The Influence of Emotional Intelligence and Workplace Well-Being on Work-Life Balance among Married Female Civil Servants in the Government of Kediri City

Abstract

This study aims to examine the influence of emotional intelligence and workplace well-being on work-life balance, with employee engagement as a mediating variable. The research focuses on married female civil servants in Kediri. The background of this study is the gender role disparity in Indonesia, where women are often culturally expected to be the primary caregivers at home despite their significant professional roles. This research uses a quantitative approach involving 97 married female civil servants in Kediri. Data were collected through a survey using a questionnaire: emotional intelligence, workplace well-being, employee engagement, and work-life balance. Data analysis was conducted using Partial Least Squares (PLS), a component of Structural Equation Modeling (SEM). PLS was chosen for its capability in testing inter-variable relationships while validating mediation models. Instrument validity and reliability were tested beforehand to ensure data accuracy. The findings indicate that emotional intelligence has a significant positive effect on work-life balance (p=0.000; t=4.585) and employee engagement (p=0.000; t=5.081). Workplace well-being does not have a direct effect on work-life balance (p=0.334; t=0.428), but significantly increases employee engagement (p=0.000; t=4.537). Employee engagement positively mediates the relationship between emotional intelligence and workplace well-being with work-life balance (p=0.002; t=2.860). These findings offer theoretical contributions by strengthening mediation models in the context of gender and public sector, and practical implications for the Government of Kediri.

KEYWORDS quality tourism; environmental responsibility; eco-tourism; place attachment.

Introduction and Hypothesis Development

Work–life balance (WLB) has become a critical issue in human resource management, particularly for married women who simultaneously perform professional and domestic roles. In the public sector, this issue is especially salient because civil servants are required to maintain high levels of accountability, service quality, and bureaucratic performance, while often facing rigid work structures. Previous studies have consistently shown that poor work–life balance is associated with stress, burnout, job dissatisfaction, and reduced organizational commitment (Lakkoju & Jeyalakshmi, 2015; Wepfer et al., 2018). However, empirical evidence also suggests that the determinants of work–life balance are highly contextual, shaped by gender norms, organizational culture, and sector-specific demands. In Indonesia, gender role inequality remains deeply embedded in social and cultural norms. Married women are commonly expected to assume primary responsibility for childcare and household management, even when they are employed full-time (Rehman & Azam Roomi, 2012; Shockley et al., 2017). For married female civil servants, this double burden is intensified by the expectations of professionalism, job security obligations, and increasing digitalization of public services (Mache et al., 2021). Although government institutions— including the Government of Kediri City—have introduced various policies to support employee well-being, such as health programs and flexible administrative systems, these initiatives do not automatically translate into improved work– life balance for women with dual roles (Kelly & Moen, 2021; Moen et al., 2011). This gap between policy intention and lived experience highlights the urgency of examining psychological and organizational mechanisms that enable women to effectively manage work and family demands (Sari, 2015). Emotional intelligence and place of business nicely-being are key elements that can affect an person’s ability to cope with strain and attain lifestyles balance (Paraswati et al., 2023; Zona, 2021). Emotional intelligence helps individuals manage stress, adapt to challenges, and balance various roles (Goleman & Intelligence, 1995). Meanwhile, workplace well-being relates to comfort and mental health in the workplace, which can foster employee engagement (Harter et al., 2003). Employee engagement itself is a mental kingdom reflecting personnel’ emotional, cognitive, and behavioral involvement in their work. High levels of employee engagement have been shown to improve work quality and reduce conflicts between professional and personal roles (Kahn, 1990). From a theoretical perspective, emotional intelligence and workplace well-being are frequently identified as key antecedents of work–life balance(Kinnary & Tanuwijaya, 2022). Emotional intelligence enables individuals to recognize, regulate, and utilize emotions in coping with role conflicts and work-related stress, while workplace well-being reflects the extent to which organizational conditions support employees’ physical and psychological health (Zafirah & Budiono, 2024). However, existing empirical findings remain inconclusive, particularly regarding the direct effect of workplace well-being on work–life balance (Putri & Hermiati, 2023). Several studies report non-significant or indirect relationships, suggesting the presence of mediating mechanisms that have not been sufficiently explored (Rashmi & Kataria, 2022; Rizal & Fipiariny, 2022). In this regard, employee engagement—representing employees’ cognitive, emotional, and behavioral involvement in their work—may serve as a crucial explanatory variable linking individual and organizational resources to work–life balance outcomes. Despite growing interest in these variables, there is a notable empirical gap in studies that simultaneously examine emotional intelligence, workplace well-being, and work–life balance through the mediating role of employee engagement, particularly within the context of married female civil servants in Indonesia (Warr, 2020). Most prior research has focused on private-sector employees or mixed-gender samples, thereby overlooking the unique structural and cultural challenges faced by women in the public sector. Addressing this gap, the present study investigates the influence of emotional intelligence and workplace well-being on work–life balance, with employee engagement as a mediating variable, among married female civil servants in the Government of Kediri City (Wasay, 2013). By situating the analysis within a gendered and public-sector context, this study aims to contribute theoretically to the work–life balance literature and practically to the development of more inclusive and genderresponsive human resource policies.

