Healing the healers: Unlocking psychological well-being through meaningful work and quality of work life

Abstract

Healthcare workers in developing countries, such as Indonesia, experience significant psychological stress due to heavy workloads, limited resources, and systemic inefficiencies, all of which negatively impact their psychological well-being (PWB). The aim of this study was to investigate the direct and indirect effects of quality of work life (QWL) on PWB, with meaningful work (MW) as a mediating variable. A cross-sectional survey was conducted with 285 healthcare professionals from various healthcare facilities, including specialists, general practitioners, and nurses. Data were collected using validated scales to assess QWL, MW, and PWB. Pearson correlation analysis was employed to examine relationships among variables, while mediation analysis tested direct and indirect effects. The results indicate that QWL positively influences PWB both directly (β=0.22, p<0.001) and indirectly through MW (β=0.13, p<0.001). Furthermore, MW was found to be a strong mediator (β=0.61, p<0.001), underscoring its critical role in enhancing purpose and resilience. Specialists reported the highest QWL and PWB, whereas nurses exhibited the lowest levels, highlighting occupational disparities. These findings suggest that enhancing the QWL and fostering MW can significantly improve healthcare professionals’ PWB. Accordingly, organizations should prioritize strategies that promote MW and improve work-life conditions to support mental well-being and job satisfaction.

Introduction

The well-being of healthcare providers is essential for maintaining the quality and sustainability of healthcare delivery. Psychological well-being (PWB), in particular, plays a crucial role in enhancing work performance, patient satisfaction, and the overall effectiveness of the healthcare system. However, healthcare providers in developing countries, such as Indonesia, often face high occupational stress due to excessive workloads, limited resources, and systemic inefficiencies. These challenges contribute to burnout, reduced job satisfaction, and compromised patient care, ultimately exacerbating workforce shortages and inefficiencies in the healthcare sector [1,2]. As the demand for healthcare services continues to rise and the availability of healthcare professionals declines, it is imperative to investigate the factors that influence their PWB.

Quality of work life (QWL) is a key determinant of PWB, encompassing various factors such as working conditions, autonomy, job security, fair remuneration, opportunities for professional development, and work-life balance [3]. A higher QWL has been linked to greater job satisfaction, improved mental well-being, and increased employee retention [4]. However, in healthcare settings, particularly in resource-limited environments, QWL varies across professional roles, with specialists generally experiencing better working conditions than general practitioners and nurses [5]. These disparities may result in uneven PWB outcomes, necessitating targeted interventions to address the specific needs of each professional group.

Beyond QWL, meaningful work (MW) has also been recognized as a significant factor influencing PWB. MW refers to an individual’s perception that their tasks contribute to a greater good, align with their values, and provide personal fulfillment [6]. Previous research demonstrated that employees who find their work meaningful exhibit higher motivation, resilience, and engagement [7,8]. However, healthcare professionals often face administrative burdens, bureaucratic constraints, and emotional stress, which can gradually erode their sense of purpose [9]. Further empirical research is needed to examine how MW is a buffer against workplace stress and mediates the relationship between QWL and PWB.

Limited research has explored the indirect effect of QWL on job satisfaction and PWB, particularly in the healthcare sector of developing countries [10,11]. Few studies have examined the mediating role of MW in this relationship despite the healthcare profession’s demanding and emotionally intensive nature [8,12]. Understanding whether MW can enhance well-being despite systemic challenges is crucial [7].

Moreover, most research on healthcare worker well-being has been conducted in high-income economies, where organizational support, work environment, and mental health provisions differ significantly from those of low-income countries such as Indonesia [13,14]. The Indonesian healthcare system presents unique structural and cultural challenges, including resource scarcity, heavy patient loads, and rigid professional hierarchies, necessitating a more context-specific examination of well-being determinants [15].

Hence, the aim of this study was to examine the direct and indirect effect of QWL on PWB with MW as a mediator. It investigates the extent to which QWL influences PWB, the contribution of MW to overall well-being, and whether MW mediates the relationship between QWL and PWB. By identifying these key relationships, this study provides empirical evidence to support workplace policies and interventions aimed at improving the well-being of healthcare professionals. The findings will inform hospital management, policymakers, and healthcare institutions on strategies to enhance job satisfaction, prevent burnout, and improve healthcare service quality. Given the critical role of healthcare workers in public health outcomes, ensuring their well-being is not only beneficial for employees but also essential for the healthcare system and society.

