AgBioForum, 26(2): 159-167. ©2024 AgBioForum Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees in Service-Based Industries Richa Mishra* School of Management, BML Munjal University, Gurugram, Haryana, India. ORCID iD: https://orcid.org/0009-0008-5681-1482 Email: richa.mishra@bmu.edu.in Hala Alsabatin College of Education, Zarqa University, Zarqa, Jordan. ORCID iD: https://orcid.org/0009-0002-9779-1007 Email: halsabatin@zu.edu.jo Shweta Upamanyu Corporate Learning & Development Manager, BlueDove Hospitality Pvt. Ltd., Bengaluru, Karnataka, India. ORCID iD: https://orcid.org/0000-0003-2727-0273 Email: s.upamanyu@gmail.com Jolly Masih School of Management, BML Munjal University, Gurugram, Haryana, India. ORCID iD: https://orcid.org/0000-0002-8420-1517 Email: jolly.masih@bmu.edu.in Azzam Hannoon School of Business, Skyline University College, University City- Sharjah- UAE. ORCID iD: https://orcid.org/0000-0003-0468-7797 Email: azzam.hannoon@skylineuniversity.ac.ae Sherine Badawi Faculty of Economics and International Trade, Egyptian Chinese University. ORCID iD: https://orcid.org/0000-0001-5900-6288 Email: sherinebadawy@yahoo.com Sameh Reyad Faculty of Business Administration Department of Finance, Banking and Accounting, German International University (GIU), Egypt. ORCID iD: https://orcid.org/0000-0002-3099-0741 Email: sameh.reyad@giu-uni.de Yussra Jamjoom College of Business Administration, University of Business and Technology, Jeddah, 21448, Saudi Arabia. ORCID iD: https://orcid.org/0000-0003-2600-5558 Email: yussra@ubt.edu.sa This study offers a comprehensive examination of the factors contributing to the increasing prevalence of psychological issues among employees within service-based industries, providing a nuanced understanding of this pressing concern. The research aims to clarify the role of marital status in shaping psychological health outcomes, particularly when considering the aforementioned challenges. The findings underscore the significant influence of demanding workloads, strict deadlines, and the relentless pressures characteristic of service-oriented employment on the mental health of workers. Marital status emerges as a key predictor of mental health outcomes, with employees who are married, divorced, or have children facing situations that exacerbate stress and anxiety. The results indicate that while all employees in the service sector are susceptible to mental health difficulties, those with additional familial responsibilities—such as those who are married or have children—are particularly vulnerable. Keywords: Mental Health Issues, Employees, Workplace, Service- Based Industries, Marital Status, Occupational Stress, Employee Well-Being. Introduction Recently, the discourse surrounding mental health in the workplace has gained considerable attention, shedding light on the multifaceted challenges faced by individuals across various sectors—particularly within service- oriented industries that emphasise efficiency, productivity, and customer satisfaction. This study aims to explore the factors contributing to the increasing prevalence of mental health issues among employees in service industries, providing a comprehensive understanding of the complexities of this pressing issue by examining the conditions that impact psychological well-being in the work environment. The subject of mental health in the workplace has attracted significant interest due to its profound effect on individual welfare, productivity, and organisational performance. Psychological disorders such as stress, anxiety, depression, and burnout not only affect individuals but also influence the overall functioning of businesses, potentially resulting in reduced productivity, higher absenteeism, and diminished morale. As noted by Wang et al. (2022), "Marital status, often overlooked, plays a critical role in shaping the mental health of employees in service-based industries. Understanding this connection is essential for creating workplaces that not only foster productivity but also nurture well-being." The primary factors contributing to the increasing prevalence of mental health issues among individuals in https://orcid.org/0009-0008-5681-1482 mailto:richa.mishra@bmu.edu.in https://orcid.org/0009-0002-9779-1007 mailto:halsabatin@zu.edu.jo https://orcid.org/0000-0003-2727-0273 mailto:s.upamanyu@gmail.com https://orcid.org/0000-0002-8420-1517 mailto:jolly.masih@bmu.edu.in mailto:azzam.hannoon@skylineuniversity.ac.ae mailto:sherinebadawy@yahoo.com https://orcid.org/0000-0002-3099-0741 mailto:sameh.reyad@giu-uni.de https://orcid.org/0000-0003-2600-5558 mailto:yussra@ubt.edu.sa AgBioForum, 