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Striking a Balance: Investigating Work-Life Balance Strategies and their Impact on Healthcare Provider Performance in Public Health Facilities, Bushenyi District, Uganda
- Patricia Atukunda
- Tom Ongesa Nyamboga
- 1534-1549
- Nov 9, 2024
- Business Management
Striking a Balance: Investigating Work-Life Balance Strategies and their Impact on Healthcare Provider Performance in Public Health Facilities, Bushenyi District, Uganda
Patricia Atukunda1, Tom Ongesa Nyamboga (PhD.)2
1Postgraduate Student School of Business and Management, Kampala International University, Western Campus
2Lecturer School of Business and Management, Kampala International University, Western Campus
*Corresponding Author
DOI: https://dx.doi.org/10.47772/IJRISS.2024.8100134
Received: 18 October 2024; Accepted: 23 October 2024; Published: 09 November 2024
ABSTRACT
The well-being of healthcare providers is intricately linked to the quality of care they deliver, yet the demanding nature of their work often compromises their own health and satisfaction. In public health facilities, where resources are scarce and patient loads are high, healthcare providers face unprecedented stress, burnout, and exhaustion. Achieving a delicate balance between work and personal life is crucial to sustain their physical, emotional, and mental resilience. This study investigated the critical intersection of work-life balance and healthcare provider performance in public health facilities, shedding light on the strategies that can harness the full potential of these dedicated professionals, improve patient outcomes, and strengthen Uganda’s healthcare system, particularly in Bushenyi District, Uganda. The study was anchored Role Theory. The research utilized a quantitative research approach and was guided by a descriptive research design. The study targeted 197 permanent healthcare workers, from which 132 respondents were selected were selected through stratified random proportionate sampling and simple random sampling. Primary data were collected using structured self-administered questionnaire and analyzed using both descriptive and inferential statistics with the aid Statistical Package for Social Sciences (SPSS) version 27. The results of the simple linear regression analysis revealed a statistically significant relationship between work-life balance strategies and healthcare provider performance (t=2.104; p= 0.037; p<0.05). The study concluded that work-life balance strategies are pivotal in fostering the performance of healthcare providers in public healthcare facilities. The study recommended that flexible work arrangements should be offered by healthcare organizations. Prioritizing employee welfare has the potential of leading to improved health outcomes.
Keywords: Work-Life Balance, Strategies, Healthcare Provider, Performance, Public Health Facilities
INTRODUCTION
Healthcare provider performance is strongly connected to work-life balance strategies, as effectively managing work-related stress directly influences job satisfaction and the quality of patient care (Shanafelt et al., 2020). High levels of burnout are common among healthcare workers due to demanding workloads, scarce resources, and emotional strain, which can diminish their overall efficiency (World Health Organization, 2021). Introducing work-life balance measures, such as flexible working hours and support systems, has proven to enhance staff well-being and boost productivity (Ministry of Health Uganda, 2021). These approaches are especially crucial in under-resourced areas like Uganda, where workforce shortages heighten workplace challenges (Miller et al., 2023).
Healthcare provider performance in Finland has improved significantly with the integration of digital health technologies in public health facilities, enhancing service accessibility and quality (Koskinen et al., 2021). The COVID-19 pandemic accelerated the adoption of telemedicine, efficiently managing outpatient care while reducing pressure on physical facilities (Ministry of Social Affairs and Health, 2024). Investments in IT infrastructure and healthcare staff training have facilitated this transformation, enabling professionals to effectively use these tools (European Commission, 2024). Continuous professional development programs help healthcare workers meet evolving demands while maintaining high-quality care (Finnish Institute for Health and Welfare, 2024). These initiatives align with Finland’s broader strategy to enhance system efficiency and improve patient outcomes in response to an aging population and rising healthcare needs (OECD, 2023).
Prolonged waiting times for non-urgent care remain a pressing issue. In 2022, 6.5% of the population reported unmet medical needs due to lengthy wait times, almost three times the EU average (European Commission, 2024). Lower-income populations face significant barriers to timely care, exacerbating socio-economic inequalities (Finnish Institute for Health and Welfare, 2024). Finland’s shortage of healthcare professionals, particularly doctors, strains the system, leading to longer wait times and restricted access to specialised care (OECD, 2023). This shortage hampers service delivery efficiency (Ministry of Social Affairs and Health, 2024).
