The Relationship between the Working Environment and Quality of Life among Home Health Aides: Focusing on the Mediation Role of Burnout

ABSTRACT

As South Korea’s population rapidly ages, there is an increasing demand for home aides. However, little is known about how the caregiving environment affects HHAs. Guided by the environment comfort model, we examined the association between care recipients’ home environment and HHA’s quality of life, focusing on how burnout mediates this relationship. Our data came from a national survey of home health aides in 2020 (N = 786). We conducted an exploratory factor analysis to identify six factors related to the care environment in three dimensions: physical (1. space; 2. indoor/outdoor conditions), functional (3. home appliances; 4. heating/air conditioning), and psychological (5. satisfaction with the home environment; 6. relationships with care recipients and their families). We then used a path analysis to examine the relationship between these factors, burnout, and quality of life. Our findings show that safe indoor/outdoor conditions and positive relationships with care recipients and their families are associated with lower levels of burnout, leading to a higher quality of life (p < .05). This highlights the importance of considering both physical and psychological aspects of the caregiving environment to prevent burnout and improve the quality of life for HHAs, ultimately contributing to high-quality services for care recipients.

Introduction

Globally, as the aging population increases, social issues have intensified, such as increased health problems among older adults and the growing burden on families who support them. In response, countries around the world have undertaken various policy efforts. For example, South Korea (hereafter Korea) started nationwide Long-term Care (LTC) program in 2008 (Chon, 2014), Taiwan has also addressed care needs through LTC that focused on home and community-based services (Lee et al., 2024), Thailand is working to improve health literacy through national programs (Srisaknok et al., 2024), and Malaysia is making efforts to reduce social isolation (Siah et al., 2023) among older adults.

Especially in the realm of caregiving, as demands for aging in place, commonly referred to as older adults’ desire to remain in their homes instead of transitioning to an institutional setting, are rapidly increasing (Wagner, 2021), the importance of caregiving has become more emphasized. Despite policy efforts to reduce the burden on informal caregivers, including family members, caregiving for older adults still burdens the informal caregivers. This burden is even greater for families of older adults with health issues such as dementia or mental illness (Cheng et al., 2022; Lin et al., 2019). Also, by supporting informal caregivers and enabling the realization of aging in place (AIP), formal caregivers such as Home Health Aides (HHAs) have been known to contribute to reducing institutionalization, decreasing healthcare costs, and improving the quality of life of older adults and their families by providing caregiving to older adults who want to remain in their homes (Bercovitz et al., 2011; Jang et al., 2017; Wagner, 2021).

Although HHAs are pivotal in the home care system, they are undervalued as unskilled or low-skilled workers with low-paying jobs (Scales & Lepore, 2020). Often, HHAs are exposed to high-risk danger in their working environment, such as violence, harassment, poor physical work environment, and conflict with relatives of recipients (Hanson et al., 2015; Zeytinoglu et al., 2007). Since their working environment is the living place of care recipients, the protective system for HHAs rarely exists. Unsafe and unhealthy working environments for HHAs may cause burnout of HHAs, leading to their poor quality of life (Oh & Kang, 2023), directly affecting the care recipients’ caregiving quality (H. Nam & Lee, 2016).

Understanding the working environment of HHAs is crucial to prevent burnout and increase the quality of life. However, few research studies have examined the relationship between working environment, burnout, and quality of life, and these studies included only direct care workers and nurses who work in long-term care facilities and hospital settings as their sample (Ampt et al., 2008; Cheng et al., 2022; Hendrich et al., 2008; Kim et al., 2019; Rouxel et al., 2016). Little is known about the working environment, burnout, and quality of life of HHAs to support the community-dwelling population better. Guided by the Environmental Comfort Model (Vischer, 2007), this study aims to examine the comprehensive working environment of HHAs and its association with the quality of life, focusing on the mediation effect of burnout of HHAs.