Emotional Intelligence Emotional intelligence refers to an person's ability to apprehend, apprehend, adjust, and manage their very personal emotions in addition to the ones of others (AlEdeinat, 2022; Salovey & Mayer, 1990; Serrat, 2017). states that emotional intelligence consists of five main dimensions:

self-cognizance, self-regulation, motivation, empathy, and social capabilities. Individuals with excessive emotional intelligence have a tendency to be better at handling work pressure, maintaining interpersonal relationships, and increasing job satisfaction and organizational commitment (Anand & UdayaSuriyan, 2010; Carmeli, 2003; Wulandari & Ratnaningsih, 2017). This makes emotional intelligence a vital thing in improving worker engagement and achieving workexistence balance.

Workplace Well-Being Workplace well-being refers to the sense of well-being experienced by individuals in their work environment, encompassing physical, psychological, and social aspects (Aryanti et al., 2020; Page, 2005). According to the WHO (Anderson et al., 2021), a healthy workplace is characterized by minimal fatigue and a high-quality environment that supports occupational health and safety. Factors such as organizational climate, quality of communication, job demands, and stress levels all influence workplace well-being (Aryanti et al., 2020). High place of work well-being can growth worker engagement, productivity, and loyalty (Harter et al., 2003; Schaufeli & Bakker, 2004).

Employee Engagement Employee engagement is defined because the emotional involvement and dedication of personnel inside the route of their work, contemplated in strength, self-discipline, and entire cognizance even as working (Kahn, 1990; Rich et al., 2010; Schaufeli & Bakker, 2004). Engagement reflects the volume to which personnel actively contribute to the company cognitively, affectively, and behaviorally (Shuck et al., 2014). Factors such as organizational support, two-way communication, training, and fairness in reward systems also influence degrees of employee engagement (Jha & Kumar, 2016).

Work-Life Balance Work-existence balance refers to a nation of equilibrium between an man or woman's roles of their professional and personal life, characterised by way of pleasure and minimum function war (Greenhaus et al., 2003; Hooja, 2018). This balance is important to prevent burnout, improve mental health, and support productivity and work commitment (T. D. Allen et al., 2000; Baker & Ibrahim, 2017; Bakker & Demerouti, 2008). Organizations that provide flexible work preparations, social help, and a conducive work surroundings play an vital position in supporting personnel gain work-existence balance (Hooja, 2018).

