1 Introduction

In the contemporary educational landscape, the pivotal role of teachers in creating the future is universally recognized [1]. Additionally, this recognition provides an understanding of the important role that training programs play in the professional development of teachers [2]. These programs serve not only to enhance teachers' skills but also to equip them with the tools necessary for effective teaching [3]. Within the complex web of educational institutions, this study highlights the critical aspect of the teaching profession, i.e., the impact of training programs on maintaining work-life balance, particularly for women employees in secondary schools.

Durg, situated in Chhattisgarh, stands out as a significant educational hub boasting 758 schools representing diverse educational boards such as CGBSE, CBSE, and ICSE [4]. Within this educational landscape, both public and private institutions coexist, adding layers of complexity to the system [5]. Therefore, emphasizing the critical importance of continuous teacher development, the research highlights the significance of these training programs within the framework of ongoing educational reconstruction efforts.

One notable initiative in this realm is the Centrally Sponsored Scheme of Restructuring and Reorganization of Teacher Education (CSSTE), along with subsequent efforts like Samagra Shiksha [6,7,8]. These initiatives demonstrate a commitment to enhancing the professional competence of teachers, recognizing it as crucial for educational reform. Among these efforts, the National Initiative for School Heads’ and Teachers’ Holistic Advancement (NISHTHA), launched in 2019–20, stands out as the world’s largest teacher training program [6, 9]. With a focus on capacity building, NISHTHA aims to elevate learning outcomes at the elementary level by addressing a wide array of areas including pedagogy, child development, information and communication technologies (ICT), art-integrated learning, and social-emotional skills [9, 10].

However, the advent of the ongoing global pandemic has forced a re-evaluation of traditional modes of teacher training, leading initiatives like NISHTHA to transition to an online platform known as DIKSHA [11]. This shift raises important questions about the efficacy of online training compared to traditional face-to-face methods. As the educational sector adapts to these changes, it becomes imperative to explore the impact of these training programs, specifically on the work-life balance of women employees in secondary schools [12, 13]. Similarly, emotional intelligence and stress management are increasingly recognized as crucial competencies for navigating the complexities of modern work environments [14, 22]. Yet, their influence on work-life balance, particularly within the context of education, warrants further investigation. Moreover, the significance of a supportive work environment in shaping teachers' experiences and perceptions of work-life balance cannot be overstated [15, 16].

Based on the above, with employing the Partial Least Squares Structural Equation Modeling (PLS-SEM), the main objective of this study is to investigate the factors influencing work-life balance among women teachers in secondary schools in Durg district, Chhattisgarh, with a focus on the role of training programs, emotional intelligence, stress management and supportive work environments. In this study, the dependent variable is work-life balance, while the independent variable is the training program. Additionally, emotional intelligence and stress management serve as mediating variables, while a supportive work environment acts as a moderating variable. Through this comprehensive analysis, the study aims to offer insights that can inform policies and practices, ultimately better supporting and empowering women educators in their multifaceted roles. The rest of the paper is organized as follows; (1) Sect. 2 provides the critical review of literature along with research gaps and conceptual framework of the study; (2) Sect. 3 provides the process of scale development and validation to finalize the questionnaire; (3) Sect. 4 provides the detailed methodology to analyse the relationship among study’s variables; (4) Sect. 5 presents the obtained results; (5) Sect. 6 provides the detailed discussion over results; and (6) finally Sect. 7 provides the conclusions, limitations and recommendations for future researches.

2 Literature review and hypotheses development

The literature review serves as a comprehensive exploration of key dimensions influencing the professional lives of educators, with a particular focus on women educators in secondary schools. Based on the variables of the study, the critical review of past researches is given below;

2.1 Training program

Training programs are fundamental to the professional development of educators [17]. These programs serve as vital channels for skill enhancement and pedagogical advancement, addressing the evolving needs of the education landscape [2]. Initiatives such as CSSTE exemplify efforts to bolster teacher competence and elevate educational standards, while NISHTHA stands as a testament to the scale and scope of endeavors aimed at enhancing pedagogical practices and improving learning outcomes [3, 5, 18]. Despite challenges such as the global pandemic prompting a shift to online platforms like DIKSHA, the adaptability of these training initiatives underscores their significance in equipping educators with the necessary knowledge and skills [11]. In the context of maintaining work-life balance for women employees in secondary schools, training programs play a multifaceted role beyond imparting pedagogical knowledge [19]. They equip educators with time-management techniques, stress-reduction strategies, and coping mechanisms necessary for balancing professional responsibilities with personal commitments, thereby contributing to overall well-being and job satisfaction [2, 20, 21].