Working environment, burnout, and quality of life of home health aides

The previous research suggests that the working environment can include various aspects of the environment. For example, studies on general employees’ working environment and outcomes primarily focused on the physical office environments and their impact on employees’ attitudes, behaviors, satisfaction, and performance. (Esfandiari et al., 2017; García-Mainar et al., 2015; S. Y. Lee & Brand, 2005). Likewise, the research on the working environment for care workers who work in institutional settings also examined the physical environment, including unit size, spatial layout, homelike features, sensory stimuli (temperature, noise, and lighting in spaces), and social areas in care facilities (Chaudhury et al., 2018; Garre-Olmo et al., 2012; Lee et al., 2021; Smith et al., 2014). Also, in the case of the home settings, the research on the working environment explored the physical environment (Berta et al., 2018; Zeytinoglu et al., 2007), such as the importance of enough size and well-equipped facilities of rooms, bathrooms, movement space, and amenities shared with recipients (Oh & Kang, 2023). On top of that, the psychosocial aspects, such as good control over work (Zeytinoglu et al., 2007) and close relationships with care recipients and their families (Cho et al., 2023), were examined as part of the home care working environment. The organizational dimensions, such as organizational and peer support (Berta et al., 2018; Zeytinoglu et al., 2007) and agency policy and culture, were included as working environments for HHAs (Cho et al., 2023).

These components of working environments have been empirically linked to the quality of life of HHAs (Huelat & Pochron, 2020; Möckli et al., 2021; Soilemezi et al., 2019). Especially the physical aspects, such as the size of the place, architectural layout, and the extent of home modifications undertaken, exert a substantial influence on the overall quality of life of HHAs (Carnemolla & Bridge, 2019; Olsen et al., 1996; Soilemezi et al., 2019). Recently, the increased use of human-centric technological resources that assist caregiving tasks has been shown to support the quality of life of HHAs (Huelat & Pochron, 2020). Also, close relationships between HHAs and care recipients are associated with higher job satisfaction (Denton et al., 2002; Neysmith & Nichols, 1994) and better work engagement (Möckli et al., 2021).

Among several potential factors that may elucidate the relationship between the home-setting work environment and the quality of life experienced by HHAs, the presence of elevated job-related stress, strain, or burnout emerges as a crucial connecting element. The working environment of physical aspects, such as unsafe homes and neighborhoods, appear to be sources of job stress and burnout for HHAs (Denton et al., 2002; Kim, 2020), while secured and comfortable working environments serve to mitigate stress among HHAs (Gitlin & Corcoran, 1996; Soilemezi et al., 2019; Unwin et al., 2009). Notably, the size of the recipient’s living space and the convenience of facilities such as rooms, bathrooms, and restrooms significantly impact the burnout of HHAs (Oh & Kang, 2023). In addition, the relationships with care recipients are significantly intertwined with job stress and burnout, especially when dealing with excessive demands, unpleasantness, and even aggression, leading to emotional distress (Denton & Zeytinoğlu, 1996; Denton et al., 2002; Hanson et al., 2015). Moreover, the relationships and conflicts with the care recipient’s family have been linked to increased burnout among HHAs (Cho et al., 2023; Kim, 2020; Oh & Kang, 2023).

Despite the limited research on the relationship between burnout and quality of life among HHAs, there is well-established evidence on a strong relationship between burnout and quality of life among health professionals (Asante et al., 2019; Fradelos et al., 2014; Meneguin et al., 2023; Suñer-soler et al., 2013; Takai et al., 2009). For example, Takai et al. (2009) found that higher levels of burnout in caregivers of patients with dementia corresponded to higher levels of depressive symptoms and lower quality of life. Suñer-soler et al. (2013) found that healthcare personnel with higher levels of burnout reported worse perceived health and lower quality of life. These findings suggest the possible relationship between burnout and decreased quality of life among HHAs.

HHAs who work in multiple care recipients’ homes on a daily basis (Zoeckler, 2018) are exposed to a higher risk of working in a poor home environment and experiencing higher burnout, potentially impacting their overall quality of life. Previous research has explored diverse facets of the working environment, encompassing both physical and psychosocial dimensions. However, there is a lack of research exploring how these aspects of the work environment may affect the burnout of HHAs until now.

