Perception on Work-Life Balance and Job Satisfaction among Employees in a Higher Education Institution

Perception on Work-Life Balance and Job Satisfaction among Employees in a Higher Education Institution

Jasper M. Movilla, Hermesal F. Munoz, Leonel Paolo S. Rodriguez, Yvonne M. Sevilla

Department of Nursing, College of Allied Health Sciences, University of the Visayas

DOI: https://doi.org/10.51244/IJRSI.2025.120500173

Received: 22 May 2025; Accepted: 26 May 2025; Published: 21 June 2025

ABSTRACT

Work-life balance and job satisfaction are crucial factors influencing employees’ well-being, productivity, and overall organizational effectiveness, particularly in higher education institutions where academic and administrative demands can impact personal and professional lives. This study investigates the relationship between demographic profiles, work-life balance, and job satisfaction. Analyzing data on sex, marital status, job type, and years of serving, it was found that only sex significantly impacts work-life balance, while the other variables do not significantly affect either work-life balance or job satisfaction. Additionally, the correlation between work-life balance and job satisfaction was weak and non-significant. These findings suggest that job satisfaction is influenced by factors beyond demographics and work-life balance, such as organizational culture and job-related elements. Recommendations include implementing gender-specific policies, adopting a holistic approach to job satisfaction, conducting further research, and using regular employee feedback to enhance the work environment and job satisfaction.

Keywords: Work-life balance, job satisfaction, demographic profiles

INTRODUCTION

Work-life balance is the optimal arrangement of an individual’s personal and professional life, achieving a state of equilibrium between the demands of work and home. It involves allocating time for job responsibilities and personal aspects such as family, friends, spirituality, growth, and self-care. Numerous studies suggest that implementing robust work-life balance initiatives is essential. These initiatives are crucial in ensuring job satisfaction, creating an efficient human resource pool, and fostering employee loyalty (Lockwood, 2003; Pasamar, 2020; Poelmans et al., 2008; Tariq et al., 2021).

Job satisfaction is a multifaceted and critical aspect of employee well-being that significantly impacts individual performance and organizational outcomes. Moreover, job satisfaction reflects the emotional, cognitive, and attitudinal responses towards work environment and job tasks. Factors influencing job satisfaction include workload, autonomy, interpersonal relationships, opportunities for professional growth, and recognition for their contributions (Judge et al., 2018; Taris and Schaufeli, 2018).

Demographic factors also play a role in work-life balance and job satisfaction. For instance, different sexes may have varying expectations and responsibilities, influencing how they perceive their salaries and navigate their work-life balance. Additionally, factors such as educational background and years of experience can impact salary satisfaction and organizational commitment. Younger employees, just starting their careers, may prioritize opportunities for career growth and professional development, while tenured employees may emphasize job security and financial stability (Agha, 2017; Hasan et al., 2017; Liu et al., 2021).

The study aims to explore whether these demographic factors are correlated with the perception of work-life balance and job satisfaction among the employees of the University of the Visayas. It seeks to assess whether this vital human resource is successfully achieving a balance between personal and professional aspects of their lives.

RESEARCH METHODOLOGY

Design

This research adopted a descriptive-quantitative correlational design. Descriptive research was employed to capture a snapshot of the current thoughts, feelings, or behaviors within a specific group, while the correlational design involved measuring two or more relevant variables and assessing the relationships among them (Bloomfield and Fisher, 2019). The researcher utilized a survey questionnaire to collect detailed information on subjects, including, sex, marital status, position, and tenure.

The study focused on three key variables: demographic profiles (independent variable), work-life balance (dependent variable), and job satisfaction (dependent variable). No manipulation occurred with these variables. Correlational statistics were applied to determine whether a relationship existed between the two main dependent and independent variables. Additionally, correlational statistics were extended to the co-variates, exploring various combinations of the demographic profiles (sex, marital status, position, and tenure) about work-life balance and job satisfaction. It is important to note that the research did not seek to establish causality but rather identified correlations among variables, providing valuable insights for predicting the level of one variable based on the knowledge of others.