Methods

Study design and setting

This study employed a quantitative cross-sectional survey design to examine the correlation between QWL, MW, and PWB among Indonesian healthcare professionals. Data were collected from various healthcare facilities, including hospitals, clinics, and community health centers, to ensure a diverse and representative sample. These facilities were selected due to their high concentration of healthcare workers and variations in workplace conditions, such as workload intensity, resource availability, and professional hierarchy. Data was collected over a four-month period, from April to July 2024, using validated measurement tools and systematic statistical analysis to assess the effects of QWL and MW on PWB. Respondents were selected through purposive sampling.

Respondents

This study included healthcare workers from various healthcare facilities across Indonesia, including hospitals, clinics, and community health centers. Participants were categorized into three primary professional groups: specialists, general practitioners, and nurses, reflecting differences in responsibility and workload. These groups were selected due to their direct patient care roles and varying levels of autonomy and work demands. Inclusion criteria required participants to have at least one year of experience in a healthcare facility, ensuring sufficient clinical exposure to assess QWL and PWB. Participants also needed to be fluent in the survey language and provide informed consent. Exclusion criteria included a diagnosed mental illness that could interfere with self-assessment, being on long-term leave, working in administrative roles without direct patient contact, or lacking fluency in the survey language. Written informed consent was obtained from participants before enrollment.

Data collection

Data collection primarily utilized online surveys due to their accessibility and the increasing internet use among healthcare workers. Respondents were given three weeks to complete the questionnaire, which was distributed via Google Forms (Google LLC, Mountain View, USA) and WhatsApp (Meta Platforms, Inc., Menlo Park, USA), allowing flexibility in participation. Additional measures were implemented for healthcare workers with limited internet access to ensure inclusivity. Printed questionnaires were distributed to those in facilities with inadequate digital infrastructure. Additionally, face-to-face sessions were conducted to provide technical support and an alternative for manually completing the survey if needed. Online surveys remained the preferred method due to their efficiency in reaching a broader sample, minimizing geographical constraints, and expediting data collection and analysis. Moreover, this approach allowed respondents to complete the questionnaire at their convenience without needing in-person meetings.

Before completing the survey, participants were required to provide written informed consent. The questionnaire consisted of three sections: (1) a consent statement confirming willingness to participate; (2) demographic information, including age, sex, profession, length of service, workplace, and number of practice sites; and (3) measurement scales assessing QWL, MW, and PWB.

Study instruments

The dependent variable in this study was the PWB of healthcare workers, while the independent variable was the QWL. Additionally, MW was a mediating variable in the relationship between QWL and PWB.

PWB was assessed using Ryff’s PWB scale [16,17], which comprises six dimensions: environmental mastery, self-acceptance, personal growth, positive relationships, purpose in life, and autonomy [18]. Operationally, PWB refers to an individual’s ability to manage their life effectively, maintain healthy social relationships, find meaning and direction, and function optimally in the workplace. Each item was rated on a 6-point Likert scale (1=strongly disagree to 6=strongly agree), with total scores ranging from 18 to 108, where higher scores indicated greater PWB. The internal consistency of this scale has been reported with a reliability value of 0.84 and an item discrimination index ranging from 0.35 to 0.68 [16].

QWL was assessed using the Work-Related Quality of Life (WRQoL) scale, which captures individuals’ perceptions of home-work interface, general well-being, job and career satisfaction, control, working conditions, and stress at work [19]. Operationally, QWL is defined as the degree of satisfaction healthcare workers derive from working conditions, opportunities for self-development, PWB, and interpersonal relationships in the workplace. Each item was rated on a 5-point Likert scale (1=strongly disagree to 5=strongly agree). The total score ranges from 24 to 120, with higher scores indicating better WRQoL. Previous validation studies have reported a reliability value of 0.90 and an item discrimination index of 0.38–0.74 [19].

Work meaning was measured using the Work and Meaning Inventory (WAMI), which comprised three key dimensions: positive meaning, meaning-making through work, and greater good motivation [20,21]. Work meaning is the extent to which individuals perceive their work as personally significant, socially impactful, and aligned with their core values. In this study, work meaning is a mediating variable in the relationship between QWL and PWB. Each item is rated on a 5-point Likert scale (1=strongly disagree to 5=strongly agree), with total scores ranging from 10 to 50. Higher scores reflected greater perceived meaning in work. Previous validation studies have demonstrated a reliability value of 0.84 and an item discrimination index of 0.49–0.80 [20,22].