Hypothesis Development Emotional intelligence is vital for self-control and social courting abilties (Bradberry & Greaves, 2009; Ojo et al., 2021). Employees with better emotional intelligence are more likely to have better working-lifestyles balance due to the fact they could affect the feelings of others in this type of manner that they can preserve a satisfying non-public and expert existence (Goleman, 1995; Ojo et al., 2021). The higher the emotional intelligence, the better the work-life balance, particularly for female workers (Alshaabani et al., 2021). H1 : Emotional intelligence has a positive effect on work-life balance. Emotional intelligence is important for employees as it enables them to find appropriate solutions when facing changes (Barreiro & Treglown, 2020; Ravichandran et al., 2011) and to understand their own emotions and those of others, allowing them to manage negative emotions during social interactions or stressful situations (Barreiro & Treglown, 2020; Mahon et al., 2014). With emotional intelligence, employees are much more likely to sense engaged and captivated with their work, because of this fostering worker engagement (Barreiro & Treglown, 2020; Robbins & Judge, 2021). H2 : Emotional intelligence has a positive effect on employee engagement. Individuals with a high level of well-being are capable of building mutually supportive relationships and leading more meaningful lives (Bennett & Hammer, 2017). Workplace wellbeing can influence productivity and organizational performance (Murthy, 2022). In line with this, previous research shows that jobs with high demands may lead to a lack of organizational responsibility toward employees, resulting in exhaustion, anxiety, and adverse impacts on quality of life both in work and family settings (Arumdani & Churiyah, 2022). However, Smith & Smith (2021) argue that a multidimensional model of workplace well-being is still needed to measure job characteristics, work attitudes, and individual characteristics in order to define the expected concept of workplace well-being. H3 : Workplace well-being has a positive effect on work-life balance. H4 : Workplace well-being has a positive effect on employee engagement. Work-life balance and employee engagement are regarded as critical factors for organizational sustainability. An imbalance between work and private life increases pressure and can result in troubles both at working and in personnel' personal lives. employees' ability to gain workexistence balance with organizational assist need to result in more engagement, dedication, and activity performance. Research by Jaharuddin & Zainol (2019) suggests that there may be an influence between employee engagement and work-life balance. H5 : Employee engagement has a positive effect on work-life balance. Employee engagement is a effective emotional nation experienced with the aid of employees, characterized by way of pleasure and happiness, readiness to commit themselves to working at any time, and enjoyment of their work (Sun & Bunchapattanasakda, 2019; Yang et al., 2021). A positive emotional state can foster motivation, resilience in the face of frustration, impulse control, emotional regulation, empathy, and spiritual balance—all elements that reflect emotional intelligence (Goleman, 2015; Handayani & Zona, 2021). Emotional intelligence positively impacts work-life balance (Aryanti et al., 2020; Muthu et al., 2015; Takong et al., 2021; Ariawaty & Cahyani, 2019). H6 : Employee engagement positively mediates the relationship between emotional intelligence and work-life balance (Karamustafa & Kunday, 2018). Employee engagement is also viewed as the willingness and ability of employees to help the organization succeed, which includes rational and emotional (or "sensual") engagement. When a task affords financial rewards, professional talents, private improvement, and different benefits, personnel are more likely to feel rational engagement. Sensual engagement depends on worker pleasure and the sense of achievement they advantage from their position as organizational participants (Fang et al., 2010; Sun & Bunchapattanasakda, 2019). Therefore, organizations need systems that improve employee conditions, demonstrated by protecting and enhancing workers’ health, safety, well-being, and sustainability at work.. H7 : Employee engagement positively mediates the relationship between workplace well-being and work-life balance.