The case of south korea

In 2008, the Korean government introduced Long-Term Care Insurance (LTCI) to enhance health and stability in later life and reduce the families’ burden of caregiving via providing formal caregiving services with certified HHAs for older adults facing physical or cognitive impairments. This mandatory nationwide social insurance program complements national health insurance, and the LTCI offers coverage for home-based and institutional services (Chon, 2014). Due to this program, many care workers provide services in institutional settings and recipients’ homes. In 2022, 486,523 care workers offered home-based services, and 85,053 provided services in institutional settings (National Health Insurance Corporation [NHIC], 2023). Consequently, the majority of care workers work in the recipients’ homes. The care workers in recipients’ homes, HHAs, assist with physical activities, provide emotional support, and manage household tasks and daily living responsibilities such as meal preparation, cleaning, and laundry at care recipients’ homes (Jang & Park, 2018). Also, the HHAs work to support community-dwelling care recipients in their daily lives, and the primary working environment of HHAs is considered the house of the care recipients (Kang & Lee, 2022).

In Korea, there has been limited research on the working environment of HHAs to date. Existing studies have not explicitly focused on HHA, instead, primarily targeted care workers in institutional settings (Jang & Yoo, 2023). The results from current studies on HHAs in Korea found that HHAs have lower self-efficacy compared to care workers in institutional settings, with higher levels of depression and a lower perceived quality of life (Kim & Lee, 2017). This may be because HHAs visit recipients’ private spaces alone, making it difficult to seek help from colleagues or other resources in case of problems (H. Lee & Kim, 2022). For example, Oh and Kang (2023) conducted a study that considered the recipients’ residential environments as the working environment of HHAs. However, this study was limited to examining the impact of these environments on the burnout of HHAs.

Theoretical framework

Previous research studies have examined how the working environment impacted healthcare workers’ burnout and quality of life, however, research examining the multi-dimensional working environments guided by the environmental comfort model is fairly limited, especially the research focusing on HHAs. We drew on the Environmental Comfort Model by Vischer (2008) to examine various aspects of the working environment of HHAs. According to the theoretical model, environmental comfort comprises three hierarchically related categories: physical, functional, and psychological (Vischer, 2007). At the bottom of the model, there is physical comfort, which refers to basic human needs like safety, hygienic conditions, and accessibility. Functional comfort is in the middle of the pyramid, indicating ergonomic support for job performance and work-related tasks, such as enclosed spaces available for their work, ergonomic furniture, appropriate lighting systems, and convenient appliances. Top of the pyramid is psychological comfort, which means the feelings of control over one’s workspace, ownership, and belonging. The Model proposes that weakness in one comfort category can be compensated for by strength in another. The optimal environmental support for performance may be achieved when the working environment’s quality is secured at all three comfort levels.

Present study

This study poses three research objectives. First, we attempt to identify the underlying empirical structure of the working environment of HHAs. Guided by the Model, we hypothesize that the working environment of HHAs can be identified as three distinctive tiers (physical, functional, and psychological). Second, we examine the empirical association between the working environment, burnout, and the quality of life of HHAs. Based on previous findings on the relationships between the working environment and the quality of life of HHAs (Huelat & Pochron, 2020; Möckli et al., 2021; Soilemezi et al., 2019) and the working environment and burnout of HHAs (Denton et al., 2002; Kim, 2020; Oh & Kang, 2023), we expected that the working environment of HHAs impacts both burnout and quality of life. Specifically, we hypothesize that HHAs’ working environment affects both burnout and their quality of life, and burnout mediates this relationship. Lastly, we examine the mediating effect of burnout on this relationship based on our hypothesis. We expected to find that an unsupportive working environment is associated with HHA’s low level of life quality through burnout. We did not set up specific hypotheses about individual dimensions of the working environment’s role. A figure of the conceptual framework is included in Figure 1.

Figure 1. Theoretical Framework (Environmental Comfort Model).

Method

Data collection

This study was based on a survey of the ‘Home and Service Environments of Long-Term Care Recipients in Receipt In-home Care’ conducted by the Korea Institute for Health and Social Affairs (KIHASA). The Korea Institute for Health and Social Affairs selected one urban (Seoul area) and one rural (Chung-cheong area) in Korea to include the characteristics of living environments in both urban and rural areas and selected 1,001 HHAs working at a home-based long-term care agency from August to September 2020 using a mail survey. The survey on the environment of HHAs obtained approval from the Korea Institute for Health and Social Affairs’ IRB. The survey includes basic information on care service recipients’ health conditions and living environment as a working place. It also consists of detailed characteristics of HHAs, including salary, working period, service duration and frequency, work activity, and satisfaction of HHAs. We restricted the analysis to the participants who fully responded to the survey. We excluded samples with missing data on the working environment and other related key variables. The final sample consisted of 786 to examine the relationship between the working environment and quality of life among HHAs, with burnout as a potential mediating factor.