Demographic and occupational factors were also analyzed in this study. Sex was categorized as male or female, while age was classified into predefined groups. The profession was divided into specialists, general practitioners, and nurses. Length of service was grouped into three categories: less than two years, three to ten years, and more than ten years. Marital status was categorized as either unmarried or married. Statistical analyses were conducted to examine the direct relationship between QWL and PWB and the mediating role of work meaning in this association.

Statistical analysis

Statistical analysis in this study was performed using JASP software (University of Amsterdam, Amsterdam, Netherlands) to examine the relationship between QWL, MW, and PWB of healthcare workers. A descriptive analysis was conducted to summarize the characteristics of the respondents, including age distribution, sex, profession, length of service, and marital status. Additionally, the means and standard deviations of the main variables (QWL, MW, and PWB) were calculated and reported.

The Pearson correlation test assessed the relationship between QWL, MW, and PWB, determining whether significant associations exist among these variables. Linear regression analysis was employed to examine the direct effect of QWL on PWB and the direct impact of work meaning on PWB. Additionally, mediation regression analysis was performed to evaluate the mediating role of the MW in the relationship between QWL and PWB. A bootstrapping approach with 5,000 resamples was used to estimate 95% confidence intervals (95%CIs), ensuring the significance of the mediating effect.

The statistical analysis results were visualized using a path diagram to illustrate the relationships among QWL, MW, and PWB. This diagram depicted the direction and strength of these relationships based on the regression analysis findings.

Results

Demographic characteristics of respondents

The total number of eligible respondents was 285 healthcare workers, comprising 52 specialists, 191 general practitioners, and 42 nurses. The characteristics of respondents are presented in Table 1. Most respondents were general practitioners (67.1%), followed by specialists (18.3%) and nurses (14.6%). Regarding sex, the number of females was higher than males, with a proportion of 60.3% and 39.7%, respectively. In terms of age distribution, the largest age group was in the range of 31–40 years, reflecting the majority of healthcare workers in the mid-career stage. Regarding length of service, more than half of the healthcare workers who participated in this study had between 3 and 10 years of work experience, indicating that most healthcare workers possess considerable expertise in their profession. In terms of income, most healthcare workers earned between IDR 2 million and 4 million per month. In contrast, the group earning above IDR 10 million accounted for about 20% of the respondents, most likely consisting of specialist doctors. The distribution of workplaces showed that almost half of the respondents worked in hospitals, while 45.6% were at community health centers, with a small proportion working in clinics.

Table 1.

Characteristics of the healthcare workers (n=285)

Description	n	%
Profession
Specialist	52	18.3%
General practitioner*	191	67.1%
Nurse	42	14.6%
Sex
Male	113	39.7%
Female*	172	60.3%
Age
21–30 years old	71	24.9%
31–40 years old*	149	52.3%
41–50 years old	50	17.5%
51–60 years old	15	5.3%
Educational background
Bachelor*	197	70.1%
Masters	25	8.5%
Doctorate	4	1.4%
Specialist	54	18.3%
Subspecialist	5	1.7%
Duration of work
<2 years	40	14.1%
3–10 years*	162	56.8%
>10 years	83	29.1%
Marital status
Not married	32	11.3%
Married*	253	88.7%
Income (rupiah/month)
<Rp 1 million	10	3.5%
Rp 1–2 million	15	5.3%
Rp 2–4 million*	101	35.4%
Rp 4–10 million	96	33.7%
>Rp 10 million	63	22.1%
Workplace
Hospitals	135	47.4%
Community health centers	130	45.6%
Clinics	20	7.0%

^*Most prevalent characteristics

Comparison of quality of work life (QWL), meaningful work (MW), and psychological well-being (PWB)

The descriptive statistics for the variables QWL, MW, and PWB across various demographic factors, including sex, occupation, marital status, and length of service, are presented in Table 2. These data describe the distribution of scores in the population and indicate individual differences in QWL, MW, and PWB. The findings indicate that specialists consistently reported higher mean scores for QWL (88.2), MW (33.3), and PWB (83.4). These results suggested that specialists, due to their advanced expertise, greater autonomy, and likely higher compensation, experienced better work-life quality and PWB compared to general practitioners and nurses, who may face more significant resource constraints and heavier patient loads. In contrast, nurses reported lower but relatively stable scores, emphasizing potential areas for improvement in their work environments. Additionally, male respondents scored higher across all constructs, suggesting potential sex-based disparities in workplace experiences and opportunities for personal growth. Specifically, males reported slightly higher mean scores in QWL (88.4) and MW (33.3) compared to females (QWL: 85.2, MW: 31.9). This disparity may reflect broader societal and workplace challenges faced by female healthcare workers, including sex-based expectations regarding work-life balance and potential workplace discrimination.