Methods

Type of Research This study employs a quantitative approach with an

explanatory research design to examine causal relationships between variables, specifically the influence of emotional intelligence and workplace well-being on work-life balance with employee engagement as a mediating variable. A quantitative approach is chosen to enable empirical measurement of the variables studied and statistical testing of hypotheses. The method used is a survey, in which data were collected through structured questionnaires to ensure consistency and ease of analysis. Population and Sample The population in this study consists of all married female civil servants in the Government of Kediri City. The sampling technique used is purposive sampling, with inclusion criteria as follows: (1) must be a civil servant, (2) must be a married female, and (3) must work at a government institution in Kediri City. A total of 98 respondents were involved in the study, determined using the Slovin formula with a 10% margin of error to ensure adequate representation. The sample was selected to focus the study on a group that specifically faces challenges related to work-life balance. Research Location The research was conducted within the Government of Kediri City, East Java, Indonesia. This location was selected based on its stable bureaucratic structure and significant number of married female civil servants, which provides a suitable context for exploring work-life balance issues within Indonesian work culture. Additionally, accessibility and institutional support for data collection were also taken into consideration. Instruments The primary instrument in this research is a closed-ended questionnaire designed using a modified Likert scale. I. E. Allen & Seaman (2007) suggest that researchers may simplify response categories into an even number (typically four), eliminating the “neutral” option. Garland (1991) also notes that removing the midpoint reduces social desirability bias, where respondents may otherwise select answers they think are favorable rather than those that reflect their actual opinions. Using a simplified Likert scale improves response consistency as the language becomes easier to understand (empirical reasons). Therefore, this study uses four response options: Always, Often, Sometimes, Never. The questionnaire is divided into four main sections to measure the relevant variables: First part is Emotional Intelligence, adapted from the scale developed by Goleman (1995), to evaluate an individual’s potential to apprehend, apprehend, and manage their personal and others' emotions. Second part is Workplace Well-being, adapted from the Gallup Workplace Well-being Index, to assess comfort, satisfaction, and perceived support in the work environment. Next, the third part is Employee Engagement, based on the Utrecht Work Engagement Scale (UWES), focusing on emotional and cognitive involvement in work. Finally, the fourth part is Work-Life Balance, developed using the scale from T. D. Allen et al. (2000), to assess the stability between work needs and personal life. Before being used for data collection, all questionnaire items were tested for validity using Corrected Item-Total Correlation (with a minimum threshold of Emotional Intelligence (X1) H1 H2 H6 Employee Engagement H5 Work-Life Balance H4 H7 Workplace Well-Being H3 (X2) Figure 1. Conceptual Thinking Framework > 0.30) and for reliability using Cronbach’s Alpha (with a minimum value of > 0.70) to ensure internal consistency and data accuracy. Data Collection Procedure Data were collected using two methods: offline and online surveys. The first stage involved preparation, including coordination with related agencies to obtain permission and access to potential respondents relevant to the research topic. The questionnaire was then distributed to respondents through two channels: directly (offline) at government offices, and digitally using Google Forms to reach a broader and more flexible respondent base. The questionnaire was filled out anonymously, with an estimated completion time of ±15 minutes per respondent, to maintain confidentiality and reduce response bias. After all data were collected, validation was performed by checking completeness and logical consistency of responses. Respondents who provided incomplete or inconsistent answers were excluded from the analysis to ensure the quality and accuracy of the data used. Data Analysis Data were analyzed using the Partial Least Squares - Structural Equation Modeling (PLS-SEM) method with the SmartPLS version 3.0 software. PLS-SEM was chosen for its strength in simultaneously testing inter-variable relationships and validating mediation models. This method is also considered appropriate for studies with relatively small sample sizes, as it provides robust results even when normal distribution assumptions are not fully met. The analysis process began with the measurement model test (outer model), aimed at testing the validity and reliability of indicators for each construct. Convergent validity was assessed using Average Variance Extracted (AVE), where an AVE value > 0.5 indicates that indicators adequately explain the construct. Discriminant validity was evaluated using the Fornell-Larcker criterion, which requires that each construct's correlation with its indicators must be higher than with other constructs. Once the measurement model was validated, the next step was the structural model test (inner model), to assess the strength and direction of relationships between latent variables. The coefficient of determination (R²) was used to determine how much influence the independent variables had on the dependent variables. Hypothesis testing was conducted using the bootstrapping technique with 500 resamples, with relationships considered significant if the tstatistic > 1.96 at a significance level of α = 5%. To test employee engagement as a mediating variable, indirect effect

(X3) (Y) significance was observed, where p-values < 0.05 indicate a significant mediation effect. This approach was expected to provide a comprehensive overview of the structural relationships in the proposed research model. Hypothesis Testing This study uses Path Coefficient Analysis to test hypotheses and assess the significance and strength of the relationships between constructs. The coefficient values range from -1 to +1, where values closer to +1 indicate strong positive relationships, while values closer to -1 indicate strong negative relationships (Furadantin, 2018; Sarstedt et al., 2017). The significance test was conducted with a 95% confidence level (α = 0.05) using a one-tailed approach, with a critical value of 1.645. The analysis includes both the measurement model (outer model) and the structural model (inner model), which together form a valid research model design.

