Factors Predicting Financial Burden Among Family Caregivers of Dependent Stroke Survivors in Selected Tertiary Care Hospitals: A Study From Thailand

Abstract

Introduction

Stroke is a neurological disease that leads to severe morbidity and mortality globally. Family caregivers are directly impacted by patients who have a stroke, especially regarding financial burdens.

Objectives

To describe and examine factors predicting family caregivers’ financial burden, using the bidirectional relationship concept developed by Isik and colleagues (2019) as a guiding model to build a new framework for Thai family caregivers.

Methods

A cross-sectional study with a predictive-correlational design was employed. Using a purposive sampling technique, 124 eligible family caregivers of dependent stroke survivors were recruited from two governmental tertiary care hospitals (Thailand). However, only 120 family caregivers were included after 4 extreme outliers were removed. The questionnaires comprised demographic information, illness perceptions, social support, financial management, non-medical costs, and family caregivers’ financial burden. Descriptive and correlational and multiple regression (MR) analyses were used to analyse data.

Results

The MR analysis revealed the model’s overall fit: F(7,112) = 27.185, p < 0.01. Age, educational level, family caregivers’ income, social support, and family caregivers’ financial management could help predict the financial burden for family caregivers of dependent stroke survivors, explaining 60.6% of the variance. Financial management was the most robust predictor of financial burden for family caregivers (β = 0.449; p < .01).

Conclusion

Family caregivers’ financial burden in dependent stroke survivors is an important focus. The findings suggested that hospital administrators and healthcare providers should prepare and tailor financial programs and support systems. Policymakers should also consider these factors when developing social welfare policies to mitigate the long-term financial burden on family caregivers. Nurses in Thailand still remain a valuable source of social support for family caregivers, helping them manage health concerns and reduce financial burdens.

Keywords

financial burden financial management stroke family caregivers

Introduction

Stroke is a severe neurological disease that leads to the second-leading cause of death and the third-leading cause of combined disabilities and deaths worldwide, and it causes both physical and mental impairments or paralysis (Feigin et al., 2025). In 2021, the global burden of stroke reported that there were 12 million new cases of stroke, 7 million deaths from stroke, and 94 million people living with disability or the impact of stroke (GBD 2021 Stroke Risk Factor Collaborators, 2024). Dependent stroke survivors often have disabilities or co-morbidities and tend to rely on caregivers.

While there are various types of caregivers internationally (Almazrou et al., 2025; Barbosa et al., 2011), the family caregiver is a type of caregivers seen in both developed and developing countries (Intaput et al., 2023; Kondeti et al., 2021; Ryuno et al., 2024). The family caregiver might be paid or unpaid. In East and Southeast Asia, more than 80% of the family caregivers were long-term caregivers (Jiang et al., 2024).

Most Thai family caregivers are spouses, siblings, and children who are unpaid or informal caregivers (Sanprakhon et al., 2023; World Health Organization, 2024). Caring for dependent stroke survivors is common in Thai families because of the strong traditional culture of repaying caring parents or ancestors (Aung et al., 2021). Caring for ill relatives in the family can leave them with insufficient financial or supportive resources, placing a financial burden on family caregivers.

In the literature, the financial burden is examined solely in terms of the difficulty of economic definitions (Frescos et al., 2023; Nemcikova et al., 2023), without considering health care costs for family caregivers. Additionally, financial burden has been used interchangeably with financial distress, financial toxicity, and financial hardship. Financial distress is defined as the negative consequences of medical treatment costs, leading to delays in care, unpleasant emotions, or the inability to pay debts (Tschanz et al., 2025). Financial toxicity is described as a person’s experiences of mental distress that lead to negative responses to behaviors under the condition of medical debt or their own extra expenses for illness treatment and care (Sadigh et al., 2022). Financial hardship is defined as a person’s experiences of financial resource scarcity, such as low income or job loss, that create difficulty with bill payments, daily living expenses, and other financial issues (Tran et al., 2025). These inconsistent terminologies for the financial burden illustrate a problem of defining meanings and measuring the actual economic impact on family caregivers. Thus, this study focuses solely on the use of the “financial burden.”

Additionally, given many factors in the literature that affect the financial burden, this study applied a bidirectional relationship concept (Isik et al., 2019) to explain how family caregiver-related factors (e.g., age, educational level, income, family caregivers’ illness perception, social support, and family caregivers’ financial management) and a patient-related factor (non-medical costs) directly affected the financial burden on family caregivers.

In previous literature, there were studies reporting caregivers’ related factors, including age (Kongkar et al., 2019), educational level (Hançerlioğlu et al., 2023), income (Hançerlioğlu et al., 2023), illness perception (Perni et al., 2022), social support (Wang et al., 2025), family caregivers’ financial management (DaDalt et al., 2016), and cost-related care (Sadigh et al., 2022; Schmidt et al., 2024) with the economic financial burden of family caregivers who needed to take care of patients with chronic illnesses.

However, these relationships have not been examined as an integrated predictive model within a bidirectional relationship framework. Exploring predictors of financial burden among family caregivers would help provide a better understanding of the factors influencing financial burden, informing future nursing and multidisciplinary health guidance research. This study employed a definition of financial burden on family caregivers that encompassed healthcare expenses incurred by both family caregivers and dependent stroke survivors. This study aimed to examine the description of financial burden and factors predicting financial burden in Thai family caregivers of dependent stroke survivors.