Measurement

The working environment of HHAs

The working environment of HHAs is measured with the physical characteristics of care recipients’ living environment) and overall HHA’s perceived satisfaction with their working environment. The physical working environment consisted of 25 questions about space, conditions, and home appliances. The overall satisfaction with the working environment consisted of 13 questions about the satisfaction of HHAs with their relationship with service users and family caregivers, space, and appliances. Specific information on the working environment is attached in Appendix 1.

Burnout of HHAs

Burnout of HHAs was assessed based on their responses to 16 questions of the Maslach Burnout Inventory – General Survey (Schaufeli et al., 1996), such as feeling exhausted from work, tired in the morning, nervous due to work, and their interest in the job decreased. Participants responded to each item using a 5-point Likert scale ranging from a response of strongly disagree (1) to strongly agree (5). Negative questions were reverse coded, and the sum score was used. Higher scores indicate a higher burnout status. The Cronbach’s alpha for this measurement was .860.

Quality of life of HHAs

Quality of life of HHAs was assessed with five questions of the Satisfaction of Life Scale (Diener et al., 1985): (1) Overall, my life is close to what I idealize, (2) conditions in my life are very good, (3) I am satisfied with my life, (4) I have achieved the important things I want in my life, (5) even if I were to be reborn, I want to live like I do now. Participants responded to each item using a 5-point Likert scale ranging from a response of strongly disagree (1) to strongly agree (5). The sum score was used, and higher scores indicate a higher quality of life. The Cronbach’s alpha for the Satisfaction of Life Scale was .871.

Covariates

Following previous literature (Jang et al., 2017; Oh & Kang, 2023; Quinn et al., 2016), we controlled for key variables associated with the life satisfaction of HHAs, such as gender, age, education, self-rated health, and weekly working hours. Gender was assessed with a binary variable of male or female. Age cohorts were coded into four categories in 10-year intervals (30–39, 40–49, 50–59, 60–69, 70+), education was coded into four categories (less than middle school, high school graduate, college graduate, university graduate and above), and weekly working hours were coded into four categories (≤15, 15–24, 25–34, 35+). Self-rated health was measured as (1) very poor – (5) very healthy.

Data analysis

Multiple statistical analysis approaches were employed in this study. First, to identify the underlying factorial structure among the working environment domains, an Exploratory Factor Analysis (EFA) was utilized. A principal axis factor analysis with an Oblimin method with Kaiser normalization was used. Oblimin rotation was used for factor rotation due to its potential correlations between the latent factors.

Tests were used to explore the potential structure among working environment domains. Data were screened using the KMO Measure of Sampling Adequacy (>0.5) and Bartlett’s Test of Sphericity (<0.05; Tabachnick & Fidell, 2001; Taherdoost et al., 2014). A Scree plot, with a cutoff eigenvalue of 1, was also employed to determine the number of factors. Factor loading estimates for all items on the factors were then utilized to establish the structure (Cattell, 1966; Worthington & Whittaker, 2006). The EFA was conducted utilizing SPSS version 26 (IBM Corp, 2022).

Second, to validate the factorial structure of coping strategies identified in the EFA, the confirmatory factor analysis (CFA) was employed. The standardized regression coefficients for all connections between latent and manifest variables were computed. Model fit quality was assessed using various indices, including the root mean square of approximation (RMSEA), the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the standardized root mean square of residual (SRMR). The suggested threshold values for these indices are: CFI between 0.90 and 0.95; TLI between 0.90 and 0.95; RMSEA between 0.05 and 0.08; and SRMR at 0.08 (Meyers et al., 2016). A higher CFI, TLI, and lower RMSEA and SRMR values indicate a better model fit. Models’ goodness of fit was assessed using four indices (CFI, TLI, RMSEA, and SRMR).

