Self-efficacy, Psychological Empowerment and Occupational Stress: A Structural Equation Model on Quality of Work Life of Local Government Employees

Self-efficacy, Psychological Empowerment and Occupational Stress: A Structural Equation Model on Quality of Work Life of Local Government Employees

Kevin P. Laud^1*, Dr. Fatma M. Idris²

¹Employee, Department of Foreign Affairs, Philippines

²Professor, University of Mindanao, Philippines

^*Corresponding author

DOI: https://dx.doi.org/10.47772/IJRISS.2025.905000319

Received: 04 May 2025; Accepted: 13 May 2025; Published: 13 June 2025

ABSTRACT

Quality of work life (QWL) is a growing priority in public service, as it significantly affects employee well-being, job satisfaction, and organizational effectiveness. In local government settings, where employees often face high demands and limited resources, understanding the factors that influence QWL is essential for creating supportive and productive work environments. This study examined how self-efficacy, psychological empowerment, and occupational stress influence the QWL of local government employees in the Davao Region, Philippines. A quantitative, non-experimental design was used to gather insights from employees across several municipalities, using validated survey instruments to assess their perceptions. To analyze the relationships among the variables and identify the most appropriate model, Structural Equation Modeling (SEM) was applied. The results showed that employees generally reported high levels of self-efficacy and very high level of psychological empowerment, while experiencing moderate levels of occupational stress. SEM analysis revealed that self-efficacy and psychological empowerment both had significant positive effects on QWL, while occupational stress had a negative impact. Among the three predictors, self-efficacy emerged as the most influential factor. The study also identified six core dimensions that define QWL in the local government context: work environment, organizational culture and climate, training and development, compensation and rewards, facilities, and job satisfaction and job security. These findings suggest that strengthening employee confidence and autonomy, while reducing stressors in the workplace, can meaningfully enhance QWL. The proposed model offers practical guidance for policymakers and human resource managers aiming to improve the work experiences and overall well-being of public sector employees.

Keywords: quality of work life, self-efficacy, psychological empowerment, occupational stress

INTRODUCTION

Quality of Work Life (QWL) is a critical factor influencing employee satisfaction, productivity, and organizational success across industries, including manufacturing, education, and the service sector (Monika & Saini, 2019). Poor QWL is linked to occupational stress, burnout, and declining job performance, increasing costs for organizations (World Health Organization [WHO], 2019). Furthermore, inadequate compensation and negative work environments contribute to higher turnover rates, threatening long-term sustainability (Cruz et al., 2022). As employees play a fundamental role in operational efficiency, organizations must prioritize improving QWL to enhance workforce engagement and overall business performance (Nanjundeswaraswamy & Beloor, 2022).

Research highlights several key determinants of QWL, including self-efficacy, psychological empowerment, and occupational stress. Self-efficacy enhances employees’ confidence in their abilities, enabling them to navigate challenges and improve workplace experiences (Saaeda et al., 2020). Psychological empowerment fosters autonomy, purpose, and motivation, promoting job satisfaction and organizational commitment (Tanriverdi et al., 2019). In contrast, occupational stress negatively affects employee well-being, reducing productivity and increasing job dissatisfaction (Singh, 2020). Given these variables’ significant impact, understanding their relationships is essential for fostering a healthier and more productive work environment.

This study aimed to identify the best-fit model for the quality of work life among local government employees in the Davao Region. Specifically, it sought to determine the level of self-efficacy of these employees in terms of coaching, participation, demonstration, mentoring, stimulation, and rewards. Additionally, the study aimed to measure their level of psychological empowerment based on meaning, competence, self-determination, and impact. Furthermore, it examined the level of occupational stress experienced by employees, considering factors such as role overload, role ambiguity, role conflict, unreasonable group and political pressure, responsibility for the person, under participation, powerlessness, poor peer relation, intrinsic impoverishment, low status, and stringent working condition. Another objective was to assess the quality of work life of local government employees by evaluating aspects such as work environment, organizational culture and climate, relation and cooperation, training and development, compensation and rewards, facilities, job satisfaction and job security, autonomy of work, and adequacy of resources. The study also sought to determine the significant relationships between self-efficacy and quality of work life, psychological empowerment and quality of work life, and occupational stress and quality of work life. Ultimately, it aimed to develop the best-fit model for understanding and enhancing the quality of work life among local government employees.

While extensive research has been conducted on QWL, studies focusing on local government employees remain limited, creating a gap in understanding the factors influencing their work experiences. This study addresses this gap by utilizing structural equation modeling to examine the relationships between self-efficacy, psychological empowerment, and occupational stress in predicting QWL. The empirical findings can inform policy-making and strategic human resource management in the public sector. This research offers valuable insights for policymakers and human resource managers, presenting practical strategies to foster a more supportive and productive work environment. By identifying key determinants of QWL, this study provides a basis for local government units to develop targeted interventions aimed at enhancing employee well-being and job satisfaction. To validate these findings, this study tested the following null hypotheses at a 0.05 level of significance: (1) No significant relationships exist between self-efficacy, psychological empowerment, and occupational stress with QWL, and (2) there is no best-fit model that predicts QWL. The resulting best-fit model serves as a framework for improving employee satisfaction, retention, and workplace efficiency, ensuring a more resilient and motivated local government workforce.

Review of Related Literature

The following literature review starts with an all-embracing analysis that highlights the influence of self-efficacy (Heslin, 1999) with the following indicators: coaching, participation, demonstration, mentoring, stimulation, and rewards; psychological empowerment (Mohsen, 2014) meaning, competence, self-determination, and impact; occupational stress (Suraksha & Chhikara, 2017) with the following indicators: role overload, role ambiguity, role conflict, unreasonable group and political pressure, responsibility for the person, under participation, powerlessness, poor peer relation, intrinsic impoverishment, low status, and stringent working conditions; and quality of work life (Swamy et al., 2015) of local government employees in Davao Region with work environment, organizational culture and climate, cooperation and relationship, training and development, facility, work satisfaction and safety, work independence, and resource adequacy as indicators.

Self-Efficacy

Self-efficacy refers to an individual’s belief in their ability to accomplish tasks and achieve desired outcomes. Lindquist et al. (2022) describe self-efficacy as crucial for motivation and performance, while Salmina et al. (2021) emphasize its role in fostering success-oriented behavior. Heslin (1999) identified six dimensions of self-efficacy: coaching, participation, demonstration, mentoring, stimulation, and rewards. Each of these factors contributes to enhancing an individual’s confidence in their work capabilities and overall job satisfaction.

Coaching is a developmental process where employees receive guidance and feedback to enhance their skills and work performance (Sarraf, 2019). Participation refers to employees’ active involvement in decision-making and problem-solving, which strengthens their sense of autonomy and organizational commitment (Lamichhane, 2021). Demonstration, often achieved through role modeling, enables employees to learn by observing experienced colleagues, reinforcing skills and behavioral expectations (Lamb et al., 2022). Mentoring involves a structured exchange of knowledge and experience between senior and junior employees, fostering career development and organizational efficiency (Bortnowska & Seiler, 2019). Stimulation comprises motivational strategies such as goal-setting and challenges that encourage employees to engage in proactive work behaviors (Vakariuk, 2023). Finally, rewards, including both financial and non-financial incentives, serve as reinforcement mechanisms that enhance motivation, job satisfaction, and performance (Landry et al., 2020; Kong et al., 2023).

Research indicates that self-efficacy positively influences work performance and resilience in challenging environments, which in turn enhances QWL by increasing employee engagement and reducing job-related stress. Organizations that invest in strengthening self-efficacy through targeted training, mentorship, and incentive programs experience higher employee retention and productivity. Employees with high self-efficacy are more resilient to workplace challenges, exhibit greater persistence, and contribute positively to organizational success (Kodden, 2020). By fostering an environment that nurtures self-efficacy, organizations can enhance job satisfaction, reduce stress, and optimize workforce performance.

Psychological Empowerment

Psychological empowerment refers to the belief and perception that individuals have control over their work and that their efforts make a meaningful impact on organizational outcomes (Dennerlein & Kirkman, 2023). Psychological empowerment enhances an individual’s perception of control over their work, fostering higher QWL by promoting job satisfaction, motivation, and organizational commitment. It consists of four key dimensions: meaning, competence, self-determination, and impact, which together foster intrinsic motivation and autonomy in tasks (Pan, 2019). Employees who find meaning in their work align their values with their responsibilities, resulting in higher motivation and job satisfaction (Singh & Sarkar, 2019). Competence, as another dimension, reflects an employee’s confidence in their ability to perform work tasks efficiently. Employees with higher perceived competence demonstrate improved performance and greater engagement in their roles (Warda, 2020). Leadership also plays a crucial role in reinforcing competence by providing constructive feedback and professional development opportunities (Schermuly et al., 2022).

