 37675149

Abstract

Introduction

Depression is increasing worldwide. Some previous studies have explored the impact of work–family conflict on depressive symptoms of married working women. However, little is known about the moderating relationship underlying them.

Objectives

This study aims to determine the moderating effects of marriage satisfaction and organizational gender discrimination climate in the relationship between work–family conflict and depressive symptoms of married working women in Korea.

Methods

A cross-sectional study was conducted using the data of the 8th Korean Longitudinal Survey of Women and Families (KLoWF). The data of 1,816 married working women employed and paid by an individual or an enterprise were analyzed.

Results

The work–family conflict had a significant effect on depressive symptoms of married working women. In the dynamics between work–family conflict and depressive symptoms, no significant moderating effect of marriage satisfaction was found. On the contrary, the organizational gender discrimination climate displayed a moderating effect on the relationship between work–family conflict and depressive symptoms.

Conclusion

Nursing strategies in the workplace or community are needed so that married working women can cope positively and actively between work–family conflicts and maintain healthy mental health. To this end, gender role awareness education should be prioritized to improve awareness of gender discrimination in the workplace. In addition, nursing interventions such as linking local or government support and information delivery should be provided so that married working women can be consulted about situations related to work–family conflicts or gender discrimination climate.

Keywords: depression, worker, women, gender discrimination, work–family conflict

Introduction

As the number of patients with depressive symptoms is increasing worldwide, there is a growing interest in depression. The World Health Organization (WHO) reported that if the increasing trend of depression continues, it will become a major disease with the largest burden by 2030 (WHO, 2016). According to the report of the Mental Health Survey 2021, the rate of depression in Organization for Economic Co-operation and Development (OECD) countries was 10.7%, and the rate of depression in South Korea was 13.2% (National Mental Health Center, 2021). It was also reported that women were more than twice as likely to experience mental health problems such as stress perception and depression than men (Statistics Korea, 2022).

Mental health in married women workers is important in that it may have an effect on guaranteed job continuity, protecting children in the next generation, reducing social costs associated with the prevention of women's health deterioration, reducing absence and early leave rates due to health and parenting, increasing enterprise productivity, and improving the country's future fertility rate (Jo & Chong, 2020; Othman et al., 2022; Patterson & Walcutt, 2013; Wang & Peng, 2017). Working women have vulnerable health conditions, it is necessary to develop measures to protect women's health in line with the rising women’s employment rate, which should be addressed as a social issue.

Review of Literature

The reason for a high rate of depression among married women workers is the complex combination of work–family balance and responsibilities required in the multiple roles as a worker, mother, and wife. The studies that reported the correlation between work–family conflict and depression among married women employees include those by Wang and Peng (2017), Yuan et al. (2022), and Kim et al. (2017). In married women workers who spend time at work and home, marital satisfaction at home (Patterson & Walcutt, 2013), and organizational gender discrimination climate (Patterson & Walcutt, 2013; Sun, 2020) can inevitably affect mental health in married women workers who have to maintain work–family balance. There are few studies that have examined the social and psychological factors of married working women's families and workplaces in a complex way. It is necessary to examine how the socio-psychological factors in the home and workplace of Korean married working women are related to depression.

In particular, married working women's relationship with their spouse was found to be an important factor for depression because they had to work and do housework, thus marital satisfaction was emphasized (Kim et al., 2017; Park & Park, 2018). Other studies have also reported married working women complaining of a double burden of family-work conflict due to a lack of support from their spouse, and that marital satisfaction in married working women in developed countries was very low (Horwood et al., 2021; Sherchand et al., 2018). Marital satisfaction, such as feelings for marriage, positive perception toward one's husband, and satisfaction with household labor sharing, had a great impact on depression among married working women.

Gender discrimination climate in the workplace was also related to depression among married working women (Batool, 2020; Choi et al., 2020; Kim et al., 2020a, 2020b; Pavalko et al., 2003). According to a longitudinal study that explored at the relationship between workplace discrimination and women's physical and emotional health, women who perceived workplace discrimination had a high degree of psychological distress (Pavalko et al., 2003). Batool (2020), through a study of the legal and institutional literature on gender discrimination in the workplace in the United Kingdom, reported that gender discrimination undermines women's empowerment and control in the workplace and increases their vulnerability to mental health problems (Batool, 2020). The relationship between gender discrimination in the workplace and women’s health was also found in Korea (Choi et al., 2020; Kim et al., 2020a, 2020b). As of 2021, women in South Korea received an average of 31.5% less wages than men, which is the highest wage gap among major OECD member countries (The Economist, 2021). In Korean society, prejudice and stereotypes about women's work and working ability are slowly changing, but these are combined with another vulnerability of women workers, resulting in multilayered discrimination (Park, 2021; Sun, 2020).