2.2 Stress management

Stress management is paramount in the teaching profession, which inherently involves high levels of pressure and demands [22]. Educators, including women employees in secondary schools, often face stress ranging from heavy workloads to challenging student behaviour [23]. Effective stress management strategies are essential for maintaining teacher well-being, job satisfaction, and ultimately, the quality of education provided [24]. Previous researches indicate that the teachers who are able to manage stress effectively are more likely to experience higher levels of job satisfaction and overall well-being [13].

For women educators, who may juggle multiple roles and responsibilities both at work and home, effective stress management becomes even more crucial [12]. The ability to cope with stress not only impacts their professional performance but also influences their personal lives [13]. Stress management techniques such as mindfulness, relaxation exercises, time management skills, and seeking social support are vital for women educators to navigate the myriad challenges they face in their daily lives [1, 25]. Moreover, fostering a supportive work environment where educators feel valued and supported in managing their stress can significantly contribute to their overall well-being [26, 27].

In the context of this study, exploring the role of stress management within training programs for women employees in secondary schools is essential. By incorporating stress management strategies into professional development initiatives, educational authorities can better equip educators with the tools and resources needed to cope with the demands of their profession [28]. Additionally, understanding the effectiveness of stress management interventions within the training context can provide valuable insights for designing targeted programs that address the unique stressors faced by women educators [29]. Ultimately, prioritizing stress management within training programs not only enhances the well-being of educators but also contributes to the creation of a more positive and supportive educational environment for both teachers and students [30].

2.3 Emotional intelligence

Emotional intelligence (EI) plays a pivotal role in the effectiveness and job satisfaction of educators, particularly women employees in secondary schools [14]. EI encompasses the ability to recognize, understand, manage, and effectively use one's own emotions, as well as respond to the emotions of others [31]. Previous researches suggest that the teachers with high levels of emotional intelligence are better equipped to handle the diverse challenges they encounter in the classroom, leading to improved classroom dynamics and student outcomes [32,33,34].

For women educators, who often navigate complex interpersonal relationships and diverse student needs, emotional intelligence is especially crucial [35]. It enables them to empathize with their students, understand their perspectives, and effectively manage classroom conflicts [36]. Furthermore, emotional intelligence empowers educators to regulate their own emotions, remain calm in challenging situations, and foster a positive and supportive learning environment [37].

In the context of this study, exploring the role of emotional intelligence within training programs for women employees in secondary schools is essential. By incorporating modules focused on emotional intelligence development, training programs can enhance educators' ability to understand and manage their emotions, as well as those of their students [38]. This, in turn, can contribute to improved teacher-student relationships, increased job satisfaction, and ultimately, better educational outcomes [39]. Additionally, understanding how emotional intelligence mediates the relationship between training programs and work-life balance can provide valuable insights for designing targeted interventions that support the holistic well-being of women educators [14, 31, 40].

2.4 Supporting work environment

A supportive work environment is paramount for the job satisfaction, well-being, and overall effectiveness of educators, including women employees in secondary schools [15, 41, 42]. This environment encompasses factors such as positive leadership, collaborative relationships, recognition of contributions, and opportunities for professional growth [16, 43]. Previous researches indicate that teachers who perceive their work environment as supportive are more likely to experience higher levels of job satisfaction, engagement, and commitment to their profession [44, 45].

For women educators, a supportive work environment is particularly crucial as they may face unique challenges such as balancing multiple roles and responsibilities both at work and home [46]. A supportive work environment can provide the necessary resources, encouragement, and flexibility to help women educators thrive in their professional roles while managing their personal commitments [47]. Moreover, a positive work environment can foster a sense of belonging and camaraderie among educators, reducing feelings of isolation and burnout [48].

In the context of this study, exploring the role of a supportive work environment in maintaining work-life balance for women employees in secondary schools is essential. Understanding how organizational practices and culture influence educators’ perceptions of support can provide valuable insights for creating conducive work environments [49]. Additionally, identifying strategies to enhance support within the workplace, such as mentorship programs, professional development opportunities, and flexible work arrangements, can contribute to the well-being and retention of women educators [42]. Ultimately, prioritizing a supportive work environment not only benefits individual educators but also contributes to the overall success and effectiveness of the educational institution [41, 42, 45, 46].