Result and Discussion

Variable Descriptions Emotional Intelligence consists of two dimensions: Personal Competence and Social Competence, measured using five indicators based on a Likert scale completed by 97 respondents (see Table 1). The descriptive statistical analysis shows that all dimensions are categorized as “High” based on index scores. The highest index was found in Personal Competence (80.41%), and the lowest in Social Competence (78.00%). Workplace Well-being consists of Intrinsic and Extrinsic Dimensions, measured using 13 indicators. All dimensions were rated “High” by the respondents. The Extrinsic Dimension recorded the highest average index (82.38%), while the Intrinsic Dimension was slightly lower (75.31%) (see Table 2). Employee Engagement comprises Emotional, Behavioral, and Cognitive Engagement, measured through 14 items. The highest index was recorded in the Behavioral Engagement dimension (81.34%), while the lowest was in Cognitive Engagement (79.00%), with all dimensions falling into the “High” category (see Table 3). Work-Life Balance includes Time Balance, Involvement Balance, and Satisfaction Balance, with four indicators. The highest index was in Time Balance (84.02%), and the lowest was Satisfaction Balance (79.90%). All were categorized as “High” (see Table 4). Partial Least Square (PLS) Based on table 5, it shows that the outer loading value of each indicator shows a value > 0.7. Therefore, all indicators can be included in the study and do not need to be excluded from the research process. Based on Table 6, the cross loading value of each indicator used in this study, all indicators have a cross loading value Table 1. Respondents’ Perceptions of Emotional Intelligence (X1) Dimension Indicator Code Respondent's Answer Index Value Interpretation Always Often Sometimes Never KE 1 42 45 3 7 81,44% High KE 2 49 31 9 8 81,19% High KE 3 34 51 4 8 78,61% High Personal Competency Index Value 80,41% High Social Competence Personal Competency KE 4 43 37 11 6 80,15% High KE 5 36 42 13 6 77,84% High Social Competence Index Value 78,00% High Table 2. Respondents’ Perceptions of Workplace Well-being (X2) Respondent's Answer Index Value Interpretation Always Often Sometimes Never Dimension Indicator Code WWB 1 35 33 23 6 75% High

WWB 2 32 27 19 19 68,56% Medium

WWB 3 37 33 22 5 76,29% High

WWB 4 39 31 23 4 77,06% High

WWB 5 45 29 19 4 79,64% High

Intrinsic Dimension Index Value 75,31% High Intrinsic Dimensions WWB 6 39 48 9 1 82,22% High

WWB 7 38 31 24 4 76,55% High

WWB 8 38 44 14 1 80,67% High

WWB 9 44 49 2 2 84,79% High

WWB 10 44 48 4 1 84,79% High

WWB 11 41 41 14 1 81,44% High

WWB 12 46 38 12 1 83,25% High

WWB 13 51 36 9 1 85,31% High

Extrinsic Dimension Index Value 82,38% High Extrinsic Dimension Table 3. Respondents’ Perceptions of Employee Engagement (Y) Respondent's Answer Index Value Interpretation Always Often Sometimes Never Dimension Indicator Code EE 1 30 59 6 2 80,15% High EE 2 32 51 13 1 79,38% High EE 3 33 47 12 5 77,83% High EE 4 33 51 10 3 79,38% High EE 5 36 46 9 6 78,86% High Emotional Engagement Index Value 79,12% High Emotional Engagement EE 6 28 54 14 1 78,09% High EE 7 37 55 3 2 82,73% High EE 8 38 52 6 1 82,73% High EE 9 36 43 16 2 79,12% High EE 10 47 40 8 2 84,02% High Behavioral Engagement Index Value 81,34% High Behavioral Engagement EE 11 50 34 12 1 84,28% High EE 12 31 35 28 3 74,23% High EE 13 36 46 13 2 79,90% High EE 14 32 46 16 3 77,58% High Cognitive Engagement Index Value 79,00% High Cognitive Engagement Table 4. Respondents’ Perceptions of Work-Life Balance (Y) Respondent's Answer Index Value Interpretation Always Often Sometimes Never Time Balance WLB 1 45 44 6 2 84,02% High