Self-determination refers to an individual’s autonomy in decision-making and task execution. Employees who experience higher levels of self-determination report increased motivation and innovative work behaviors (Bantha & Nayak, 2020). Supportive organizational environments further enhance self-determination, resulting in reduced stress and improved workplace satisfaction (Forner et al., 2020). Lastly, impact refers to an employee’s perception of their influence within an organization. Employees who feel that their work contributes meaningfully to organizational goals are more likely to exhibit high levels of commitment and knowledge-sharing behaviors (Judeh et al., 2022). The sense of impact is closely tied to job satisfaction, as employees who believe they can affect workplace outcomes report higher engagement and affective commitment (Shah et al., 2019).

Psychological empowerment is a critical factor in employee well-being and organizational success. It serves as a key predictor of job satisfaction, leadership effectiveness, and lower turnover rates (Mohsen, 2014). Organizations that implement policies supporting psychological empowerment benefit from a motivated and resilient workforce. By fostering a work culture that encourages meaning, competence, self-determination, and impact, companies can enhance employee satisfaction, innovation, and overall workplace effectiveness.

Occupational Stress

Occupational stress refers to an individual’s stress experience at work. It is a result of excessive workloads, limited autonomy, and adverse working conditions, which are inversely related to QWL, as increased stress leads to job dissatisfaction, disengagement, and decreased productivity (Tsimakuridze et al., 2022; Gunasekra & Perera, 2023). Singh and Verma (2019) further emphasize that occupational stress manifests in behavioral and psychological symptoms, including anxiety, burnout, and reduced work engagement, ultimately diminishing both individual and organizational performance.

Suraksha and Chhikara (2017) identified 11 dimensions of occupational stress: role overload, role ambiguity, role conflict, unreasonable group and political pressure, responsibility for others, under-participation, powerlessness, poor peer relations, intrinsic impoverishment, low status, and stringent working conditions. Role overload occurs when employees are assigned excessive tasks beyond their capacity, leading to frustration and burnout (Tang & Vandenberghe, 2021). Role ambiguity refers to unclear job expectations, which cause anxiety and reduced job satisfaction (Cengiz et al., 2021). Role conflict arises when employees face contradictory job demands, affecting their focus and efficiency (Chenevert et al., 2022). Unreasonable group and political pressure involve coercive workplace dynamics that force employees into unethical or conflicting situations, impacting mental well-being (Zhang et al., 2023).

Responsibility for person entails the stress associated with being accountable for colleagues or subordinates, leading to emotional exhaustion (Karapetyan, 2019). Under participation occurs when employees have limited involvement in decision-making processes, making them feel undervalued and increasing workplace stress (Teraoka & Kyougoku, 2019). Powerlessness is a related dimension, wherein employees experience a lack of control over their work environment, resulting in frustration and disengagement (Foulk et al., 2019). Poor peer relations, characterized by workplace isolation and conflict, exacerbate stress and reduce collaboration (Agarwal et al., 2020).

Intrinsic impoverishment refers to a lack of fulfillment in one’s job, where employees feel their work is monotonous and lacks meaning, leading to dissatisfaction (Ali & Miralam, 2019). Low status is another contributing factor, wherein employees with limited recognition or authority experience higher stress levels due to perceived inequities (Mohammadi et al., 2020). Finally, stringent working conditions encompass high job demands, strict deadlines, and minimal autonomy, leading to physical and psychological exhaustion (Sorensen et al., 2020). Organizations aiming to mitigate occupational stress should implement supportive policies that address these dimensions, promote work-life balance, and enhance employee well-being (Vasantha & Santhi, 2020).

Quality of Work Life

Quality of work life (QWL) is defined as the favorable conditions and environments of a workplace that support and promote employee satisfaction by providing workers with rewards, job security, and growth opportunities (Fakhri et al., 2020). Swathi and Dasari (2020) highlight that QWL influences both employee well-being and organizational success by fostering a supportive work environment. Swamy et al. (2015) identified nine key dimensions of QWL: work environment, organizational culture and climate, relation and co-operation, training and development, compensation and rewards, facilities, job satisfaction and job security, autonomy of work, and adequacy of resources.

The work environment, which includes both physical and social aspects, significantly influences job satisfaction. A positive work environment fosters engagement and productivity through supportive leadership and well-maintained facilities (Begum & Mohd, 2021). Organizational culture and climate shape employee attitudes and behaviors, with a cohesive culture enhancing morale and workplace cohesion (Coelho & Pires, 2020). Relation and co-operation, characterized by teamwork and effective communication, strengthen employee collaboration and foster a productive work environment (Geary & Signoretti, 2021).

Training and development ensure employees acquire relevant skills for career growth and organizational effectiveness (Opute, 2020). Additionally, Compensation and rewards, both monetary and non-monetary, significantly impact motivation and job satisfaction, reinforcing employees’ sense of value within the organization (Sudheer, 2021). Adequate workplace facilities, including ergonomic furniture and well-maintained office spaces, improve employee well-being and efficiency (Pidada & Saputra, 2021). Job satisfaction and job security are also essential, as they reduce turnover intentions and increase long-term organizational commitment (Rath & Hentry, 2022).

Autonomy of work, which grants employees control over their tasks and decision-making, enhances motivation and performance (Huybrechts, 2023). Finally, adequacy of resources ensures that employees have access to the necessary tools and support systems for optimal performance, reducing workplace stress and improving overall job efficiency (Amankwah et al., 2022). Collectively, these dimensions highlight the critical role of QWL in improving both employee satisfaction and organizational performance.

Correlation Between Variables

Self-efficacy has been strongly linked to quality of work life (QWL) as it influences employees’ confidence in managing their job responsibilities. Bandura’s (1997) Social Cognitive Theory highlights that individuals with high self-efficacy are more likely to exert control over their work environment, enhancing their job satisfaction and performance. Jaguaco et al. (2022) highlighted that self-efficacy and social support were significant predictors of QWL among Ecuadorian teachers, suggesting that fostering self-efficacy through professional development programs can enhance job satisfaction and overall well-being. Furthermore, Saaeda et al. (2020) argue that self-efficacy allows employees to excel in their roles, effectively managing job-related challenges and improving their overall QWL. Zhang et al. (2022) emphasize that self-efficacy, combined with positive coping strategies, leads to greater well-being and job satisfaction among nursing managers, illustrating its pivotal role in fostering a positive work experience.

Psychological empowerment is another key determinant of QWL, as it fosters a sense of purpose and control over work responsibilities. Tanriverdi et al. (2019) suggest that psychological empowerment improves QWL by enhancing competence, autonomy, and overall work engagement. Bakker and Demerouti’s (2007) Job Demands-Resources Theory further supports this correlation, proposing that when employees experience high levels of empowerment, they are more likely to be motivated, engaged, and satisfied with their work. Maleki (2021) found that employees who perceive greater psychological empowerment report increased job satisfaction and reduced workplace stress, while Monje-Amor et al. (2021) demonstrate that empowered employees have lower turnover intentions and higher job commitment, contributing to a stable and productive workforce.

Conversely, occupational stress has been found to negatively impact QWL, reducing employee well-being and productivity. According to Singh (2020), high levels of occupational stress lead to burnout, mental fatigue, and dissatisfaction, ultimately affecting organizational outcomes. Karasek and Theorell’s (1990) Demand-Control-Support model asserts that job stress is heightened when employees experience excessive demands with minimal control and support, increasing the risk of job-related strain. Purkait and Mohanty (2016) found that occupational stressors, such as role conflict and excessive workload, undermine employees’ confidence in their job stability and career growth, leading to diminished QWL. As a result, organizations must implement strategies to mitigate occupational stress by fostering supportive work environments and promoting work-life balance, ensuring a healthier and more productive workforce.

Theoretical Framework

This study is grounded in Bandura’s (1997) Social Cognitive Theory, which emphasizes the role of self-efficacy in shaping behavior, motivation, and overall well-being. The theory suggests that individuals with high self-efficacy are more likely to persist in challenging tasks, experience reduced occupational stress, and maintain a higher quality of work life. Additionally, social support and positive reinforcement from colleagues and supervisors can enhance self-efficacy, leading to improved job performance and workplace satisfaction (Marcionetti & Castelli, 2022).

Bakker and Demerouti’s (2007) Job Demands-Resources (JD-R) Theory provides further insight into the relationship between psychological empowerment and quality of work life. The theory posits that when employees have access to adequate job resources, such as autonomy and organizational support, they experience greater empowerment, leading to increased motivation, job satisfaction, and overall well-being. Conversely, excessive job demands without sufficient resources contribute to burnout and reduced work engagement, highlighting the importance of balancing job demands and resources to foster a positive work environment.