From the perspective of stress adaptation, the results of psychological adaptation (e.g., depression) of married working women in stressful situations can vary depending on environmental resources such as spouse and organizational culture (Lazarus & Folkman, 1987). For example, workplace social support in a stressful situation can have a buffering effect (Nagy et al., 2022). According to the studies marriage satisfaction based on the intimacy between husband and wife could influence depression among married women employees (Yuan et al., 2022; Wang & Peng, 2017). The studies on the negative effect of gender discrimination in the workplace on the level of depression among married women employees include those by Batool (2020) and Choi et al. (2020). Therefore, it can be assumed that the depression of married working women is related to work–family conflict, and this relationship can be regulated by marriage satisfaction and organizational gender discrimination climate. Based on these previous results, it is necessary to examine the factors affecting the depression of married working women caused by the work–family conflict in terms of the complex dynamics as using moderating effects.

This study focuses on work–family conflict, marital satisfaction, and organizational gender discrimination climate and their the relationship between depressive symptoms and each factor among married women workers. As such, it intends to derive recommendations to improve and prevent depression among married women employees with work–family conflict.

This study aimed to determine the moderating effects of marital satisfaction and organizational gender discrimination climate in the relationship between work–family conflict and depressive symptoms for married working women in South Korea.

Methods

Study Design

This study was conducted as a cross-sectional study using the data of the 8th Korean Longitudinal Survey of Women and Families (KLoWF).

Research Questions

  1. Are work–family conflict, marriage satisfaction, and organizational gender discrimination climate related to married working women’s depressive symptoms?

  2. Do marriage satisfaction and organizational gender discrimination climate have moderating effects on the relationship between work–family conflict and depressive symptoms for married working women?

Sample

The data of the 8th KLoWF conducted by the Korean Women's Development Institute in 2020 were used in this study, as it was the most recent (Korean Women's Development Institute, 2022; https://klowf.kwdi.re.kr/portal/eng/dataSet/rdssListPage.do?phDivCd=P). The KLoWF is a nationwide panel survey that has been conducted biennially since 2007 to accurately capture and analyze changes in women's lives (Ju et al., 2020).

The KLoWF adopted a stratified multistage sampling design to construct a systematic and representative sample (Ju et al., 2020). The KLoWF used the Korean Population and Housing Census to extract the primary sample frame. The sampling frame was prepared through a multi-level stratified probability sampling method based on the residential area. The survey was conducted using a face-to-face interview method via the TAPI system by visiting households to which interviewers were assigned. The survey method using the TAPI survey program has the advantage that a separate data input process is not required because the data is immediately transmitted in real time even while the survey is in progress, and input errors can be checked by program logic. In addition, KLoWF tried to reduce information bias through continuous interview method education for interviewers and the supervisor's management system (Ju et al., 2020). All participants provided informed consent prior to participation (Ju et al., 2020).

The inclusion criteria for participating in the study were as follows: married working woman who be at 19–64 years old, wage worker who is employed by someone or by a company. The exclusion criteria were unpaid family workers or women who were single, divorced, or widowed. The following inclusion/exclusion criteria were implemented: married wage workers (n = 1,821) were included from the total sample (N = 9,175), while five participants were excluded due to missing values for education (n = 1), monthly household income (n = 2), and marriage satisfaction (n = 2). Since the missing rate was 0.27% in the total proportion of values and the KLoWF used the probability sampling method, it was considered as ignorable missing data (Hair et al., 2014). Finally, 1,816 participants (mean age 48.80 ± 7.62) were included in the analysis.

Ethical Considerations

This study was approved for exemption by the Woosuk University Institutional Review Board (IRB No. WS 2022-8). In this study, the secondary data with privacy protection were analyzed.

Measures

Depressive Symptoms

The instrument to measure depressive symptoms was the CES-D (Center for Epidemiologic Studies Depression Scale) 10, developed by Radloff (1977) and modified to a short version with 10 questions by Andersen et al. (1994). The questions on personal feelings and attitudes in the recent past week were assessed by a 4-point Likert scale based on the frequency of depressive symptoms ranging from “rarely” (less than 1 day per week, 0) to “most or all of the time” (5 or more days per week, 3). The total score ranged between 0 and 30, whereby a total score ≥ 10 was interpreted as clinical depression (Andersen et al., 1994). Participants with scores ≤ 9 were placed in the nondepression group, and those with scores ≥ 10 were placed in the Depression group. The Cronbach's α in this study was .853.

Work–Family Conflict

The work–family conflict used seven questions to identify the effect of work on family and the effect of family on work, like previous studies (Lee et al., 2022). The Korean Women's Development Institute adapted the items developed by Bond et al. (1997) to measure work-family conflict. Previous studies validated the questionnaire (Kim et al., 2017; Lee et al., 2022). Some items are as follows: “My working hour is too long, and it has been affecting my home life” and “The heavy load of housework often makes me feel overwhelmed at work.” Each question was on a 4-point Likert scale from “Strongly disagree” to “Strongly agree,” whereby higher scores indicated higher levels of work–family conflict. The Cronbach's α in this study was .701.

Marriage Satisfaction

One question was used to measure marriage satisfaction: “Please choose the number that best represents your feelings about married life with your husband these days.” This was on a graphic rating scale from a score of 1 indicating “Very unhappy” to a 10 showing “Very happy,” with higher scores indicating higher levels of marital satisfaction.