Time Balance Index Value 84,02% High

Involvement Balance WLB 2 46 42 7 2 84,02% High

WLB 3 35 49 12 1 80,41% High

Involvement Balance Value 82,22% High

Satisfaction Balance WLB 4 35 47 14 1 79,90% High

Satisfaction Balance Index Value 79,90% High Dimension Indicator Code above 0.700 and have the highest correlation with their latent variables. Thus, no indicators need to be removed. Based on Table 7, the composite reliability value of all variables has a value above 0.700, this indicates that each

variable used in this study meets the standards. Thus, all indicators can be included in the study and do not need to be excluded from the research process. Based on Table 8. shows that all variables listed have Table 5. Outer Loading Values (SmartPLS Model) Num Indicator Outer Loading Inf Num Indicator Outer Loading Inf 1 WLB1 0,836 Valid 19 KE1 0,821 Valid 2 WLB2 0,792 Valid 20 KE2 0,877 Valid 3 WLB3 0,818 Valid 21 KE3 0,848 Valid 4 WLB4 0,779 Valid 22 KE4 0,856 Valid 5 EE1 0,804 Valid 23 KE5 0,859 Valid 6 EE2 0,821 Valid 24 WWB1 0,78 Valid 7 EE3 0,757 Valid 25 WWB2 0,75 Valid 8 EE4 0,762 Valid 26 WWB3 0,823 Valid 9 EE5 0,716 Valid 27 WWB4 0,821 Valid 10 EE6 0,823 Valid 28 WWB5 0,796 Valid 11 EE7 0,781 Valid 29 WWB6 0,832 Valid 12 EE8 0,748 Valid 30 WWB7 0,775 Valid 13 EE9 0,783 Valid 31 WWB8 0,808 Valid 14 EE10 0,734 Valid 32 WWB9 0,822 Valid 15 EE11 0,769 Valid 33 WWB10 0,814 Valid 16 EE12 0,72 Valid 34 WWB11 0,821 Valid 17 EE13 0,845 Valid 35 WWB12 0,808 Valid 18 EE14 0,709 Valid 36 WWB13 0,747 Valid Table 6. Cross Loading Results Indicator Employee Engagement Emotional Intelligence Workplace Well-Being EE1 0,804 0,490 0,553 0,520 EE2 0,821 0,575 0,565 0,482 EE3 0,757 0,559 0,540 0,416 EE4 0,762 0,446 0,511 0,470 EE5 0,716 0,538 0,451 0,359 EE6 0,823 0,484 0,572 0,560 EE7 0,781 0,476 0,562 0,492 EE8 0,748 0,478 0,618 0,506 EE9 0,783 0,523 0,508 0,496 EE10 0,734 0,382 0,508 0,345 EE11 0,769 0,581 0,606 0,446 EE12 0,720 0,511 0,456 0,524 EE13 0,845 0,578 0,583 0,486 EE14 0,709 0,419 0,504 0,322 KE1 0,481 0,821 0,523 0,360 KE2 0,630 0,877 0,654 0,412 KE3 0,564 0,848 0,689 0,437 KE4 0,514 0,856 0,621 0,338 KE5 0,587 0,859 0,701 0,459 WLB1 0,556 0,560 0,836 0,296 WLB2 0,552 0,600 0,792 0,293 WLB3 0,592 0,631 0,818 0,525 WLB4 0,559 0,634 0,779 0,473 WWB1 0,491 0,360 0,403 0,780 WWB2 0,467 0,295 0,322 0,750 WWB3 0,468 0,274 0,336 0,823 WWB4 0,403 0,297 0,375 0,821 WWB5 0,512 0,457 0,473 0,796 WWB6 0,469 0,418 0,443 0,832 WWB7 0,449 0,305 0,280 0,775 WWB8 0,461 0,367 0,449 0,808 WWB9 0,554 0,487 0,495 0,822 WWB10 0,552 0,466 0,439 0,814 WWB11 0,451 0,344 0,372 0,821 WWB12 0,439 0,372 0,316 0,808 WWB13 0,475 0,412 0,395 0,747