Table 2.

Comparison of quality of work life (QWL), meaningful work (MW), and psychological well-being (PWB) based on respondent characteristics (n=285

Characteristic	n	Quality of work life		Work and meaning inventory (WAMI)		Psychological well- being
		Mean	SD	Mean	SD	Mean	SD
Profession
Specialist	52	88.2	8.8	33.3	3.7	83.4	6.0
General practitioner	191	86.3	12.5	32.3	3.9	82.9	7.5
Nurse	42	85.1	12.9	32.6	4.0	83.7	7.0
Sex
Male	113	88.3	12.5	33.3	4.2	83.5	7.1
Female	172	85.2	11.4	31.9	3.6	82.8	7.1
Marital status
Single	32	84.7	13.3	32.5	3.9	82.7	7.5
Married	253	86.7	11.8	32.5	3.9	83.1	7.1
Work tenure
<2 years	40	86.9	16.7	33.4	4.7	82.5	10.3
3–10 years	162	86.7	12.0	32.7	3.9	82.9	6.9
>10 years	83	85.8	8.8	31.7	3.2	83.8	5.5

Furthermore, respondents with less than two years of service reported the highest scores for QWL (86.9) and MW (33.4), likely reflecting newly employed workers’ initial enthusiasm and optimism. However, longer tenures were associated with slightly lower scores, possibly due to job fatigue, accumulated stress, or unmet career expectations. The decline in scores among long-serving workers highlights the need for retention strategies that sustain engagement and well-being over time.

Additional analyses using analysis of variance (ANOVA) and crosstab tests were conducted to evaluate the relationship between demographic variables and QWL, MW, and PWB. However, the analysis showed that age, sex, marital status, and place of work had no significant relationship with the main variables of the study (p>0.05). Therefore, these results were not reported further in the main tables but were still considered in interpreting the findings. To ensure the accuracy of the results, normality and homogeneity of variance assumption tests were also conducted before running the ANOVA analysis, and no significant violations of the underlying statistical assumptions were found.

Correlation analysis

The Pearson correlation analysis measuring the linear relationship between scores of QWL, MW, and PWB is presented in Table 3. Pearson correlation has a range of values from -1 to 1, where values close to 1 indicate a strong positive relationship, values close to -1 indicate a strong negative relationship and values close to zero indicate no linear relationship. All relationships between variables in this study showed significant positive correlations (p<0.001). The main result of the correlation analysis showed that the relationship between QWL and MW had a correlation coefficient of 0.66 with a significance level of p<0.001. This indicates a strong positive relationship between the two variables, meaning that the higher the QWL of healthcare workers, the more likely they are to find meaning in their work. The relationship between MW and PWB has a correlation coefficient of 0.58 with a significance level of p<0.001 included in the moderate to strong correlation category, which indicates that healthcare workers who consider their work meaningful tend to have higher PWB. Meanwhile, the correlation between QWL and PWB of 0.59 with a significance level of p<0.001 also falls into the moderate to strong correlation category, confirming that better working conditions are associated with higher PWB.

Table 3.

Pearson’s correlation coefficients among study variables

Variables	Mean	SD	QWL	MW	PWB
QWL	86.46	11.96	1.00	0.66***	0.59***
MW	32.48	3.91	0.66***	1.00	0.58***
PWB	83.09	7.14	0.59***	0.58***	1.00

MW: meaningful work; PWB: psychological well-being; QWL: quality of work life; SD: standard deviation