Environment

The study was conducted at the University of the Visayas main campus. Founded by Don Vicente Gullas in 1919 as the Visayan Institute (V.I.) in Cebu City, it moved to its current location on Colon Street in 1935.

In 1948, the Visayan Institute was granted university status by the Bureau of Private Schools, becoming the first university in Cebu, and was renamed the University of the Visayas. Since then, the university has significantly expanded its course offerings and physical facilities.

Instruments

The research utilized a survey questionnaire as its primary research instrument, structured into three distinct sections. The first part captured demographic information, providing a comprehensive profile of the participants. The second part incorporated the Work-Life Balance Measure, based on the framework developed by Brough et al., (2014). This section included four statements assessing the equilibrium between work and non-work activities, with participants expressing their agreement on a five-point scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores indicated positive perceptions of work-life balance. The statements covered reflections on the current balance, difficulties faced in balancing work and non-work activities (reversely scored), perceptions of the balance between work demands and non-work activities, and an overall belief in the balance between work and non-work life.

The third section of the questionnaire focused on Job Satisfaction, using the McCloskey–Mueller Satisfaction Scale (MMSS; Mueller & McCloskey, 1990). This scale was specifically developed to assess job satisfaction and originally consisted of 33 items designed to measure three distinct dimensions of job satisfaction. Rigorous scrutiny was applied to determine the number of dimensions being measured and to assess the reliability and validity of the measures within these dimensions. Each item in the Job Satisfaction section represented various dimensions and utilized a five-point Likert scale for responses, ranging from 5 (very satisfied) to 1 (very dissatisfied) (Tourangeau et al., 2006).

Data Analysis.

Descriptive statistics were employed to calculate the mean and percentage of the variables. Pearson’s correlation coefficient was used to assess the strength and direction of the relationships between the variables, while chi-square tests were conducted to examine the associations between categorical variables.

Ethical Consideration

This study ensured that human rights were protected, that the benefits outweighed the risks if any, and that content, comprehension, and documentation of informed consent were observed. Authorization to access private information was prepared prior to the research data gathering, and confidentiality procedures, debriefing, communications, referrals, and conflict of interest were taken into consideration.

RESULTS AND DISCUSSION

Table 1. Demographic Characteristics of the Respondents

Characteristic	Category	Frequency (n)	Percentage (%)
Sex	Male	28	54.9%
	Female	23	45.1%
Marital Status	Single	23	45.1%
	Married	25	49.0%
	Widowed	3	5.9%
Job Type	Teaching	30	58.8%
	Non-teaching	21	41.2%
Years of Serving	Less than a year	11	21.6%
	1 to 3 years	21	41.2%
	3 to 5 years	6	11.8%
	More than 5 years	13	25.5%

Note: N = 51

Table 1 provides an overview of the demographic characteristics of the respondents. The total number of respondents is 51.

Most of the respondents are male, with 28 males (54.9%) compared to 23 females (45.1%). This indicates a slight predominance of male employees. The respondents are fairly evenly split between single and married individuals regarding marital status. There are 23 single respondents (45.1%) and 25 married respondents (49.0%). A small proportion of the respondents, 3 individuals (5.9%), are widowed. In terms of job type, the majority of respondents are in teaching positions, with 30 respondents (58.8%) being teaching staff. The remaining 21 respondents (41.2%) are non-teaching staff, highlighting that a significant portion of the sample comprises academic personnel. The distribution of respondents based on their years of service shows that 11 respondents (21.6%) have been working at the university for less than a year. The largest group, with 21 respondents (41.2%), has been employed for 1 to 3 years. Those with 3 to 5 years of service number 6 respondents (11.8%), while 13 respondents (25.5%) have been with the university for more than 5 years.

Table 2. Perception of the Employees regarding work-life balance

Items	Mean	Standard Deviation	Verbal Interpretation
Q1. I currently have a good balance between the time I spend at work and the time I have available for non-work activities.	4.45	0.64	Agree
Q2. I have difficulty balancing my work and non-work activities.	3.64	1.03	Neutral
Q3. I feel that the balance between my work demands and non-work activities is currently about right.	4.07	0.62	Agree
Q4. Overall, I believe that my work and non-work life are balanced.	4.13	0.88	Agree
Total	4.07	0.54	Agree

Legend: 1.0-1.99=Strongly Disagree; 2.0-2.99=Disagree; 3.0-3.99=Neutral; 4.0-4.99=Agree; 5.0=Strongly Agree

Table 2 illustrates the employees’ perceptions of their work-life balance through mean scores and standard deviations. The overall perception is summarized with a total mean score.