26(2), 2024 | 160 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… service-based sectors are excessive workloads and heightened levels of pressure. Employees within these industries frequently face significant time constraints, stringent deadlines, and a relentless influx of customer demands. For married workers, the challenge of balancing dual responsibilities—professional duties and domestic obligations—can result in either emotional stability or heightened stress, contingent upon the presence or absence of interpersonal conflicts (Womack & Jones, 2005). Divorced or separated employees, on the other hand, experience unique emotional and financial strains, which exert a considerable impact on their psychological well- being. Employed parents encounter additional responsibilities and complexities in time management, leading to increased stress levels. Furthermore, organisational factors exacerbate the issue, including inadequate support systems, limited access to mental health resources, and the persistent stigma associated with mental health conditions (Eisenberger, Malone, & Presson, 2016). Marital status represents a significant yet frequently overlooked social determinant that substantially influences the mental well-being of employees. Individuals who lack access to robust social support networks may experience heightened levels of stress and feelings of isolation (Cattani & Rizza, 2024). In contrast, married employees are often required to balance dual responsibilities encompassing both their personal and professional lives. This dual role may either facilitate the resolution of familial matters or, conversely, exacerbate existing anxieties. Additionally, divorce or separation from a spouse can have profound detrimental effects on an employee’s emotional stability, further underscoring the critical role of marital status in shaping mental health outcomes. A 2022 study conducted by the National Institute of Mental Health and Neuro-Sciences (NIMHANS) in Bengaluru explored the relationship between marital status and mental health challenges among information technology (IT) professionals, revealing a significant correlation. The study, which included a sample of 500 employees, found that unmarried individuals experienced higher levels of anxiety and stress, primarily due to the lack of a supportive domestic environment and concerns regarding job security. In contrast, married employees faced stress arising from the dual demands of managing both work and family responsibilities. However, they reported improved mental well-being when receiving adequate support from their spouses. These findings highlight the need for tailored mental health interventions that address the distinct pressures associated with varying marital statuses, thereby fostering the overall well-being of employees (Salahat et al, 2023; Anand, 2024). Individuals with children are more susceptible to stress due to the heightened demands of balancing professional responsibilities and domestic duties, often leading to fatigue exacerbated by a lack of empathy and the burden of emotional labour. Employees in service-based sectors frequently engage in "emotional labour," which involves the regulation and outward expression of emotions (Grundström et al., 2021). This can be particularly mentally taxing, as it requires maintaining composure in challenging situations or demonstrating empathy towards clients. Additionally, these individuals often face unstable employment conditions and precarious work arrangements. Concerns over job security and unpredictable schedules are prevalent among workers in service-oriented industries, contributing to elevated levels of anxiety and stress. Sectors such as customer service and hospitality are characterised by a high prevalence of contract work, zero-hour contracts, and the growing influence of the "gig economy." These factors foster uncertainty among workers regarding job stability, fringe benefits, and financial security (Ozduran et al., 2023; Al-Sartawi et al. 2024). The study aims to explore the interplay between these factors and marital status to achieve a comprehensive understanding of how different marital statuses influence the mental well- being of individuals employed in service-based industries. Through an extensive review of contemporary literature and systematic data collection, the research seeks to identify the primary stressors prevalent within these sectors. Additionally, the study endeavours to elucidate the impact of marital status on psychological health outcomes when considered alongside these stressors. By doing so, it aspires to provide employers with valuable