Finland’s healthcare system displayed resilience during the COVID-19 pandemic. To address ongoing challenges, the government launched the Good Work Programme, aimed at improving working conditions and reducing the burdens on healthcare workers (Ministry of Social Affairs and Health, 2024). This programme involves task reallocation and increased education to mitigate staff shortages, particularly in rural areas (OECD, 2023). Enhancing job satisfaction and staff retention is crucial for workforce stability (European Commission, 2024). Effective implementation of these reforms, supported by sufficient funding, is vital for sustainable improvements in healthcare (Finnish Institute for Health and Welfare, 2024). Addressing issues such as workforce shortages, wait times, and socio-economic disparities remains critical to ensuring equitable healthcare access (Ministry of Social Affairs and Health, 2024). The success of these strategies will shape the long-term sustainability of Finland’s healthcare system (European Commission, 2024).
Significant advancements in public health facility performance in the United States include improvements in quality, the adoption of digital health technologies, and a shift towards patient-centred care. Electronic health records (EHRs) have improved data sharing, streamlined workflows, and enhanced care coordination, reducing medical errors and boosting efficiency (Centers for Medicare & Medicaid Services, 2023). Telemedicine has expanded access to healthcare, particularly in rural and underserved areas, ensuring care continuity during the COVID-19 pandemic (American Hospital Association, 2022; Health Resources and Services Administration, 2022). Digital health adoption enables public health facilities to manage resources more effectively and meet patient needs more comprehensively (Centers for Disease Control and Prevention, 2022).
The COVID-19 pandemic worsened the long-standing shortage of healthcare professionals in the United States. The surge in demand during the pandemic led to increased burnout and turnover among providers (American Hospital Association, 2022; National Academy of Medicine, 2021). Disparities in healthcare access and outcomes continue to affect low-income and minority populations, driven by socio-economic factors, systemic barriers, and regional variations in healthcare quality (Centers for Disease Control and Prevention, 2022; National Academies of Sciences, Engineering, and Medicine, 2021). Financial constraints pose additional challenges for public health facilities, as limited funding hampers quality improvement efforts and the adoption of new technologies (American Hospital Association, 2022; Commonwealth Fund, 2023). The U.S. healthcare system’s complex regulatory environment, characterised by differing state and federal regulations, complicates care delivery and the implementation of uniform practices (National Academies of Sciences, Engineering, and Medicine, 2021).
Japan has also made substantial progress in enhancing healthcare provider performance, focusing on the integration of digital health, workforce development, and quality improvement initiatives (Sakamoto et al., 2022). EHRs have enhanced care coordination and clinical decision-making, while telemedicine has increased healthcare accessibility, particularly during the COVID-19 pandemic (Ministry of Health, Labour and Welfare, 2023; OECD, 2023). These measures have supported continuity of care.
Challenges related to Japan’s aging population and workforce shortages, however, remain significant. With nearly 30% of its citizens aged 65 or older, there is a growing demand for chronic and long-term care services (OECD, 2023; Ministry of Health, Labour and Welfare, 2023). Financial sustainability is a concern due to rising healthcare costs, with cost-containment strategies like medical fee adjustments and the use of generic drugs yielding mixed results (World Health Organization, 2023). Strict regulations further impede the adoption of new technologies and innovative healthcare models (Japan International Cooperation Agency, 2022; OECD, 2023). Addressing these challenges requires policy reforms, workforce development strategies, and financial sustainability measures (Ministry of Health, Labour and Welfare, 2023).
Rwanda has made notable strides in healthcare performance through reforms and innovative strategies (Binagwaho et al., 2021). The Community-Based Health Insurance (CBHI) scheme has improved healthcare access and affordability, ensuring financial barriers do not limit access to essential services (World Health Organization, 2023). Investments in infrastructure and technology, such as electronic medical records (EMRs) and telemedicine, have improved patient management and reduced wait times (Rwanda Biomedical Center, 2021).
Persistent challenges, including the shortage of healthcare professionals, limit the ability to provide comprehensive care, especially in remote areas (World Health Organization, 2023). Despite improvements in access, disparities in service quality and infrastructure persist in underserved regions (Rwanda Biomedical Center, 2021). Rwanda’s reliance on donor funding also raises concerns about the long-term stability of the healthcare system, necessitating more diversified funding strategies and expanded insurance coverage (Ministry of Health, 2023).
In Uganda, healthcare delivery has advanced through the National Health Sector Development Plan (NHSDP) 2020/21-2024/25, which seeks to achieve universal health coverage and improve healthcare quality (Ministry of Health Uganda, 2021). Digital health technology has improved efficiency, and investments in infrastructure have enhanced access, especially in rural areas (World Bank, 2022). Training programs are aimed at addressing workforce shortages, particularly in underserved regions (World Health Organization, 2021).