^***p<0.001

Mediation analysis

The mediation analysis results that examined the role of MW in the relationship between QWL and PWB using the path analysis model are presented in Table 5. This analysis evaluated three main paths: the direct effect of QWL on MW, the direct effect of MW on PWB, and the direct and indirect effects of QWL on PWB through MW. The results showed that the path from QWL to MW had an estimate of 0.22 with a standard error of 0.02 and a significance level of p<0.001. This indicates that QWL has a significant direct effect on MW, which means that healthcare workers with good working conditions are more likely to feel meaning in their work. The path from MW to PWB had an estimate of 0.61 with a standard error of 0.11 and a significance level of p<0.001, indicating that healthcare workers who find meaning in their work tend to have higher PWB. The direct path from QWL to PWB had an estimate of 0.22 with a standard error of 0.03 and a significance level of p<0.001, indicating that QWL directly influences PWB. However, the indirect path through MW was also significant, with an estimated 0.13, a standard error of 0.03, and p<0.001. This value suggests that MW mediates the relationship between QWL and PWB, meaning that healthcare workers who have good working conditions but do not find meaning in their work may not have optimal levels of PWB.

Table 5.

Direct and mediation effects of quality of work life on psychological well-being

Pathway	Estimate	SE	z-value	p-value	95%CI (lower)	95%CI (upper)
QWL (IV) → MW (M)	0.22	0.02	14.98	<0.001	0.19	0.25
MW (M) → PWB (DV)	0.61	0.11	5.45	<0.001	0.39	0.82
QWL (IV) → PWB (DV) (direct effect)	0.22	0.03	6.08	<0.001	0.15	0.30
QWL (IV) → MW (M) → PWB (DV) (indirect effect)	0.13	0.03	5.12	<0.001	0.08	0.18

CI: confidence interval; DV: dependent variable; IV: independent variable; M: mediator; MW: meaningful work; PWB: psychological well-being; QWL: quality of work life; SE: standard error

The relationship between QWL, MW, and PWB using a path diagram is presented in Figure 1. The MW to PWB path has the highest coefficient, which confirms that MW has the greatest impact on PWB compared to other factors. The indirect path from QWL to PWB via MW is stronger than the direct path of QWL to PWB, which means that perceived MW strengthens the impact of QWL on PWB. Visually, this diagram confirmed that MW was not just an additional variable but a key factor linking QWL to the PWB of healthcare workers. The significant path from QWL to MW and MW to PWB, having the largest effect, suggests that efforts to improve PWB should not only focus on enhancing physical and administrative working conditions but also on how healthcare workers can find meaning in their work. This diagram makes it clear that MW acted as a partial mediator, as the direct effect of QWL on PWB remains significant but smaller than the indirect path through MW. The conclusion from the analysis of this table and diagram is that the PWB of healthcare workers is strongly influenced by how they find meaning in their work. Although a better QWL can improve PWB, the impact will be more optimal if healthcare workers find meaning in their work. Therefore, strategies to improve the well-being of healthcare workers should not only focus on increasing salaries, reducing workload, or improving the work environment but also on creating conditions that allow them to feel that their work has a significant and valuable impact.

Figure 1.

Path diagram of the relationship between quality of work life (QWL), meaningful work (MW), and psychological well-being (PWB).

Discussion

The findings of this study establish a strong association between work satisfaction and PWB, highlighting the quality of the work environment as a key determinant of PWB. Employees who experience high work-life quality across six core dimensions report greater happiness and job satisfaction. This aligns with previous research, emphasizing that enhancing workplace quality through employee well-being initiatives contributes to organizational effectiveness [23-25]. A workplace that fosters motivation and engagement encourages employees to invest greater effort in their work. Consequently, a high QWL enhances job satisfaction and broader life satisfaction, including family functioning, social relationships, economic stability, and overall well-being [26,27]. Furthermore, a supportive work environment promotes organizational performance while mitigating negative workplace behaviors, such as absenteeism, staff turnover, and workplace accidents.

Enhancing the QWL is closely linked to greater job satisfaction, more substantial organizational commitment, and increased employee productivity [3,25,28]. Implementing such initiatives can also reduce negative workplace behaviors and promote a healthier work-life balance, improving employees’ well-being, job satisfaction, lower stress levels, and organizational loyalty [29]. Recent studies further highlight a strong correlation between employee well-being and job performance, suggesting that individuals who experience more positive emotional states are more likely to receive higher performance evaluations [30].