2.5 Work-life balance

Work-life balance is a critical factor influencing the overall well-being, job satisfaction, and retention of educators, particularly women employees in secondary schools [3, 5]. It refers to the perceived equilibrium between professional responsibilities and personal life commitments, including satisfaction with this balance [18]. Achieving work-life balance can be particularly challenging for women educators who may face additional responsibilities related to caregiving, household duties, and familial obligations [19]. Previous researches indicate that the educators who perceive a better balance between their work and personal lives are more likely to experience higher levels of job satisfaction, lower levels of stress, and greater overall well-being [2, 18, 50]. Conversely, experiencing conflict between work and personal life can lead to feelings of burnout, exhaustion, and reduced job satisfaction [20, 21].

In the context of this study, understanding the factors that contribute to work-life balance for women employees in secondary schools is essential. Factors such as the availability of supportive work environments, effective stress management strategies, access to flexible work arrangements, and opportunities for professional development and advancement can all influence educators’ ability to balance their professional responsibilities with their personal lives [32, 33, 36]. Additionally, exploring how training programs, emotional intelligence, and stress management strategies impact work-life balance can provide valuable insights for designing interventions and policies that support the holistic well-being of women educators [51, 52]. By prioritizing work-life balance and addressing the unique challenges faced by women educators, educational institutions can create environments that promote job satisfaction, retention, and ultimately, the success of both educators and students [53, 54].

Based on the variables of the study, following hypotheses are proposed;

H1: There is significant direct positive relationship between TP and WLB.

H2: There is significant direct positive relationship between TP and EI.

H3: There is significant direct positive relationship between TP and SM.

H4: There is significant direct positive relationship between EI and WLB.

H5: There is significant direct positive relationship between SM and WLB.

H6: EI significantly mediates the relationship between TP and WLB.

H7: SM significantly mediates the relationship between TP and WLB.

H8: SWE significantly moderates the relationship between TP and WLB.

2.6 Research gaps and measurement model

Despite extensive research on various aspects of teacher training, stress management, emotional intelligence, supportive work environments, and work-life balance individually, there is a notable gap in the literature regarding comprehensive models that integrate all these factors within the context of women employees in secondary schools. Above existing studies often focus on isolated aspects or limited combinations of these variables, failing to capture the complex interplay and synergistic effects among them. Additionally, while there is ample research on the impact of these factors on teacher well-being and job satisfaction, there is a dearth of studies specifically exploring their influence on work-life balance, especially concerning women educators. Moreover, most existing studies are conducted in Western contexts, and there is a lack of research examining these dynamics within diverse cultural and educational settings, such as secondary schools in regions like Durg, Chhattisgarh, India. Therefore, there is a pressing need for empirical research that addresses these gaps and provides a comprehensive understanding of the factors influencing work-life balance among women employees in secondary schools, particularly within the Indian context.

With considering the variables of study (Table 1), as shown in Fig. 1, the conceptual framework of the study illustrates the interrelationships among the key constructs: Training Program (TP), Emotional Intelligence (EI), Stress Management (SM), Supportive Work Environment (SWE), and Work-Life Balance (WLB). The framework posits that training programs act as the primary driver, directly influencing emotional intelligence, stress management, and work-life balance among women employees in secondary schools. Emotional intelligence and stress management are depicted as mediating variables through which training programs impact work-life balance. Additionally, supportive work environment is conceptualized as a moderating variable that influences the strength and direction of the relationship between training programs and work-life balance.

Table 1 Constructs and variables of the study
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Fig. 1
figure 1

Measurement Model

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2.7 Underpinning theory

This study utilizes Social Exchange Theory (SET) and Conservation of Resources Theory (COR) to support the research model and hypotheses. SET posits that social behavior results from an exchange process where individuals seek to maximize benefits and minimize costs. When schools invest in training programs, stress management resources, and a supportive work environment, women educators reciprocate with increased job satisfaction and improved work-life balance [55]. COR theory postulates that individuals strive to obtain, retain, and protect their resources, with stress occurring when these resources are threatened or depleted. Training programs that enhance resources such as emotional intelligence and stress management skills help educators cope with job demands more effectively, thus reducing stress and improving overall well-being [55]. Together, these theories provide a robust foundation for understanding the relationships among the variables in this study.

3 Scale development and validation

3.1 Initial questionnaire development

Building on insights from the literature review, a comprehensive 98-item questionnaire was initially crafted to capture the multifaceted aspects of teacher training programs, stress management, emotional intelligence, supportive work environments, and work-life balance. The relevance of each item was evaluated through expert reviews using a 1–4 scale, where 1 and 2 indicated low relevance, and 3 and 4 indicated high relevance. The Content Validity Ratio (CVR) formula was applied to assess item relevance [56].

$$CVR = \frac{{N_{e} - \frac{N}{2}}}{\frac{N}{2}}$$
(1)

where:

\({N}_{e}\) is the number of experts indicating “3” or “4” (items rated as highly relevant), and N is the total number of experts. Items with CVR scores equal to or above the predetermined 0.5 cut-off value were retained, ensuring that only items deemed sufficiently relevant by the experts remained in the questionnaire. This meticulous process led to the retention of 72 items, reflecting both theoretical relevance and expert consensus.