Karasek and Theorell’s (1990) Demand-Control-Support (DCS) Model further supports the study by explaining the impact of occupational stress on quality of work life. The model asserts that employees facing high job demands with limited control and minimal social support are at greater risk of job strain, leading to lower job satisfaction and diminished well-being (Babamiri, 2022). By identifying these stressors, organizations can develop strategies to enhance job control, provide supportive work environments, and improve employees’ overall quality of work life.

Conceptual Framework

In this study, four hypothesized models were generated showing the potential causal dependence between the hypothesized models of the two latent constructs, namely the exogenous and endogenous variables. The hypothesized model demonstrates the following: the oval shapes represent the latent variables of the study, the rectangular figures connected from the oval are the measured variables of a latent construct, the single headed arrow represents the direct relation from one variable to another while the double headed arrow signifies correlation.

Figure 1. The Conceptual Model Showing the Direct Relationship

of the Latent Exogenous Variables towards the Latent Endogenous Variables

Legend:

COA – coaching

PAR – participation

DEM – demonstration

MEN – mentoring

STI – stimulation

REW – rewards

IMP – impact

SEC – self-determination

COM – competence

MEA – meaning

SWC – stringent working condition

LOS – low status

INI – intrinsic impoverishment

PPR – poor peer relation

POW – powerlessness

UNP – under participation

RFP – responsibility for the person

UGP – unreasonable group and political pressure

ROC – role conflict

ROA – role ambiguity

ROO – role overload

WOE – work environment

OCC – organizational culture and climate

RAC – relation and co-operation

TAD – training and development

CAR – compensation and rewards

FAC – facilities

JSJ – job satisfaction and job security

AOW – autonomy of work

AOR – adequacy of resources

Hypothesized Model 1 as shown in Figure 1 illustrates the direct causal relation of the latent exogenous variables towards the latent endogenous variable. This is illustrated through a single headed arrow connected from self-efficacy, psychological empowerment, and occupational stress towards quality of work life. Furthermore, the rectangular shapes represent the indicators of the corresponding latent exogenous and endogenous variables.

Significance of the Study

This study contributes to the growing body of knowledge on Quality of Work Life (QWL) by examining its determinants among local government employees, with a particular focus on self-efficacy, psychological empowerment, and occupational stress. By identifying the key factors that influence QWL, this research provides a framework for developing strategies that promote a healthier and more productive workforce, aligning with global efforts to enhance Decent Work and Economic Growth (SDG #8).

Moreover, this study underscores the social significance of improving QWL, recognizing that employees in local government spend a substantial portion of their lives at work. A high QWL fosters job satisfaction, motivation, and retention, leading to a workforce that is more engaged in public service and committed to creating Sustainable Cities and Communities (SDG #11). Enhancing the work environment for local government employees can improve governance, service delivery, and overall urban resilience.

From a well-being perspective, occupational stress is a pressing concern that affects both mental and physical health. By investigating the impact of stressors in the workplace and proposing interventions that promote psychological empowerment and self-efficacy, this research aligns with the goals of Good Health and Well-being (SDG #3). Healthier employees contribute to a more effective workforce, reducing absenteeism and improving overall public service efficiency.

Additionally, this study provides valuable insights for local government units, equipping administrators and policymakers with evidence-based recommendations for fostering a supportive and empowering work culture. By enhancing leadership practices, optimizing workplace conditions, and addressing stressors, organizations can create a sustainable framework for improving QWL. This research also serves as a foundation for future investigations, encouraging scholars to further explore strategies for enhancing work life quality in public sector institutions. Through these contributions, the study ultimately supports broader efforts to promote economic sustainability, social resilience, and workforce well-being.

METHOD

Presented in this section are the research respondent, material and instrument and design and procedure including the ethical consideration.

Research Respondent

The data required in this study were obtained from 400 employees of Local Government Units in Region XI (Davao Region) focusing on three provinces and their capital city. Of the 400 respondents, 51 comes from Provincial Government of Davao del Norte, 75 from Provincial Government of Davao de Oro, 69 from Provincial Government of Davao Oriental, 141 from City Government of Tagum of Davao del Norte, and 64 from City Government of Mati of Davao Oriental. Private employees, employees from national government agencies and GOCCs either in or out of the Davao Region, local government employees do not belong to the above-mentioned local government units, and other subjects that have not met the inclusion criteria are not qualified to participate on the study.

Respondents who met the inclusion criteria and who were willing to participate on the study implies participation is voluntary. Their refusal to participate will involve no penalty or loss of benefits to which they are otherwise entitled. At any time, they may withdraw their consent and discontinue participation without penalty especially when they cannot provide the information that is needed on them. Due to their involvement in this research study, the respondents did not waive any legal allegations, freedom or remedies. The sample size was determined by the researcher by means of Taro Yamane’s Formula. In addition, the researcher utilized random sampling in determining the representative sample for each local government unit.

The study was conducted in the Davao Region, designated as Region XI, one of the regions in the Philippines located in the southern portion of Mindanao. It is circumscribed on the North by CARAGA region, on the east and south by the Philippine Sea, on the west by Bukidnon and SOCSARGEN Region as shown in the vicinity map. The Davao Region consists of five provinces and six cities, namely: Davao del Norte, Davao de Oro, Davao del Sur, Davao Oriental and Davao Occidental, Davao City, Digos City, Mati City, Panabo City, Island Garden City of Samal (IGACOS), and Tagum City, respectively. Taking into account that the researcher works and live in the said province and was assigned by the Department of Foreign Affairs to work on its Consular Office in Tagum City in Region XI explains why Davao Region is the optimal locale of the study.

Materials and Instrument

Four validated survey instruments were adapted and modified for this study. The Self-Efficacy Survey Questionnaire by Heslin (1999) was used to assess the self-efficacy of local government unit employees, comprising 19 items categorized into six dimensions: coaching, participation, demonstration, mentoring, stimulation, and rewards. The Psychological Empowerment Measurement Tool by Spreitzer (1995) included 16 items evaluating four dimensions: meaning, competence, self-determination, and impact. The Occupational Stress Questionnaire by Srivastava and Singh (1981) measured occupational stress through 41 items across eleven indicators, including role overload, role ambiguity, and powerlessness. Lastly, the Quality of Work Life Questionnaire by Swamy et al. (2015) assessed nine dimensions, such as work environment, organizational culture, and job satisfaction, using 50 items. These instruments provided a comprehensive framework for evaluating the study variables.

The scale guide in the analysis and interpretation of the responses on self-efficacy, psychological empowerment, occupational stress and quality of work life was categorized into five mean range levels describe as follow:

Primary data were used in gathering information about the study which consists of four parts, namely: self-efficacy, psychological empowerment, occupational stress and quality of work life. The survey questionnaires utilized for the study was sourced from various related researches. Restructuring was carried out to make the instrument more applicable to current, local government setting. To make the instrument more contemporary, it was validated by five expert validators with an overall rating of 4.47 or Very Good.

Pilot testing was conducted after validation. Cronbach’s alpha was used to verify the questionnaire’s validity with the following measures: self-efficacy (0.977), psychological empowerment (0.957), occupational stress (0.973) and quality of work life (0.967). Cronbach’s alpha consistency coefficient customarily ranges between zero to one. However, there was no lower limit to the coefficient. The closer the Cronbach’s alpha coefficient is to one, the larger the internal constancy of the items in the scale (Gliem & Gliem, 2003). In addition, Darren and Mallery (1999) suggested the following ground rules in measuring the reliability of the questionnaire with the use of Cronbach’s alpha: if the result is greater than or equal to 0.9 it is excellent; greater than or equal to 0.8 is good; greater than or equal to 0.7 is acceptable; greater than or equal to 0.6 is questionable; greater than or equal to 0.5 is poor and greater than or equal to 0.4 is unacceptable.

Design and Procedure

This study employed a quantitative non-experimental research design, which involves observing and analyzing relationships between variables without manipulating them. Non-experimental designs are particularly useful when studying naturally occurring phenomena, making them ideal for investigating workplace dynamics without imposing artificial conditions (Nwabuko, 2024). This approach allowed the study to examine how self-efficacy, psychological empowerment, and occupational stress influence employees’ quality of work life in real-world settings. Since directly manipulating these workplace factors would be impractical or unethical, a non-experimental design ensured that findings accurately reflected actual employee experiences.