Work-Life Balance Table 7. Composite Reliability Variable Composite Reliability Work-Life Balance 0,882 Employee Engagement 0,953 Emotional Intelligence 0,930 Workplace Well-Being 0,959 Table 8. Cronbach’s Alpha Variable Cronbach's Alpha Work-Life Balance 0,821 Employee Engagement 0,947 Emotional Intelligence 0,906 Workplace Well-Being 0,953 Table 9. R-Square Results Variable R Square R Square Adjusted Work-Life Balance 0,645 0,634 Employee Engagement 0,538 0,528 Table 10. Q-Square Predictive Relevance Variable Q Square Work-Life Balance 0,406 Employee Engagement 0,296 values above 0.7. Therefore, all variables applied in this study show a consistent level of consistency in each measurement. Thus, all indicators can be included in the study and do not need to be excluded from the research process. Based on the results of the R Square test in Table 9, it can be concluded that the dependent variable Work-Life Balance is influenced by its independent variables by 0.645 or 64.5%. Meanwhile, the remaining 35.5% is influenced by other factors that are not included in the scope of this study. Then, the intervening variable Employee Engagement is influenced by its independent variables by 0.538 or 53.8%. Meanwhile, the remaining 46.2% is influenced by other factors that are not included in the scope of this study. From table 10, it can be seen that the Q Square value on the Work-Life Balance variable is 0.406 > 0, so it can be concluded that the independent variable is able to explain the Work-Life Balance variable. Furthermore, the Q Square value on the Employee Engagement variable has a value of 0.296 > 0, meaning that the independent variable is able to predict Employee Engagement well. Hypothesis Testing Based on the results of the hypothesis testing shown in Table 11, of the seven relationships between variables tested in the research model, six of them showed a positive and significant influence, while one relationship was declared insignificant. First, the variable Emotional Intelligence is proven to have a positive and significant effect on Work-Life Balance with a coefficient value of 0.507, a t-statistic value of 4.585, and a p-value of 0.000. This shows that the higher a person's emotional intelligence, the better the balance between work life and personal life. Furthermore, Emotional Intelligence also has a significant positive effect on Employee Engagement with a coefficient value of 0.479, a t-statistic of 5.081, and a p-value of 0.000. This means that individuals with high emotional intelligence tend to have better work engagement. However, unlike the two previous relationships, the Workplace Well-Being variable does not have a significant effect on Work-Life Balance. This can be seen from the low coefficient value, which is 0.056, the t-statistic is only 0.428, and the p-value is 0.334 which exceeds the significance limit