Organizational Gender Discrimination Climate

Six questions on the perceived level of gender discrimination in the workplace were used to measure the organizational gender discrimination climate. Each question asks about six types of discrimination: hiring, promotion, paid wages, work assignments, training opportunities, and firing. Examples from the questionnaires are as follows: “In recruitment, men seem to be preferred to women under similar conditions,” “In promotion, male workers tend to be promoted earlier than women workers if the career length is the same or similar,” and others. Each question was on a 4-point Likert scale from “Strongly disagree” to “Strongly agree,” with higher total scores indicating higher levels of gender discrimination in the workplace. The Cronbach's α in this study was 0.954.

Covariates

The selected covariates in this study were the variables identified to have a relationship with depression in women in previous studies: age, education, and monthly household income among the demographic characteristics; underlying diseases diagnosed by health professionals, and daily stress among the health-related characteristics; work contract, a monthly wage, and work satisfaction among the work-related characteristics (Cho et al., 2012; Kim et al., 2017; Lee et al., 2022; Park & Park, 2018; Sherchand et al., 2018; Wang & Peng, 2017; Yuan et al., 2022). The education variable was categorized into ≤ middle school, high school, and ≥ college. The number of underlying diseases diagnosed by health professionals was estimated as the total score of each specific disease field (heart, cardiovascular, musculoskeletal, respiratory, digestive, endocrine, and gynecological disease). Daily stress was measured using seven questions on daily thoughts and feelings (e.g., I feel stressed at work, home, or school). Each question was on a 4-point Likert scale from “Strongly disagree” to “Strongly agree,” with higher total scores indicating higher levels of daily stress. The Cronbach's α in this study was .715. The work contract was categorized into regular and nonregular. To measure work satisfaction, 10 questions on the level of satisfaction with the current work (e.g., I am satisfied with my current wage or income). Each question was on a 5-point Likert scale from “Very satisfied” to “Very dissatisfied,” with higher scores indicating higher work satisfaction. The Cronbach's α in this study was .908.

Statistical Analysis

The data were analyzed using the Statistical Package for the Social Science (SPSS) statistical program 22.0. Descriptive statistics (frequency, percentage, mean, and standard deviation [SD]) were performed on participants’ characteristics (demographic, health-related, and work-related characteristics). As a result of checking the skewness and kurtosis of all quantitative variables, annual household income and monthly wage showed positive skewness, so they were put into multiple regression analysis after log transformation. T-test and χ2-test were performed to detect the variation between the depression group and the nondepression group per the characteristics and the main variables. Subsequently, a hierarchical logistic regression analysis was conducted to determine the moderating effects of marital satisfaction and organizational gender discrimination climate in the relationship between work–family conflict and depressive symptoms and presented as odds ratios (ORs) and 95% confidence intervals (CIs). Variables were entered into the models in three steps: Step 1 contained covariates that showed a significant difference in depressive symptoms. And main variables (work–family conflict, marital satisfaction, and organizational gender discrimination climate) were additionally entered in Step 2. The interaction terms of independent variables and moderating variables were entered in Step 3. All continuous independent variables were standardized before the examination of the interactive effect. The effect of the moderators was estimated at values of the moderator corresponding to the mean and minus/plus one SD from the mean of the moderator, which represents low, and high scores of gender discrimination climate.

Results

Sample Characteristics

The characteristics of the participants are presented in Table 1. For work–family conflict and marital satisfaction, the mean scores were 1.91 ± 0.41 (range 1–4) and 3.83 ± 1.37 (range 1–10), respectively. The mean score for organizational gender discrimination climate was 1.72 ± 0.62 and the work assignment was 1.79 ± 0.73, the highest score among the subdomains (range 1–4). The number of women in the Depression group was 191 (10.5%) (Table 2).

Table 1.

Variation in Depressive Symptoms Depending on Participant's Characteristics (N = 1,816).

Variables Total
n = 1,816		 Depression group
n = 191 (10.5%)		 Nondepression group
n = 1,625 (89.5%)		 t or χ2
p-value
n (%) or M ± SD
Age
 ≤ 44 509 (28.0) 46 (24.1) 463 (28.5) 9.272
(.010)
 45–54 861 (47.4) 81 (42.4) 780 (48.0)
 55–64 446 (24.6) 64 (33.5) 383 (23.5)
Education
 ≤ Middle school 157 (8.6) 33 (17.3) 124 (7.6) 20.991
(<.001)
 High school 785 (43.2) 69 (36.1) 716 (44.1)
 ≥ College 874 (48.1) 89 (46.6) 785 (48.3)
Annual household income (10,000 KRW) 6,812.05 ± 599.12 6,081.52 ± 2775.68 6,897.82 ± 3675.00 −2.972
(.003)
Preschooler children number
 0 1,628 (89.6) 175 (89.6) 1,453 (89.4) 0.898
(.382)
 ≥ 1 188 (10.4) 16 (10.4) 172 (10.6)
 Underlying diseases 0.22 ± 0.51 0.35 ± 0.62 0.20 ± 0.49 2.891
(.004)
 Daily stress 1.96 ± 0.41 2.24 ± 0.41 1.92 ± 0.40 10.167
(<.001)
Work contract
Regular 949 (52.3) 91 (47.6) 858 (52.8) 1.821
(.177)
 Nonregular 867 (47.7) 100 (52.4) 767 (47.2)
 Monthly wage (10,000 KRW) 202.59 ± 113.38 186.62 ± 91.93 204.47 ± 155.52 −2.465
(.014)
 Work satisfaction 3.39 ± .53 3.22 ± .54 3.41 ± .53 4.455
(<.001)
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Table 2.