Inadequate pay, poor working conditions, and resource shortages continue to affect the quality of care and staff motivation in Uganda (Ministry of Health Uganda, 2021). Heavy reliance on donor funding undermines the sustainability of healthcare programmes, while infrastructure limitations hamper the delivery of quality care (World Bank, 2022). The COVID-19 pandemic exposed weaknesses in emergency preparedness, highlighting the need for a more resilient healthcare system.
Healthcare provider performance in Bushenyi District, Western Uganda, faces challenges from worker shortages, inadequate remuneration, and limited resources. The under-equipped facilities and poor infrastructure further compromise service quality. The reliance on donor funding also creates financial instability, worsening these issues (Ministry of Health Uganda, 2021; World Health Organization, 2021). This study was conducted to explore the impact of work-life balance strategies on healthcare provider performance in Bushenyi District, Uganda.
Statement of the Problem
Effective work-life balance strategies are essential for enhancing healthcare provider performance in public health facilities, contributing to increased job satisfaction and productivity. Flexible scheduling, comprehensive leave policies, and mental health support enable providers to reconcile professional responsibilities with personal needs, reducing burnout and improving performance outcomes (De Oliveira et al., 2022; Kim et al., 2023). Research indicates that healthcare organizations prioritizing work-life balance see higher engagement and lower turnover rates, which correlate with improved patient care quality (Huang et al., 2021; Goh et al., 2024). Additionally, workplaces fostering a healthy balance between work and personal life promote better communication and collaboration among healthcare teams, further enhancing performance metrics in public health settings (Thompson et al., 2022; Venners et al., 2023). Therefore, implementing comprehensive work-life balance strategies is vital for maximizing healthcare providers’ performance in public facilities.
The Ugandan government has introduced various measures to enhance healthcare provider performance in public facilities, including increased health budget allocations, improved infrastructure, and training programs (Tumushabe et al., 2023). Recent years have seen significant increases in the national health budget to address shortages in medical supplies and staffing (Ministry of Health Uganda, 2023). Investments in refurbishing healthcare facilities aim to create better working environments, while the Uganda Health Sector Strategic Plan emphasizes ongoing professional development and training for healthcare workers (WHO, 2022). Policies to improve healthcare provider remuneration and benefits have been implemented to motivate staff and reduce turnover rates, ultimately aiming to enhance service delivery (Republic of Uganda, 2023). These strategies reflect the government’s commitment to improving healthcare outcomes by empowering healthcare providers.
Despite these efforts, public healthcare providers in Bushenyi District encounter substantial challenges. Issues such as insufficient staffing, inadequate medical supplies, and high patient-to-provider ratios persist (Nabiryo et al., 2022). The shortage of healthcare workers, exacerbated by low retention rates and the migration of skilled professionals to urban centers or abroad, disrupts the delivery of quality services (Mugisha et al., 2023). Many facilities also grapple with shortages of essential medical supplies and equipment, negatively impacting both patient care and staff morale (Nabukenya et al., 2024). Inadequate infrastructure and limited funding further constrain the effectiveness of services, increasing healthcare providers’ workload and leading to burnout (Kagoda et al., 2023). These challenges undermine the performance and long-term sustainability of healthcare services in the district.
Neglecting the challenges facing public healthcare providers in Bushenyi District could result in severe consequences, including deteriorating health outcomes for the population. Ongoing shortages of healthcare workers and essential medical supplies may lead to longer waiting times, reduced access to vital services, and higher rates of preventable diseases and mortality (Kagoda et al., 2023). High patient-to-provider ratios can intensify provider burnout, decreasing job satisfaction and further attrition of skilled personnel, creating a cycle that undermines healthcare delivery (Mugisha et al., 2023). Eroding public trust in the healthcare system may push individuals toward informal or unregulated providers, posing serious risks to patient safety and community health (Nabukenya et al., 2024). Immediate intervention is crucial to prevent these issues from compromising healthcare services’ efficiency and sustainability in the district. Implementing work-life balance strategies could enhance job satisfaction and retention among healthcare providers in Bushenyi District, leading to improved service delivery and patient care in public health facilities. This study aimed to assess the impact of work-life balance strategies on healthcare provider performance in public health facilities in Bushenyi, Uganda.
Objective of the Study
To establish the impact of work-life balance strategies on performance of healthcare providers in public health facilities, Bushenyi, Uganda.
Hypothesis of the Study
This study was guided by the null hypothesis that stated that:
H0: There is no significant relationship between work-life balance strategies and performance of healthcare providers in public health facilities, Bushenyi, Uganda.
