Therapeutic landscapes, networks, and health and wellbeing during the COVID-19 pandemic: A mixed-methods study among female domestic workers

Abstract

The COVID-19 pandemic has had profound impacts on access to and use of therapeutic landscapes and networks, especially for people who are vulnerable due to economic, social, and work-related disadvantage. For one such vulnerable population, Indonesian female domestic workers (FDWs) in Hong Kong, this study employed a mixed methods approach to examine the associations between perceptions of therapeutic landscapes (TLs), therapeutic networks (TNs), subjective wellbeing, and self-rated health during the COVID-19 pandemic. Data from an online survey were analyzed via structural equation modeling (SEM) and confirmatory factor analysis (CFA) to investigate the direct and indirect associations between TLs, TNs, and health and wellbeing. The findings demonstrate little or no association among FDWs’ perceptions of TLs and TNs and FDWs’ self-rated health and subjective wellbeing, except for a negative total association between TL and subjective wellbeing. Using insights gleaned from thematic analysis of in-depth interviews with FDWs, we suggest that these unexpected findings are mainly due to restricted access to public places, reduced social gatherings, and the fact that employers rarely granted days off during the lockdown. Although processes at the employer and municipal scales limited FDWs’ access to therapeutic places, increased use of digital communications and spaces provided an important source of social and emotional support during the pandemic.

1. Introduction

The COVID-19 pandemic has significantly changed some people’s access to and use of therapeutic places and social interactions that are crucial for maintaining health and wellbeing. An expanding body of literature shows that in some places, public spaces such as parks and other green infrastructure have had a key role in supporting physical and mental wellbeing during the pandemic (Heckert and Bristowe, 2021; Bustamante et al., 2022; Guzmán et al., 2022), while social interactions and support, based in residential neighborhoods, social media, and online, have increased in importance (Foley et al., 2022; Lupton and Lewis, 2022). However, these impacts are likely to vary widely across population groups: groups that are marginalized by low income, social isolation, and/or challenging work conditions may experience reduced access to therapeutic landscapes and social networks that complicate their ties with health and wellbeing. Using a mixed methods approach, this research focuses on one such vulnerable population, Indonesian female domestic workers (FDWs) in Hong Kong, and it investigates FDWs’ experiences of therapeutic landscapes and networks during the pandemic.

FDWs are susceptible to stress, loneliness, and other poor mental health outcomes due to demanding work tasks and limited social interactions outside their employers’ homes (Hall et al., 2019; Chung and Mak, 2020). Previous studies have reported that FDWs rely on community and religious activities, and social networks and engagement with their FDW counterparts as coping strategies (Dutta et al., 2018; van Bortel et al., 2019; Chung and Mak, 2020). By visiting their “favorite places” (Korpela and Hartig, 1996), engaging with friends, and participating in cultural and social activities, FDWs can develop therapeutic lanscape and network encounters outside their employers’ homes that support and promote healing from tiring and stressful work days (Dutta et al., 2018; van Bortel et al., 2019). Before the COVID-19 pandemic, FDWs regularly engaged with social networks and visited various landscapes to sustain their physical and mental health and wellbeing (Chu et al., 2016; Chung and Mak, 2020). During the pandemic, however, restricted access to public places (e.g., parks, gardens, beaches, promenades, recreation centers/areas, libraries, religious sites, learning centers, community support groups, shops, and markets) and mobility restrictions and social distancing requirements, may have limited FDWs’ access to therapeutic landscape encounters that are essential for their health and wellbeing.

The concepts of therapeutic landscape (TL) (Gesler, 1992) and therapeutic network (TN) (Smyth, 2005) have been widely applied to study how vulnerable populations, including immigrants, experience landscapes and networks as therapeutic (Chakrabarti, 2010; Agyekum and Newbold, 2016; Tomalin et al., 2019). However, the concept of TL has not been applied to study FDWs, a group that faces highly restrictive time-space constraints and mental and emotional stresses due to demanding work responsibilities. Furthermore, within the subfield of health geography, previous explorations of how TLs and TNs affect health and wellbeing have mainly employed qualitative approaches (Milligan et al., 2004; Chakrabarti, 2010; Finlay et al., 2015; Agyekum and Newbold, 2016; Ireland et al., 2019; Tomalin et al., 2019). We argue that a mixed-methods study using statistical analysis coupled with qualitative data from interviews may enhance our understanding of how TL and TN encounters affect health and wellbeing among FDWs and how these associations may be influenced by the pandemic. In general, quantitative methods complement qualitative approaches by investigating associations within larger populations that cannot typically be studied qualitatively. At the same time, qualitative interview data deepen our knowledge of FDWs’ personal experiences with accessing TLs and TNs during the pandemic.

This study has two main objectives: (1) to investigate the direct and indirect effects of FDWs’ perceptions of TLs and TNs on health and wellbeing; (2) to explore whether the COVID-19 pandemic has limited access to public places and social networks and the implications for FDWs’ perspectives on TL and TN encounters. We focus on Indonesian FDWs working in Hong Kong, a major destination for FDWs and a place that enacted strong pandemic restrictions. We employed confirmatory factor analysis (CFA) to identify constructs representing TL,TN, health, and wellbeing from survey responses, and then used structural equation modeling (SEM) to examine the associations between these constructs and self-rated health and subjective wellbeing during the COVID-19 pandemic. Using qualitative data from semi-structured interviews conducted via Zoom, we then explore how the COVID-19 pandemic affected FDWs’ access to public places and social networks; how the women responded; and how their work and personal lives were changed.

Overall, this research has three main contributions: (1) it explores new applications of TLs and TNs to domestically employed women living a foreign country; (2) it uses innovative methods in a study of TLs and TNs by integrating advanced statistical modeling analyses with detailed qualitative data from interviews; (3) it expands current research on TLs and TNs associated with health and wellbeing in response to the global pandemic for a vulnerable population.

1.1. Female domestic workers’ health and wellbeing

An emerging body of research has analyzed the physical and mental health and wellbeing of FDWs. Studies have documented that financial and food insecurity, employment-related issues, such as the uncertainty of contract renewal, working conditions, and relationships with employers cause stress and poor mental health outcomes among FDWs (Dutta et al., 2018; Hall et al., 2019; Chung and Mak, 2020). In addition, FDWs experience demanding work responsibilities, unrealistic expectations, and other pressures that negatively impact their health and wellbeing (van der Ham et al., 2015; van Bortel et al., 2019; Chung and Mak, 2020).