insights into enhancing employee well-being and satisfaction, as well as fostering a supportive work environment that addresses their diverse needs. The identification of these relationships is intended to assist organisations and policymakers in designing tailored support systems capable of effectively addressing mental health challenges and promoting a healthier, more inclusive workplace. Furthermore, the study contributes to the broader discourse on the relationship between marital status and mental well-being in service-oriented sectors. It also seeks to inform researchers in developing targeted interventions aimed at improving workplace conditions and advancing the overall well-being of employees. Literature Review This section of the study includes assessments of related previous studies that have been carried out to help comprehend the current state of the topic. For clarity, the section has been split into three categories. Marital Status and the Prevalence of Mental Health Issues among Employees Torres, Backstrom, & Duffy (2023) examined the factors associated with mental health burdens in two distinct groups of workers. The first group consisted of individuals employed in critical sectors who remained active during the pandemic, including healthcare, military, commerce, finance, and media. The second group comprised workers significantly impacted by protective measures, either operating under altered work arrangements or unable to work at all. Sopa et al. (2020) found that workers who perceive support from their employers—whether in the form of rewards, favourable working conditions, or encouragement from superiors—are more likely to remain employed with the organisation (Ahmedani, 2011). Similarly, Sumarsi & Rizal (2021) observed that employees tend to exhibit greater dedication when they perceive that the organisation aligns with their standards, desires, and expectations. In this context, Chiu, Wai‐Mei Luk, & Li‐Ping Tang (2002) identified that when workers AgBioForum, 26(2), 2024 | 161 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… are able to operate comfortably and conveniently within the organisation, their commitment to staying is strengthened, and they experience a sense of alignment with the organisation's core values. Factors Specific to Workplace Stressors on the Mental Health of Employees with Different Marital Statuses Vaingankar et al. (2020) examined the specific factors related to workplace stress and their impact on the mental health of employees with varying marital statuses. The study explored the links between married life and psychological disorders, considering the potential influence of social support, trust, and financial constraints. Similarly, Hossain et al. (2021) found that employees who were single, divorced, or widowed were significantly more likely to experience poor mental health compared to those who were married or living with a partner. These higher odds ratios remained consistent across studies, with trust and financial difficulties only slightly weakening the associations. A further study by Bayrakçeken, Alkan, & Abar (2023) emphasized that mental health can be defined as the ability to maintain positive and balanced relationships, adapt to personal and social environments, and effectively resolve conflicts and personal aspirations in a rational, fair, and appropriate manner. According to Sopa et al. (2020), the marital history of working women significantly influenced their mental well-being. The complex stress experienced by married working women, who juggle responsibilities in multiple areas, may contribute to their diminished mental health (Abadi, Dirani, & Rezaei, 2022). Optimal allocation of counselling time and regular meditation were identified as effective strategies for enhancing mental well-being. Finally, Parker & Jorritsma (2021) noted the widespread presence of significant psychological distress across all categories of employees, a concern that is often unaddressed. Identifying risk factors should guide the development of behavioural health interventions, prevention, and assessment initiatives. Factors Contributing to the Correlation Between Married and Unmarried Employees According to Hämmig, Gutzwiller, & Bauer (2009), married women, in particular, exhibited a degree of atypical deviation in both types of aberrant activities. For women, the dissolution of marriage was more strongly linked to indicators of sadness, while men were more prone to displaying unhealthy drinking habits and behavioural issues. In contrast, the transition from "unmarried" to "married" marital status did not appear to have a significant