UNDERPINNING THEORY
This study is grounded in Role Theory, introduced by Mead in the early 20th century and further developed by Parsons, with significant contributions from Merton in the late 1950s and 1960s (Merton, 1957). Role Theory posits that individuals occupy various social roles each with specific expectations, norms, and behaviors guiding actions in different contexts (Mead, 1934; Merton, 1957). These roles organize social interactions and contribute to social system stability. Challenges arise from role conflict, where demands from different roles clash, or role strain, when expectations tied to a single role become overwhelming (Biddle, 1986). Importantly, roles are dynamic and evolve with societal shifts and personal circumstances (Turner, 2001). Understanding these roles and their expectations is vital for analyzing human behavior and social structures.
This theory provides a valuable framework for exploring the link between work-life balance strategies and healthcare provider performance in public facilities. Clearly defined roles enable healthcare workers to manage their duties effectively, reducing role ambiguity and enhancing job satisfaction (Wheeler et al., 2020; Hakanen et al., 2021). With clear roles, providers can allocate time efficiently between work and personal life, fostering a healthier work-life balance. In contrast, role conflict can increase stress and burnout, negatively affecting job performance and personal well-being (Kirkpatrick et al., 2022; Lee et al., 2023). Furthermore, organizational environments that emphasize work-life balance through policies like flexible scheduling and mental health support enable healthcare workers to meet professional duties while addressing personal needs, ultimately enhancing performance (Baker et al., 2022; McGowan et al., 2022). Thus, promoting role clarity and work-life balance is essential for optimizing healthcare provider performance in public facilities.
Impact of Work-life Balance on Healthcare Provider Performance in Public Health Facilities
Yadav et al. (2021) examined the effect of work-life balance on employee engagement and performance in Indian public hospitals using a mixed-methods approach. The quantitative phase involved surveying 250 healthcare professionals selected through simple random sampling, while the qualitative phase included interviews with 20 participants. Validated instruments assessed work-life balance and engagement, yielding a reliability coefficient of α = 0.85. Data analysis employed structural equation modeling and thematic analysis, following strict ethical protocols, including participant anonymity and informed consent. Findings indicated that improved work-life balance significantly enhanced employee engagement and performance.
Fowler et al. (2022) conducted a longitudinal study in a U.S. public health organization to evaluate flexible work arrangements’ effects on provider performance. The study sampled 150 healthcare workers through convenience sampling, using surveys to assess work-life balance and job performance. Validity was established through expert reviews, and the reliability coefficient was α = 0.91. Repeated measures ANOVA assessed changes over time, with ethical approval and confidentiality ensured. Results showed that flexible work arrangements significantly improved work-life balance and provider performance.
Ebrahimi et al. (2023) assessed the link between work-life balance and burnout among healthcare professionals in Iranian public hospitals, using a descriptive correlational design. The study targeted 400 healthcare workers selected through random sampling. Instruments included the Maslach Burnout Inventory and a work-life balance scale, achieving a reliability coefficient of α = 0.88. Data analysis involved correlation coefficients and regression analysis, adhering to ethical standards. Results revealed a strong negative correlation between work-life balance and burnout, emphasizing the need for programs to enhance provider performance.
Nare et al. (2022) studied the effects of work-life balance policies on nurse retention rates in South Africa’s public health facilities. This quantitative cross-sectional survey sampled 200 nurses through stratified sampling. Researchers used validated questionnaires for assessing work-life balance and turnover intentions, achieving a reliability coefficient of α = 0.84. Data analysis employed logistic regression and chi-square tests, following ethical guidelines including informed consent and confidentiality. Findings demonstrated that effective work-life balance policies correlated with increased retention rates, positively influencing healthcare facility performance.
Smith et al. (2024) conducted a qualitative study in Canada’s public healthcare settings to explore providers’ lived experiences regarding work-life balance. The research involved in-depth interviews with 30 participants selected through purposive sampling. Semi-structured interview guides, validated through expert reviews, served as the instruments. Thematic analysis facilitated data interpretation while ensuring ethical considerations like confidentiality and voluntary participation. Findings revealed that inadequate work-life balance caused considerable stress, adversely affecting performance and well-being.
Lee et al. (2023) examined the influence of organizational culture on healthcare providers’ perceptions of work-life balance in Malaysia’s public health institutions. The study employed a mixed-methods approach, combining a quantitative survey of 350 healthcare professionals with qualitative interviews of 25 selected participants. Researchers utilized validated instruments to measure organizational culture and work-life balance, achieving a reliability coefficient of α = 0.90. Statistical methods were applied for quantitative analysis, and thematic analysis was used for qualitative data. Ethical considerations included participant consent and confidentiality. Results indicated that a supportive organizational culture significantly enhances work-life balance, leading to improved provider performance.