of 0.05. Thus, this hypothesis is rejected because it is not statistically supported. Meanwhile, the relationship between Workplace Well-Being and Employee Engagement shows a positive and significant effect, with a coefficient of 0.373, a tstatistic of 4.537, and a p-value of 0.000. This shows that a work environment that supports employee well-being can increase their involvement in work. Furthermore, Employee Engagement is proven to have a positive and significant influence on Work-Life Balance with a coefficient of 0.335, t-statistic of 2.860, and p-value of 0.002. This indicates that employees who are actively involved in their work tend to be able to balance their work and personal lives better. In addition, the Emotional Intelligence variable also has an indirect influence through Employee Engagement on WorkLife Balance with a coefficient of 0.161, t-statistic of 2.297, and p-value of 0.011, which means significant. Finally, Workplace Well-Being also has an indirect influence on Work-Life Balance through Employee Engagement with a coefficient of 0.125, tstatistic of 1.984, and p-value of 0.024, which shows a significant relationship although weaker than other variables. The findings of this study provide several important insights into the determinants of work–life balance among married female civil servants in Kediri City. Consistent with prior research, emotional intelligence was found to have a significant positive effect on both work–life balance and employee engagement. This result underscores the role of emotional regulation, empathy, and social skills in enabling women to navigate competing work and family demands. In line with selfregulation perspectives, emotionally intelligent employees are better equipped to manage stress, resolve interpersonal conflicts, and allocate psychological resources across multiple roles, thereby achieving a more balanced life arrangement. While these findings confirm the importance of individual psychological resources, the results also reveal a more complex pattern concerning organizational factors. In particular, the non-significant direct effect of workplace well-being on work– life balance warrants deeper examination. Rather than treating this result as merely supportive of prior studies, it is essential to interpret it within the specific organizational, cultural, and technological context of married female civil servants in the Government of Kediri City. In contrast, workplace well-being did not exhibit a significant direct effect on work–life balance. Although workplace well-being generally reflects health support, job security, and comfort at work, these conditions do not automatically reduce work–family conflict in the public sector context (Odle-Dusseau et al., 2018). For married female civil servants, high job security and supportive facilities may increase work attachment without alleviating domestic responsibilities. Moreover, the increasing digitalization of public services in Kediri City enables employees to access work systems beyond formal working hours, thereby blurring the boundaries between work and personal life. As a result, workplace well-being initiatives that emphasize stability and accessibility may paradoxically intensify role overlap rather than promote balance. This finding also reflects broader organizational norms within the civil service, where informal expectations often prioritize responsiveness and task completion over strict time boundaries. Despite formal regulations supporting work–family balance, unwritten rules and performance pressures may limit employees’ ability to disengage from work roles. Consequently, workplace well-being functions more as a condition that sustains performance rather than as a direct mechanism for achieving work–life balance. Importantly, the mediating role of employee engagement offers a more nuanced explanation of this relationship. The results demonstrate that workplace well-being positively influences employee engagement, which in turn enhances work–life balance. This suggests that organizational support Table 11. Hypothesis Testing Summary Original Sample T Statistics Hypothesis Path (O/STDEV) P Values Effect

Conclusion

(O) Emotional Intelligence -> Work-Life Balance 0,507 4,585 0,000 Positive Effect Hypothesis Accepted Emotional Intelligence -> Employee Engagement 0,479 5,081 0,000 Positive Effect Hypothesis Accepted Workplace Well-Being -> Work-Life Balance 0,056 0,428 0,334 No Significant Effect Hypothesis Rejected Workplace Well-Being -> Employee Engagement 0,373 4,537 0,000 Positive Effect Hypothesis Accepted Employee Engagement -> Work-Life Balance 0,335 2,860 0,002 Positive Effect Hypothesis Accepted Emotional Intelligence -> Employee Engagement -> Work-Life Balance 0,161 2,297 0,011 Positive Mediation Hypothesis Accepted Workplace Well-Being -> Employee Engagement -> Work-Life Balance 0,125 1,984 0,024 Positive Mediation Hypothesis contributes to work–life balance only when it fosters meaningful psychological involvement and a sense of purpose at work. In other words, workplace well-being becomes effective when it translates into engagement rather than remaining a passive organizational condition (Ananda & Oktariani, 2022). This finding extends existing engagement theory by highlighting its bridging role between structural support and personal life outcomes, particularly in publicsector settings characterized by strong performance accountability. From a theoretical standpoint, this study contributes to the literature by reinforcing mediation-based models of work– life balance within a gendered and public-sector context. The findings suggest that individual resources (emotional intelligence) and organizational resources (workplace wellbeing) do not operate in isolation but interact through employee engagement as a critical psychological mechanism. Practically, these results imply that government institutions should move beyond general well-being programs and focus on strengthening employee engagement through participative leadership, realistic performance targets, and emotionally supportive work environments. Such strategies may enable married female civil servants to experience not only better work performance but also a more sustainable balance between professional and personal roles. Conclusion This study concludes that emotional intelligence plays a pivotal role in enhancing work–life balance among married female civil servants in the Government of Kediri City, both

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