To analyze these relationships, the study utilized structural equation modeling (SEM), a statistical method that allows for the testing of direct and indirect relationships between multiple variables in a single model. SEM integrates factor analysis, which measures latent variables, and path analysis, which examines the structural relationships among observed and latent variables (Stoffels et al., 2023). This method enables researchers to explore complex relationships while accounting for measurement errors and theoretical assumptions. The modeling process involved five key steps: model specification, identification, estimation, goodness-of-fit assessment, and model respecification, ensuring the validity and reliability of the model.

The data collection process followed several systematic procedures. First, ethical clearance was obtained from the University of Mindanao Ethics Review Committee (UMERC). Following approval, the research instrument underwent expert validation by a panel of five specialists. The manuscript was revised based on their recommendations and resubmitted to UMERC with the required attachments, including validated questionnaires and UMERC forms. A second review was conducted to ensure compliance with initial feedback. Prior to full implementation, a pilot test was conducted to assess respondent comprehension and response time. The actual survey followed, with 400 questionnaires distributed across various areas in the Davao Region over a 12-week period to account for the study’s broad geographic scope. Data collection was completed in the last quarter of 2023. Screening procedures were applied to minimize outliers before encoding, tabulating, and analyzing the data. Finally, the results were interpreted in alignment with the study’s objectives.

The data gathered were analyzed using various statistical tools. Mean was utilized to quantify the levels of each variable by computing the average of data sets. Pearson Product-Moment Correlation (r) measured the strength of linear associations, revealing interrelationships between self-efficacy, psychological empowerment, occupational stress, and quality of work life. Goodness of Fit was employed to evaluate how well the statistical model aligned with observed data, using tests like Chi-square to measure the model’s accuracy. Finally, Structural Equation Modeling (SEM) was applied to analyze relationships between measured variables and latent constructs, ensuring the identification of the best-fit model by eliminating attributes with low correlations.

The researcher followed ethical guidelines, as specified by the Office of Professional Schools, University of Mindanao. This includes undergoing an Ethics Review process before conducting surveys to the respondents to ensure that procedures were fair and unbiased to all involved. The researcher written a permission letter to conduct the study with the approval of the adviser along with where the survey will be conducted and how the data will be collected. After the approval of the adviser and the issuance of the UMERC certificate with protocol number UMERC-2023-233, the letters were distributed to the Local Government Units in Davao Region. After the permission was granted, the researcher approached the heads or proper departments who assist in identifying the potential participants of the study such as the Human Resource Management Office (HRMO) and/or Research and Development Office (RDO). These offices have the data on the qualified employees to participate in the study. Hence, it is appropriate to closely coordinate with them during the administration of the questionnaire.

RESULTS AND DISCUSSION

In this section, the data collected on self-efficacy, psychological empowerment, occupational stress, and quality of work life of local government employees in Region XI are presented.

Self-efficacy of Local Government Employees

Shown in Table 1 the level self-efficacy of local government employees measured by coaching, participation, mentoring, stimulation, and rewards. An overall mean of 4.04 (SD of 0. 77) was obtained which is described as high. This means that the level of self-efficacy is often manifested. On a per-indicator analysis, it was found that the indicator stimulation has the highest mean of 4.16 or High, with a standard deviation of 0.72, while the indicator mentoring has the lowest mean of 4.10 or High, with a standard deviation of 0.70.

Table 1. Level of Self-Efficacy of Local Government Employees

The results show that self-efficacy among the respondents is high. This implies that self-efficacy of local government employees is often manifested. The high descriptive levels on every indicator of self-efficacy showed that local government employees in Region XI showed high regards on coaching, participation, mentoring, stimulation, and rewards.

This aligns with the research of This aligns with the research of Heslin (1999), who emphasized that these dimensions are key to enhancing employees’ confidence and overall job satisfaction. Studies have shown that self-efficacy positively influences workplace engagement, resilience, and productivity (Kodden, 2020). Organizations that cultivate self-efficacy through structured development programs experience higher employee motivation and commitment (Lindquist et al., 2022; Salmina et al., 2021). Thus, the high self-efficacy levels observed among local government employees in Region XI suggest a work environment that fosters professional growth, motivation, and overall job effectiveness.

Psychological Empowerment of Local Government Employees

Presented in Table 2 is the level of psychological empowerment of local government employees in terms of meaning, competence, delf-determination, and impact. The obtained overall mean at 4.33 (SD 0.50) signifies a very high level. This indicates that the level of psychological empowerment of local government employees is always manifested. On per-indicator analysis, the indicator, meaning has highest mean of 4.48 or Very High with a standard deviation of 0.53, while the indicator impact has the lowest mean of 4.19 or High with a standard deviation of 0.56.

Table 2. Level of Psychological Empowerment of Local Government Employees

The very high level of result of the indicators of psychological empowerment of local government employees in Region XI in terms of meaning, competence, and self-determination imply that the local government established the psychological empowerment for their employees.

This finding aligns with the study of Pan (2019), who emphasized that psychological empowerment enhances intrinsic motivation and autonomy in tasks, leading to higher job satisfaction and commitment. Employees who perceive their work as meaningful, feel competent in their roles, and have autonomy in decision-making are more engaged and productive (Singh & Sarkar, 2019; Bantha & Nayak, 2020). Furthermore, supportive organizational environments that reinforce these dimensions contribute to reduced workplace stress and improved employee well-being (Forner et al., 2020). The high levels of psychological empowerment observed among local government employees in Region XI suggest that the existing workplace culture effectively fosters motivation, resilience, and a strong sense of contribution to organizational goals.

Occupational Stress of Local Government Employees

Shown in Table 3 is the level of occupational stress of local government employees in terms of role overload, role ambiguity, role conflict, unreasonable group and political pressure, responsibility for the person, under participation, powerlessness, poor peer relation, intrinsic impoverishment, low status, and stringent working condition. The level of occupational stress of local government employees in Region XI attained an overall mean of 2.63 which is described as moderate. This means that the level of occupational stress among local government employees in Region XI is sometimes manifested.  On a per-indicator analysis, it was found that the indicator, responsibility for the person, has the highest mean of 3.13, or moderate, with a standard deviation of 1.09, while the indicators, intrinsic impoverishment and low status, have the lowest mean scores of 2.21 or low and with both standard deviation of 0.99.

Table 3. Level of Occupational Stress of Local Government Employees

The level of occupational stress among local government employees in Region XI is moderate.  The findings of the study suggest that occupational stress is moderately manifested by LGU employees which affects their overall quality of work life.

This is in line with the findings of Tsimakuridze et al. (2022), which highlights that occupational stress arises from excessive workload, lack of control, and unfavorable work conditions, impacting both job performance and well-being. While moderate levels of stress can sometimes serve as a motivator, prolonged exposure may lead to decreased productivity, job dissatisfaction, and burnout (Gunasekara & Perera, 2023; Singh & Verma, 2019). Factors such as role ambiguity, workload pressure, and limited participation in decision-making contribute to workplace stress, affecting employees’ engagement and efficiency (Cengiz et al., 2021; Teraoka & Kyougoku, 2019). However, organizations that implement supportive policies, such as clear job expectations, participatory decision-making, and stress management programs, can mitigate these effects and enhance employee well-being (Vasantha & Santhi, 2020). The moderate level of occupational stress observed among local government employees in Region XI suggests that while workplace challenges exist, organizational strategies may be in place to help employees manage stress and maintain a balanced quality of work life.

Quality of work life of Local Government Employees

Displayed in Table 4 is the level of quality of work life of local government employees which is measured in terms of work environment, organizational culture and climate, relation and co-operation, training and development, compensation and rewards, facilities, job satisfaction and job security, autonomy of work, and adequacy of resources. It obtained an overall mean of 4.03 which is described as High, which indicates that quality of work life is often manifested.  The indicator that got the highest mean, organizational culture and climate at 4.15 which is described as high. On the other hand, the indicator autonomy of work obtained the lowest mean at 3.75 which is described as very high.

Table 4. Level of Quality of Work Life of Local Government Employees

The high descriptive levels on every indicator of quality of work life showed that local government employees in Region XI showed high regards on work environment, organizational culture and climate, relation and co-operation, training and development, compensation and rewards, facilities, job satisfaction and job security, autonomy of work, and adequacy of resources.  These result to overall high level of quality of work life which implies that quality of work life of local government employees is often manifested.

This finding aligns with the study of Fakhri et al. (2020), which emphasizes that a favorable work environment, strong organizational culture, and adequate support systems contribute significantly to employees’ job satisfaction and overall well-being. Swathi and Dasari (2020) further highlight that a high quality of work life fosters employee motivation, engagement, and productivity, ultimately benefiting both individuals and the organization. Additionally, providing adequate compensation, training opportunities, and workplace facilities enhances employees’ sense of value and commitment to their roles (Sudheer, 2021; Pidada & Saputra, 2021). The high level of quality of work life observed among local government employees in Region XI suggests that existing workplace policies and practices effectively promote a supportive and fulfilling work environment, reinforcing employee retention, job performance, and overall organizational success.