Variation in Depressive Symptoms Depending on Main Variable (N = 1,816).

Variables Total
n = 1,816		 Depression group
n = 191 (10.5%)		 Nondepression group
n = 1,625 (89.5%)		 t
p-value
M ± SD
Work–family conflict 1.91 ± 0.41 2.10 ± 0.43 1.89 ± 0.40 6.686
(<.001)
Marriage satisfaction 3.83 ± 1.37 6.33 ± 0.43 6.90 ± 1.36 −5.391
(<.001)
Organizational gender discrimination climate 1.72 ± 0.62 1.78 ± 0.70 1.72 ± 0.61 1.152
(.250)
Hiring 1.71 ± 0.65 1.75 ± 0.47 1.71 ± 0.64 .863
(.389)
Promotion 1.72 ± 0.69 1.78 ± 0.78 1.71 ± 0.68 1.099
(.273)
Paid wage 1.71 ± 0.69 1.75 ± 0.75 1.71 ± 0.68 1.535
(.507)
Work assignment 1.79 ± 0.73 1.87 ± 0.85 1.78 ± 0.71 1.535
(.126)
Training opportunity 1.70 ± 0.67 1.76 ± 0.79 1.69 ± 0.66 1.236
(.208)
Job security 1.75 ± 0.68 1.76 ± 0.77 1.72 ± 0.67 .747
(.406)
Depressive symptoms 1.34 ± 0.41 2.27 ± 0.33 1.24 ± 0.25 41.715
(<.001)
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Variation in Depressive Symptoms Depending on Participant's Characteristics

Table 1 shows variation in depressive symptoms depending on the participant's characteristics. The depressive symptoms varied significantly according to age (χ2 = 9.272, p = .010), education (χ2 = 20.991, p < .001), annual household income (t = −2.972, p = .003), daily stress (t = 10.167, p < .001), monthly wage (t = −2.465, p = .014) and work satisfaction (t = 4.455, p < .001).

The levels of work–family conflict (t = 6.686, p < .001) and marriage satisfaction (t = −5.391, p < .001) as the main variables significantly varied between the depression group and the nondepression group. The perceived level of organizational gender discrimination climate did not greatly vary between the two groups (t = 1.152, p = .250).

Main and Moderating Effects

The variables identified as the significant factors in the univariate analysis; age, education, annual household income, underlying disease, daily stress, monthly wage, and work satisfaction, were applied as covariates. Table 3 shows the result of the hierarchical logistic regression analysis. Step 1 was statistically significant for education and daily stress. The odds for depressive symptoms decreased by 56% in high school than in middle school or lower (95% CI = 0.26–0.76). The odds for depressive symptoms increased by 6.40 times with one unit increase in daily stress (95% CI = 4.25–9.64).

Table 3.

Main and Moderating Effects Test of Depressive Symptoms (N = 1,816).

Variables Categories Step 1a Step 2b Step 3c
OR 95% CI OR 95% CI OR 95% CI
Age
(reference: ≤ 44)		 45–54 0.96 0.64–1.44 1.01 0.67–1.52 1.04 0.69–1.57
55–64 1.35 0.83–2.21 1.43 0.87–2.35 1.47 0.89–2.42
Education
(reference:
≤ middle school)		 High school 0.44** 0.26–0.76 0.44** 0.26–0.75 0.43* 0.25–0.74
≥ College 0.67 0.38–1.20 0.68 0.38–1.22 0.67 0.37–1.20
Annual household income 0.75 0.34–1.68 0.86 0.38–1.93 0.89 0.39–2.03
Underlying diseases 1.24 0.94–1.64 1.24 0.94–1.65 1.23 0.93–1.63
Daily stress 6.40*** 4.25–9.64 5.36*** 3.50–8.22 5.18*** 3.38–7.95
Monthly wage 1.42 0.64–3.12 1.22 0.55–2.70 1.24 0.56–2.75
Work satisfaction 0.66* 0.48–0.92 0.73 0.52–1.03 0.72 0.51–1.01
Work–family conflict 1.32* 1.03–1.68 1.30* 1.01–1.69
Marriage satisfaction 0.87* 0.77–0.98 0.88* 0.78–0.99
Organizational gender discrimination climate 0.93 0.71–1.20 0.82 0.62–1.09
Work–family conflict * Marriage satisfaction 0.99 0.92–1.07
Work–family conflict * Organizational gender discrimination climate 1.24* 1.05–1.46
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Note. OR = odds ratio; CI = confidence interval.

a

χ2 (p) = 131.731 (<.001), Nagelkerke's R2 = .143, Hosmer–Lemeshow χ2 = 5.741 (p = .676).

b

χ2 (p) = 141.368 (<.001), Nagelkerke's R2 = .153, Hosmer–Lemeshow χ2 = 8.926 (p = .349).

c

χ2 (p) = 148.188 (<.001), Nagelkerke's R2 = .160, Hosmer–Lemeshow χ2 = 6.820 (p = .556).