In most Asian countries, FDWs live in their employers’ homes, and in Hong Kong, many FDWs do not have private bedrooms (Chung and Mak, 2020). Many sleep on folding beds in small spaces between the kitchen and living room (Jensen, 2014) or in a grandmother’s or child’s bedroom. FDWs also report that domestic employment prevents them from having enough hours to sleep, rest, and eat (Hall et al., 2019; van der Ham et al., 2015; van Bortel et al., 2019). Thus, living and working with and for their employers can make it difficult for FDWs to maintain their physical and mental health (van der Ham et al., 2015; Hall et al., 2019; Chung and Mak, 2020).

Furthermore, the gendered nature of domestic work impacts FDWs encounters with TL and TN. Most FDWs in Asia are women living in their employers’ homes where gender relations constrain their access to TL. In Singapore, for instance, research has found that female employers, their mothers, or mothers-in-law often control FDWs’ day-to-day work including the timing and locations of tasks (Yeoh and Huang, 2010). FDWs lack power to negotiate with their employers (Bélanger and Silvey, 2019). FDWs also often have gendered responsibilities in their home country, serving as breadwinners for their families and sending money back home for their husbands, children, parents, and other family members (Dewi, 2011). Long separations from families can result in feelings of guilt, loneliness, and depression (van der Ham et al., 2015). During the pandemic, economic uncertainties in host countries affected FDWs’ mental health, especially from the fear of losing their jobs (Lui et al., 2021).

FDWs’ health and well-being are also influenced by the length of living in foreign countries (Chou, 2009). Those who have been working and living in host countries longer know many people, have established social connections, and have visited various places. They are well-situated to actively participate in and lead social and community activities outside their employers’ homes. In contrast, those who are new to host countries are still figuring out their lives and developing social networks. At the same time, established FDWs are typically older, and their physical ability may deteriorate affecting overall health, mobility, and access to public places. This lack of mobility can impede social interactions outside their employers’ homes which is critically important for maintaining mental health and wellbeing (Chung and Mak, 2020).

To address the everyday challenges of living in foreign countries, long work hours, and demanding jobs, FDWs adopt psychological, social, and religious coping strategies. FDWs engage in social activities including meeting with other FDWs and attending religious services (van der Ham et al., 2015; Dutta et al., 2018). Many of these activities require free time so that the FDW can travel outside the employer’s home. In Hong Kong, which requires that employers provide FDWs with a mandated rest day after seven days of work, Indonesian and Filipino FDWs use the rest day to socialize with their FDW friends in public spaces (Ching, 2006; Chu et al., 2016). Gathering with other FDWs provides opportunities to receive emotional and social support, which helps FDWs to maintain their mental health (van Bortel et al., 2019). Thus, we argue that these places, and the social networks associated with them, serve as therapeutic landscape and network encounters that support FDWs social and physical health and wellbeing.

1.2. Therapeutic landscapes and therapeutic networks

Therapeutic landscapes (TL) and therapeutic networks (TN) are core concepts in health and medical geography. Gesler (1992) proposed therapeutic landscapes as landscapes that influence the healing process. In early explorations of TLs, researchers’ attention focused on physical sites viewed as ‘healing places’ (Williams, 2010). These included both natural and built environments promoting health (Conradson, 2005). In turn, the concept has been expanded beyond Gesler's (1992) first intentions and has been applied to various types of places, including sites in the built environment, and to different population groups such as immigrants living in foreign countries (Chakrabarti, 2010; Agyekum and Newbold, 2016).

Another key conceptual development was the introduction of the therapeutic network concept by Smyth (2005). Smyth (2005) defined therapeutic networks as the presence of care and support provided by family, friends, and therapists. Further, Chakrabarti (2010) argued that the construction of therapeutic networks requires a considerable amount of time and interactions among individuals. The networks grow over time as people meet, socialize, and interweave their relationships and trust. In turn, social networks play an important role in maintaining people’s health and wellbeing (Classen, 2004).

The concepts of therapeutic landscapes and therapeutic networks have long been interconnected. Gesler's (1992) seminal work discussed how social interactions and networks contributed to therapeutic place-based experiences. More recently, Völker and Kistemann (2013) and Bell et al. (2015) identified social experience --“opportunities for a conversation; engaging in convivial social ambiance without feelings of crowding; comfortable companionship and a shared sense of wellbeing” (Bell et al., 2015, p. 65) as a core dimension of TL. While acknowledging the close interconnections between TL and TN, in the quantitative modeling for this paper, we separate the two into distinct constructs. Therapeutic networks emphasize connectivity and support among people (Smyth, 2005; Chakrabarti, 2010), whereas therapeutic landscapes emphasize the relationships of individuals with places/landscapes or person-place encounters (Conradson, 2005). People can have therapeutic landscape experiences without interacting with others, and therapeutic social interactions do not necessarily depend on the therapeutic qualities of places. Thus, the two concepts overlap and are intertwined, but they are also distinct.

Investigating the effects of TLs and TNs on FDWs’ health and wellbeing is complex. By definition, TLs and TNs are beneficial for wellbeing, but the associations are likely to vary over time as peoples’ abilities to engage with therapeutic places and networks change according to the realities and constraints of daily life. Also, individual characteristics like age and length of residency influence knowledge of and access to places and social interactions that are beneficial for wellbeing. Both qualitative and quantitative approaches are essential for understanding these complex relationships.

As discussed earlier, researchers investigating TLs and TNs have relied heavily on qualitative methods, with a few exceptions. A recent study by Zhang et al. (2021) was among the first to adopt a quantitative approach to evaluate TLs. They examined the effect of health tourism destinations on older adult migrants’ subjective health perception by employing SEM and path analyses. Although Zhang et al. (2021) did not find that physical landscapes directly affect health perception, they documented the indirect effect of health perception through migrants’ restorative experiences. To study FDWs in Hong Kong during the pandemic, we adopt a similar approach in examining the direct and indirect effects of TL on self-rated health. We are particularly intrigued to test TNs and wellbeing as mediating factors that shape TLs’ influences on self-rated health.

1.3. The COVID-19 pandemic and female domestic workers

The COVID-19 pandemic disproportionately impacted FDWs’ lives by restricting access to public spaces and social gatherings (Yeung et al., 2020; 2022; Lui et al., 2021). Before the pandemic, socializing, and attending social and community activities in public places on rest days benefited FDWs by reducing work-related stressors and providing positive social experiences (Ching, 2006; Chu et al., 2016; Chung and Mak, 2020). However, in practice, implementation of rest day has always varied. For instance, many FDWs are not given rest days on the weekend. The rest day decision mainly depends on agreement between the employer and domestic workers mediated by the placement agency (Yeoh and Huang, 1998).