Relationship between Self-efficacy and Quality of Work Life

Displayed on Table 5 are the results of the assessment on the relationship between self-efficacy and quality of work life among local government employees. As shown in the hypothesis, the relationship was tested at a 0.05 level of significance. The overall correlation coefficient (r-value) is 0.787 with a p-value less than .05, indicating that the null hypothesis was rejected. It can be deduced that there is a very strong positive relationship between self-efficacy and quality of work life.

Individually, all dimensions of self-efficacy correlate positively with aspects of quality of work life, having p-values less than .05. The r-values for each factor include .750 for participation, .733 for coaching, .720 for stimulation, .709 for demonstration, .697 for mentoring, and .685 for rewards. As a result, there is a significant relationship between self-efficacy and various aspects of quality of work life, suggesting that improvements in self-efficacy could lead to better work life quality for local government employees.

Table 5. Significance of the Relationship between Levels of Self-efficacy and Quality of Work Life

Legend:

The results indicate that enhancing self-efficacy among local government employees can lead to substantial improvements in their quality of work life. Given the significant positive correlations across various dimensions of self-efficacy (such as coaching, participation, and rewards) with all aspects of quality of work life, interventions that bolster self-efficacy are likely to have a broad and meaningful impact. By focusing on strategies that improve employees’ self-belief in their capabilities, organizations can foster a work environment that enhances overall job satisfaction, organizational culture, and the adequacy of resources, thereby promoting a more engaged and productive workforce.

The results of this study align with existing research, confirming the strong relationship between self-efficacy and quality of work life (QWL). Bandura’s (1997) Social Cognitive Theory asserts that individuals with high self-efficacy exert greater control over their work environment, mirroring this study’s findings that self-efficacy significantly enhances QWL. Similarly, Jaguaco et al. (2022) identified self-efficacy as a key predictor of QWL among teachers, just as this study found strong correlations across self-efficacy dimensions. Saaeda et al. (2020) and Zhang et al. (2022) further support this by demonstrating that self-efficacy improves job satisfaction and well-being, comparable to this study’s evidence that higher self-efficacy leads to better work conditions and employee experiences.

Relationship between Psychological Empowerment and Quality of Work Life

Shown on Table 6 are the results of the test of relationship between psychological empowerment and quality of work life (QWL) in local government units. As shown in the hypothesis, the relationship was tested at a 0.05 level of significance. The overall correlation coefficient (r-value) is 0.574 with a p-value less than .05, indicating that the null hypothesis was rejected. It can be deduced that there is a strong positive relationship between psychological empowerment and quality of work life.

More specifically, the results show that all indicators of psychological empowerment correlate positively with quality of work life, with p-values less than .05. The r-values are .537 for impact, .526 for meaning, .498 for self-determination, and .491 for competence. As a result, there is a significant relationship between psychological empowerment and quality of work life, suggesting that enhancements in psychological empowerment can positively influence various aspects of employees’ work life quality.

Table 6. Significance of the Relationship between Levels of Psychological Empowerment and Quality of Work Life

Legend:

The results from Table 6 suggest that psychological empowerment plays a critical role in enhancing the QWL for local government employees. Given the strong positive correlations between the various dimensions of psychological empowerment (such as meaning, competence, self-determination, and impact) and different aspects of QWL, initiatives aimed at fostering psychological empowerment could lead to significant improvements in work environment, job satisfaction, and overall well-being. This implies that by investing in strategies that empower employees psychologically, local government units can create a more motivated, satisfied, and productive workforce, ultimately leading to better organizational outcomes.

The findings support existing research, demonstrating that psychological empowerment significantly improves QWL. Studies by Tanriverdi et al. (2019) and Bakker and Demerouti (2007) emphasize that empowerment enhances competence, autonomy, and motivation, thereby increasing job satisfaction. Similarly, Maleki (2021) and Monje-Amor et al. (2021) found that empowered employees experience reduced stress, greater commitment, and lower turnover rates. These findings align with the positive correlations observed in this study, affirming that psychological empowerment is a crucial factor in enhancing QWL.

Relationship between Occupational Stress and Quality of Work Life

Table 7 presents the analysis of the relationship between occupational stress and the quality of work life among local government employees. Data showed an overall correlation coefficient of -.227 at a 0.05 level of significance, indicating a significant negative relationship. This suggests that as occupational stress increases, the quality of work life decreases.

Specifically, all dimensions of occupational stress, except responsibility for the person, show negative correlations with QWL, with the strongest effects seen in stringent working conditions (-0.292), low status (-0.289), and intrinsic impoverishment (-0.261). These negative correlations imply that higher levels of occupational stress negatively impact the quality of work life.

Table 7. Significance of the Relationship between Levels of Occupational Stress and Quality of Work Life

Legend:

The results from Table 7 imply that occupational stress has a significant detrimental impact on the quality of work life (QWL) among local government employees. The negative correlations between various stress indicators and QWL suggest that higher levels of occupational stress, such as stringent working conditions, low status, and powerlessness, contribute to a decrease in overall work life quality. This underscores the importance of addressing and mitigating occupational stress through targeted interventions and organizational strategies to enhance employees’ well-being, job satisfaction, and overall productivity. By reducing stressors in the workplace, local government units can foster a healthier and more supportive work environment.

The findings align with existing research, confirming that occupational stress negatively impacts quality of work life (QWL). Singh (2020) highlights that high occupational stress leads to burnout, dissatisfaction, and reduced well-being, consistent with this study’s observed negative correlations. Karasek and Theorell’s (1990) Demand-Control-Support model supports this by explaining that excessive job demands with limited control increase stress, lowering QWL. Similarly, Purkait and Mohanty (2016) found that stressors like role conflict and workload instability diminish employees’ job satisfaction and career growth, reflecting this study’s findings that stringent working conditions and low job status significantly reduce QWL. These results emphasize the need for supportive policies and stress-reduction strategies to improve employee well-being.

Influence of Self-efficacy, Psychological Empowerment and Occupational Stress on Quality of Work Life

Displayed in Table 8 are the results of the analysis on the influence of self-efficacy, psychological empowerment, and occupational stress on the quality of work life (QWL) of local government employees.  The results show that self-efficacy has the most substantial positive influence on QWL, with a beta coefficient (β) of .666 and a t-value of 19.362, significant at p < .000. This indicates that higher self-efficacy significantly enhances employees’ quality of work life. Psychological empowerment also positively influences QWL, with a beta coefficient (β) of .238 and a t-value of 7.009, significant at p < .000, though its impact is less pronounced than that of self-efficacy. On the other hand, occupational stress has a negligible and non-significant negative influence on QWL, with a beta coefficient (β) of -.006 and a t-value of -.213, showing that it does not significantly affect the quality of work life in this context.

The overall model, with an R-squared value (R²) of .662, indicates that approximately 66.2% of the variance in quality of work life can be explained by these three variables combined. The F-value of 258.608 and a p-value of .000 suggest that the model is statistically significant.

Table 8. Significance of the Influence of Self-Efficacy, Psychological Empowerment, and Occupational Stress on Quality of Work Life of Local Government Employees

The results of Table 8 suggest that self-efficacy and psychological empowerment are crucial factors in enhancing the quality of work life (QWL) among local government employees. With self-efficacy showing the most substantial positive influence and psychological empowerment also having a significant positive impact, it’s clear that fostering these attributes can lead to improved job satisfaction, work environment, and overall well-being. Conversely, occupational stress does not significantly impact QWL in this context, suggesting that the positive effects of self-efficacy and psychological empowerment may mitigate the detrimental effects of stress. These findings underscore the importance of developing programs and interventions that enhance self-efficacy and psychological empowerment to promote a more motivated, resilient, and productive workforce in local government units.

This is consistent with the findings of several studies. Kodden (2020) and Aggarwal et al. (2020) highlighted the significant role of self-efficacy and psychological empowerment in employees’ well-being, work engagement, and achievements. On the other hand, Bui et al. (2019) noted that self-efficacy at work, influenced by physiological and emotional states, vicarious experiences, and verbal persuasion, in turn, affects the quality of work life. Meanwhile, Gunasekra and Perera (2023) emphasized that occupational stress, a subset of stress linked to occupation/work/job, can negatively impact the quality of work life. However, when psychological empowerment is high, it leads to improved work engagement, reduced psychological withdrawal behavior, and enhanced quality of work life (Aggarwal et al., 2020).

Generated Structural Models

Five models were generated to obtain the best fit model of quality of work life of LGU employees.  The models were assessed against the given fit indices and served as basis to accept or reject the model.