The main variables (work–family conflict, marital satisfaction, and organizational gender discrimination climate) were added to Step 2. The odds for depressive symptoms increased by 32% (95% CI = 1.03–1.68) with one unit increase in work–family conflict and decreased by 13% (95% CI = 0.77–0.98) with one unit increase in marriage satisfaction. However, the organizational gender discrimination climate was not significant.

The interaction terms of independent variables and moderating variables were entered in Step 3. The interaction between work–family conflict and organizational gender discrimination climate concerning depression was found to be substantial (OR 1.24, 95% CI = 1.05–1.46). This implied that the effect of work–family conflict on depression was more significant in the group with a higher level of gender discrimination in the workplace than in the group with a lower level. For the convenience of interpreting the moderating effects, a schematic diagram of the relationship between work–family conflict and depression was drawn for high and low perceived levels of gender discrimination in the workplace (Figure 1).

Figure 1.

Figure 1.

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The moderating effect of organizational gender discrimination climate.

Discussion

Work–family conflicts can cause irreversible losses to individuals, families, or organizations, as well as become a significant issue for the mental health of married working women. Using the representative samples of 1,816 married working women in South Korea, this study investigated the moderating effects of marriage satisfaction and workplace gender discrimination in the relationship between work–family conflict and depressive symptoms. The results indicated a significant impact of work–family conflict and marriage satisfaction on depressive symptoms. A moderating effect of work–family conflict on depressive symptoms through interaction with workplace gender discrimination was verified. Hence, an increase in the perceived level of gender discrimination in the workplace was shown to cause a more significant impact of work–family conflict on depressive symptoms in married working women.

This study showed that work–family conflict significantly impacted depressive symptoms in married working women, the depression group showed a significantly higher level of work–family conflict than the nondepression group. This was similar to previous studies (Lee et al., 2022; Wang & Peng, 2017; Yuan et al., 2022). Married working women have duties and responsibilities to their families as wives or mothers, along with social achievements in personal growth and development (Yuan et al., 2022). Consequently, married working women can become tired and exhausted through the multiple roles as a worker, mother, and wife, and gradually experience burnout in work and family (Cho et al., 2012; Seligman et al., 2005). This can lead to neglect of family obligations and decreased work performance, resulting in work–family conflict (Lee et al., 2022; Wang & Peng, 2017). Work–family conflict increases work-related stress, dissatisfaction, fatigue, etc., which may lead to negatively affect productivity, child care, social costs associated with preventing women's health deterioration, and future fertility rates (Jo & Chong, 2020; Othman et al., 2022; Patterson & Walcutt, 2013; Wang & Peng, 2017; Yuan et al., 2022). This suggests that work–family conflict could have negatively affected the mental health of married working women, including depression. Meanwhile, how to perceive and respond to work–family conflict can have a different impact on mental health (Seligman et al., 2005). In order for married working women to solve the work–family conflict positively, it is necessary to provide self-esteem and socialization programs in the community by linking the health home support center or government support program to the community (Kim et al., 2020b). It will be a nursing intervention plan for prevention and improvement.

In this study, marriage satisfaction significantly affected depression in married working women. Contrastingly, the depression group showed lower marital satisfaction than the nondepression group. This was in line with Jo and Chong's (2020) and Othman et al.'s (2022) studies. The relationship between work–family conflict and marriage satisfaction is critical to parenting and the well-being of family and society (St. Vil, 2014). The switch in work and family of married working women can play an important role in maintaining the mental health of married working women because they desperately need their husbands’ housework and childcare support (Choi et al., 2020). When married working women feel high work–family compatibility and equality with their husbands, they can increase marital satisfaction as well as reduce depression (Jo & Chong, 2020; Othman et al., 2022). Meanwhile, work–family conflicts can increase the depression of married working women because they can reduce the quality of family relationships or reduce work performance and negatively affect mental health (O’Brien et al., 2014).

However, the interaction between work–family conflict and marriage satisfaction concerning the effect on depression was not significant in this study. Contrastingly, Jo and Chong showed that the negative impact of a high level of work–family conflict on marriage satisfaction was reduced through the fair sharing of parenting by the husband. Furthermore, the level of depression in married working women did not increase (Jo & Chong, 2020). To protect the mental health of married working women, factors such as intimacy and communication between husband and wife can reduce work–family conflict and maintain marriage satisfaction and psychological well-being (Othman et al., 2022; Worley & Shelton, 2020). Therefore, further research is needed to plan various mediation strategies. Meanwhile, in South Korea, marriage and childbirth cannot be ignored in the life cycle of a family because they bring significant life changes to married working women. However, it is still challenging for Korean women to return to work after childbirth or find a job with stable working conditions (Choi et al., 2020; Jo & Chong, 2020). As with the generalization of dual-income households, they are correlated with work done at the organizational level, such as concrete and substantial social support and family support workplace policies (Worley & Shelton, 2020). Therefore, it is necessary to find the factors that can affect the mental health of married working women according to the life cycle of the family, and to establish differentiated nursing strategies for healthy mental health and quality of life considering social and organizational support.