During the data collection for this project, Hong Kong’s COVID-19 restrictions on social distancing and gatherings in public places changed, greatly affecting rest days for FDWs. For instance, in September 2020, Hong Kong’s social distancing measure was relaxed, while in October 2020, public gatherings were restricted to up to four people. By late November, the maximum gathering size was reduced to two people (The Government of the Hong Kong SAR, 2021). For FDWs, these policy changes might affect TL and TN experiences by limiting the number of people they could interact with and types of places they could visit.

Besides limiting access to public places, the COVID-19 pandemic exacerbated FDWs’ lives with changes in work expectations (Yeung et al., 2020; Lui et al., 2021). FDWs worked more during the pandemic as many employers required them to clean the house frequently and maintain cleanliness for the household to prevent Coronavirus spread (Yeung et al., 2022). In addition, while FDWs’ work expectations increased, they also experienced anxiety and stress about COVID-19 in Hong Kong and in their home countries (Lui et al., 2021).

The COVID-19 pandemic also upended the mandated rest day for FDWs, as many employers required FDWs to stay at home, even during the rest day (Lui et al., 2021; Oktavianus and Lin, 2021). Concerned about losing their jobs, FDWs became more powerless. When employers asked them to stay at home and did not provide a rest day, FDWs could not argue. Thus, most FDWs did not have a rest during the pandemic, which may have affected their access to and use of therapeutic landscapes and networks.

2. Data and methods

2.1. Data collection and research participants

To analyze the relationships between FDWs’ perceptions of TL and TN encounters, and self-rated health and subjective wellbeing during the COVID-19 pandemic, we administered an online survey that includes a mix of Likert-scale and categorical questions and open-ended responses. Written in Bahasa Indonesia, the questionnaire survey was administered online to a sample Indonesian FDWs in Hong Kong. Data collection was from August to December 2020. Within the same time frame, we also conducted semi-structured interviews. Our mixed methods integration at the design level followed the convergent approach (Fetters et al., 2013) as we collected quantitative and qualitative data at the same time, but separately. As discussed earlier, during this time, Hong Kong’s COVID-19 policy changed, especially the rule for social gatherings within public places. Prior to data collection, we obtained Institutional Review Board (IRB) #21059 approval from the University of Illinois Urbana-Champaign’s Office for the Protection of Research Subjects.

The survey participants were Indonesian FDWs; aged 18 and older; who had been working and living in Hong Kong for at least six months. To collect data and recruit participants, we collaborated with two nonprofit organizations (1) Dompet Dhuafa Hong Hong (DDHK), an organization that provides social, religious, and educational activities for Indonesian FDWs in Hong Kong; (2) Peduli Sehat Hong Kong (PSHK), an FDW-led organization that promotes breast cancer awareness among FDWs.

The online survey was delivered through DDHK’s social media platforms such as their Facebook fan page and PSHK’s WhatsApp groups. FDWs also voluntarily shared the survey link through their religious chat groups such as Majelis 1 groups for Muslim FDWs and fellowship and church groups for Christians. In addition, the survey URL was distributed through snowball sampling among FDWs and through migrant union groups. Since the survey and recruitment materials were in Bahasa Indonesia, the national language of Indonesia, they were accessible to a large group of FDWs. Fig. 1 displays the study area and the number of research participants (N = 172) who took the online survey in each district.

Fig. 1.

Number of Indonesian FDWs who took online survey in each district (N = 172).

2.2. Quantitative measures

The survey questions (Table 1 ) assessed FDWs’ health and subjective wellbeing and their use and experiences of therapeutic landscapes and networks. Each group of survey items is discussed in the following sections.

Table 1.

Items of self-rated health conditions, subjective wellbeing, and perceptions on therapeutic landscapes and networks.

Items	Description or question on the survey	Likert scale and categorical order
Self-rated health (HLT)
HLT1	How would you (self) rate your current health status?	1 (Poor) to 5 (Excellent)
HLT2	How would you describe your health status this past month?	1 (Poor) to 5 (Excellent)
HLT3	How would you describe your health status in this past year?	1 (Poor) to 5 (Excellent)
Subjective wellbeing (WLB)
WLB1	Overall, how satisfied are you with your life currently?	1 (Not at all satisfied) to 5 (Completely satisfied)
WLB2	How happy are you in general?	1 (Not at all happy) to 5 (Completely happy)
ANX	How anxious are you in general?	1 (Not at all anxious) to 5 (Completely anxious)
Perceptions of therapeutic landscapes (TL)
TL1	Do you have any favorite place(s) in Hong Kong? Favorite place(s) in this context is a place(s) that makes people feel good about their lives and makes them happy when they visit or consider as their “healing places.”	1 (Yes) and 0 (No)
TL2	How often do you visit your favorite place(s)?	1 (Never) to 5 (Always/Every week)
Perceptions of therapeutic networks (TN)
TN1	Have you joined any groups or community organizations with other domestic workers?	1 (Yes) and 0 (No)
TN2	How often do you attend a social gathering with other Indonesian domestic workers?	1 (Never) to 5 (Always/Every week)
For TN3 question, how much do you agree or disagree with these following statements?
TN3	I feel comfortable talking about any problems with my groups	1 (Strongly disagree) to 5 (Strongly agree)

2.2.1. Self-rated health

We designed survey questions for self-rated health based on the Current Health Status questions on the National Health and Nutrition Examination Survey, 2017–2018 questionnaire instrument (CDC, 2020). We asked FDWs to rate their health status for three different durations: (1) current condition; (2) the last month; and (3) within a year. The time frame for all self-rated health questions was during the COVID-19 pandemic.

2.2.2. Subjective wellbeing

To conceptualize subjective wellbeing questions, we referred to guidelines from the Panel on Measuring Subjective Wellbeing in a Policy-Relevant Framework (Stone and Mackie, 2013). We modified subjective wellbeing questions to adapt to the circumstances of Indonesian FDW in Hong Kong, including questions related to life satisfaction, happiness, and feeling anxious.

2.2.3. Perceptions of therapeutic landscapes

We developed questions associated with perceptions of therapeutic landscapes based on Gesler (1992). One question asks about the presence of TL (“favorite places”) in FDWs’ everyday lives. Following Korpela and Hartig (1996) and Korpela et al. (2002), we defined TL by asking about “favorite places.” In Bahasa Indonesia, we asked about “tempat yang Anda sukai dan menyenangkan untuk Anda,” a term whose closest English translation is “favorite places.” In the survey form, we also added a short definition as shown in Table 1. We acknowledge that some favorite places such as bars or gambling sites actually may not be beneficial for a person’s wellbeing. However, these kinds of places were not mentioned by Indonesian FDWs in the survey or interviews; rather, they described places like parks and religious sites that have been widely discussed in past research on TLs. A second question asks about the frequency of visiting those favorite places which is important for therapeutic experiences (Gesler and Kearns, 2002).