Table 9. Summary of Goodness of Fit Measures of the Five Generated Models

Legend:

CMIN/DF – Chi Square/Degrees of Freedom

GFI         – Goodness of Fit Index

RMSEA  – Root Mean Square of Error Approximation

NFI – Normed Fit Index

TLI – Tucker-Lewis Index

CFI – Comparative Fit Index

Table 9 presents the evaluation of Structural Model 1, which examines the direct relationship between the endogenous variable, quality of work life, and the exogenous variables, self-efficacy, psychological empowerment, and occupational stress. The model’s fit was assessed using multiple goodness-of-fit indices, all of which indicate a poor overall fit. Among the five generated models, Model 1 is the worst fit, as reflected in several key metrics. The Chi-Square/Degrees of Freedom (CMIN/DF) value of 4.256 significantly exceeds the acceptable range (0–2), indicating substantial model misfit. Additionally, the P-value of 0.000, while statistically significant, suggests that the model does not adequately represent the data. The Root Mean Square Error of Approximation (RMSEA) is 0.090, surpassing the recommended threshold of less than 0.05, further confirming poor fit, while the P-close value of 0.000 reinforces that Model 1 fails to meet the criteria for a well-fitting model. Other fit indices fall below the acceptable standard of greater than 0.95, including the Goodness of Fit Index (GFI) at 0.749, the Comparative Fit Index (CFI) at 0.880, the Normed Fit Index (NFI) at 0.840, and the Tucker-Lewis Index (TLI) at 0.871. Since all model fit indices are outside acceptable thresholds, Model 1 exhibits the poorest fit among all five generated models. Similarly, Models 2, 3, and 4 also demonstrate poor fit, as their CMIN/DF values remain excessively high, their RMSEA values exceed 0.05, and their fit indices (GFI, CFI, NFI, and TLI) all fail to reach the required thresholds.

Best Fit Model of Quality of Work Life

On the other hand, Structural Model 5 demonstrates a strong model fit. All indices successfully met the established criteria: CMIN/DF was below 2, while GFI, CFI, NFI, and TLI all exceeded 0.95. Additionally, the RMSEA was below 0.05, and the P-close value was greater than 0.05, confirming an acceptable fit. These results align with the guidelines set by Arbuckle and Wothke (1999), which emphasize that CMIN/DF should be less than 2, and that GFI, CFI, NFI, and TLI should all surpass 0.95. Furthermore, the RMSEA and P-close values are consistent with the recommendations of MacCallum et al. (1996), who classified RMSEA values of 0.01, 0.05, and 0.08 as indicative of excellent, good, and mediocre fit, respectively, with an acceptable model requiring a P-close greater than 0.05.

Figure 2: Best Fit Model in Standard Solution

Legend:

REW – rewards

DEM – demonstration

PAR – participation

COA – coaching

IMP – impact

COM – competence

MEA – meaning

SWC – stringent working condition

ROO – role overload

WOE – work environment

OCC – organizational culture and climate

TAD – training and development

CAR – compensation and rewards

FAC – facilities

JSJ – job satisfaction and job security

Figure 2 presents Structural Model 5, which illustrates the interrelationships among the latent exogenous variables—self-efficacy, psychological empowerment, and occupational stress—and their direct causal effects on the latent endogenous variable, quality of work life in local government units. As the best-fit model, it highlights the significant pathways between these variables. The model also demonstrates the interconnectedness of the three exogenous variables, with self-efficacy directly influencing psychological empowerment and occupational stress, while psychological empowerment also exhibits a direct relationship with occupational stress.

Furthermore, four out of six indicators of self-efficacy—rewards, demonstration, participation, and coaching—remained as significant measures of the construct. Similarly, psychological empowerment retained three out of four indicators—impact, competence, and meaning—which effectively captured the variable. In contrast, occupational stress was measured by only two out of its eleven indicators, namely, stringent working conditions and role overload. These findings suggest that quality of work life in Region XI is primarily influenced by self-efficacy, psychological empowerment, and occupational stress, with each factor being assessed through its strongest indicators.

Moreover, Structural Model 5 confirms a direct causal link between the exogenous variables and the endogenous variable. Quality of work life was initially conceptualized using nine indicators: work environment, organizational culture and climate, relation and cooperation, training and development, compensation and rewards, facilities, job satisfaction and job security, autonomy of work, and adequacy of resources. However, the final model retained only six of these indicators—work environment, organizational culture and climate, training and development, compensation and rewards, facilities, and job satisfaction and job security—as viable constructs for measuring quality of work life.

Certain indicators were removed from the model due to their low beta values and non-significant p-values. Specifically, mentoring and stimulation, self-determination, role ambiguity, role conflict, unreasonable group and political pressure, responsibility for the person, under-participation, powerlessness, poor peer relations, intrinsic impoverishment, and low status were eliminated from the occupational stress construct. Additionally, relation and cooperation, autonomy of work, and adequacy of resources were excluded as indicators of quality of work life. The trimming of these indicators suggests that only the most robust factors contribute significantly to the model’s overall fit and explanatory power.

The direct causal link of self-efficacy, psychological empowerment and occupational stress towards quality of work life among local government unit employees in Region XI, corroborates the research outcomes revealed by Syahidah et al. (2021) emphasize that career growth, appropriate compensation, employee participation, and work stress significantly influence organizational commitment aligning with the self-efficacy factors of rewards and participation. Jati (2022) adds that adequate and fair compensation, social integration, growth and security, and development of human capacities are pivotal to enhancing quality of work life. Moreover, self-efficacy factors such as rewards, demonstration, participation, and coaching play a significant role in shaping employees’ quality of work life.

Evidence according to Al-Kasasbeh (2021) underscores the impact of employee empowerment elements like influence and competency on organizational performance and work-life quality. Psychological empowerment aspects like impact and competence are integral to this dynamic as well. Meanwhile, Denis and Ndanyi (2022) highlight the negative effects of occupational stress, due to work overload and negative work relations, on job performance, which can be linked to the occupational stress factors of stringent working conditions and role overload. Nanjundeswaraswamy and Beloor (2022), Fakhri et al. (2020), and Begum and Mohd (2021) all emphasize the significant influence of factors such as compensation and rewards, job security, work environment, training and development, job satisfaction, facilities, and organizational culture on quality of work life. These factors can be linked to both self-efficacy and psychological empowerment factors, demonstrating the interconnectedness of these constructs in influencing quality of work life.

The model fit for quality of work life among local government unit employees is aligned with the Social Cognitive Theory of Bandura (1997) which emphasizes the importance of self-efficacy to produce specific performance outcomes and how people are both influenced by and actively influence their environments.  Further, this is also supported by the Demand-Control-Support model of Karasek and Theorell (1990) that posits occupational stress can negatively impact the quality of work life, as it can lead to burnout, job dissatisfaction, and reduced productivity.

CONCLUSIONS AND RECOMMENDATIONS

In conclusion, this study has demonstrated the significant impact of self-efficacy, psychological empowerment, and occupational stress on the quality of work life (QWL) among local government employees in the Davao region. The findings indicate high levels of self-efficacy and very high levels of psychological empowerment among employees, contributing positively to their overall QWL. Conversely, moderate levels of occupational stress have been shown to negatively affect QWL, though the strong positive influences of self-efficacy and psychological empowerment mitigate this impact. The best-fit model identified six key QWL indicators: work environment, organizational culture and climate, training and development, compensation and rewards, facilities, and job satisfaction and job security. These findings emphasize the need for policies and programs that enhance self-efficacy, sustain psychological empowerment, and mitigate occupational stress to ensure an improved and sustainable work environment for employees.

The results of this study align with Bandura’s (1997) Social Cognitive Theory, which highlights self-efficacy as a key determinant of behavior, motivation, and well-being. The findings affirm that employees with high self-efficacy and psychological empowerment experience better QWL, supporting Bandura’s proposition that belief in one’s abilities leads to positive workplace outcomes. Furthermore, the theory suggests that reducing occupational stress through social support and positive feedback can strengthen self-efficacy, which resonates with the study’s findings that supportive workplace structures can improve employee satisfaction and productivity. By integrating Bandura’s framework, this study reinforces the importance of fostering confidence, empowerment, and supportive work environments to enhance overall QWL in local government settings.

Given the findings on the levels of exogenous variables, local government units should sustain and further enhance self-efficacy and psychological empowerment while addressing moderate occupational stress among employees. Training programs focusing on leadership development, mentorship, and continuous skills training should be institutionalized to maintain high self-efficacy levels. Psychological empowerment initiatives such as participatory decision-making, job enrichment, and autonomy in task execution should be reinforced to sustain its very high level. Meanwhile, to address moderate levels of occupational stress, implementing stress management workshops and promoting work-life balance through flexible work arrangements and employee wellness programs can help alleviate stress and improve overall well-being.