The interaction between work–family conflict and gender discrimination in the workplace was significant in this study regarding depression. This aligns with Kim et al.'s (2022) study. Many married working women claim that their organizations are not taking the necessary measures to help them maintain the work–family balance, one cause of which is workplace gender discrimination (Kaur & Singh, 2021). Compared to men, married working women have fewer opportunities for decision-making and work control in the workplace due to gender discrimination, which can lead to depression (Othman et al., 2022). As women have traditionally been assigned a more significant load of housework, married working women experience an even more severe level of work–family conflict. In combination with family demands, depressive symptoms could appear (Sandberg et al., 2012). After all, as gender discrimination in the workplace reduces overall work productivity, young married women employees may face increased risks of depression and other mental problems (Kim et al., 2020a, 2020b).

The Korean government enacted the Act on Gender Discrimination in 2005 (Kim et al., 2020a, 2020b), but women are more likely to experience gender discrimination than men due to Korea's Confucian concept of male superiority and patriarchal family structure (Kim et al., 2022). Therefore, married working women should receive supportive educational sessions or programs that promote gender equality and open-minded thoughts, and, the stereotypical ideas of gender roles should be changed. In addition, as even a married women employee with a good sense of gender equality could be under the influence of work–family conflict regarding mental health, a higher level of social support, including organizational and spousal support, should be given at work and home (Noroozi et al., 2022). Therefore, it is also necessary to develop related policies to create a family supported society and organizational culture that guarantees gender equality. In addition, evidence-based interventions or qualitative health services should be developed to protect the healthy lives of married working women.

Strengths and Limitations

This study has both strengths and limitations. The main strength is that this study suggested the importance of prevention and improvement of depressive symptoms in consideration of socio-psychological factors in married working women. And this study suggested the need for related policy strategies to create a family-supported society and organizational culture that alleviates work–family conflicts and ensures a culture of organizational gender equality in order to maintain and improve the healthy mental health of married working women. Finally, the significance of our study is that sample representativeness was secured using a nationally representative systematic sample.

Despite the significance of this study, there are several limitations as follows. First, as the cross-sectional design limits the cause-effect analysis, the follow-up study should conduct a longitudinal study to clarify the cause–effect relationship between work–family conflict and depression. Second, as secondary data were used in this study, a questionnaire incorporating the investigator's intentions could not be applied, which could have limited the scope of the study. Third, Because CES-D 10 is a widely used self-reporting questionnaire in epidemiological studies with high levels of reliability and validity (Irwin et al., 1999), it was used as a basic screening instrument for the early detection of depression risks. So, clinical confirmation of depression is insufficient because mental health checkups have not been conducted to confirm the occurrence of depression in married working women.

Implications for Practice

Although married working women experience work–family conflict with various factors that can occur between work and family, the influence on mental health can vary depending on how they perceive and respond to it. Therefore, in order to solve problems for married working women, it is necessary to seek to link the community or government's home and workplace support programs as a nursing intervention strategy to prevent and improve depression in the community. And community health nurses will have to consider work–family conflict, marital satisfaction, and organizational gender discrimination climate to manage the mental health of married women. On the other hand, marriage and childbirth can bring about important life changes for married working women, as well as affect the quality of family relationships and the mental health of married working women. In future studies related to work–family conflicts and factors that cause depression or intervention in married working women, the family's life cycle should be considered. Lastly, married working women in a men-centered or gender-discriminating workplace are more likely to be negatively affected by work–family conflict. Therefore, it is also necessary to develop related policies so that a family-supported society and organizational culture that guarantees gender equality can be created. In addition, evidence-based and qualitative health services should be developed to protect the healthy life of married working women.

Conclusions

This study confirmed that the factors of work–family conflict, marital satisfaction, and organizational gender discrimination climate affect married working women's depressive symptoms using the 8th Korea Women's Family Panel Survey (KLoWF) data. Also, the interaction between work–family conflict and organizational gender discrimination climate concerning depression was found to be substantial.

Based on the above results, nursing strategies in the workplace or community are needed to help married working women cope with work–family conflicts positively and actively and maintain healthy mental health. To this end, education on gender role recognition should be prioritized as one of the nursing strategies to improve awareness of gender discrimination in the workplace. In addition, nursing intervention measures such as linking local or government support and delivering information should be prepared so that married working women can seek advice on situations related to family conflict or gender discrimination in the workplace.

Acknowledgments

All authors are grateful to Professor Song Hye-young for her support, encouragement, and advice until this paper is completed.

Footnotes

Author Contributions: For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used conceptualization, J-YK, and J-HK; methodology J-YK and J-HK; software J-YK and J-HK; validation, J-YK, G-HJ, and J-HK; formal analysis, J-HK; investigation, J-HK; resources, J-HK; data curation, J-HK; writing—original draft preparation, J-YK and J-HK; writing—review and editing, J-YK, G-HJ, and J-HK; visualization, J-YK, G-HJ, and J-HK; supervision, J-YK, G-HJ, and J-HK; project administration, J-YK, G-HJ, and J-HK. All authors have read and agreed to the published version of the manuscript.