2.2.4. Perceptions of therapeutic networks

We created questions on perceptions of therapeutic networks based on Smyth's (2005) conceptualization including questions about FDWs’ experience of joining social and community groups, frequency of attending these groups, and willingness to share personal issues with their social groups. The questions also reflect literature emphasizing how FDWs seek social support, are involved in community and group activities, and connect with other FDWs (see Dutta et al., 2018; van Bortel et al., 2019).

2.2.5. Demographic and employment characteristics

The questionnaire also asked about the demographics of research participants, such as age, marital status, and length of working and living in Hong Kong. Age is relevant because as FDWs get older, they may have more health problems. Marital status is an important variable because married FDWs who moved to Hong Kong often left their family behind. Separation from family is challenging and often makes FDWs feel guilty about leaving their children and husband in Indonesia which might affect their overall wellbeing. Finally, the length of working and living in Hong Kong is crucial because people living in the area longer are likely to have built familiarity and connections with places and with other FDWs that positively affect health and wellbeing.

2.3. Semi-structured interviews

To gain in-depth understanding of FDWs’ perceptions of TL and TN encounters and their overall well-being, semi-structured interviews were conducted via Zoom with a subset of research participants (n = 31) who responded to the online survey. FDWs participated in the interviews from a time and place that they chose. Many interviews took place on the FDW’s rest day, and participants joined the interview while at a public place like a park. Some FDWs attended the interview at the mosque and a few participated from the employers’ homes, during work days in the evening when their employers slept.

Each virtual interview was about an hour long. The interviews were conducted by the first author in Bahasa Indonesia, the national language of Indonesian FDWs and of the first author who is female and Indonesian. The interviews explored FDWs’ experiences and challenges in accessing public places and maintaining social networks during the COVID-19 pandemic. In addition, questions were included about the impacts of the pandemic on FDWs’ everyday lives and employment in Hong Kong. Interview questions are shown in Table 2 .

Table 2.

Questions related to therapeutic landscapes and networks asked during the interviews.

Questions related to therapeutic landscapes:

1. Do you have any “favorite place(s)” in Hong Kong? (For example, these would be places that make you feel comfortable and safe, and where you feel happy when you visit these places) ⁃Why do you like this place? Why is this place special to you?

2. What are the descriptive characteristics of your favorite place(s)? For example, is there a lot of greenery? Is there water? Note: [augmented with photograph] feel free if you want to show/share the photo of your favorite places.

3. How do you feel when you visit your favorite place? Does the place promote a different feeling? [Follow-up questions related to the COVID-19 pandemic] ⁃Tell me your feelings when you visit those places during the COVID-19 pandemic? Does COVID-19 affect your engagement with places?

4. How long have you been visiting your favorite place(s)? How frequently do you visit the/ose place(s)? [Follow-up questions related to the COVID-19 pandemic] ⁃How does the COVID-19 pandemic affect your access to those places? Tell me about your visits during the pandemic.

5. Do you usually visit your favorite place(s) on your rest day? [Follow-up questions related to the COVID-19 pandemic] ⁃How about during the COVID-19 pandemic, do you still visit those places on the rest day?

Questions related to therapeutic networks:

1. Do you usually socialize with other Indonesian female domestic workers (FDWs) in Hong Kong? [Follow-up questions related to the COVID-19 pandemic] ⁃How does the COVID-19 pandemic affect your social interactions with other FDWs and people in Hong Kong and your living/working in Hong Kong in general?

2. Do you participate in or attend any social groups or community programs/events in Hong Kong? [Follow-up questions related to the COVID-19 pandemic] ⁃Do you still participate in social events during the COVID-19 pandemic? How does the pandemic affect your social activities?

3. What are the social groups or community programs/events that you usually participate in? Can you provide the name of the social groups or community programs/events? [Follow-up questions related to the COVID-19 pandemic]

4. What activities do you usually do when you are participating in social groups or community programs/events? [Follow-up questions related to the COVID-19 pandemic]

2.4. Data analysis: mixed methods approach

We employed a mixed methods approach (Creswell et al., 2006) to investigate FDWs’ access to therapeutic landscapes and networks during the COVID-19 pandemic. This method essentially integrates quantitative data, which includes statistical analysis, with qualitative data gathered from personal interviews (Creswell, 2021). We began by using SEM to analyze quantitative data from the online survey (n = 172). Further, we applied qualitative data analysis, specifically thematic coding, to uncover FDWs’ perceptions and experiences of TL and TN during the pandemic. Thereafter, at the interpretation and reporting level, we integrated the qualitative and quantitative results via “integrating through narrative, contiguous approach” (Fetters et al., 2013). In this paper, we first report the quantitative findings, then discuss the qualitative findings in relation both to the quantitative results and to FDWs’ perspectives on access to experiences of TL and TN during the pandemic.

2.4.1. Statistical analysis

We employed structural equation modeling with MPlus version 8.7 (Muthén and Muthén, 1998–2017) to assess the associations between therapeutic landscapes and networks, subjective wellbeing, and self-rated health. The statistical analysis consisted of a two-step process to first assess the hypothesized measurement models via CFA and second test the full SEM (Fig. 2 ). The model includes four latent variables: self-rated health (HLT), subjective wellbeing (WLB), perceptions of therapeutic landscapes (TL), and perceptions of therapeutic networks (TN). These four variables were not directly observed, but were treated as latent constructs, and were measured using multiple items (Fig. 2). In the first step we conducted CFA to evaluate the model fit of these four latent variables by estimating several CFA models to achieve an acceptable model fit without necessary modifications.

Fig. 2.

Conceptual model of the study.

Second, to model the direct and indirect associations between latent and observed variables and self-rated health, we used SEM. In the full SEM, we adjusted for the participants’ demographics (age, marital status, and length of working and living in Hong Kong). To evaluate the associations between therapeutic landscapes and self-rated health, we developed direct and indirect pathways: (1) the direct pathway from therapeutic landscapes to self-rated health (TL → HLT); (2) the indirect pathway from therapeutic landscapes to self-rated health via therapeutic networks (TL→ TN → HLT); (3) the indirect pathway from therapeutic landscapes to self-rated health via subjective wellbeing (TL → WLB → HLT); (4) the indirect pathway from therapeutic landscapes to self-rated health via therapeutic networks and subjective wellbeing (TL→ TN→ WLB → HLT). The estimates of direct and indirect effects and their confidence interval were bootstrapped with 20,000 replications.