3.2 Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)

A subsequent survey involving 128 teachers facilitated both Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). EFA aimed to unveil the latent factor structure and dimensions of the retained items, leading to further questionnaire refinement. In EFA, key indicators such as factor loadings, communalities, and eigenvalues were utilized to uncover the latent factor structure and refine the questionnaire by eliminating items with low factor loadings or cross-loadings. This resulted in a reduced set of 65 items. Subsequently, CFA was performed to validate the factor structure identified through EFA. In CFA, essential indicators including factor loadings, standardized residuals, modification indices, and goodness-of-fit indices such as CFI, TLI, and RMSEA were pivotal for validating the factor structure identified through EFA and ensuring coherent constructs with robust covariance patterns. The CFA process further refined the questionnaire, retaining 49 items displaying robust factor loadings and covariance patterns.

3.3 Test–retest reliability and discriminant validity

A third survey, with a 40-day gap, was conducted to assess the stability and reliability of the finalized questionnaire. Test–retest reliability was computed by administering the questionnaire to a subset of the original sample, demonstrating consistent responses over time. Discriminant validity was established by analyzing construct correlations to ensure the questionnaire effectively distinguished between various study variables.

3.4 Final validated questionnaire

The rigorous process of item development, exploratory and confirmatory factor analyses, and reliability testing led to the creation of a valid and reliable questionnaire consisting of 49 items. Table 3 in result and discussion part of paper provides the distribution of items across each dimension. These items comprehensively cover the dimensions of teacher training programs, stress management, emotional intelligence, supportive work environments, and work-life balance. The final questionnaire not only reflects the theoretical foundations derived from the literature review but also incorporates empirical evidence of construct validity, reliability, and discriminant validity through robust statistical analyses.

4 Research methodology

4.1 Research design

The research design adopted for this study is descriptive research design that follows a cross-sectional approach, allowing for the collection of data from women teachers in secondary schools at a specific point in time [57]. This design facilitates the investigation of various factors influencing work-life balance, including training programs, emotional intelligence, stress management, and supportive work environments, within a specific timeframe. By capturing data at a particular moment, the study provides insights into the current state of work-life balance among women educators and explore associations between these factors and work-life balance perceptions.

4.2 Population and sampling

The population under consideration for this study comprises women teachers in secondary schools located in Durg district, Chhattisgarh. The calculation of the required sample size (no) in this study follows Cochran's formula [58], as expressed in Eq. (2):

$${n}_{o}= \frac{{z}^{2}pq}{{e}^{2}}$$
(2)

This formula, denoted by Eq. (2), incorporates a 95% confidence level, corresponding to a standard normal deviation (z) of 1.96, a 5% margin of error (e = 0.05), and a degree of population variability (p) set at 0.5 to accommodate maximum variability. The complementary probability, q, is calculated as 0.5 (1–p). By substituting these specified values into Cochran's formula, the study determined that the minimum required sample size is 384.

The study utilized stratified sampling to ensure representation across demographic variables among women teachers in secondary schools in Durg district, Chhattisgarh. This approach involved dividing the population into strata based on key factors like age, experience, school type, and educational board, then randomly selecting respondents from each group. By employing this method, the study aimed to enhance generalizability and minimize biases associated with sample selection.

4.3 Data collection

Data for the research study were collected via an online Google Form over the period from July to December 2023. Participants were approached through a combination of methods, including email invitations and dissemination of survey links through social media platforms frequented by teachers. This approach facilitated efficient and organized data collection, ensuring accessibility and timely responses from the target population. Out of 505 forms distributed, 471 responses were received, with 422 deemed suitable for analysis after screening for correctness and completeness. The online platform provided participants with convenience and flexibility in completing the survey, contributing to a diverse and representative sample. Overall, Google Forms facilitated high-quality data collection, supporting the validity and reliability of the study findings by offering a user-friendly interface and real-time monitoring capabilities, which streamlined data collection, minimized errors, and ensured participant accessibility.