After confirming the factorial structure through CFA, Structural Equation Modeling (SEM) was employed to examine the hypothesized model that the working environment’s latent factors incorporate burnout and the quality of life of HHAs. Following the approach suggested by Anderson and Gerbing (1988), a two-step process SEM was implied. First, a measurement model was utilized to explore the connections between the latent constructs and their corresponding variables. Standardized factor loadings were computed for each variable, and bivariate correlations were provided across the working environment and all other variables. Then, SEM was applied to assess the hypothesized mediation model, calculating standardized regression coefficients for all variable paths. Similar to the CFA for the working environment, the model’s goodness of fit was evaluated using several indices, including RMSEA, CFI, and TLI. The mediation effects were examined to identify whether burnout wholly or partially mediates the link between working environment and quality of life. CFA and the SEM were conducted using Amos version 26.

Results

Demographic statistics

The characteristics of the sample are shown in Table 1. Females comprised 97.3% of the sample, and the average age was 62.7. About 60.4% of the sample was high school graduates, and overall health status was healthy. Over half of the sample worked more than 35 hours weekly, and the average monthly income was $816.58 (U.S. dollars).

Table 1. Demographic characteristics (N = 786).

	Frequency (%) or Mean (SD)
Gender
Male	21(2.7)
Female	765(97.3)
Age	62.7(7.06)
Education
Less than a middle school graduate	189(24.0)
High school graduate	475(60.4)
College Graduate	66(8.4)
More than a university graduate	56(7.1)
Self-report health	4(0.7)
Weekly working hours
Less than 15 hours	112(14.2)
15 to 24 hours	143(14.4)
25 to 34 hours	104(13.2)
More than 35 hours	457(58.1)
Average Monthly income (U.S. dollars)	816.58(364.05)

EFA and CFA for the working environment of HHAs

Using the principal axis factor analysis, the Oblimin rotation method with Kaiser normalization, EFA was employed to identify the factorial structure among working environment domains. The KMO index, which ranges from 0 to 1, is considered adequate for factor analysis when it reaches 0.60 or higher. In this study, the KMO was 0.951, which indicated that the sample was adequate for performing factor analysis, and Bartlett’s Test of Sphericity was significant (χ2 = 25783.77; df = 703, p < .001), indicating a robust relationship among the variables, and the data were suitable to conduct an EFA.

Six factors were identified out of 38 item scales; 25 items on physical working environment consisted of 25 questions and 13 items on overall satisfaction with the working environment. The factor loadings of working environment domains onto six factors appear in Appendix Table 1. These six factors of the working environment accounted for 63.43% of the cumulative variance. According to domains in the clusters, the six factors were labeled as (1) sufficiency of space, (2) satisfaction with the working environment, (3) the physical condition of the house, (4) conditions of home appliances, (5) the relationship between care recipient/family members, and (6) air conditioning facilities.

Results from CFA indicated that 6 factors can be grouped with 3 latent variables based on the Environmental Comfort Model (Figure 2). To conduct model estimation, the regression weight of the first item of each latent variable was set to 1. For the Physical Comfort, two indicators loaded significantly, including the sufficiency of space (1.00) and the physical condition of the house (3.26). Two indicators loaded significantly for Functional Comfort, including the conditions of home appliances (1.00) and air conditioning facilities (8.74). For Psychological Comfort, two indicator variables loaded significantly, including satisfaction with the working environment (1.00) and satisfaction with the relationship between care recipient/family members (0.07). In Figure 3, standardized parameter estimates and correlations between latent variables are displayed. The model had a good model fit with χ2(6) = 38.46, p < .001; CFI = 0.977, RMSEA = 0.078, TLI = 0.942.

Figure 2. Analysis Conceptual Model.

Figure 3. Result of Confirmatory Factor Analysis (CFA).