We used several measures to evaluate the model fit. The chi-squared (χ²) test records the overall model fit, with a small value and a non-significant p-value of χ², indicating that the model fit is acceptable. The comparative fit index (CFI) measures the distance between the hypothesized and the null models. A CFI value greater than 0.95 indicates a good model fit (or appropriate model) (Hu and Bentler, 1999). The root mean square error of approximation (RMSEA) indicates how good the hypothesized model is compared with the population model. A value less than 0.06 indicates an acceptable model fit.

2.4.2. Qualitative data analysis

We transcribed the 31 interview recordings and applied thematic analysis (Braun and Clarke, 2006) to understand FDWs’ access to public places and engagement with social networks during the COVID-19 pandemic. We also explored FDWs’ challenges in maintaining physical, mental health, and wellbeing during the pandemic. We implemented inductive coding to determine common themes in the interview transcriptions. Finally, we incorporated FDWs’ perspectives on reduced and restricted access to their TLs and TNs. The thematic analysis followed six steps (get familiar with our data; generate initial codes; search for themes; review themes; define and name themes; and produce the analysis and write-up the results) as proposed by Braun and Clarke (2006).

3. Results

3.1. Participant demographics and general health & wellbeing profile

Table 3 summarizes the sample FDWs’ social, demographic, and work-related characteristics. The median age of survey respondents was 40, the youngest respondent was 25, and the oldest was 54, with approximately half (49.41%) aged 36–45 years. Very few participants were older than 50. Most survey respondents had worked and lived in Hong Kong for more than two years, and the median was eight years, with more than 16% FDWs working for 15 years or more, FDWs in the first contract cycle (<2 years) comprised only a small percentage (6%) of the sample. Nearly 60% FDWs were married, and the remainder were approximately equally split among widowed, divorced, and single. Demographic characteristics for the subset of respondents who participated in in-depth interviews are also presented in Table 3. The interview participants’ characteristics closely follow those of the survey participants, except that no interviewees were older than 50, and a slightly higher percentage (70%) were married.

Table 3.

Demographic characteristics of Indonesian FDWs in Hong Kong.

Demographic characteristics	Survey responses (N = 172)	Interview participants (N = 31)
	Median (Min; Max) or Percenta	Median (Min; Max) or Percentb
Age	40 (25; 54)	40 (25; 49)
25–30	13.95%	19.35%
31–35	13.37%	9.68%
36–40	22.67%	25.81%
41–45	26.74%	25.81%
46–50	18.86%	19.35%
>50	1.74%	N/A
Prefer not to answer	4.65%	N/A
Length of time working in HK	8 (0.5; 30)	8 (0.5; 22)
<2 years	5.81%	9.68%
2–5 years	27.91%	32.26%
6–10 years	25.58%	12.90%
11–15 years	20.35%	16.13%
>15 years	16.28%	29.03%
Prefer not to answer	4.07%	N/A
Marital status
Single	12.21%	12.90%
Married	59.88%	67.74%
Widowed	15.12%	16.13%
Divorced	9.88%	3.23
Prefer not to answer	2.91%	N/A

N/A = Not Available.

^aPercent was relative to the total number of participants in online survey; the denominator was 172.

^bPercent was relative to the total number of participants in the interview; the denominator was 31. All 31 interview participants were sub-sample of the online survey.

Table 4 presents the responses to self-rated health and subjective wellbeing questions among FDWs. Overall, despite challenging work conditions, many FDWs in our sample reported relatively good self-rated health. More than 50% of respondents rated their health as “good,” both for current health conditions and health status in the past year. More than 70 percent described their health status for the past month as “good” or “very good.” Only a few FDWs rated their health condition as “poor” or preferred not to report it. With respect to life satisfaction, more than 60% were moderately satisfied with their life, and 22.7% reported being very satisfied. Their general happiness was also high, with almost 70% describing themselves as moderately happy and very happy. None of the FDWs reported not being happy at all and completely anxious. Most FDWs felt slightly anxious (64.53%), and an additional 22.7% stated that they were not anxious at all.

Table 4.

Self-rated health and subjective wellbeing among FDWs (N = 172).

Health and wellbeing status	Percent (%)
Self-rate health	Excellent	Very good	Good	Fair	Poor	Not reported
Current health condition	6.98%	26.74%	51.74%	13.37%	0.00%	1.16%
Health status in the past month	4.07%	27.33%	44.74%	19.19%	2.91%	1.74%
Health status in the past year	5.23%	19.77%	50.58%	20.93%	1.16%	2.33%
Subjective wellbeing
Overall life satisfaction	Completely satisfied	Very satisfied	Moderately satisfied	Slightly satisfied	Not at all satisfied	Not reported
	8.72%	22.67%	61.63%	5.81%	0.58%	0.58%
General feeling of happiness	Completely happy	Very happy	Moderately happy	Slightly happy	Not at all happy	Not reported
	6.40%	22.67%	66.86%	4.07%	0.00%	0.00%
General feeling of anxiety	Completely anxious	Very anxious	Moderately anxious	Slightly anxious	Not at all anxious	Not reported
	0.00%	1.74%	9.88%	64.53%	22.67%	1.16%

In addition to overall health and wellbeing, FDWs reported common illnesses they experienced in the past year (Table 5 ). Only a minority of respondents reported any illnesses. The most common illnesses FDWs experienced were dizziness, including headache and migraine, cough, and cold. Respondents highlighted that coughs and colds were mainly due to changing weather in Hong Kong. Other types of illnesses (Table 5) were only reported by a few participants, and only one participant reported a serious disease -- kidney disease.

Table 5.

Common illnesses experienced by FDWs in the past year (N = 172).

Type of illnesses	Number of FDWs who reported each illnessa
Dizziness including headache and migraine	17
Coughs	12
Colds	11
Menstrual cramps	6
Flu	5
Menorrhagia (heavy menstrual bleeding), gastroesophageal reflux disease (GERD), and toothache	4
Fatigue, nausea, and leg pain	3
Allergy, rheumatic, hypotension, and stomachache	2
Vertigo, gallbladder disease, kidney disease, skin rashes, lymphedema, sprained ankle, hypertension, tiredness, sore throat, oral thrush, back pain, and sinusitis	1

^aSome FDWs reported more than one type of illness, and some FDWs did not report any illnesses. The number reflects number of FDWs who reported each type of illness.