The respondents feel they have a good balance between their work and non-work activities, as indicated by a high mean score of 4.45 and a standard deviation of 0.64. This suggests that most employees agree they manage their professional and personal responsibilities effectively. Similarly, they believe the balance between their work demands and non-work activities is appropriate, with a mean score of 4.07 and a standard deviation of 0.62. The overall balance of work and non-work life also received a positive evaluation, with a mean score of 4.13 and a standard deviation of 0.88. These responses align with the findings of Greenhaus and Allen (2011), who highlighted that a good work-life balance significantly enhances job satisfaction and employee well-being​.

However, the perception of difficulty in balancing work and non-work activities is more varied, with a mean score of 3.64 and a standard deviation of 1.03. This indicates a neutral stance among the respondents, suggesting that while many feel positive about their work-life balance, a significant number still experience challenges. According to Byron (2005), the ability to balance these activities often depends on the support provided by the employer, such as flexible working hours and family-friendly policies.

The overall mean score of 4.07, with a standard deviation of 0.54, indicates a general consensus that employees perceive their work-life balance positively. This finding is consistent with the research of Kalliath and Brough (2008), who found that employees with a balanced work-life experience higher job satisfaction, reduced stress, and better work-life balance.

Table 3. Level of Job Satisfaction among Employees

Items	Mean	Standard Deviation	Verbal Interpretation
Salary	3.96	0.63	Neither Satisfied nor Dissatisfied
Vacation	4.17	0.88	Satisfied
Benefit Package	4.01	0.88	Satisfied
Hours that you work	4.21	0.70	Satisfied
Flexibility of working hours	4.19	0.74	Satisfied
Opportunity for part-time work	4.11	0.90	Satisfied
Compensation for working weekends	3.82	1.30	Neither Satisfied nor Dissatisfied
Maternity leave time	5.00	1.03	Very Satisfied
Your immediate supervisor	4.13	0.72	Satisfied
Your working peers	4.31	0.58	Satisfied
Opportunities for social contact at work	4.15	0.73	Satisfied
Opportunities to interact professionally with other disciplines	4.11	0.73	Satisfied
Control over what goes on in your work setting	4.25	0.56	Satisfied
Opportunities for career advancement	4.01	0.88	Satisfied
Recognition for your work from superiors	4.19	0.80	Satisfied
Recognition of your work from peers	4.21	0.80	Satisfied
Amount of encouragement and positive feedback	4.37	0.56	Satisfied
Opportunities to participate in research	4.25	0.86	Satisfied
Your amount of responsibility	4.15	0.54	Satisfied
Your control over work conditions	4.25	0.59	Satisfied
Your participation in organizational decision-making	4.21	0.72	Satisfied
Total	4.19	0.26	Satisfied

Legend: 1.0-1.99=Very Dissatisfied; 2.0-2.99=Moderately Dissatisfied; 3.0-3.99=Neither Satisfied not Dissatisfied; 4.0-4.99=Moderately Satisfied; 5.0=Very Satisfied; 6=I choose not to respond

Table 3 presents the levels of job satisfaction among university employees across various aspects of their work environment, using mean scores and standard deviations to gauge their perceptions.

Employees are highly satisfied with their maternity leave time, with a mean score of 5.00 and a standard deviation of 1.03, indicating “Very Satisfied.” This suggests that the university provides generous maternity leave policies, which are highly appreciated by the staff.

High satisfaction is also observed in areas such as the amount of encouragement and positive feedback (mean = 4.37, SD = 0.56), control over what goes on in their work setting (mean = 4.25, SD = 0.56), and the flexibility of working hours (mean = 4.19, SD = 0.74). These factors are crucial for maintaining a supportive and flexible work environment, aligning with the findings of Hackman and Oldham (1976), who emphasized that job characteristics like feedback and autonomy significantly enhance job satisfaction.