Work is crucial to individual and societal well-being, influencing physical and mental health, financial security, personal values, and environmental balance. Contemporary management approaches emphasize enhancing employment quality by addressing eight key social dimensions, ranging from individual experiences to broader community impacts [5,31]. Among these, the concept of “meaningful work” is particularly significant, as it is strongly linked to job satisfaction and serves as a key motivator in this study. The findings indicate that individuals who perceive their work as meaningful demonstrate higher motivation levels, aligning with previous research on the subject [32].

This study contributes to the Job Demands-Resources (JD-R) theory by demonstrating the dynamic interaction between job and personal resources within a shared ecosystem. It emphasizes the interdependence of these resources and the necessity of balancing job demands with organizational objectives to foster employee well-being [33,34]. In healthcare, MW is critical in shaping employee well-being. Beyond technical expertise, healthcare professionals navigate emotional challenges inherent in their demanding roles. Failure to manage these challenges effectively can negatively impact employee well-being and patient care, underscoring the importance of strong support systems within healthcare organizations [35].

Individuals who clearly understand their strengths, goals, and contributions are more likely to engage fully in their work—physically, mentally, and emotionally. Such individuals often exceed the formal requirements of their roles, actively contributing to organizational success while seeking professional opportunities that allow them to make meaningful contributions [36]. Moreover, when individuals perceive a sense of control over their work, they establish boundaries that align with their values and preferences, fostering a stronger sense of work meaningfulness. This alignment between work demands and individual values significantly enhances their work experience and job satisfaction [21,37] .

In the context of healthcare workers in Indonesia, demographic analysis indicates that the workforce predominantly consists of individuals in their productive years with moderate work experience. This demographic profile is particularly relevant, as age and work experience are closely associated with perceptions of work-life balance and PWB [2]. Additionally, married respondents benefit from significant social support, which can enhance their psychological resilience to work-related stress [3]. However, the findings also highlight unique challenges for female healthcare workers, who constitute a substantial proportion of the workforce. These challenges often arise from the dual burden of professional and domestic responsibilities, which may negatively impact their work-life balance, PWB, and sense of meaningfulness at work [54].

Existing research further supports these findings, indicating that female healthcare workers face a higher risk of burnout and occupational stress compared to their male counterparts. For instance, Gyorffy [54] found that female doctors frequently experience significant strain due to imbalances between work and family responsibilities. Moreover, sex-based discrimination in the workplace, as highlighted by Knaak and Patten [55], adversely affects women’s work experiences, particularly their perceptions of MW and QWL. These findings emphasize the urgent need for targeted interventions to improve the well-being of female healthcare professionals. Implementing sex-sensitive workplace policies and strengthening institutional support systems can help mitigate these challenges. Addressing these issues is essential for fostering a more equitable and supportive work environment, ultimately enhancing workforce productivity and job satisfaction.

Regarding tenure, perceptions of work meaning were lower among employees with longer tenure. Linzer [38] found that healthcare workers with extended tenure often experience burnout due to repetitive job demands and increasing responsibilities, which can diminish their sense of work meaning and PWB. Similarly, Olson [39] noted that chronic fatigue among long-tenured employees can lead to feelings of alienation from their work, further reducing their perception of meaning at work. A study [40] suggested that newer employees generally view their roles more favorably due to initial enthusiasm and unmet expectations. In contrast, senior employees may find their work less meaningful over time as their experiences diverge from their initial expectations. These findings highlight that work meaning is dynamic, evolving with individual experiences and shifting life priorities.

Research findings indicate that specialists experience a higher QWL, largely due to greater job control and adequate structural support [57]. Specialists typically have more defined responsibilities and higher autonomy, which increases job satisfaction and reduces stress levels [4]. In contrast, nurses report a lower perceived QWL, likely due to their roles’ physical and mental demands, which are often intensified by resource constraints and limited autonomy [4]. The emphasis on ‘job control’ and ‘job stress’ is particularly relevant to this study, as both factors directly impact healthcare workers’ ability to perform their roles effectively and derive meaning from their work. General practitioners and nurses predominantly serve in primary healthcare facilities, such as community health centers and clinics, which form the frontline of Indonesia’s healthcare system. These facilities frequently face shortages of medical personnel, equipment, and essential medicines, hindering their ability to deliver optimal care [4]. Furthermore, disparities in the distribution of healthcare workers remain a persistent challenge in Indonesia [34], with nurses and general practitioners often stationed in remote areas with limited access to healthcare infrastructure.