3.2. Confirmatory factor analysis (CFA)

Table 6 presents the standardized parameter estimates (factor loadings) and the R-squared values explaining the correlations between the observed and latent variables. The full model consists of four latent variables (HLT, WLB, TL, and TN) that represent the observed variables within each construct. Overall factor loadings for all observed variables are high (>0.30) except in the case of “general feeling of anxiety,” which has a small, negative loading. The negative value is expected, because this variable is worded negatively. All standardized estimates are statistically significant, and the correlation between the observed and latent variables is high, indicating that the observed variables greatly represent the latent variables. The CFA full model has a good fit with χ² = 45.892, df = 38, p-value = 0.178; RMSEA = 0.035 (90% CI [0.000, 0.067], p = 0.752); CFI = 0.965; SRMR = 0.061. Table 6 presents the correlation matrix among the latent variables measured in CFA models. All correlations are low (<0.5), indicating little collinearity among the latent variables constructed.

Table 6.

Standardized parameter estimates (factor loadings) and R-squared for observed and latent variables.

Variable	Standardized estimate	R-squared
Self-rated health (HLT)
Current health status	0.935***	0.875
Health status in the past month	0.816***	0.666
Health status in the past year	0.844***	0.712
Subjective wellbeing (WLB)
Overall life satisfaction	0.767***	0.589
General feeling of happiness	0.702***	0.493
General feeling of anxiety	−0.288***	0.083
Perceptions of therapeutic landscapes (TL)
The presence of therapeutic landscapes	0.451**	0.203
The frequency of visiting therapeutic landscapes	0.798**	0.638
Perceptions of therapeutic networks (TN)
Experience of joining social & community groups	0.809***	0.655
Frequency of attending social & community gatherings	0.523***	0.274
Willingness to share personal issues with the social & community groups	0.374***	0.140

***p < 0.001; **p < 0.01; *p < 0.05; negative standardized estimate is for the negative wording on observed variable.

3.3. Structural equation model (SEM)

The TL, TN, and WLB latent variables from the CFA models and the participants’ demographics were used to predict self-rated health (HLT) in the full structural model. The full SEM has a good fit with χ² = 90.761, df = 68, p-value = 0.034; RMSEA = 0.046 (90% CI [0.013, 0.069], p = 0.585); CFI = 0.907; SRMR = 0.199. Table 7 presents a full structural model evaluating the relationships between self-rated health with therapeutic landscapes and networks, subjective wellbeing, and demographic characteristics. We found therapeutic landscapes has positive and significant associations with therapeutic networks (B = 0.501, p = 0.018). Self-rated health and subjective wellbeing also have positive and significant associations (B = 0.434, p = 0.011). But therapeutic landscapes were negatively and not significantly associated with self-rated health (B = −0.206, p = 0.501) and wellbeing (B = −0.052, p = 0.863). Also, the associations between therapeutic networks and subjective wellbeing were negative and not significant (B = −0.291, p = 0.229). None of the demographic characteristics had significant associations with self-rated health (see Table 8).

Table 7.

Correlation matrix between unobserved variables.

	1	2	3	4
1. Self-rated health (HLT)	1.000
2. Subjective wellbeing (WLB)	0.457***	1.000
3. Perceptions of therapeutic landscapes (TL)	−0.185	−0.062	1.000
4. Perceptions of therapeutic networks (TN)	−0.247**	−0.342**	0.462*	1.000

***p < 0.001; **p < 0.01; *p < 0.05.

Table 8.

Results for the structural equation model for self-rated health among Indonesian FDWs in Hong Kong (N = 172).

Exogenous variable	Endogenous variables
	Therapeutic networks	Subjective wellbeing	Self-rated health
Therapeutic landscapes	B = 0.501 [0.202, 0.877]**	B = −0.052 [-0.413, 0.516]	B = −0.206 [-0.599, 0.088]
Therapeutic networks	–	B = −0.291 [-0.632, 0.176]	B = −0.014 [-0.244, 0.635]
Subjective wellbeing	–	–	B = 0.434 [0.200, 0.673]**
Age	–	–	B = −0.007 [-0.158, 0.157]
Marial status	–	–	B = 0.081 [-0.075, 0.232]
Length of working & living	–	–	B = −0.106 [-0.276, 0.075]

***p < 0.001; **p < 0.01; *p < 0.05; B = Standardized beta coefficients; [ ] = Bootstrapped 95% confident interval.

Total Effect

• Therapeutic landscapes → self-rated health: B = −0.299 (95% CI: −0.499, −0.041), p = 0.033.

Direct Effect

• Therapeutic landscapes → self-rated health: B = −0.206 (95% CI: −0.599, 0.088), p = 0.490.

Indirect Effect

• Therapeutic landscapes → self-rated health: B = −0.093 (95% CI: −0.301, 0.186), p = 0.709.

• Therapeutic landscapes → therapeutic networks → self-rated health: B = −0.007 (95% CI: −0.128, 0.327), p = 0.975.

• Therapeutic landscapes → subjective wellbeing → self-rated health: B = −0.023 (95% CI: −0.183, 0.244), p = 0.901.

• Therapeutic landscapes → therapeutic networks → subjective wellbeing → self-rated health: B = −0.063 (95% CI: −0.517, −0.005), p = 0.673.

Based on the SEM, we observed the direct and indirect effects from the model. None of the direct and indirect effects of therapeutic landscapes on self-rated health were statistically significant. Only the total effect between TL and HLT was statistically significant with a negative association (standardized beta coefficient = −0.299, p = 0.033). The direct effect (TL → HLT) is largest in magnitude and negative (standardized beta coefficient = −0.206, p = 0.490), but not significant. The indirect effects are all negative and not statistically significant, but substantially smaller in magnitude than the direct effect. Of the indirect effects, the pathway through wellbeing (TL →WLB → HLT) is the strongest (standardized beta coefficient = −0.023, p = 0.901), but the p-value shows that it is not discernible from zero.

The SEM modeling results are unexpected, especially the negative association between therapeutic networks and subjective wellbeing and the negative total effect from therapeutic landscapes to self-rated health. According to the therapeutic landscapes literature (Gesler, 1992; Gesler and Kearns, 2002), we expected to find positive associations between TLs and TNs and self-rated health. Although we cannot confidently identify the causes of these unexpected findings, we expect that the pandemic may have played a significant role. FDWs’ perceptions of and access to TLs and TNs might have shifted during the pandemic and influenced the results. Furthermore, FDWs’ physical and mental health and wellbeing may have been adversely impacted by the pandemic. Nevertheless, some of the model results fit expectations: TLs and TNs are positively related indicating their synergistic relationships, and the associations between subjective wellbeing and self-rated health, are positive and significant, indicating that wellbeing is beneficial for self-rated health.