Structural equation modeling of the hypothesized mediation model

In subsequent analyses, the structural model was tested via maximum likelihood estimation. The direct path coefficient from the predictor (working environment: psychological comfort) to the criterion (quality of life) in the absence of mediators was significant (β = 0.06, p < .05), and psychological comfort had a negative direct link with burnout (β = −0.21, p < .01). Regarding the direct links between burnout and quality of life, burnout was negatively associated with quality of life (β = −0.32, p < .001). We then ran an SEM to examine the mediation effect of burnout on the relationship between the working environment and quality of life. For the final model, all structural paths are shown in Figure 4. Estimations of the goodness of fit for the model indicated adequate values (CFI = 0.937; TLI = 0.816; RMSEA = 0.065). We used the bootstrap estimation procedure in AMOS 22.0 to test the significance of the mediating effect of burnout. The basic principle for the bootstrapping approach is the standard error estimates and confidence intervals (CIs) and is recommended for examining the indirect effects. It balances between controlling type 1 errors and ensuring high statistical power. The 95% confidence intervals of the indirect effects are [0.01, 0.06], which did not overlap with zero, further indicating that burnout mediates the impact of psychological comfort and quality of life (β = 0.64, p < .05), with a higher level of psychological comfort being associated with a lower level of burnout, and at the same time, a lower level burnout being associated with a higher level of the quality of life of HHAs (Table 2).

Table 2. Direct and indirect effects and 95% confidence intervals (CI) for the final model.

Model pathways	Standardized estimated effect	95% CI Lower bonds	95% CI Up bonds
Direct effect
Psychological Comfort -> Burnout	−0.21*	−0.02	−.01
Burnout -> Quality of life	−0.32*	2.75	1.83
Indirect effect
Psychological Comfort -> Burnout -> Quality of life	0.64*	0.01	0.06

Note: Control variables included were self-rated health, working hours, income, age, education, and gender.

*p < .05, **p < .01, ***p < .001

Figure 4. Final Structural Equation Modeling (SEM) Result of the hypothesized mediation model among working environment, burnout, and Quality of life.

Discussion

Focusing on the multiple aspects of HHAs’ working environment, this study examined the role of burnout in the relationship between the working environment and the quality of life of HHAs from Korea. Our study makes several significant contributions to the literature on the working environment, burnout, and the quality of life of HHAs.

First, based on the Environmental Comfort Theory, this research is the first to identify three aspects of the working environment from the six specific factors among HHAs: physical (sufficiency of space and physical condition of the house), functional (condition of home appliances and air conditioning facility) and psychological (satisfaction with the working environment and the relationship between the care recipient and families). Identifying the dimensions within the working environment of HHAs makes a meaningful contribution toward elucidating the concept of their working environment. While the physical and functional aspects of the HHAs’ working environment are widely recognized for enhancing the quality of life of care recipients (Carnemolla & Bridge, 2019; Soilemezi et al., 2019), this study extends the understanding of the psychological aspects of the HHA’s working environment which were related to a subjective perception of working environment and satisfaction with care recipients and families.

Second, we examined the empirical association of the working environment, burnout, and the quality of life of HHAs. Among the three dimensions underlying the working environment of HHAs, we found that psychological comfort (e.g., satisfaction with the relationship between recipients and families and satisfaction with the working environment) impacts the burnout of HHAs. We also found that psychological comfort directly impacts the quality of life of HHAs. Understanding how these multi-dimensional work environments influence the lives of HHAs can provide valuable insight regarding their potential implications for promoting improved care quality and continuity in the future. Considering that psychological comfort was the significant dimension in both the relationship with burnout and quality of life, future policies aimed at enhancing HHAs’ psychological comfort (e.g., quarterly satisfaction surveys and group training organized by local government) can be considered.

Third, as hypothesized, we found that burnout mediates the relationship between the working environment and the quality of life of HHAs. Among the underlying structure of the working environment, low psychological comfort was likely to be associated with a higher level of burnout and low quality of life of HHAs, respectively, consistent with previous research (Denton et al., 2002; Hanson et al., 2015; Harrad & Sulla, 2018; Kim, 2020; Cho et al., 2023). Specifically, among the three domains of the working environment for HHAs, physical comfort, and functional comfort may be considered as objective aspects of the working environment that are directly observable and measurable by HHAs. On the other hand, psychological comfort is a subjective aspect that depends on HHAs’ perceptions and satisfaction with the environment and their relationships with care recipients and families, regardless of the actual size of the space and available resources. This finding underscores the importance HHAs place on psychological comfort, as it significantly impacts their quality of life by reducing burnout experiences, which are crucial for job satisfaction and overall life satisfaction.