4.4 Data analysis

The data obtained were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). PLS-SEM is a robust statistical technique suitable for exploring complex relationships within the proposed conceptual framework [59]. This method allowed for the examination of direct and indirect effects, making it particularly appropriate for investigating the interplay between training programs, emotional intelligence, stress management, a supportive work environment, and work-life balance. The use of PLS-SEM aligned with the study’s aim to unravel the intricate dynamics of these components and offer insights that could inform policies and practices supporting women educators. Additionally, SPSS (Statistical Package for the Social Sciences) was used for preliminary data screening, descriptive statistics, and initial analyses to explore relationships among variables before conducting the PLS-SEM analysis.

5 Results and discussion

In the questionnaire survey, a total 422 responses were collected. The analysis of collected responses is discussion in subsequent sub-sections;

5.1 General information of respondents

Table 2 presents the demographic information of the respondents, offering insights into the characteristics of women teachers in secondary schools in Durg district, Chhattisgarh. The respondents are distributed across various age groups, with 20.9% falling within the 18–30 years bracket, 27.5% in the 30–40 years category, 26.5% in the 40–50 years range, and 25.1% aged more than 50 years. In terms of experience, 23.2% have 0–5 years, 26.5% have 5–10 years, 25.4% have 10–15 years, and 24.9% have more than 15 years of teaching experience. Regarding the type of school, the study encompasses a balanced representation, with 50.7% from public schools and 49.3% from private schools. The location of schools is distributed between rural (46.2%) and urban (53.8%) settings, reflecting the diversity of educational environments in the district. The distribution of schools based on the educational board is almost equal, with 49.1% affiliated with the CG Board and 50.9% with the CBSE Board. Finally, respondents were asked to assess the quality of the training programs they attended. The majority (55.9%) agreed, and 28.4% strongly agreed that the quality of the training programs was satisfactory. A smaller proportion expressed disagreement, with 6.9% disagreeing and 2.4% strongly disagreeing, while 6.4% remained neutral on this aspect.

Table 2 General Information of Respondents
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5.2 Internal consistency and convergent validity of constructs

Table 3 presents the internal consistency and convergent validity of the constructs measured in the study. Internal consistency is assessed using Cronbach's alpha coefficient, while composite reliability (rho_a) provides an alternative measure of internal consistency. Composite reliability (rho_c) reflects the reliability of the constructs in the context of structural equation modeling. Average Variance Extracted (AVE) assesses convergent validity by measuring the variance captured by the constructs relative to the measurement error.

Table 3 Internal consistency and convergent validity of constructs
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The constructs demonstrate strong internal consistency, with Cronbach's alpha coefficients ranging from 0.744 to 0.934. Composite reliability values (rho_a and rho_c) further confirm the reliability of the constructs, with all values exceeding the recommended threshold of 0.70 [60]. Average Variance Extracted (AVE) values range from 0.569 to 0.829, indicating satisfactory convergent validity as they surpass the threshold of 0.50 [57]. These results suggest that the measurement items reliably measure their respective constructs and capture a substantial proportion of variance, supporting the validity and reliability of the measurement model employed in the study.

Table 4 displays Heterotrait-Monotrait (HTMT) ratios to evaluate discriminant validity among the study constructs. Diagonal elements exhibit perfect correlations (HTMT = 1), representing the comparison of a construct with itself. Off-diagonal elements generally have HTMT values below the commonly accepted threshold of 0.85, indicating good discriminant validity [59]. The HTMT values range from 0.052 to 0.819, suggesting distinguishability between constructs with relatively low shared variances. Notably, “Training Program (TP)” displays higher correlations with constructs like “Supportive Work Environment (SWE)” and “Stress Management (SM),” but all HTMT ratios are below the threshold. “SWE x TP” also maintains a value (0.361) within acceptable limits. These findings affirm the satisfactory discriminant validity of the measurement model, supporting the robustness of the study's constructs in capturing distinct dimensions of the variables.

Table 4 Discriminant Validity–Heterotrait-Monotrait (HTMT) ratio
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5.3 Descriptive analysis of constructs

Table 5 presents the descriptive statistics of the study constructs, providing insights into the distribution and central tendencies of the measured variables. The range indicates the span between the minimum and maximum values, reflecting the variability within each construct. The minimum and maximum values represent the extremes observed in the dataset. The mean signifies the average score across respondents, while the standard deviation measures the degree of dispersion or variability around the mean.

Table 5 Descriptive statistics of constructs
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The “Training Program (TP)” construct exhibits a range of 4.00, with scores ranging from 1.00 to 5.00. The mean is 3.5787, suggesting a moderate level of agreement or satisfaction among respondents, with a standard deviation of 0.82883 indicating some variability in responses.