Since self-efficacy and psychological empowerment significantly enhance quality of work life (QWL), while occupational stress negatively affects it, interventions should prioritize enhancing the positive predictors while mitigating the negative effects of stress. Policies should be formulated to integrate self-efficacy-building programs into employee development plans, ensuring that employees gain confidence in their roles. Additionally, fostering a culture of empowerment through clear communication, recognition programs, and team-based problem-solving will strengthen employees’ sense of competence and impact. Simultaneously, addressing stress through support systems, grievance mechanisms, and mental health initiatives will ensure that occupational stress does not undermine QWL.

Considering the best fit model, local government units should adopt a comprehensive approach that integrates these findings into organizational strategies. The model identified six key indicators of QWL: work environment, organizational culture and climate, training and development, compensation and rewards, facilities, and job satisfaction and job security. Improvement efforts should include investments in infrastructure and ergonomic workspaces, promoting a supportive and inclusive workplace culture, increasing professional development opportunities, and ensuring competitive salaries and benefits. Organizational policies must emphasize employee well-being by integrating job security measures, structured career growth paths, and accessible support services. These practical initiatives will reinforce a sustainable and high-quality work life, leading to increased employee satisfaction, retention, and overall organizational efficiency.

REFERENCES

1. Agarwal, B., Brooks, S., & Greenberg, N. (2020). The Role of Peer Support in Managing Occupational Stress: A Qualitative Study of the Sustaining Resilience at Work Intervention. Workplace Health & Safety, 68(2), 57-64.
2. Aggarwal, A., Chand, P., Jhamb, D., & Mittal, A. (2020). Leader–Member Exchange, Work Engagement, and Psychological Withdrawal Behavior: The Mediating Role of Psychological Empowerment. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.00423.
3. Ali, N., & Miralam, M. (2019). The Effect of Job Stress and Need Deficiency on Performance. Management Science Letters.
4. Al-Kasasbeh, M. (2021). Mediating Role of Quality of Work-Life in the Relationship between Employees Empowerment and Organizational Performance Using Balanced Scorecard. International Journal for Quality Assurance. https://doi.org/10.34028/IJQA/4/1/155.
5. Amankwah, O., Choong, W., & Boakye-Agyeman, N. (2022). The Relationship between Facilities Management Service Quality and Patients’ Health-care Experience: The Mediating Effect of Adequacy of Health-care Resource. Facilities. and Reference. USA: Allyn &Bacon.
6. Babamiri, M., Heydari, B., Mortezapour, A., & Tamadon, T. (2022). Investigation of Demand–Control–Support Model and Effort–Reward Imbalance Model as Predictor of Counterproductive Work Behaviors. Safety and Health at Work, 13(4), 469-474.
7. Bakker, A., & Demerouti, E. (2007). The Job Demands-resources Model: State of the art. Journal of Managerial Psychology, 22(3), 309-328.
8. Bandura, A. (1997). Self-efficacy: The Exercise of Control. New York: W.H. Freeman.
9. Bantha, T., & Nayak, U. (2020). The Relation of Workplace Spirituality with Employees’ Innovative Work Behaviour: The Mediating Role of Psychological Empowerment. Journal of Indian Business Research.
10. Begum, B., & Mohd, A. (2021). Workplace Environment and its Impact on the Quality of Life of Employees. Journal of University of Shanghai for Science and Technology.
11. Bortnowska, H., & Seiler, B. (2019). Formal Mentoring in Nonprofit Organizations. Model Proposition. Management, 23, 188-208.
12. Bui, T. H. T., Nguyen, T. A. T., & Nguyen, T. M. (2019). Vietnamese Young Graduate Employees’ Evaluation of Sources of Self-efficacy at Work. The Open Psychology Journal, 12(1).
13. Cengiz, A., Yoder, L., & Danesh, V. (2021). A Concept Analysis of Role Ambiguity Experienced by Hospital Nurses Providing Bedside Nursing Care. Nursing & health sciences.
14. Chenevert, M., Vignoli, M., Conway, P., & Balducci, C. (2022). Workplace Bullying and Post-Traumatic Stress Disorder Symptomology: The Influence of Role Conflict and the Moderating Effects of Neuroticism and Managerial Competencies. International Journal of Environmental Research and Public Health, 19.
15. Coelho, D., & Pires, R. (2020). Impact of Organizational Climate. Scientific Electronic Archives, 14, 67.
16. Cruz, L., Sengco, B., & Gadin, N. (2022). Working To Leave Or Living To Work? A Study On DCLC Employees’ Quality Work Life Factors And Its Impact On Turnover Intention. International Research Journal of Science, Technology, Education, and Management. 5. 23-30.
17. Darren, G., & Mallery, P. (1999). SPSS for Windows Step by Step: A Simple Guide
18. Denis, M., & Ndanyi, D. (2022). Occupational Stress and How It Influences Employee Performance Among Public Servants in Uganda. International Journal of Social Sciences and Management Review. https://doi.org/10.37602/ijssmr.2022.5211.
19. Dennerlein, T., & Kirkman, B. (2023). The Forgotten Side of Empowering Others: How Lower Social Structural Empowerment Attenuates the Effects of Empowering Leadership on Employee Psychological Empowerment and Performance. Journal of Applied Psychology, 108(11), 1856–1872.
20. Fakhri, M., Nurnida, I., Winarno, A., Kurnia, B., & Suryana, D. (2020). Characteristics of Quality of Work Life on Employees at Consultant Company in Indonesia. Journal of Asian Finance, Economics and Business, 7, 1105-1111. https://doi.org/10.13106/jafeb.2020.vol7.no11.1105.
21. Forner, V., Jones, M., Berry, Y., & Eidenfalk, J. (2020). Motivating Workers: How Leaders Apply Self-determination Theory in Organizations. Organization Management Journal.
22. Foulk, T., De Pater, I., Schaerer, M., Du Plessis, C., Lee, R., & Erez, A. (2019). It’s lonely at the bottom (too): The Effects of Experienced Powerlessness on Social Closeness and Disengagement. Personnel Psychology. 73. 10.1111/peps.12358.
23. Geary, J., & Signoretti, A. (2021). The Role of Socio-economic Embeddedness in Promoting Cooperation in the Workplace: Evidence from Family-owned Italian firms. Economic and Industrial Democracy, 43, 1867-1890.
24. Gliem, J., & Gliem, R. (2003). Calculating, Interpreting, and Reporting Cronbach’s Alpha Reliability Coefficient for Likert-type Scales. Midwest Research- to-Practice Conference in Adult, Continuing, and Community Education, 82-88.
25. Gunasekra, K., & Perera, B. (2023). Defining Occupational Stress: A Systematic Literature Review. FARU Journal.
26. Heslin, P. (1999). Boosting Empowerment by Developing Self-efficacy. Asia Pacific Journal of Human Resources, 37(1), 52-64. https://doi.org/10.1177/103841119903700105
27. Huybrechts, S. (2023). Working Time and Autonomy: Lessons for the New Ways of Working. European Labour Law Journal, 14, 570-587.
28. Jaguaco, D., Turpo-Chaparro, J., Vásquez-Villanueva, S., & Apaza-Romero, A. (2022). Social support and general self-efficacy: Two Predictors of Quality of Life at Work in Ecuadorian Teachers. 7. https://doi.org/10.3389/feduc.2022.946723.
29. Jati, H. (2022). Quality of Work Life: A Literature Review. International Journal of Research and Innovation in Social Science.
30. Judeh, M., Al-Ghasawneh, J., Al-Zu’bi, H., & Ngah, A. (2022). Linking Resonant Leadership, Psychological Ownership, and Organizational Commitment: The Mediating Role of Employee Empowerment. Problems and Perspectives in Management.
31. Karapetyan, L. (2019). Responsibility as a Predictor of Emotional and Personal Wellbeing. 44-53. 10.35853/LAU.WS.2019.SP04
32. Karasek, R., & Theorell, T. (1990). Healthy work: Stress, productivity, and the reconstruction of working life. Basic Books.
33. Kodden, B. (2020). The Impact of Self-efficacy. Springer Briefs in Business. 10.1007/978-3-030-46463-9_5