Creating a satisfying relationship between care recipients and HHAs is essential to reduce burnout, which affects a better quality of life among HHAs. Any possible threat of the workplace that prevents HHAs from being psychologically comfortable with care recipients needs to be addressed, such as potential aggressors of sexual harassment or violence from care recipients (Cho et al., 2023; Sherman et al., 2017), perception and bias where care recipients and families view HHAs not as professional healthcare providers but as house chore helpers, and unconditional client-oriented approach that lead HHAs to feel distressed from excessive service demands (Kim, 2012). To address these problems, governmental guidelines for the protection of HHAs should be established, and education should also be implemented to reinforce the understanding of the responsibilities of HHAs. In addition, our finding stresses the necessity to create a satisfying working environment for HHAs to reduce burnout, leading to a better quality of life among HHAs. Enhancing satisfaction with the physical environment involves modifying the house’s physical conditions and supporting HHAs to increase their satisfaction with the environment. For this purpose, once home modification is planned, home healthcare agencies should conduct periodic assessments of care recipients’ living environments along with participating HHAs in the assessment and considering HHAs as essential components which enable HHAs to perceive the living environment of care recipients as satisfactory working environments.

Given the job status of HHAs in Korea (Seok, 2020), efforts to improve their working environment and reduce burnout can be considered through training to develop practical communication skills and improve problem-solving skills, which might mitigate conflicts with recipients (Yoon et al., 2016; Faul et al., 2010). It will be crucial to regularly monitor the health status of HHAs through support at the organizational level, ensuring that their health does not deteriorate due to occupational factors. The support should include supporting medical examinations, vaccinations, sick leave, and alternative work arrangements per the condition of care recipients. Since HHAs are subject to injuries related to musculoskeletal disorders from handling patients (Markkanen et al., 2014; Zoeckler, 2018), if the recipients require high physical demand for HHAs, it should be considered the pair work system so that two HHAs can work with one high demanding recipient, such as recipient with aggression,obesity and even dementia. Further research should examine the difference between the work environment, burnout, and quality of life perceived by HHAs depending on the care recipients’ conditions. In sum, policy efforts to ensure appropriate compensation, updated training, and healthier working conditions are pivotal for enhancing the quality of healthcare service provided in recipients’ homes (Zoeckler, 2018).

This study has several limitations. First, since the data was collected during the COVID-19 era, we could not visit care recipients in-person and could not practically observe how care recipients’ living environments and daily lives look like due to concerns about the infection. Future research is anticipated, considering the type and structure of housing grounded in field observation studies. In addition, the primary contribution of the current study lies in empirically extracting the constituent concepts of the working environment of HHAs and examining their association with the quality of life through burnout of HHAs. In future research, it will be crucial to explore how these individual dimensions interconnect with each other, as suggested by the theory. Also, it is important for future research to continue to identify the empirical structure of the multi-dimensional working environment and its role in health and well-being among HHAs in different contexts. In particular, such future replication research should test the validity and reliability of HHA’s working environment structure. Top of FormBottom of FormLastly, as this is a cross-sectional study, it could not establish causality between variables. Future research should consider conducting longitudinal studies to identify how the influence of each dimension changes over time.

Conclusion

This study has illuminated the multifaceted substructures of the HHAs’ working environment, such as physical, functional, and psychological comfort. Also, this study has examined how these dimensions of the working environment are associated with the quality of life of HHAs and how burnout mediated the association. This study found that the working environment is associated with the quality of life of HHAs and burnout, and burnout mediates the relationship between the quality of life and burnout. The result is anticipated to provide the background for developing strategies to improve the working environment and quality of life for HHAs to enhance the quality of services provided to care recipients in need.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.