Chao et al. (2021) examined how work-life balance affects patient satisfaction in Taiwan’s public health facilities. The study employed a cross-sectional design, targeting 400 patients and their healthcare providers. Researchers utilized validated instruments, including a work-life balance questionnaire for providers and a patient satisfaction survey, both demonstrating reliability with coefficients exceeding α = 0.85. Data analysis included correlation and regression techniques, while ethical considerations ensured participant anonymity and informed consent. The findings indicated that the work-life balance of healthcare providers positively impacted patient satisfaction, thereby influencing overall performance indirectly.
Rizwan et al. (2022) evaluated the effects of work-life balance interventions on the mental health and performance of healthcare workers in Pakistan’s public hospitals. The quasi-experimental study comprised a control group of 150 healthcare workers and an intervention group of 150. Researchers employed validated questionnaires to measure mental health and job performance, achieving a reliability coefficient of α = 0.87. The data were analyzed using t-tests and ANOVA to assess differences between the groups, with ethical considerations that included informed consent and approval from relevant authorities. The results revealed that work-life balance interventions significantly enhanced mental health and performance among healthcare workers.
Abdi et al. (2023) investigated barriers to achieving work-life balance among healthcare professionals in Ethiopia’s public hospitals. This qualitative study involved focus group discussions with 40 healthcare providers selected through purposive sampling. The researchers conducted thematic analysis for data interpretation, ensuring ethical considerations such as participant consent and confidentiality were upheld. The findings highlighted systemic issues, including staffing shortages and excessive workloads, as major barriers to attaining work-life balance, ultimately impacting healthcare provider performance.
Wambui et al. (2021) performed a cross-sectional study in Kenya’s public health facilities to investigate the relationship between work-life balance and job satisfaction among healthcare workers. The research utilized a stratified random sampling technique, targeting 350 healthcare providers. The study instruments comprised a structured questionnaire measuring work-life balance and job satisfaction, which were validated through pilot testing and achieved a reliability coefficient of α = 0.88. Researchers analyzed the data using descriptive and inferential statistics, adhering to ethical considerations through informed consent. The findings revealed a significant positive correlation between work-life balance and job satisfaction, underscoring the importance of supportive workplace policies.
METHODOLOGY
The researcher employed a quantitative research approach, analyzing data numerically. This method facilitated the examination of quantitative data and testing of the null hypothesis through statistical figures. The study utilized a descriptive research design to gather and present the opinions and views of healthcare providers regarding work-life balance strategies in a statistical format. The focus was on public healthcare providers in the Bushenyi district, targeting a sample of 197 healthcare providers from various departments, as outlined in Table 1. The selected categories were chosen purposefully, as they included staff members relevant to the research questions.
Table 1: Target Population
Departments | Target Population |
Management/In-charges | 28 |
OPD | 52 |
IPD | 38 |
MCH | 44 |
Dental clinic | 2 |
Ophthalmology/eye Clinic | 2 |
OR | 9 |
ART | 6 |
Laboratory | 14 |
Dispensary | 2 |
Total | 197 |
Source: National District Staff Human Resources for Health Information System (2024).
The researcher used Yamane’s (1967) formula to calculate the sample size as illustrated below;
n =Â Â Â Â Â Â Â Â Â N / (1 + N(e)2)
Where:
n – Sample size
N – Population size
E – Margin Error (5%)
The study population was heterogeneous, comprising strata with diverse proportions. To ensure equity in sampling, the researcher employed stratified random sampling. This approach required proportional representation of the samples, as detailed in Table 2.
Table 2: Sample Size Distribution
Department | Target population | Sample size |
Management/ In-charge | 28 | 19 |
OPD | 52 | 35 |
IPD | 38 | 25 |
MCH | 44 | 30 |
Dental Clinic | 2 | 1 |
Ophthalmology/eye | 2 | 1 |
OR | 9 | 6 |
ART | 6 | 4 |
Laboratory | 14 | 10 |
Dispensary | 2 | 1 |
Total | 197 | 132 |
Source: Researcher (2024)
To select individual participants from each stratum, the researcher utilized a simple random sampling technique, ensuring that each participant had an equal chance of being selected through the use of random numbers. Primary data were collected using a structured self-administered questionnaire, which consisted of close-ended questions designed on a four-point Likert scale aligned with the study’s objectives. This approach facilitated the acquisition of quantitative data. The researcher employed a drop-and-pick later method to gather completed questionnaires, coordinating with participants to collect them at a mutually agreed time within two weeks.