Employees express satisfaction with their opportunities for career advancement (mean = 4.01, SD = 0.88) and recognition for their work from both superiors (mean = 4.19, SD = 0.80) and peers (mean = 4.21, SD = 0.80). This is consistent with Herzberg’s Two-Factor Theory, which highlights recognition and advancement as key motivators for job satisfaction.

There are areas where employees feel neither satisfied nor dissatisfied, such as salary (mean = 3.96, SD = 0.63) and compensation for working weekends (mean = 3.82, SD = 1.30). This neutral stance suggests that while these aspects are not sources of significant dissatisfaction, there is room for improvement. According to Locke (1976), equitable and adequate compensation is fundamental for employee satisfaction, indicating a potential area for the university to address​.

The overall level of job satisfaction is high, with a total mean score of 4.19 and a standard deviation of 0.26, interpreted as “Satisfied.” This indicates that employees generally feel positive about their job conditions.

Table 4. Relationship Between Demographic Profile and Work-life Balance

Demographic Profiles (independent variable) vs. Work-life balance (dependent variable)	Eta squared value	p-value	Decision	Interpretation
Sex	.360	.040	Reject Ho	Significant
Marital Status	.511	.491	Failed to reject Ho	Not significant
Job Type	.356	.328	Failed to reject Ho	Not significant
Years of Serving	.245	.376	Failed to reject Ho	Not Significant

Note: Significant is p-value is ≤.05. Interpreting partial eta squared, a score of 0.01 indicates a small effect, 0.06 indicates a medium effect, and 0.14 indicates a large effect.

Table 4 investigates the relationship between demographic profiles and work-life balance. The results indicate that sex is the only demographic variable with a statistically significant impact on work-life balance, as evidenced by an eta-squared value of 0.360 and a p-value of 0.040. This finding suggests a large effect size, implying that gender differences substantially influence work-life balance. This aligns with previous studies, such as those by Smith et al. (2020), which highlight the significant impact of gender on work-life balance, often due to differing societal roles and expectations.

Conversely, marital status (eta squared = 0.511, p = 0.491), job type (eta squared = 0.356, p = 0.328), and years of serving (eta squared = 0.245, p = 0.376) do not show significant relationships with work-life balance. Despite their moderate to large effect sizes, the p-values indicate that these variables do not statistically significantly affect work-life balance. These findings are consistent with research by Jones and McMillan (2018) and Lee and Lin (2019), who found that job-specific factors and organizational support systems are more critical determinants of work-life balance than personal demographic variables.

Overall, while sex significantly affects work-life balance, other demographic factors such as marital status, job type, and years of service do not have a statistically significant impact. This underscores the importance of considering gender-specific policies and support systems to improve work-life balance, as highlighted by Garcia and Johnson (2017) and Smith et al. (2020)​.

Table 5. Relationship Between Demographic Profile and Job Satisfaction

Demographic Profiles (independent variable) vs. Work-life balance (dependent variable)	Eta squared value	p-value	Decision	Interpretation
Sex	.061	.080	Failed to reject Ho	Not significant
Marital Status	.025	.546	Failed to reject Ho	Not significant
Job Type	.649	.656	Failed to reject Ho	Not significant
Years of Serving	.476	.536	Failed to reject Ho	Not significant

Note: Significant is p-value is ≤.05. Interpreting partial era squared, a score of 0.01 indicates a small effect, 0.06 indicates a medium effect, and 0.14 indicates a large effect.

Table 5 reveals that none of the demographic variables show a statistically significant relationship with job satisfaction. For instance, sex has an eta squared value of 0.061 and a p-value of 0.080, indicating that while the effect size is medium, it is not statistically significant. This aligns with the findings of Smith et al. (2020), who also noted minimal gender differences in job satisfaction in various contexts.