Appendix 1

Questions for the Working Environment of Home Health Aides

Table

Num.	Variables	Item	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5	Factor 6	Factor	Dimension
1	SS1	The care recipients’ homes have sufficient space in the bedroom	−.218	−.232	−.757	−.011	−.016	−.028	Sufficiency of Space	Physical Comfort
2	SS2	The care recipients’ homes have sufficient space in the kitchen	.239	.245	.849	.047	.039	.029
3	SS3	The care recipients’ homes have sufficient space in the bathroom	.259	.266	.825	.053	.033	.022
4	SS4	The care recipients’ homes have sufficient space in the living room	.274	.244	.832	.009	−.002	.107
5	SS5	The care recipients’ homes have sufficient space in the laundry room	.303	.234	.806	.038	.015	.087
6	SS6	The care recipients’ homes have sufficient space in the entrance	.335	.233	.787	.061	.001	.113
7	C1	The structural condition of care recipients’ homes (solid structure, fracture)	.778	.232	.217	.055	−.019	.024	Physical Condition of the house
8	C2	The waterproof condition of care recipients’ homes (humidity, leak)	.819	.192	.169	.067	.025	.080
9	C3	The heating and insulation condition of care recipients’ homes	.799	.181	.143	.089	.059	.116
10	C4	The ventilation condition of care recipients’ homes (available windows, air flow)	.767	.194	.197	.085	.046	.098
11	C5	The lighting condition of care recipients’ homes	.703	.196	.249	.105	−.021	.092
12	C6	The noise condition of care recipients’ homes (vehicle horn, noise between floors)	.625	.120	.169	−.005	.073	.125
13	C7	The safety from the fire of care recipients’ homes (fire prevention and evacuation facilities)	.788	.157	.190	−.007	.040	.100
14	C8	The security condition of care recipients’ homes (security from stranger intrusion)	.785	.191	.178	−.006	.007	.102
15	C9	The hygiene condition of care recipients’ homes (odor, bugs)	.803	.254	.140	.003	.037	.114
16	C10	The wallpaper condition of care recipients’ homes	.796	.272	.137	.049	−.032	.023
17	C11	The floor condition of care recipients’ homes	.809	.261	.154	.014	−.017	.010
18	C12	The electric wire condition of care recipients’ homes	.785	.244	.184	.072	.031	.026
19	D1	The condition of care recipients’ washing machine	−.003	−.040	−.033	−.503	−.101	.090	Condition of Home Appliances	Functional Comfort
20	D2	The condition of refrigerators in the care recipients’ homes	.016	.011	.021	.580	−.006	−.051
21	D3	The condition of vacuum cleaners in the care recipients’ homes	.183	.120	.131	.209	−.024	.256	N/A	N/A
22	D4	The condition of air conditioners in the care recipients’ homes	.152	.173	.079	.143	.027	.512	Air Conditioning Facility	Functional Comfort
23	D5	The condition of fans in the care recipients’ homes	.033	.025	.012	.485	−.047	.084	Condition of Home Appliances
24	D6	The condition of household heaters in the care recipients’ homes	.006	.082	−.008	.592	−.005	.164
25	D7	The condition of the hot water system in the care recipients’ homes	.094	.071	.032	.590	.029	.134
26	SA1	The satisfaction with the relationship between care recipients	.022	.359	.024	.055	.752	.050	Relationship between care recipient/family members	Psychological Comfort
27	SA2	The satisfaction with the relationship between care recipients’ family	.030	.388	.014	.021	.744	.048
28	SA3	The satisfaction with the space of care recipients’ room	.142	.740	.225	.015	.226	−.025	Satisfaction with the Working Environment
29	SA4	The satisfaction with the equipment of care recipients’ room (bed, layout)	.184	.734	.214	.057	.164	.006
30	SA5	The satisfaction with the space of the toilet/bathroom	.218	.797	.260	.111	.061	.008
31	SA6	Satisfaction with the equipment of the toilet/bathroom (shower booth, toilet seat)	.279	.795	.224	.116	.046	.067
32	SA7	The satisfaction with the space of the kitchen/dining room	.238	.816	.228	.082	.095	.064
33	SA8	The satisfaction with the equipment of the kitchen/dining room	.305	.796	.227	.064	.111	.139
34	SA9	The satisfaction with the drain system in care recipients’ room	.309	.750	.194	.058	.114	.171
35	SA10	The satisfaction with the usage of the heating/insulation system in care recipients’ room	.351	.617	.118	.082	.177	.265
36	SA11	The satisfaction with the usage of the air conditioning system in care recipients’ room	.285	.501	.109	.089	.188	.567
37	SA12	The satisfaction with the space for moving with care recipients	.320	.613	.186	.042	.011	.227
38	SA13	The satisfaction with the equipment for moving with care recipients	.264	.532	.083	.027	.131	.148