The researcher obtained approval from the Research Ethics Committee and secured a letter of introduction from the Directorate of Higher Degrees and Research at the institution. This letter was presented to the Bushenyi District Health Officer (DHO) for authorization before being forwarded to the health in-charges of the selected facilities. For quality assurance, a pretest was conducted in a pilot study involving 13 respondents, representing 10% of the sample size, as recommended by Mugenda and Mugenda (2003). Participants in the pretest were excluded from the final study. To ensure consistency, the researcher calculated the Cronbach Alpha coefficient, considering a value of 0.7 or higher as acceptable for reliability. Using SPSS Software, the researcher obtained a coefficient value of 0.82, indicating that the questionnaire items were reliable for data collection. The study also assessed validity through the judgment of experts and supervisors.
The researcher analyzed the data using both descriptive and inferential statistics. Measures of central tendency and dispersion helped summarize the participants’ responses. The study employed simple linear regression to determine the relationship between work-life balance strategies and healthcare provider performance. Correlation analysis was used to assess the strength and direction of these variables. The null hypothesis was evaluated at a significance level of 0.05. The results from the data analysis were presented in appropriate tables, following APA version 6 guidelines. The researcher maintained ethical considerations throughout the study, ensuring the confidentiality of respondents and emphasizing voluntary participation. The researcher obtained all necessary permissions prior to conducting the study.
FINDING OF THE STUDY
The following are main findings of this study
Response Rate
A total of 125 completed questionnaires were retrieved, indicating a 94.7 % response rate. For data analysis and reporting, fifty % is sufficient, sixty % is commendable, and seventy % or higher is noteworthy (Mugenda & Mugenda, 2003). As a result, the study’s response rate of 94.7 % was deemed appropriate as in table shown in Table 3.
Table 3: Response Rate for Questionnaires
Respondents | Questionnaire Distributed | Questionnaire Returned | Non-Response | Response (%) | Non-Response (%) |
Healthcare Staff | 132 | 125 | 7 | 94.7 | 5.3 |
Source: Field Data (2024)
Descriptive Statistical Analysis on Work-life Balance Strategies and Performance of Healthcare Givers
This analysis measured the impact of work-life balance strategy on performance of healthcare providers in government-aided health facilities in Bushenyi District, Uganda, using a scale ranging from 1 to 4. Specifically, the scale was defined as follows: 4= Strongly agree, 3 = Agree, 2 = Disagree, and 1 =Strongly disagree. Measures of central tendency were used to analyze the data, as presented in Table 4
Table 4: Work-Life Balance Strategies and Performance of Healthcare Providers
Statement | N | Mean | SD |
You receive pay for working longer hours and overtime. | 125 | 2.1440 | 1.03 |
You are content with the allotted annual and sick leave provided. | 125 | 2.9837 | .91 |
You are pleased with both the flexibility and the number of working hours. | 125 | 2.7661 | .85 |
You are content with how shifts are managed at the health center. | 125 | 3.0560 | .75 |
You are entitled to paid annual, maternity, and paternity leave entitlements. | 125 | 3.3040 | .82 |
Valid N (listwise) | 125 | Â Â Â Â 2.8507 | Â Â Â Â .87 |
Source: Field Data (2024)
With mean scores ranging from 2.14 to 3.30 on a scale of 1 to 4, these results show that facility users have differing degrees of satisfaction regarding work-related benefits and conditions. According to the data, users are generally dissatisfied with compensation for overtime and excessive working hours (M = 2.14, SD = 1.03), with 4 representing strongly agree and 1 representing strongly disagree. Users are more satisfied, however, with paid annual, maternity, and paternity leaves (M = 3.30, SD = 0.82), shift management (M = 3.06, SD = 0.75), flexibility and quantity of working hours (M = 2.77, SD = 0.85), and annual and sick leave policies (M = 2.98, SD = 0.91). These findings are consistent with earlier research (Davis et al., 2020) that found these variables to be critical for worker satisfaction and well-being.
Descriptive Statistical Analysis on Performance of Healthcare Providers in Government aided Health Facilities                            Â
This study assessed healthcare providers’ efficiency in government-supported health facilities in Bushenyi District, using measures of central tendency on a scale ranging from 1 to 4. In this scale, 4 denoted Strongly Agree, 3 denoted Agree, 2 denoted Disagree, and 1 denoted Strongly Disagree, as illustrated in Table 5.
Table 5:Â Performance of Healthcare Providers in Government-Aided Health Facilities
Statement | N | Mean | SD |
You are consistently present to assist clients at the facility. | 125 | 3.70 | .52 |
You demonstrate efficiency in carrying out your duties at the facility. | 125 | 3.54 | .59 |
You dedicate your full attention to clients throughout your shift. | 125 | 3.72 | .54 |
Valid N (listwise) | 125 | Â Â Â Â Â Â Â 3.65 | Â Â Â .55 |
Source: Field Data (2024)
The findings reveal that respondents strongly agree they are consistently available at the facility to attend to clients (M = 3.70, SD = 0.52) and devote their time on duty to clients with full attention (M = 3.70, SD = 0.54). They also indicate they are efficient in fulfilling their responsibilities at the facility (M = 3.54, SD = 0.59). The high mean scores on these measures suggest employees are dedicated to delivering quality care, remaining attentive and present during their shifts, factors crucial for enhancing patient satisfaction and achieving positive outcomes (Berry et al., 2019).