3.4. Semi-structured interviews

To better understand the weak and even negative associations between TL, TN, and self-rated health, and to investigate the role of the pandemic, we incorporate qualitative data from the semi-structured interviews. Each FDW shared their experiences with access to public places and social networks, along with changes in job expectations and rest day implementation during the pandemic that might have affected their perception of TLs and TNs.

3.4.1. Restricted access to public space and gathering places

Hong Kong implemented a strict policy during the COVID-19 pandemic that impacted FDWs’ everyday lives. Before the pandemic, FDWs relied on the rest day to ‘escape’ from their demanding jobs. They visited public places to gather with friends and strengthen their social networks. However, many public places were closed and guarded during the pandemic. For instance, public places where Indonesian FDWs usually met, like Victoria Park and Kowloon Park, were patrolled by security guards. A research participant reported the conditions at Kowloon Park during the pandemic.

“We used to meet and gather at Kowloon Park, but the COVID-19 policy in Kowloon Park is so strict now. There are security guards/officers checking us all the time at the park. If they saw us gathering and did not follow the strict COVID-19 rule, they would subject us to a fine of HKD 2,000.” – Interview Participant #24

In addition, the number of people allowed to gather was limited by the government, and the restriction changed during the pandemic. At one time the government allowed four people to get together; however, when COVID-19 cases rose rapidly, gatherings were restricted to only two people. Many FDWs were afraid to go out if only two people were allowed to meet. Further, due to the limited number of people, many FDWs considered not going anywhere, including to their therapeutic landscapes, and they tried to find safe places to go alone or with only one friend. One FDW below shared her experiences with the gathering rules.

“Since the COVID-19 policy limits the social gathering, we are only allowed to meet two people. So, if it is only two people, I am afraid that if something happens to us, nobody will know. So, for now, we are not meeting or going out. Sometimes, we only visit open spaces like the beach. Because right now, many public places in Hong Kong are closed.” – Interview Participant #27

This participant was fortunate because her employer’s house was near the beach which afforded a therapeutic space for her to escape from domestic daily routines during the pandemic. In other parts of the world, such as England, beaches were closed during the lockdown: residents could not access coastal therapeutic encounters to sustain their mental health and wellbeing during the pandemic (Jellard and Bell, 2021).

Aside from the closure of public places, religious organizations also implemented restricted access. Religious sites such as Masjid Ammar Wan Chai and Masjid Kowloon, which many Muslim FDWs view as therapeutic places, only opened during prayer times and were closed again afterwards. During the COVID-19 pandemic, these Mosques did not allow for gathering and hosting of religious and social activities. Moreover, Majelis groups – informal religious groups that many Muslim FDWs enjoy -- which usually congregate inside the Mosque and other public places across Hong Kong, limited and suspended their religious, social, and humanitarian activities and programs. One of the Majelis group members documented the low participation rate during the COVID-19 pandemic.

“These days, we don’t have much participation in our Majelis group because the gathering is restricted, and because of the COVID-19 pandemic, only a few people joined. So, it is like we are not allowed to have a gathering activity. Because there no more activities in our Majelis, the participation plumed, and people were getting bored because the group is empty.” – Interview Participant #15

3.4.2. (No) rest day during the pandemic

The COVID-19 pandemic exacerbated FDWs’ vulnerability, particularly with the change in rest day implementation. The rest day provided a crucial opportunity for FDWs to cope with stressful and tiring working days, by meeting friends and sustaining their wellbeing. However, to limit the risk of COVID-19 and everyone’s safety, many employers asked FDWs to stay at home and did not allow them to go out. As a result, many FDWs did not leave their employers’ homes on their rest days: public spaces and gathering places were ‘empty,’ and FDWs who (still) had their rest days could not meet their friends. One of our interview participants detailed her observations of the rest day changes.

“Not all my FDW friends get rest days during the pandemic. For instance, some of them cannot go out during the rest day, and some of them are not allowed to have a rest day. So, yeah, we cannot do anything. So, now, public places we used to visit, like Victoria Park and Under the Bridge (UB), seem empty. Before the pandemic, those places were always packed by FDWs’ gatherings.” – Interview Participant #6

The COVID-19 pandemic also affected FDWs who still were given the rest day by their employers. Many FDWs were confined to their employers’ homes during their rest days, because pandemic restrictions prevented them from visiting places and meeting other FDWs. Many FDWs reported that these conditions were challenging and stressful, especially in the early pandemic and during Hong Kong’s lockdown. During this time, FDWs utilized social media and chat messengers to communicate and check with each other. WhatsApp, Facebook, and WeChat were popular online platforms that enabled FDWs to support and be virtually present for each other during the pandemic. In the interview, one of the research participants shared her feelings and experiences about being confined to home and communicating digitally.

“During the early pandemic, when Hong Kong was lockdown, I only communicated with my social group via WhatsApp. We only talked through WhatsApp. Our group’s activities were only held through WhatsApp. I also experienced a month that did not go out at that time. During my rest day, I got my rest day but only stayed at home. I felt like I was in prison.” – Interview Participant #24

4. Discussion

This study evaluated how experiencing therapeutic landscapes and networks impacts subjective wellbeing and self-rated health among Indonesian FDWs in Hong Kong and how the COVID-19 pandemic has shaped these associations. Overall, our qualitative findings from interviews support and extend quantitative modeling results from CFA and SEM by providing deeper meaning and understanding of what was going on with FDWs’ TLs, TNs, health, and wellbeing.

Based on CFA, our research identified well-defined composite variables to represent core concepts associated with FDWs’ health and wellbeing, including therapeutic landscapes, therapeutic networks, and subjective wellbeing. However, our SEM incorporating these unobserved variables, along with FDWs’ sociodemographic characteristics, as predictors of self-rated health, uncovered little evidence of the expected associations between TLs, TNs, subjective wellbeing, and self-rated health. Insights from the qualitative interviews suggest that this lack of association of TL and TN with health and wellbeing is likely a result of limited access to therapeutic encounters during the pandemic, as government and employer-imposed restrictions reduced FDWs’ travel and social interactions outside employers’ homes, especially on rest days.

The SEM model revealed that subjective wellbeing and self-rated health had positive and significant associations, as expected. This indicates that FDWs who felt good about their lives and had higher life satisfaction had better self-rated health. Subjective wellbeing, including mental and emotional health, has been widely shown to promote physical health (Rosenbaum et al., 2020). The results also confirm that TLs and TNs are strongly and positively associated. For FDWs, TLs and TNs are intertwined and work synergically to provide therapeutic experiences in their everyday lives, as described in the in-depth interviews. Among immigrants, existing literature emphasizes that social networks that provide therapeutic experiences are equally important as TLs (Chakrabarti, 2010; Agyekum and Newbold, 2016). Our work indicates that TLs and TNs are closely connected, as the presence and use of TLs supports FDWs in building social connections.