Similarly, “Stress Resilience (SR),” “Social Skills (SS), “Self-Regulation (SR)” “Empathy Index (EPI),” “Stress Tolerance (ST),” “Stress Reduction (SRD),” “Supportive Work Environment (SWE),” and “Work Interference with Personal Life (WIPL)” show ranges of 4.00, with means ranging from 3.2978 to 3.5746, indicating moderate to high average scores and moderate variability. “Personal Life Interference with Work (PLIW)” has a narrower range of 3.25, reflecting less variability, and a mean of 4.0746, suggesting a higher level of agreement or occurrence among respondents, with a standard deviation of 0.72251 indicating relatively low variability. “Work or Personal Life Enhancement (WPLE)” has a range of 4.00, a mean of 3.5611, and a standard deviation of 0.97289, indicating moderate variability in responses. “Emotional Intelligence (EI)” and “Stress Management (SM)” both have ranges of 4.00, with means of 3.4388 and 3.3169, respectively, suggesting moderate average scores and moderate variability. “Work-Life Balance (WLB)” has a range of 3.00, reflecting a narrower span, a mean of 3.9103, indicating a relatively high average score, and a standard deviation of 0.61011, suggesting low variability in responses. These descriptive statistics offer a comprehensive overview of the central tendencies and distribution characteristics of the study variables.

The descriptive statistics for various constructs in Table 6 reveal consistent trends across items. For constructs such as Training Program (TP), Self-Regulation (SR), Social Skills (SS), Empathy Index (EPI), Stress Reduction (SRD), and Stress Resilience (SRL), mean values generally hover around 4, indicating positive responses. Standard deviations are mostly around 1, suggesting moderate variability. Skewness values predominantly indicate left-skewed distributions, reflecting higher frequency of high scores. Factor loadings are generally strong, with most above 0.7, and VIF values are all below the cutoff of 5, indicating no severe multicollinearity issues.

Table 6 Descriptive statistics of items
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5.4 Correlation analysis between constructs

The Table 7 presents the correlation analysis between constructs, including Emotional Intelligence (EI), Stress Management (SM), Work-Life Balance (WLB), Training Program (TP), and Supportive Work Environment (SWE). Each cell shows the Pearson correlation coefficient between the corresponding constructs, along with the p-value indicating the significance level. All correlations are significant at the 0.01 level (2-tailed), indicating strong relationships between the variables. For example, EI has a high positive correlation with both SM (r = 0.876) and SWE (r = 0.835), suggesting that higher levels of emotional intelligence are associated with better stress management and a more supportive work environment. Similarly, SM shows a strong positive correlation with TP (r = 0.510) and SWE (r = 0.888), indicating that effective stress management is linked to participation in training programs and supportive work environments. These correlations provide valuable insights into the interrelationships among key constructs in the study.

Table 7 Correlation analysis between constructs
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5.5 Multiple linear regression analysis

As shown in Table 8, the multiple linear regression analysis conducted with the independent variables Training Program (TP), Emotional Intelligence (EI), Stress Management (SM), and Supportive Work Environment (SWE) predicting the dependent variable Work-Life Balance (WLB) yielded significant results. The regression model showed a strong relationship between the independent and dependent variables, as evidenced by the high coefficient of determination (R-squared = 0.646), indicating that approximately 64.6% of the variance in work-life balance can be explained by the independent variables included in the model. The adjusted R-squared value (0.641) suggests that this model is robust and accounts for the complexity of the relationships.

Table 8 Multiple Linear Regression Analysis
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The standardized coefficients indicate the relative importance of each independent variable in predicting the dependent variable. Among the independent variables, Training Program (TP) had the highest standardized coefficient (β = 0.839, p < 0.001), indicating that it has the strongest impact on work-life balance among the variables included in the model. Emotional Intelligence (EI) also showed a significant positive effect (β = 0.563, p < 0.001), followed by Stress Management (SM) (β = 0.560, p = 0.003) and Supportive Work Environment (SWE) (β = 0.664, p = 0.007).

The regression equation derived from the analysis is as follows:

$$WLB=0.605+0.839\times TP+0.563\times EI+0.560\times SM+0.664\times SWE$$
(3)

This equation suggests that for every unit increase in Training Program, Emotional Intelligence, Stress Management, and Supportive Work Environment, Work-Life Balance increases by 0.839, 0.563, 0.560, and 0.664 units respectively. The constant term (0.605) represents the baseline level of Work-Life Balance when all independent variables are zero. Overall, the results of the regression analysis underscore the importance of training programs, emotional intelligence, stress management, and supportive work environments in promoting a healthy work-life balance among employees.