Simple Linear Analysis on Work-Life Balance Strategy and Performance of Healthcare Givers
The study investigated how Work-Life Balance Strategies impact healthcare providers’ performance in government-aided medical facilities in Bushenyi District, Uganda. To assess this, the following hypothesis was tested:
H0: Work-Life Balance Strategies have no statistically significant influence on the performance of healthcare givers in government-aided health facilities
Model: Y = β0 + β1 X1
Table 6: Model Summary
Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
1 | .188a | .035 | .027 | .44975 |
a. Predictors: (Constant), Work-Life Balance Strategies |
Source: Field Data (2024)
The model summary table displays a linear regression analysis with the work-life balance strategies as the sole predictor of the dependent variable. The correlation coefficient (R = 0.188) reveals a weak positive correlation amid the predictor and the dependent variable. The R2 value (0.035) implies that only 3.5% of the variability in performance of healthcare providers can be linked to the work-life balance strategies, while the adjusted R2 value (0.027) shows a more conservative estimate, considering model complexity. The Standard Error of the Estimate (0.44975) indicates moderate variability in the residuals, suggesting a moderate fit of the model to the data.
Furthermore, the study evaluated the goodness of fit of the model using ANOVA, with the results presented in Table 7.
Table 7: ANOVAa
Model | Sum of Squares | Df | Mean Square | F | Sig. | |
1 | Regression | .896 | 1 | .896 | 4.429 | .037b |
Residual | 24.475 | 121 | .202 | |||
Total | 25.371 | 122 |
- Dependent Variable: Performance of healthcare providers
- Predictors: (Constant), Work-life balance strategies
Source: Field Data (2024)
The results of a linear regression analysis are presented in the table above where work-life balance serves as the predicting variable and employee performance (EP) as the output variable. The table presents a significant regression model (F = 4.429, p = 0.037) that illustrates the noteworthy influence of work-life balance strategies on performance of healthcare providers. The Sum of Squares column shows the variation in employee performance that the regression model (0.896) and the residual variation (24.475) explain. The Mean Square column displays the residual variation (0.202) and average variation per degree of freedom (0.896) for the regression model. The df column displays the degrees of freedom for the regression model (1) as well as the residual variation (121). The correlation amid work-life balance and employee effectiveness is statistically significant. These findings are consistent with previous research conducted by Shanafelt et al. (2020) and West et al. (2018).
The hypothesis was then tested by running a simple linear regression. The acceptance or rejection was based on p-value where p<0.05 was accepted and vice versa. The results of this test are presented in Table 8.
Table 8: Coefficientsa
Model | Unstandardized Coefficients | Standardized Coefficients | T | Sig. | ||
B | Std. Error | Beta | ||||
1 | (Constant) | 3.252 | .190 | 17.132 | .000 | |
Work-Life Balance Strategies | .137 | .065 | .188 | 2.104 | .037 |
- Dependent Variable: Performance of healthcare providers
- Predicator: Work-life balance strategies
Source: Field Data (2024)
These findings indicate a significant relationship between work-life balance strategies performance of healthcare providers (t=2.104; p= 0.037; p<0.05). Based on this, the null hypothesis (H0) was rejected and the alternative hypothesis (H1) accepted.
The model equation derived from the results is therefore,
Y | = β0 + β1 X1 | |
Y | =3.252+ 0. 137 X2 | |
Where: | Y | – Performance of Healthcare Providers |
X1 | – Work-Life Balance Strategies | |
E | – error term |
Correlation Analysis on Work-Life Balance Strategies and Performance of Healthcare Providers
The study computed correlation analysis to assesses both the direction and strength of the relationship between work-life balance strategies and performance of healthcare providers. The correlation coefficients obtained from the study variables are presented in the correlation matrix displayed in Table 9.
Table 9: Correlation Matrix of Study Variables
Wok-life Balance | Employee Performance | ||
Wok-life balance strategies | Pearson Correlation | 1 | |
Sig. (1-tailed) | |||
Performance of healthcare providers | Pearson Correlation | .188* | 1 |
Sig. (1-tailed) | .037 |
Source: Field Data (2024)
The correlation analysis shows that work-life balance strategies have weak but statistically positive significant relationship with performance of healthcare providers (r = 0.188, p < 0.37).