association with the respondents' mental health. Abas et al. (2024) suggested that these differences may be attributed to the emotional and socialisation experiences of men and women, which make individuals more susceptible to responding to stress throughout their lives. Further research has shown that married individuals are less likely to engage in criminal activities (Baek et al., 2024) and are less vulnerable to aberrant behaviour (Rony, Md. Numan, & Alamgir, 2023) compared to their unmarried counterparts. Vorina, Simonič, & Vlasova (2017) also reported notable differences in the prevalence of depression, anxiety, and stress between married and unmarried employees. Objectives of the Study Onj.1: To identify the primary factors contributing to the increasing prevalence of mental health issues among employees in service-oriented industries. H1: There are multiple underlying factors that significantly contribute to mental health issues among employees in service-based industries. Obj.2: To investigate the relationship between marital status and mental health challenges among employees in service-oriented industries. H2: Marital status is significantly associated with the prevalence of mental health issues among employees in service-based industries. Obj.3: To examine the influence of the workplace environment on the mental health of employees with varying marital statuses. H3: The impact of workplace environment on mental health varies significantly across different marital statuses. Research Methodology Data Collection: The study incorporated multiple sources of knowledge to assess the relationship dynamics and psychological health at three distinct stages of the lifespan. Furthermore, the research sought to explore the timing at which relationship status influenced these associations. Primary data was collected using a structured questionnaire, with participants selected through stratified random sampling from two categories: unmarried and married. Study Area: The Delhi National Capital Region was selected as the study area due to its diverse and dense service industry, a wide range of socioeconomic backgrounds, and distinct urban stressors that influence employee mental health. Targeted Population: Since the targeted population is undefined, the sample size was calculated to be 385 using Cochran's formula. Accordingly, a total of 385 questionnaires were distributed to employees from various professional organisations using the offline method, with 270 employees responding. Data from 200 respondents who completed the questionnaire in full were considered for analysis. Research Technique: A mixed methods approach was employed to provide a comprehensive understanding of mental health issues by integrating quantitative data on prevalence and correlations with qualitative insights into personal experiences and contextual factors. Data Extraction: The data were analysed using SPSS 26 and Excel software. SPSS facilitated advanced statistical analysis and detailed data modelling, while Excel provided essential tools for data organisation and basic calculations, making the two programs complementary for efficient and accurate data processing. The study utilised a structured questionnaire and employed stratified random sampling to select participants from two categories: unmarried and married. Study Technique: The study utilised mean, standard deviation, Analysis of Variance (ANOVA), correlation, AgBioForum, 26(2), 2024 | 162 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… and the t-test to test the study’s hypotheses. A pilot study was conducted to ensure the reliability and accuracy of the questionnaire, with a sample size of 50 questionnaires selected to further validate these aspects. Results This section presents the findings and interpretation of the data, structured according to the demographic characteristics, objectives, and hypotheses outlined in the study. The outcomes have been categorised to align with the research aims and hypotheses. A detailed Table 1 summarising the results has been included, accompanied by an explanatory analysis of these findings. This approach ensures a clear and systematic presentation of the data, facilitating a comprehensive understanding of how the results relate to the study's objectives and hypotheses. Table 1: Reliability and Validity Statistics. Reliability Statistics Label Cronbach's Alpha Number of Items Kaiser–Meyer–Olkin and Bartlett’s Value Significance Value Workload and Job Stress 0.818 3 0.716 0.000 Work–Life Balance 0.777 3 0.700 0.000 Organizational Culture and Support 0.721 4 0.727 0.000 Mental Health Issues 0.813 10 0.779 