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

Funding: The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

  1. Andersen M., Malmgren J. A., Carter W. B., Patrick D. L. (1994). Screening for depression in well older adults: Evaluation of a short form of the CES-D. American Journal of Preventive Medicine, 10(2), 77–84. 10.1016/S0749-3797(18)30622-6 [DOI] [PubMed] [Google Scholar]
  2. Batool F. (2020). Gender discrimination at workplace and mental health of women: A systematic literature review. PJAEE, 17(8), 622–633. [Google Scholar]
  3. Bond J. T., Galinsky E., Swanberg J. E. (1997). The national study of the changing work force. Families and Work Institute. [Google Scholar]
  4. Cho I., Ahn S., Kim S. Y., Park Y. S., Kim H. W., Lee S. O., Lee S. H., Chung C. W. (2012). Depression of married and employed women based on social-role theory. Journal of Korean Academy of Nursing, 42(4), 496–507. 10.4040/jkan.2012.42.4.496 [DOI] [PubMed] [Google Scholar]
  5. Choi S. Y., Kim H. R., Myong J. P. (2020). The mediating effects of marital intimacy and work satisfaction in the relationship between husbands’ domestic labor and depressive mood of married working women. International Journal of Environmental Research and Public Health, 17(12), 1–12. 10.3390/ijerph17124547 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Hair J. F., Black W. C., Babin B. J., Anderson R. E. (2014). Multivariate data analysis: person new international edition (7th ed.). Pearson Education. [Google Scholar]
  7. Horwood C., Haskins L., Hinton R., Connolly C., Luthuli S., Rollins N. (2021). Ad dressing the interaction between food insecurity, depression risk and informal work: Findings of a cross-sectional survey among informal women workers with young children in South Africa. BMC Women’s Health, 21(1), 1–12. 10.1186/s12905-020-01147-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Irwin M., Artin K. H., Oxman M. N. (1999). Screening for depression in the older adult: Criterion validity of the 10-item center for epidemiological studies depression scale (CES-D). Archives of Internal Medicine, 159(15), 1701–1704. 10.1001/archinte.159.15.1701 [DOI] [PubMed] [Google Scholar]
  9. Jo S. L., Chong Y. S. (2020). The relationships between work–family conflict, marital satisfaction and depression of working mother: The moderated mediation effect of democratic parenting of father. The Korean Journal of Culture and Social Issues, 26(4), 435–456. 10.20406/kjcs.2020.11.26.4.435 [DOI] [Google Scholar]
  10. Ju J. S., Lee D. S., Song C. S., Par G. P., Lee J. S., Park S. Y., Lim Y. G. (2020). Korean women’s development institute, Korean longitudinal survey of women & families: the 2020 annual report. Korean Women’s Development Institute, Seoul. [Google Scholar]
  11. Kaur M., Singh M. (2021). A study on women employees and their work–life balance. NIU International Journal of Human Rights, 8, 797–802. [Google Scholar]
  12. Kim G. E., Kim J. M., Lee S. K., Sim J. H., Kim Y. W., Yun B. Y., Yoon J. H. (2020a). Multi-dimensional gender discrimination in workplace and depressive symptoms. PLOS ONE, 15(7), e0234415. 10.1371/journal.pone.0234415 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Kim H. J., Kim J. H., Jang Y. J. (2020b). The effects of working conditions and work–family conflict on health of married female workers. Korean Journal of Family Social Work, 67(1), 5–33. 10.16975/kjfsw.67.1.1 [DOI] [Google Scholar]
  14. Kim S. K., Park S., Rhee H. (2017). The effect of work–family conflict on depression in married working women. Journal of Digital Convergence, 15(3), 267–275. 10.14400/JDC.2017.15.3.267 [DOI] [Google Scholar]
  15. Kim S. Y., Won E. S., Jeong H. G., Lee M. S., Ko Y. H., Paik J. W., Han C. S. (2022). Gender discrimination in workplace and depressive symptoms in female employees in South Korea. Journal of Affective Disorders, 306, 269–275. 10.1016/j.jad.2022.03.050 [DOI] [PubMed] [Google Scholar]
  16. Korean Women’s Development Institute (2022). 8th Korean longitudinal survey of woman and families. (2022, April 7). Retrieved from https://klowf.kwdi.re.kr/portal/dataSet/rdssFileListPage.do
  17. Lazarus R. S., Folkman S. (1987). Transactional theory and research on emotions and coping. European Journal of Personality 1(3), 141–169. 10.1002/per.2410010304 [DOI] [Google Scholar]
  18. Lee J. S., Lim J. E., Cho S. H., Won E. S., Jeong H. G., Lee M. S., Ko Y. H. (2022). Association between work–family conflict and depressive symptoms in female workers: An exploration of potential moderators. Journal of Psychiatric Research, 151, 113–121. 10.1016/j.jpsychires.2022.04.018 [DOI] [PubMed] [Google Scholar]
  19. Nagy E., Moore S., Silveira P. P., Meaney M. J., Levitan R. D., Dubé L. (2022). Low socioeconomic status, parental stress, depression, and the buffering role of network social capital in mothers. Journal of Mental Health, 31(3), 340–347. 10.1080/09638237.2020.1793118. [DOI] [PubMed] [Google Scholar]
  20. National Mental Health Center. (2021). National mental health survey 2021. (2023, March 6). Retrieved from http://www.korea.kr/news/pressReleaseView.do?newsId=156488517