Discussion of Findings
The study revealed a significant connection between work-life balance strategies and the performance of healthcare providers. The descriptive analysis showed an overall mean of 2.8507 and a standard deviation of 0.87, indicating that most respondents agreed that work-life balance strategies positively influenced healthcare provider performance. These findings align with Bashir et al. (2020), who found that healthcare workers with improved work-life balance experienced higher job performance and motivation, highlighting the crucial role work-life balance plays in enhancing productivity within healthcare settings.
The study results also correspond with Khan et al. (2021), who identified a strong positive correlation between work-life balance and job satisfaction, which subsequently improved overall job performance. This further emphasizes the need for supportive workplace policies. Similarly, Malik et al. (2022) reported that a favorable work-life balance greatly improved nurses’ performance, reinforcing the need for healthcare institutions to implement effective work-life balance initiatives for better nursing outcomes.
These findings are also in consistent with Singh et al. (2022), who discovered a robust positive correlation between work-life balance and performance, with enhanced mental well-being serving as a mediating factor. This underscores the importance of establishing work-life balance programs in healthcare. Zhang et al. (2023) also found that healthcare professionals with a balanced work-life exhibited higher job performance and lower turnover intentions, reinforcing the strong link between work-life balance and employee retention within healthcare. The findings are further in line with Omar et al. (2021), who demonstrated a significant positive relationship between work-life balance and job performance, highlighting the value of flexible work arrangements in promoting employee productivity and satisfaction.
The results of this study align with Adebayo et al. (2021), who emphasized the importance of implementing institutional policies that support work-life balance to enhance the performance of healthcare providers. Their research highlighted that fostering work-life balance policies is essential for improving overall productivity and job satisfaction among healthcare professionals. By promoting a healthy balance between personal and professional responsibilities, healthcare institutions can significantly improve employee performance and well-being.
These findings are also consistent with those of Tariq et al. (2022), who demonstrated that a positive work-life balance significantly improved the quality of care provided to patients. Their research linked the well-being of healthcare workers directly to patient satisfaction and health outcomes. This reinforces the notion that the well-being of healthcare professionals is critical not only for their personal performance but also for the quality of services they deliver to patients.
Similarly, this study’s findings correspond with those of Hassan et al. (2023), who found that strong organizational support for work-life balance led to better performance among healthcare providers. Their research showed that such support enhanced employee productivity and contributed to improved patient care. This underscores the importance of creating a supportive environment where healthcare professionals can maintain a balance between their work and personal lives, leading to better healthcare outcomes.
The results resonate with Nguyen et al. (2023), who reported that effective work-life balance initiatives positively impacted job performance. Their research highlighted that organizational commitment to these initiatives is vital for optimizing healthcare delivery. By prioritizing work-life balance, healthcare organizations can ensure their staff remains motivated and productive, which ultimately contributes to more efficient and effective patient care.
CONCLUSION
The study concludes that a substantial positive correlation exists between work-life balance and the performance of healthcare providers in public facilities. This correlation underscores the vital role of work-life balance in enhancing healthcare provider performance and improving overall healthcare delivery. Organizations can boost job satisfaction, motivation, and productivity among providers by facilitating a better equilibrium between their professional responsibilities and personal lives. This beneficial effect on healthcare provider performance is crucial for delivering high-quality patient care and achieving improved health outcomes within public health facilities.
RECOMMENDATIONS
Healthcare organizations must prioritize the development of comprehensive work-life balance policies that address the varied needs of their employees. Implementing flexible work schedules, telecommuting options, and job-sharing arrangements enables healthcare providers to effectively manage personal responsibilities alongside their professional duties. Creating an environment that values work-life balance significantly enhances job satisfaction and retention among healthcare professionals.
It is essential for healthcare facilities to strengthen support systems that promote mental health and well-being. Offering access to counseling services, wellness programs, and stress management workshops equips healthcare providers to cope with the emotional and psychological demands of their roles. These initiatives not only improve performance but also contribute to overall job satisfaction.
Maintaining adequate staffing levels plays a critical role in preventing burnout among healthcare providers. Ensuring that sufficient staff is available to meet patient needs alleviates the pressures that often lead to work-life imbalance. Addressing workload concerns and reducing excessive overtime fosters a more sustainable work environment, enabling providers to perform at their best.
Training and awareness programs designed to educate both management and employees about the significance of work-life balance can enhance organizational culture. Such programs encourage understanding and acceptance of work-life balance initiatives, cultivating a supportive atmosphere where healthcare providers feel empowered to pursue balance without fear of judgment or repercussions.
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