0.000 Workplace Environment 0.745 10 0.740 0.000 Table 1 presents the reliability statistics for various variables. The "Cronbach's Alpha" values range from 0.721 to 0.818, indicating the reliability of the questionnaire, as all values exceed 0.700. The items range from 3 under "Workload and Job Stress" and "Work-Life Balance" to 4 under "Organizational Culture and Support," and 10 under both "Mental Health Issues" and "Workplace Environment." The Kaiser–Meyer–Olkin (KMO) values confirm the validity of the questionnaire, as all values are greater than 0.700, suggesting that the data are suitable for factor analysis. All significance values are 0.000, indicating that the results are statistically significant. Independent reliability and validity testing were conducted for each factor (e.g., Workload and Job Stress, Work-Life Balance, Organizational Culture and Support) to ensure the distinctiveness and internal consistency of each construct. This approach was considered appropriate, as the factors represent conceptually distinct dimensions of the overall framework under analysis. Table 2: The Respondents' Demographic Profile. Sr. No. Demographic Characteristics Category N % 1 Gender Female 98 49.0% Male 102 51.0% 2 Age 18–25 Years 60 30.0% 26–35 Years 70 35.0% 36–45 Years 40 20.0% 46–55 Years 20 10.0% ≥56 Years 10 5.0% 3 Marital Status Married 110 55.0% Unmarried 90 45.0% 4 Employment Type Contractual 30 15.0% Full-Time 120 60.0% Part-Time 30 15.0% Temporary 20 10.0% 5 Job Role Administrative 30 15.0% Managerial 50 25.0% Supervisory 40 20.0% Support 20 10.0% Technical 60 30.0% 6 Years of Experience <1 Year 20 10.0% 1–3 Years 60 30.0% 4–6 Years 50 25.0% 7–10 Years 40 20.0% >10 Years 30 15.0% Table 2 presents the "Demographic Characteristics of the Respondents," detailing their gender, age, marital status, employment type, job role, and years of experience. As shown in the table, 49.0% of the respondents were female, and 51.0% were male. The largest group of respondents (35.0%) were aged between 26 and 35 years. A majority of the respondents (55.0%) were married. Regarding employment type, 60% of respondents were full-time employees, and 25.0% held managerial positions. Additionally, the table indicates that the majority of respondents (30.0%) had 1 to 3 years of experience in the corporate field. O1: To identify the primary factors contributing to the increasing prevalence of mental health issues among employees in service-oriented industries. H1: There are multiple underlying factors that significantly contribute to mental health issues among employees in service-based industries. Table 3 presents the results of the KMO and Bartlett's test. The KMO measure of sampling adequacy is 0.701, and AgBioForum, 26(2), 2024 | 163 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… Bartlett's test of sphericity yielded a significant result, with an approximate chi-squared value of 283.187, degrees of freedom = 45, and a p-value of 0.000. These results from the KMO and Bartlett's test confirm the suitability of the data for factor analysis in testing the hypothesis. Moreover, Table 4 presents the commonalities for various items. Items such as WJS_1 (0.512), WJS_2 (0.597), WLB_1 (0.516), WLB_2 (0.677), WLB_3 (0.524), OCS_2 (0.677), and OCS_3 (0.535) exhibit medium commonalities, indicating reasonably strong correlations with the factors, although a significant portion of the variance remains unexplained. Conversely, items such as WJS_3 (0.351), OCS_1 (0.434), and OCS_4 (0.488) display lower commonalities, suggesting that less of their variance is accounted for by the factors. The lower representation of these items may require further review for potential modification or removal to improve the validity and reliability of the hypothesis. Table 3: Kaiser–Meyer–Olkin (KMO) and Bartlett’s Test. KMO and Bartlett's Test KMO Measure of Sampling Adequacy 0.701 Bartlett's Test of Sphericity Approximate Chi-Squared 283.187 Degree of Freedom 45 Significance 0.000 Table 4: Commonalities. Commonalities Initial Extraction WJS_1 1.000 0.512 WJS_2 1.000 0.597 WJS_3 1.000 0.351 WLB_1 1.000 0.516 WLB_2 1.000 0.677 WLB_3 1.000 0.524 OCS_1 1.000 0.434 OCS_2 1.000 0.677 OCS_3 1.000 0.535 OCS_4 1.000 0.488 Extraction Method: Principal Component Analysis Table 5, showing the total variances, reveals that a significant proportion of the variance is explained by the first three components. The initial eigenvalues indicate that Component 1 explains 26.577%, Component 2 accounts for 14.602%, and Component 3 contributes 11.940%, collectively explaining 53.118% of the total variance. After these three components, there is a marked decline in the variance explained by subsequent components. From the fourth component onward, their contribution diminishes, with the fourth explaining 8.865% and the cumulative percentage reaching 61.983%. This suggests that the first three components are crucial in capturing the main patterns in the data, and justifies their use in further analysis, as they effectively account for the majority of the variance. Table 5: Total Variance. Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 2.658 26.577 26.577 2.658 26.577 26.577 2.223 22.226 22.226 2 1.460 14.602 41.178 1.460 14.602 41.178 1.571 15.714 37.939 3 1.194 11.940 53.118 1.194 11.940 53.118 1.518 15.179 53.118 4 0.887 8.865 61.983 5 0.787 7.871 69.854 6 0.748 7.481 77.336 7 0.722 7.219 84.555 8 0.556 5.562 90.118 9 0.553 5.533 95.651 10 0.435 4.349 100.000 Extraction Method: Principal Component Analysis Table 6: Rotated Component Matrix. Rotated Component Matrixa Component 1 2 3 WJS_1 0.692 WJS_2 0.721 WJS_3 0.500 WLB_1 0.694 WLB_2 0.822 WLB_3 0.713 OCS_1 0.626 OCS_2 0.811 OCS_3 0.532 OCS_4 0.603 Extraction Method: Principal Component Analysis Rotation Method: Varimax with Kaiser Normalization a. Rotation Converged in Four Iterations The first component, "Workload and Job Stress," is strongly defined by WJS_1 (0.692) and WJS_2 (0.721), with WJS_3 (0.500) contributing to a lesser degree. The second component, "Work-Life Balance," is primarily defined by WLB_1 (0.694) and WLB_2 (0.822), though WLB_3 (0.713) cross-loads on Component 1. The third component, "Organizational Culture and Support," is characterised by OCS_1 (0.626), OCS_2 (0.811), and OCS_3 (0.532), with OCS_4 (0.603) cross-loading on Component 1. The cross- loadings of WLB_3 and OCS_4 suggest redundancy across components. It is recommended to exclude these variables for a clearer factor structure. Overall, the matrix indicates that while the three factors are distinct, further refinement is needed for a more accurate model. O2: To investigate the relationship between marital status AgBioForum, 26(2), 2024 | 164 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… and mental health challenges among employees in service- oriented industries. H2: Marital status is significantly associated with the prevalence of mental health issues among employees in service-based industries. Table 7 presents the distribution and variability of mental health issues among vulnerable populations, stratified by marital status. The mean rating for unmarried individuals is 34.99 (SD = 6.43), while for married individuals, the mean rating is 32.93 (SD = 6.66). Moreover, Table 8 reveals a significant difference between the two groups of vulnerable populations. The mean of the variable is significantly lower in one group compared to the other, with a 95% confidence interval. The significance value for vulnerable populations is 0.028, which is below the 0.05 threshold. Table 7: Group Statistics Table. Group Statistics Marital Status N Mean Standard Deviation Standard Error Mean Mental Health Issues Unmarried 90 34.9889 6.43288 0.67808 Married 110 32.9273 6.65770 0.63479 Table 8: Independent Samples Test. Independent Samples Test Levene's Test for Equality of Variances T-Test for Equality of Means F Significance T Degree of Freedom Significance (2-tailed) Mean Difference Standard Error Difference 95% Confidence Interval of the Difference Lower Upper Mental Health Issues Equal Variances Assumed 0.088 0.767 2.212 198 0.028 2.06162 0.93206 0.22359 3.89965 Equal Variances not Assumed 2.220 192.580 0.028 2.06162 0.92884 0.22960 3.89363 O3: To examine the influence of the workplace environment on the mental health of employees with varying marital statuses. H3: The impact of workplace environment on mental health varies significantly across different marital statuses. Table 9 presents the descriptive statistics for married and unmarried employees. The mean score for married employees is 32.93 (SD = 6.66), while for unmarried employees, the mean score is 34.99 (SD = 6.43). Moreover, Table 10 demonstrates that both the workplace environment (F = 35.905, p = 0.000) and marital status (F = 13.448, p = 0.000) significantly affect mental health issues. The model explains approximately 17.5% of the variation in mental health issues (R² = 0.175). Furthermore, Table 11 highlights a statistically significant positive effect of the workplace environment, leading to a slight decrease in mental health issues (p = 0.000). Unmarried employees experience significantly more mental health issues than married employees, with a negative difference (p = 0.000), suggesting that marital status moderates the