  21. Noroozi F., Bagherzadeh R., Cousins R., Nazari M., Ghahremani L. (2022). Alleviating work–family conflict for female employees in Iran: The effect of a multimedia educational intervention. Current Psychology, 7, 1–14. 10.1007/s12144-022-03068-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. O’Brien K. M., Ganginis Del Pino H. V., Yoo S. K., Cinamon R. G., Han Y. J. (2014). Work, family, support, and depression: Employed mothers in Israel, Korea, and the United States. Journal of Counseling and Psychology, 61(3), 461–472. 10.1037/a0036339 [DOI] [PubMed] [Google Scholar]
  23. Othman W. N., Zainudin Z. N., Yusop Y. M., Jaafar W. M., Mokhtar M. Y. O. (2022). A systematic review of marital satisfaction and psychological well-being among career women. Journal of Positive School Psychology, 6(4), 5831–5844. [Google Scholar]
  24. Park C. R. (2021). Depressive symptoms, stress, and self-rated health in Korean adults based on the types of tobacco use: A focus on gender differences. Korean Journal of Health Education and Promotion, 38(2), 55–69. 10.14367/kjhep.2021.38.2.55 [DOI] [Google Scholar]
  25. Park S. Y., Park S. Y. (2018). Longitudinal study on ecological determinants associated with middle-aged and elderly women’s life satisfaction and depressive symptoms. Health and Social Welfare Review, 38(4), 129–163. 10.15709/hswr.2018.38.4.129 [DOI] [Google Scholar]
  26. Patterson L., Walcutt B. (2013). Korean workplace gender discrimination research analysis: A review of the literature from 1990 to 2010. Asia Pacific Business Review, 19(1), 85–101. 10.1080/13602381.2012.697774 [DOI] [Google Scholar]
  27. Pavalko E. K., Mossakowski K. N., Hamilton V. J. (2003). Does perceived discrimination affect health? Longitudinal relationships between work discrimination and women’s physical and emotional health. Journal of Health and Social Behavior, 43(March), 18–33. 10.2307/1519813 [DOI] [PubMed] [Google Scholar]
  28. Radloff L. S. (1977). The CES-D scale: A self-report of depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. 10.1177/014662167700100306. [DOI] [Google Scholar]
  29. Sandberg J. G., Yorgason J. B., Miller R. B., Hill E. J. (2012). Family-to-work spillover in Singapore: Marital distress, physical and mental health, and work satisfaction. Family Relations, 61(1), 1–15. 10.1111/j.1741-3729.2011.00682.x [DOI] [Google Scholar]
  30. Seligman M. E. P., Steen T. A., Park N., Peterson C. (2005). Positive psychology progress: Empirical validation of interventions. American Psychologist, 60(5), 410–421. 10.1037/0003-066X.60.5.410 [DOI] [PubMed] [Google Scholar]
  31. Sherchand O., Sapkota N., Chaudhari R., Khan K. S. A., Baranwal J. K., Niraula A. (2018). Gender differences in the prevalence of depression among the working population of Nepal. Psychiatry Journal, 2018, 8354861. 10.1155/2018/8354861 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Statistics Korea. (2022). Korean Statistical Information Service (KOSIS) database. (2023, April 15). Retrieved from https://kosis.kr/search/search.do [Google Scholar]
  33. St. Vil N. M. (2014). African American marital satisfaction as a function of work–family balance and work–family conflict and implications for social workers. Journal of Human Behavior in the Social Environment, 24(2), 208–216. 10.1080/10911359.2014.848694 [DOI] [Google Scholar]
  34. Sun M. J. (2020). A case study on the relationship between work–family conflict experience of married working women with an infant and willingness to have the second child. Journals of Women’s Studies, 30(1), 77–111. 10.272/pnujws.30.1.20204.7 [DOI] [Google Scholar]
  35. The Economist. (2021). “Is the lot of female executives improving?” The Economist. (2021, August 3) Retrieved from http://www.economist.com/business/2021/03/06/is-the-lot-of-female-executives-improving
  36. Wang Y., Peng J. (2017). Work–family conflict and depression in Chinese professional women: The mediating roles of job satisfaction and life satisfaction. International Journal of Mental Health and Addiction, 15(2), 394–406. 10.1007/s11469-017-9736-0 [DOI] [Google Scholar]
  37. World Health Organization (WHO). (2016). Depression and other common mental disorders. (2020, December 19). Retrieved from http://apps.who.int/iris/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf;jsessionid=D127AB787B4D3C307E7FB8CD1CC9E719?sequence=1
  38. Worley T. R., Shelton M. R. (2020). Work–family conflict, relational turbulence mechanisms, conflict tactics and marital satisfaction. Journal of Applied Communication Research, 48(2), 248–269. 10.1080/00909882.2020.1735647 [DOI] [Google Scholar]
  39. Yuan T., Liang L., Ren H., Hu Y., Qin Z., Fei J., Cao R., Li C., & S Mei. (2022). Age moderates the effect of work–family conflict on life satisfaction among Chinese women employees: A propensity score matching method. Personality and Individual Differences, 185, 111279. 10.1016/j.paid.2021.111279 [DOI] [Google Scholar]

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