On the other hand, specialists primarily work in large city hospitals with better-equipped facilities. In contrast, general practitioners often take on dual roles, balancing clinical duties with administrative responsibilities such as managing public health programs [38]. Nurses also face significant pressure, juggling administrative workloads alongside direct patient care. The high volume of patient interactions, particularly in resource-limited settings, heightens the risk of stress and burnout among general practitioners and nurses [2]. Consequently, these challenges negatively impact their perceived QWL and PWB.

MW is integral to PWB, providing healthcare workers with a sense of accomplishment and societal contribution [31]. The high scores among specialists suggest a strong link between patient-centered clinical work and perceived job meaning [41]. In contrast, general practitioners and nurses may struggle to find occupational meaning, particularly when burdened with administrative or repetitive tasks that diminish intrinsic satisfaction [42]. These findings highlight the need for healthcare organizations to foster a work environment that enhances job meaning through recognition, rewards, and professional engagement.

High PWB among specialists can be attributed to greater job control and a strong sense of professional accomplishment [43]. In contrast, low autonomy scores suggest systemic constraints, such as rigid policies or limited resources, that hinder healthcare workers from making independent decisions [44]. Addressing these challenges is essential in ‘healing the healers,’ as improved PWB enhances workforce productivity and directly impacts patient care quality.

This analysis confirms the mediating role of MW in the relationship between QWL and PWB. The strong correlation between QWL and MW suggests that a supportive work environment— characterized by autonomy, control, and recognition—enhances perceptions of job meaning [7,22]. Furthermore, the significant relationship between MW and PWB highlights the importance of providing healthcare workers with opportunities to witness the positive impact of their work on society [45]. Within the framework of ‘healing the healers,’ these findings offer empirical support for policies that prioritize improving the QWL by fostering MW, ultimately enhancing healthcare professionals’ PWB.

Although this study offers valuable insights, several limitations should be acknowledged. First, its cross-sectional design prevents definitive conclusions about causal relationships between variables. Future research could adopt a longitudinal approach to better establish causality between QWL, MW, and PWB. Second, the sample primarily consisted of healthcare workers in urban areas, limiting the generalizability of the findings to those in remote regions or with more extensive work experience. Future research should broaden population coverage by including diverse demographics of healthcare workers to provide a more comprehensive perspective. Additionally, this study relied on self-reported questionnaire data, which may be susceptible to respondent bias. A mixed-method approach incorporating qualitative insights could offer a deeper understanding of healthcare workers’ experiences regarding QWL and job meaningfulness. Lastly, this study focused on three primary variables. Future research could explore additional factors, such as social support, workload, and organizational culture, which may also influence the PWB of healthcare workers. Despite its limitations, this study offers a strong foundation for developing effective management strategies to enhance healthcare workers’ well-being. Addressing these limitations in future research will help deepen the understanding of work dynamics across healthcare settings.

Conclusion

This study highlights a positive correlation between QWL and PWB, with MW acting as a partial mediator. The findings contribute to a conceptual model that positions QWL as an exogenous variable and MW as a moderating factor in enhancing healthcare workers’ PWB. These results provide strong empirical support for the existing theoretical framework, underscoring the role of organizational efforts in improving work quality, fostering meaning, and promoting overall well-being.

Ethics approval

The Archipelago Scientific Psychology Consortium (KPIN) Ethics Committee has reviewed and approved the research project. The respondents provided written informed consent for participation in the survey.

Competing interests

The authors have declared that no competing interests exist. All co-authors have seen and agree with the manuscript’s contents, and there is no financial interest to report. The authors certify that the submission is original work and is not under review at any other publication.

Funding

This research project was conducted without the receipt of any external grants or funding. The authors declare that they have independently funded this study.

Underlying data

Derived data supporting the findings of this study are available from the corresponding author on request.

Declaration of artificial intelligence use

We hereby confirm that no artificial intelligence (AI) tools or methodologies were utilized at any stage of this study, including during data collection, analysis, visualization, or manuscript preparation. All work presented in this study was conducted manually by the authors without the assistance of AI-based tools or systems.

How to cite

Aprilia ED, Adam M, Zulkarnain Z, Mawarpury M. Healing the healers: Unlocking psychological well-being through meaningful work and quality of work life. Narra J 2025; 5 (2): e2152 - http:// doi.org/10.52225/narra.v5i2.2152.