Contrary to expectations, the results showed an inverse association between therapeutic landscapes and self-rated health. We suspect that decreased access to therapeutic landscapes during the COVID-19 pandemic in Hong Kong influenced these findings and those who had poor self-rated health did not or could not visit places they viewed as therapeutic. In addition, this study focused on places FDWs thought were therapeutic subjectively; however, with the current COVID-19 restrictions, some of these places, such as Victoria Park, might have become (un)therapeutic for FDWs – a finding supported by the interviews. This issue may lead to the observed negative association between TL and HLT.

Our research extends research on TL by analyzing how the pandemic influenced access to therapeutic places. A significant finding is that for Indonesian FDWs in Hong Kong, access was greatly reduced due to social distancing, travel restrictions, and limited access and closure of public places. Employer-level restrictions were also important in limiting access, confirming other work (such as Lui et al., 2021; Oktavianus and Lin, 2021). Thus, FDWs’ access to therapeutic landscapes was influenced by place-based political and economic factors at the territory- and employer-scales (Buzinde and Yarnal, 2012).

Previous studies (Rice and Pan, 2021; Bustamante et al., 2022; Guzmán et al., 2022) found the use of outdoor public spaces (parks, gardens, and walking trails) increased during the COVID-19 pandemic and identified those natural spaces as key for coping with domestic and work responsibilities and the pandemic itself (Foley et al., 2022; Guzmán et al., 2022). However, those findings do not reflect our findings because FDWs’ access to TLs and TNs was highly constrained both by employers and by governmental restrictions. In addition, work-related constraints limited FDW’s engagement with purposeful outdoor projects (e.g., gardening, yard work, and photography) that have been identified in other recent studies as strategies for maintaining wellbeing during the pandemic (Bustamante et al., 2022).

Interviews with FDWs revealed that, while confined to their employers’ homes. FDWs often relied on the “digital spaces” to sustain their social networks and maintain communications with FDW friends, as has been found in other studies of vulnerable populations (see Lupton and Lewis, 2022). These digital therapeutic networks helped FDWs cope with challenging work conditions and limited mobility. Digital spaces also substituted in part for therapeutic landscapes, especially as FDWs attended activities online. The importance of digital spaces for sustaining people’s everyday social interactions during the pandemic has been highlighted in research from other parts of the globe (Foley et al., 2022). However, FDWs’ online experiences were also somewhat diminished by their lack of privacy and personal space in the employer’s home. For some FDWs, the home became “prison”-like, with frequent employer supervision.

For Indonesian FDWs in Hong Kong, therapeutic networks are crucial for their wellbeing because they have no family nearby and have stressful work lives. During the COVID-19 pandemic, social support from other FDWs was essential for coping with anxiety (Yeung et al., 2020). For FDWs, social networks also allowed them to access, share, and circulate information to sustain their lives in Hong Kong, including information about maintaining physical and mental health (Oktavianus and Lin, 2021). Despite the limited access to in-person social gatherings, their social connections remained strong.

Combining advanced statistical analysis and qualitative data from interviews, the results shed light on associations during the pandemic between therapeutic landscapes and networks and health and wellbeing for FDWs, a vulnerable population that faced heighted challenges and constraints due to pandemic restrictions. Challenges emerged from governmental and employer restrictions, revealing how access to therapeutic places and networks is impacted by processes at different scales. Our findings also show how women actively coped by drawing on digital interactions and spaces.

Despite these strengths, this study has several limitations. First, we could not conduct research in Hong Kong in person due to the COVID-19 pandemic. Conducting fieldwork in Hong Kong and immersing with FDWs during data collection would enhance our understanding of their everyday lives. Also, in our quantitative modeling analyses, we did not find much variation in self-rated health among FDWs. The findings indicate that FDWs were quite healthy overall regardless of the illnesses reported in the survey. Thus, the dependent variable of self-rated health did not vary much, leaving little variation to be captured in the models. In addition, our definition of therapeutic landscapes in the quantitative modeling may be limited by its reliance on the concept of favorite places.

Our quantitative modeling did not include other factors that might contribute to FDWs’ overall health and wellbeing. These include working conditions, hours of work per day, hours of resting on work days, personal bedroom availability, and other variables measuring FDWs’ working conditions at their employers’ homes. These factors might be important as previous studies (Dutta et al., 2018; van Bortel et al., 2019; Chung and Mak, 2020) have reported that these variables affect FDWs’ physical and mental health and wellbeing. Lastly, the questionnaire was constructed before the pandemic and did not include a comprehensive set of pandemic-related questions, nor questions about experiences of TL and TN before the pandemic. So, changes in key constructs such as TL and HLT before and during the pandemic cannot be analyzed. Quantitatively modeling those changes is an important topic for future research.

5. Conclusion

This research explored new applications of TL and TN to women with domestic employment living in a foreign country who face significant space-time constraints in their everyday lives. To cope with work-related challenges, FDWs in Hong Kong often rely on the rest day to visit their therapeutic landscapes and strengthen their therapeutic networks. However, during the COVID-19 pandemic, the results show that access to these crucial resources was sharply restricted, weakening the links between TLs, TNs, and health outcomes, as estimated SEM. Our study confirmed that maintaining TNs and visiting TLs contributed to FDWs’ physical and mental health and wellbeing in complex ways. We did not find positive associations between TLs and self-rated health during the COVID-19 pandemic as experiences of places changed and access to public places was reduced.

Moreover, FDWs needed more social support during the pandemic, especially to cope with stress and anxiety from their jobs and COVID-19 concerns. With limited access to public places and in-person gatherings at public places, FDWs utilized digital platforms such as WhatsApp and Facebook to maintain their communications with other FDWs and with their families in Indonesia. FDWs also used chat messenger and social media to attend social, educational, and religious activities. FDWs’ resourcefulness in sustaining and developing social networks was critical in maintaining health and wellbeing despite limited access to therapeutic landscapes.

Credit author statement

Fikriyah Winata: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data Curation, Writing – Original Draft, Writing – Review & Editing, Visualization, Project administration, and Funding acquisition; Sara L. McLafferty: Conceptualization, Methodology, Validation, Investigation, Writing – Review & Editing, Visualization, and Supervision.

Handling Editor: S Susan J Elliott

Data availability

The data that has been used is confidential.