mental health impact of the workplace environment. Table 9: Descriptive Statistics. Descriptive Statistics Dependent Variable: Mental Health Issues Marital Status Mean Standard Deviation N Married 32.9273 6.65770 110 Unmarried 34.9889 6.43288 90 Total 33.8550 6.62142 200 Table 10: Tests of Between-Subjects Effects. Tests of Between-Subjects Effects Dependent Variable: Mental Health Issues Source Type III Sum of Squares Degree of Freedom Mean Square F Significance Corrected Model 1,522.992a 2 761.496 20.830 0.000 Intercept 4,084.361 1 4,084.361 111.725 0.000 Workplace Environment 1,312.604 1 1,312.604 35.905 0.000 Marital Status 491.614 1 491.614 13.448 0.000 Error 7,201.803 197 36.557 Total 237,957.000 200 Corrected Total 8,724.795 199 a. R2 = 0.175 (adjusted R2 = 0.166) AgBioForum, 26(2), 2024 | 165 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… Table 11: Parameter Estimates. Parameter Estimates Dependent Variable: Mental Health Issues Parameter B Standard Error T Significance 95% Confidence Interval Lower Bound Upper Bound Intercept 23.461 2.027 11.576 0.000 19.464 27.458 Workplace Environment 0.354 0.059 5.992 0.000 0.237 0.470 [Marital Status1_A = 1.00] −3.232 0.881 −3.667 0.000 −4.970 −1.494 [Marital Status1_A = 2.00] 0a . . . . . a. This parameter is set to zero because it is redundant. Discussion This study contributes to the expanding body of literature examining the development of mental health issues among employees in service-based industries, with a specific focus on the relationship between these issues and marital status. The findings provide valuable insights into the interplay between workplace demands, marital status, and mental health outcomes. In this regard, several key factors have been identified as significant contributors to the emergence of psychological disorders among workers in service-based sectors. High job demands, work-related stress, poor work-life balance, and insufficient organisational support emerged as primary drivers of mental health challenges (Musleh Alsartawi et al., 2022). The robustness of these findings is supported by statistical measures of reliability and validity; the Cronbach’s alpha values ranged from 0.721 to 0.818, indicating that the instruments utilised in the study were highly reliable. Additionally, the results of the Kaiser-Meyer-Olkin (KMO) and Bartlett’s tests confirmed the suitability of the data for factor analysis, further validating the study’s conclusions. The study highlights that high workload and pressure are significant stressors, which are inherently characteristic of service-based industries. Employees in these sectors are consistently subjected to intense time pressures and stringent deadlines, which frequently contribute to elevated levels of stress and anxiety. Furthermore, the research underscores the critical role of organisational culture and support—or the lack thereof—in either mitigating or exacerbating mental health challenges. The findings align with existing literature, which suggests that employees who perceive a lack of support from their organisations are more susceptible to mental health issues (Sopa et al., 2020). This study thus reinforces the importance of fostering supportive workplace environments to address the growing mental health concerns among service-sector employees. Marital status is significantly linked to mental health. Married workers, often balancing dual responsibilities at home and work, experience various stressors that may impact emotional stability and contribute to mental health issues. While marriage may provide home-based support, the increased responsibilities can counteract the stress- relief benefits, particularly when work-life balance is disrupted. Single employees, potentially lacking strong social support networks, are more prone to feelings of loneliness and stress. This study supports previous research, such as Cattani & Rizza (2024), which highlights higher stress levels among single workers due to the absence of a robust social support system. Divorced or separated employees also face emotional and financial challenges, which significantly affect their mental well- being (Atymtayeva et al., 2023 and Tunsi et al. 2023). The study further establishes marital status as a crucial factor in understanding and addressing mental health issues in the workplace. The work environment's impact on mental health, moderated by marital status, was also explored. Results show that a negative work environment can particularly hinder married workers' ability to balance work and family responsibilities, exacerbating stress. In contrast to previous studies in this field, the