5.6 Results of hypotheses testing and proposed structural model

Table 9 presents the outcomes of hypothesis testing, revealing significant insights into the relationships examined within the study. Firstly, the analysis indicates a substantial direct positive correlation between teacher training programs (TP) and work-life balance (WLB), with a path coefficient of 0.561 (p < 0.001), suggesting that effective training initiatives contribute significantly to fostering a better balance between professional responsibilities and personal life. Similarly, the study finds significant direct positive associations between TP and both emotional intelligence (EI) (path coefficient = 0.457, p < 0.001) and stress management (SM) (path coefficient = 0.671, p < 0.001), highlighting the role of training in enhancing educators' emotional well-being and ability to cope with job-related stressors.

Table 9 Results of Hypotheses Testing
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Moreover, the results demonstrate significant direct positive relationships between EI and WLB (path coefficient = 0.563, p < 0.001) and SM and WLB (path coefficient = 0.780, p < 0.001), underscoring the importance of emotional intelligence and stress management in promoting a healthier work-life equilibrium among women teachers. Further analysis reveals that both EI (path coefficient = 0.257, p < 0.001) and SM (path coefficient = 0.523, p < 0.001) significantly mediate the relationship between TP and WLB, indicating that these factors play crucial intermediary roles in translating the benefits of training programs into improved work-life balance outcomes.

Additionally, the study identifies a significant moderation effect of supportive work environments (SWE) on the relationship between TP and WLB, with a path coefficient of 0.782 (p < 0.001). This suggests that organizational cultures emphasizing employee well-being, flexibility, and resource support contribute significantly to creating an environment conducive to achieving a positive work-life balance among women teachers. Overall, these findings provide robust empirical support for the proposed structural model, highlighting the interconnectedness of teacher training programs, emotional intelligence, stress management, supportive work environments, and work-life balance in the context of secondary school education in the Durg district. Based on the hypotheses testing, the proposed structural model is shown as Fig. 2.

Fig. 2
figure 2

Proposed Structural Model (Based on Hypotheses Testing)

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6 Discussion

The study investigates into the critical dimension of work-life balance among women educators in secondary schools, particularly in the context of training programs. Through an extensive literature review, the study establishes the significance of training programs, stress management, emotional intelligence, and supportive work environments in fostering work-life equilibrium. The findings from the research methodology, including scale development, validation, and data analysis, provide robust insights into the complex interplay of these factors. The multiple linear regression analysis and hypothesis testing using PLS-SEM offer compelling evidence of the direct and mediating effects of training programs, emotional intelligence, stress management, and the moderating influence of a supportive work environment on work-life balance. The discussion below synthesizes these findings, highlighting the implications for policy, practice, and future research.

6.1 Significance of training programs and continuous professional development

The study underscores the crucial role of training programs in enhancing work-life balance among women teachers. This finding aligns with previous research emphasizing the positive impact of professional development on teacher well-being and job satisfaction [3, 19]. Quality training initiatives equip educators with the necessary skills and resources to effectively manage their workload, navigate challenges, and maintain a healthy work-life equilibrium [18]. Furthermore, continuous professional development fosters a culture of lifelong learning, empowering teachers to adapt to evolving educational trends and technologies [5].

6.2 Integration of emotional intelligence and stress management

Emotional intelligence and stress management emerge as key factors mediating the relationship between training programs and work-life balance. This finding is consistent with research highlighting the importance of emotional resilience and coping strategies in mitigating job-related stressors among educators [12, 23]. Teachers with higher levels of emotional intelligence exhibit greater self-awareness, empathy, and emotional regulation, which are crucial for maintaining well-being and professional effectiveness [14, 31]. Similarly, effective stress management techniques, such as mindfulness and relaxation strategies, have been shown to reduce burnout and improve overall job satisfaction among teachers [1].

6.3 Role of supportive work environments

A supportive work environment emerges as a critical moderator in the relationship between training programs and work-life balance. This finding resonates with the organizational support theory, which posits that supportive workplace cultures enhance employee well-being and performance [15, 43]. Educational institutions that prioritize teacher support, recognition, and collaboration create conducive environments where educators feel valued and empowered [44]. Moreover, supportive leadership and adequate resources contribute to a positive organizational climate, fostering trust and job satisfaction among staff members [45].

6.4 Implications for policy and practice

The study's findings have significant implications for policy and practice in the education sector. Policymakers are encouraged to allocate resources for the development and implementation of high-quality training programs tailored to the needs of educators. Moreover, educational institutions should prioritize the cultivation of supportive work environments through leadership development, resource allocation, and organizational policies [51, 52]. By investing in teacher well-being and professional development, stakeholders can create conditions conducive to a healthy work-life balance, ultimately benefiting both educators and students [34, 36].