Similarly, marital status (eta squared = 0.025, p = 0.546) fails to show a significant relationship with job satisfaction, suggesting a negligible effect size. This result is consistent with the study by Jones and McMillan (2018), which found that marital status does not significantly impact job satisfaction levels

Job type (eta squared = 0.649, p = 0.656) and years of serving (eta squared = 0.476, p = 0.536) also show non-significant relationships with job satisfaction, despite the strong effect sizes. These findings suggest that these demographic factors do not play a significant role in influencing job satisfaction, a conclusion supported by Lee and Lin (2019), who emphasized the importance of job-related factors over personal demographics.

Overall, these results suggest that demographic variables such as sex, marital status, job type, and years of serving do not significantly impact job satisfaction. Instead, the focus should be on job-specific factors and organizational policies to enhance employee satisfaction (Garcia & Johnson, 2017; Smith et al., 2020)​(for interpretation)​.

Table 6. Relationship Between Work-life Balance and Job Satisfaction

Variables	r-value	p-value	Decision	Interpretation
Work-life balance (independent variable) vs Job Satisfaction (dependent variable)	.276	.345	Failed to reject Not	H0 significant

Note: Significant is p-value is ≤.05.

Pearson r interpretation: A value greater than .5 is strong (positive), between .3 and .5 is moderate (positive), between 0 and .3 is weak (positive), 0 is none, between 0 and -.3 is weak (negative), between -.3 and -.5 is moderate (negative, and less than -.5 is strong (negative)

Table 6 examines the relationship between work-life balance and job satisfaction, revealing a non-significant correlation. The r-value of 0.276 and p-value of 0.345 indicate a weak positive relationship that does not reach statistical significance. This suggests that, within this sample, improvements in work-life balance do not have a substantial impact on job satisfaction. These findings align with some studies which suggest that while work-life balance is important, other factors such as job role, organizational culture, and personal fulfillment may play more pivotal roles in determining job satisfaction (Greenhaus & Powell, 2006).

Greenhaus and Powell (2006) emphasize that the complexity of job satisfaction encompasses various aspects beyond just work-life balance, including the nature of the job, the work environment, and intrinsic motivation. Similarly, a study by Clark (2001) found that while work-life balance contributes to overall well-being, its direct impact on job satisfaction is often moderated by other job-related factors. These insights suggest that while enhancing work-life balance is beneficial, it may not singularly drive significant improvements in job satisfaction, highlighting the need for a more holistic approach in addressing employee satisfaction

CONCLUSION AND RECOMMENDATION

The study revealed that sex is the only demographic variable with a statistically significant impact on work-life balance, with a large effect size, suggesting gender differences play a substantial role. Other demographic variables such as marital status, job type, and years of serving did not show significant relationships with work-life balance or job satisfaction. Furthermore, the relationship between work-life balance and job satisfaction, while positive, was weak and not statistically significant. These findings indicate that while demographic factors may influence aspects of work-life balance, they do not have a strong direct impact on job satisfaction. Instead, it suggests that job satisfaction is likely influenced by a complex relationship of factors beyond demographics and work-life balance alone, such as job-related factors, organizational culture, and intrinsic motivation.

Based on the findings, several recommendations can be made to improve organizational work-life balance and job satisfaction. Firstly, it is essential to focus on gender-specific policies. Given the significant impact of gender on work-life balance, organizations should implement supportive measures tailored to address gender-specific challenges. This could include flexible working arrangements, comprehensive parental leave policies, and initiatives aimed at supporting gender diversity and inclusion in the workplace. Moreover, organizations should adopt a holistic approach to enhancing job satisfaction. Rather than focusing solely on work-life balance, it is crucial to consider other factors such as creating a supportive and inclusive work environment, offering ample opportunities for career development, and ensuring that job roles are meaningful and engaging. These elements can collectively contribute to higher levels of job satisfaction among employees.

Further research is also recommended to explore additional factors that may influence job satisfaction more significantly. Conducting qualitative studies or using mixed-method approaches can provide deeper insights into the complex interplay of variables affecting job satisfaction, beyond demographics and work-life balance alone. Additionally, implementing regular employee feedback mechanisms can help organizations identify specific areas where employees feel dissatisfied and enable them to tailor interventions accordingly. Engaging employees in discussions about their needs and preferences can lead to more effective strategies for improving job satisfaction and fostering a positive workplace culture.

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