34. Kong, M., Tj, H., & Fushen (2023). The Influence of Leadership Style and Rewards on Employee Performance with Self-Efficacy as a Mediation Variable in Pramita Manado Clinic Laboratory. Formosa Journal of Multidisciplinary Research.
35. Lamb, E., Burford, B., & Alberti, H. (2022). The Impact of Role Modelling on the Future General Practitioner Workforce: A Systematic Review. Education for Primary Care, 33, 265-279.
36. Lamichhane, B. (2021). Workers’ Participation in Management in Nepal. Kalika Journal of Multidisciplinary Studies, 3(1), 34–44 https://doi.org/10.3126/kjms.v3i1.48183
37. Landry, A., Zhang, Y., Papachristopoulos, K., & Forest, J. (2020). Applying Self-Determination Theory to Understand the Motivational Impact of Cash Rewards: New Evidence from Lab Experiments. International Journal of Psychology: Journal International de Psychologie.
38. Lindquist, L., Miller-Winder, A., Schierer, A., Murawski, A., Opsasnick, L., Kim, K., & Ramirez-Zohfeld, V. (2022). Improvement in Self-efficacy Among Older Adults Aging-in-place During COVID-19. J Am Geriatr Soc., 70(11), 3318-3321.
39. Maleki, A. (2021). Examining the Relationship Between Psychological Ability and Quality of Work Life with Job Satisfaction of Professors. International Journal of Innovation Management and Organizational Behavior.
40. Marcionetti, J., & Castelli, L. (2022). The Job and Life Satisfaction of Teachers: A Social Cognitive Model Integrating Teachers’ Burnout, Self-efficacy, Dispositional Optimism, and Social Support. Int J Educ Vocat Guidance.
41. Mohammadi, S., Hosseininejad, M., Taghizadeh, S., & Kabir-Mokamelkhah, E. (2020). The Relationship Between Different Aspects of Occupational Stress and General Health. Hygiene and Sanitation.
42. Mohsen, M. (2014). Psychological Empowerment and Job Satisfaction in the Hotel Industry: A Study on Egyptian Employees in KSA Hotels. In 32nd EuroCHRIE conference. Hospitality and Tourism Futures, 6-9.
43. Monika & Saini, M. (2019). Review of Literature on Quality of Work Life.
44. Monje-Amor, A., Xanthopoulou, D., Calvo, N., & Vázquez, J. (2021). Structural Empowerment, Psychological empowerment, and Work Engagement: A cross-country study. European Management Journal.
45. Nanjundeswaraswamy, T., & Beloor, V. (2022). Quality of Work Life of Employees Working in the Indian Garment Industry. Research Journal of Textile and Apparel.
46. Nwabuko, O., 2024. An Overview of Research Study Designs in Quantitative Research Methodology. American Journal of Medical and Clinical Research & Reviews.
47. Opute, J. (2020). Training and Development. HRM in Africa. 10.1007/978-3-030-47128-6_3
48. Pan, Y. (2019). A Review of Psychological Empowerment. 10.23977/emss.2019.014
49. Pidada, I., & Saputra, I. (2021). Examining Value of Employees: Effect of Quality of Work Life, Work Facilities, and Organizational Commitments on Work Satisfaction. International Journal of Social Sciences and Humanities.
50. Purkait, S., & Mohanty, M. (2016). Impact of Occupational Stress on Quality Work Life among Employees in Banking Sector: A Study in West Bengal Region. Nternational Journal of Advanced Research (IJAR), 4(7), 1215-1222.
51. Rath, J., Hentry, J., & Krithika, D. (2022). Job Satisfaction of the Service Sectors Employees with Special Reference to Chennai: A Study. International Journal for Research in Applied Science and Engineering Technology.
52. Saaeda, H., Raheemahb, S., & Mohammedc, A. (2020). The Influence of Employee Self- Efficacy on the Quality of Work Life.
53. Salmina, N., Zvonova, E., & Elizarova, E. (2021). Components of Ideas About Self-Efficacy of the Specialist. Vestnik Universiteta, 177-182.
54. Sarraf, A. (2019). Coaching in Multi-Generational Organizations. Business and Economics Journal, 10, pp. 1-5.
55. Schermuly, C., Creon, L., Gerlach, P., Graßmann, C., & Koch, J. (2022). Leadership Styles and Psychological Empowerment: A Meta-Analysis. Journal of Leadership & Organizational Studies, 29, 73-95.
56. Shah, T., Khattak, M., Zolin, R., & Shah, S. (2019). Psychological Empowerment and Employee Attitudinal Outcomes. Management Research Review.
57. Singh, M., & Sarkar, A. (2019). Role of Psychological Empowerment in the Relationship Between Structural Empowerment and Innovative Behavior. Management Research Review.
58. Singh, P. (2020). Occupational Stress and Quality of Work Life in Police Personnel during covid-19. Mukt Shabd Journal, 9(6), pp.4628-4636. Cranwell,W. and Alyssa,A.J.(2005). Organisational stress. Pal grave. Macmillan, New York 10010, USA.
59. Singh, S., & Verma, M. (2019). A Conceptual Study on Occupational Stress and its Impact on Employees. Journal of Emerging Technologies and Innovative Research.
60. Sorensen, G., Dennerlein, J., Peters, S., Sabbath, E., Kelly, E., & Wagner, G. (2020). The Future of Research on Work, Safety, Health and Wellbeing: A Guiding Conceptual Framework. Social Science & Medicine, 269, 113593-113593.
61. Spreitzer, G. M. (1995). Psychological Empowerment in the Workplace: Dimensions, Measurement, and Validation. Academy of Management Journal, 38(5), 1442-1465.
62. Srivastava, A., & Singh, A. (1981). Occupational Stress Index (OSI) [Database record]. APA PsycTests.
63. Stoffels, M., Torre, D., Sturgis, P., Koster, A., Westein, M., & Kusurkar, R., (2023). Steps and Decisions Involved When Conducting Structural Equation Modeling (SEM) Analysis. Medical Teacher, 45, 1343-1345.
64. Sudheer, A. (2021). Role of Compensation Management in Balancing the Employees relationship in Retail Industry in India, 12, 1777-1780.
65. Suraksha & Chhikara, K. (2017). An Empirical Study of the Factors of Occupational Stress in Indian Banking Industry. Pacific Business Review International, 9(8), 31-40.
66. Swamy, D., Nanjundeswaraswamy, D., & Srinivasaiah, R. (2015). Quality of Work Life: Scale Development and Validation. Scandinavian Journal of Caring Sciences.
67. Swathi, G., & Dasari, K. (2020). Quality of Work Life at Banking Sector. Journal of Emerging Technologies and Innovative Research.
68. Syahidah, D., Zulaikha, S., & Ahmad, M. (2021). A University Quality Assurance Team Should Strive for Quality of Work-life. Jurnal Cakrawala Pendidikan. https://doi.org/10.21831/cp.v40i2.37944.
69. Tang, W., & Vandenberghe, C. (2021). Role Overload and Work Performance: The Role of Psychological Strain and Leader–Member Exchange. Frontiers in Psychology, 12.
70. Tanriverdi, H., Turan, S., & Yimaz, A. (2019). The Effect of Psychological Empowerment on Work Life Quality. The European Proceeding of Social and Behavioural Sciences, 13, 152–162.
71. Teraoka, M., & Kyougoku, M. (2019). Structural Relationships Among Occupational Dysfunction, Stress Coping, and Occupational Participation for Healthcare Workers. Work. 10.3233/WOR-193045
72. Tsimakuridze, M., Khachapuridze, N., Khunashvili, N., Zurashvili, D., & Maĭsuradze, E. (2022). Etiological Factors Determining Occupational Stress. Experimental & Clinical Medicine Georgia.
73. Vakariuk, L. (2023). To the Issue of Legal Stimulation of Labor Activity of Employees. Uzhhorod National University Herald. Series: Law.
74. Vasantha, S., & Santhi, R. (2020). Relationship between Occupational Stress and Resilience. Indian Journal of Public Health Research & Development.
75. Warda, M. (2020). The Impact of Psychological Empowerment on the Effectiveness of Performance. International Journal of Teacher Education and Professional Development.
76. World Health Organization (2019). Burn-out an “Occupational Phenomenon”: International Classification of Diseases. https://www.who.int/news/item/28-05-2019-burn-out-an-occupational-phenomenon-international-classification-of-diseases.
77. Zhang, C., Gong, X., Xiao, Y., Zhong, Y., Zhong, Y., Chen, L., Wang, Y., Zhu, L., Xiong, W., & Liao, C. (2022). Relationships Between Self-efficacy, Coping-style and Quality of Work-life Among Nursing Managers in China: A Cross-sectional Study. Journal of Nursing Management.
78. Zhang, H., Hu, M., Liu, X., Yu, X., & Xie, J. (2023). From Citizenship Pressure to Pro-Group Unethical Behavior: The Dual-Stage Moderating Role of Self-Serving Political Will. Behavioral Sciences, 13(7), 544. https://doi.org/10.3390/bs13070544