7 Implications of the study

7.1 Theoretical implications of study

The study’s theoretical implications are manifold, significantly advancing our comprehension of work-life balance dynamics among women teachers in secondary schools. By empirically probing the relationships between training programs, emotional intelligence, stress management, supportive work environments, and work-life balance, the research supplements several key theories. Firstly, the findings align with Human Capital Theory, asserting that investment in professional development improves work-life balance by enhancing employees’ skills and resources [61]. Secondly, the study supports emotional labor theories, emphasizing the significance of emotional regulation and resilience in maintaining educators' well-being and job satisfaction [62]. Thirdly, the emphasis on the moderating role of supportive work environments aligns with Organizational Support Theory, suggesting that such cultures enhance employee well-being and performance [63]. Lastly, Social Exchange Theory is supported by the finding that a supportive work environment significantly impacts the effectiveness of training programs on work-life balance [55]. By integrating these theories, the study enriches our understanding of the intricate interplay between individual, organizational, and contextual factors in shaping work-life balance among women teachers, offering valuable insights for advancing theoretical knowledge in this field.

7.2 Managerial implications

The findings of this study offer practical insights for educational managers and policymakers aiming to enhance work-life balance among women teachers in secondary schools. Firstly, investing in high-quality training programs is paramount [64]. The study underscores the positive impact of such programs on work-life balance, emphasizing the need for continuous professional development. Secondly, creating supportive work environments is essential [65]. Organizational policies should prioritize teacher support, recognition, and collaboration to foster cultures where educators feel valued and empowered. Thirdly, advocating for systemic changes is crucial [66]. Policymakers must integrate work-life balance considerations into education policies and funding initiatives to create supportive and sustainable work environments for educators. Lastly, adopting holistic approaches to teacher support is necessary [67]. Educational institutions should implement initiatives focusing on both professional development and personal well-being to address the multifaceted needs of educators effectively. Overall, by implementing these recommendations, educational managers and policymakers can create conducive environments for a healthy work-life balance, benefiting both educators and students alike.

8 Conclusion

The study on the role of training programs in maintaining work-life balance for women teachers in Durg district secondary schools yields several noteworthy conclusions. Firstly, the adoption of a descriptive research design allowed for a thorough exploration of the subject matter, highlighting the nuanced dynamics between various factors influencing work-life balance. Through the collection of data using an online Google Form over the period of July to December 2023, a robust sample size of 422 responses was obtained, ensuring a diverse and representative dataset for analysis. The findings revealed that high-quality training programs significantly contribute to enhancing work-life balance among women teachers. This emphasizes the importance of investing in professional development initiatives tailored to the needs of educators, particularly focusing on skill-building, support mechanisms, and stress management techniques.

Moreover, the study identified emotional intelligence and stress management as crucial mediating factors in the relationship between training programs and work-life balance. Educators with higher levels of emotional intelligence were better equipped to navigate workplace challenges, while effective stress management strategies mitigated the negative impact of job-related stressors, thereby fostering a healthier work-life equilibrium. These findings highlight the necessity of incorporating emotional intelligence training and stress management techniques into teacher development programs, promoting not only professional growth but also personal well-being.

Additionally, the study underscored the pivotal role of supportive work environments in moderating the relationship between training programs and work-life balance. Organizational cultures that prioritize employee well-being, offer flexibility, and provide adequate resources contribute significantly to fostering a positive work environment for educators. By cultivating a culture of support and recognition, educational institutions can empower women teachers to achieve a sustainable work-life balance, ultimately leading to higher job satisfaction and retention rates.

In conclusion, the study's findings have substantial implications for policy and practice in the education sector. Policymakers are encouraged to prioritize investments in teacher training and development programs that encompass elements aimed at enhancing emotional intelligence, stress management, and supportive work environments. Educational institutions, on the other hand, are urged to adopt holistic approaches to teacher support, incorporating initiatives that address the multifaceted needs of educators. By prioritizing work-life balance and well-being, stakeholders in the education sector can create a more conducive environment for women teachers to thrive both personally and professionally, ultimately benefiting the entire educational community.

8.1 Limitations and future research recommendations

Limitations of this study include its reliance on self-reported online survey data, which may introduce response bias. Future research could incorporate control variables such as age, experience, school type, and education board to mitigate bias and enhance the study’s robustness. Employing mixed-method approaches and longitudinal designs could provide deeper insights and causal inference. Additionally, the study’s focus on a specific geographic location and gender may limit generalizability, suggesting the need to explore diverse contexts and organizational cultures for a comprehensive understanding of work-life balance dynamics among educators and to inform targeted interventions.