current research builds upon existing literature and introduces new perspectives on the impact of marital status on employee mental health. Older studies, such as those by Torres et al. (2023), focus on workplace support and organisational assistance as key factors for maintaining employee well- being. However, these studies generally address the broader employee population without considering the specific challenges faced by individuals of different marital statuses. Hossain et al. (2021) and Vaingankar et al. (2020) advanced the research by examining the interaction between marital status and workplace stress, finding that unmarried, divorced, and widowed individuals are more prone to poor mental health compared to their married counterparts. While these studies highlight useful correlations, they do not thoroughly investigate how marital status may exacerbate or mitigate mental health issues at work. Similarly, Abas et al. (2024) and Hämmig et al. (2009) explored the impact of marital transitions on the mental health of both genders, emphasising emotional-socialisation experiences as crucial factors. While these studies identified specific agendas, they fell short of fully explaining the variations in deviant behaviours and mental health symptoms across different marital statuses in the workplace. This study builds on existing research, deepening the understanding of how marital status influences psychological well-being in the workplace. It explores the impact of marital transitions and responsibilities, providing a more comprehensive view of the factors affecting mental health disparities among employees. The findings suggest that single employees, in the absence of a strong organisational culture, may feel isolated. The study recommends that organisations give greater attention to employee well-being by considering marital status. Targeted support, such as flexible working arrangements for married employees and social support networks for single employees, could mitigate the negative effects of workplace stress on mental health. AgBioForum, 26(2), 2024 | 166 Mishra et al — Exploring the Impact of Marital Status and Workplace Environment on Mental Health among Employees… Employers in service industries should establish a comprehensive mental health support system tailored to employees' marital status. This includes offering counselling services, promoting work-life balance through flexible schedules, and fostering a supportive organisational culture that reduces stigma around mental health issues. Policymakers can use these findings to drive policies that promote mental health in the workplace. A policy ensuring access to mental health resources would help reduce psychological problems among workers. In summary, the study provides a detailed analysis of the factors contributing to the rise of mental health issues in service sectors, highlighting the importance of marital status in addressing these challenges. By enhancing employee well-being, companies can create a more supportive work environment, improving both mental health outcomes and organisational performance. Conclusion This study offers a comprehensive examination of the factors contributing to rising mental health issues among employees in service industries, with a particular emphasis on the role of marital status. The findings highlight the significant impact of heavy workloads, tight deadlines, and constant pressures in service-based employment on employees' mental health. The study further identifies marital status as a key predictor of mental health outcomes, noting that employees who are married, divorced, or have children face compounded stress and anxiety. It suggests that while all service industry employees are susceptible to mental health challenges, those with additional familial responsibilities, such as married employees or those with children, are more vulnerable, experiencing dual stressors from both work and family demands, leading to burnout. Conversely, single employees may experience strain due to insufficient social support, which contributes to feelings of loneliness. Additionally, organizational factors such as poor support systems, inadequate mental health resources, and stigma exacerbate these challenges. The study advocates for more personalized interventions that account for differences in marital status and individual circumstances. It makes a significant contribution to the broader discussion on mental health in the workplace, highlighting the complex relationship between marital status and mental health outcomes in service industries. 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