Review of Literature

Previous literature has shown that family caregivers have a significant impact on dependent stroke survivors (Comer et al., 2024; Tziaka et al., 2024). Caregivers provide the majority of care, including physical, psychological, and social support, to dependent stroke survivors (Muhrodji et al., 2021), which makes caregivers face difficulties and feel burdened in their caregiving roles in taking care of dependent stroke survivors. In addition, patients’ clinical conditions, disease severity, and insurance type impact all the healthcare costs (Lucas-Noll et al., 2023). Financial burden is thus a major challenge for family caregivers, who cover costs for long-term care, outpatient visits, and rehabilitation (Eriksson et al., 2021; Mishra et al., 2016).

This study applied a bidirectional relationship concept (Isik et al., 2019) between the caregiver-related factors and patient-related illness factors, which impacts the caregivers’ burden, especially financial burdens. Previous literature reported that younger age groups had greater financial burdens than older age groups (Poco et al., 2025). Additionally, caregivers with lower education and income might have greater difficulty accessing financial information or resources to manage healthcare costs (Poco et al., 2025). Different illness perceptions among family caregivers could contribute to a mismatch in financial burdens (Y. Zhang et al., 2024). Social support has been important for family caregivers in managing financial burdens (Rapiya et al., 2025), and it has been significantly associated with caregiver burdens among family caregivers of dependent stroke survivors (Cao et al., 2022). A study reported that social support and stress among family caregivers of dependent stroke survivors were positively associated with caregiving experiences and reduced stress (Ou et al., 2024). Previous studies reported that financial management including financial literacy, mental budgeting, and self-control could improve financial well-being and reduce financial burdens (Bai, 2023; Patel et al., 2022).

Financial burden was defined as whether a family caregiver experienced difficulties with direct costs such as medical and non-medical costs and indirect medical costs including loss of productivity (Park et al., 2025). For example, caregivers who could not pay medical bills (Liu et al., 2024; Valero-Elizondo et al., 2019) might affect medication adherence such as taking fewer medications, skipping doses, and delaying prescription refills (Patel et al., 2022; Springer et al., 2023). Direct and indirect medical costs for unpaid family caregivers may increase disease severity among patients with chronic conditions (Monfared et al., 2023).

Methodology

Design and Sample

A cross-sectional study with a predictive-correlational design was employed to investigate predictors (e.g., age, educational level, income, family caregivers’ illness perceptions, social support, family caregivers’ financial management, and non-medical costs) on family caregivers’ financial burden. Using a purposive sampling technique, researchers recruited two governmental tertiary-care university hospitals located in Bangkok, Thailand as data collection sites. The study was conducted from March 2024 to June 2024. According to the 2023 statistics of these two hospitals, the number of dependent stroke survivors ranged from 1,555 to 1,598, indicating a nearly equal distribution. Thus, the sample collection was equal.

Using the G*power version 3.1.9.7 with an effect size of 0.15, which was calculated from a study of Chinese family caregivers of dependent stroke survivors (Han et al., 2017), the power of 0.8, and the alpha of .05. The sample was 103. However, 20% of the original sample was added to account for incomplete data collection (Polit & Beck, 2021). The total sample was, thus, 124. A pilot study involving 10 individuals with similar characteristics was also conducted.

The inclusion criteria for this study were that family caregivers were at least 18 years old, had no serious physical illnesses, were able to understand and communicate in Thai, were willing to participate, and had no cognitive impairments. If they were 60 years old or older, they were screened with the Thai version of the 6-item Cognitive Impairment Test or 6-CIT (Aree-Ue & Youngcharoen, 2020). Exclusion criteria included being paid professional caregivers, secondary caregivers without primary responsibilities for the dependent stroke survivors’ care, and family caregivers experiencing a significant life event or withdrawing their consent to participate.

Data Collection

After obtaining Institutional Review Board (IRB) approval, participants were approached and informed of the purpose of the study and their rights to participate. Those who were interested in participating in this study were invited to a private area. They read and signed an informed consent form before the interview. Eligible participants were interviewed for 30-40 minutes with the structured questionnaire. After the interview process was completed, participants were allowed to ask any questions before leaving.

Variables and Instruments

Study Variables and Theoretical Justification

The selection of study variables guided by the bidirectional relationship concept (Isik et al., 2019) suggested an interplay between caregiver-related factors and the patient-related illness factor. Caregiver-related factors comprised age, educational level, income, illness perception, social support, and family caregivers’ financial management. These predictors served as important keys to family caregivers’ financial burden. However, the patient-related illness factor was non-medical costs including personal, food, and transportation expenses. These involved predictors formed a conceptual framework for evaluating the financial burden on family caregivers.

The questionnaires included demographic information such as age, educational level, income, non-medical costs, and other necessary information.

Illness Perceptions were measured by the Revised Illness Perception Questionnaire (IPQ-R) developed by Moss-Morris et al. (2002). The original scale consists of 38 items and is available for use with permission. However, in the previous Thai version (Sriprasong et al., 2009), only 37 items were used because a similar 2-item statement was retained after translation into Thai. This scale is composed of 37 items with a 5-point Likert scale (1= strongly disagree; 5= strongly agree). The positive items remain the same, while the negative items are reverse-scored. An example of a statement is “My illness is a serious condition”. The Cronbach’s alphas of this questionnaire in the previous international studies varied from 0.60 to 0.79 (Giannousi et al., 2010; Moss-Morris et al., 2002; Rivera et al., 2024). In Thailand, the IPQ-R for a previous Thai version had a Cronbach alpha of 0.87 (Sriprasong et al., 2009). However, the Cronbach’s alphas in the pilot and current studies were 0.70 and 0.63, respectively. Additionally, the Cronbach’s alphas of the multi-attribute construct in the current study were from 0.54 to 0.83. The total Cronbach’s alpha of 0.63 was acceptable for research, as it has been observed in previous studies (Giannousi et al., 2010; Rivera et al., 2024). The content validity index (CVI) in the previous Thai version was 0.87 (Sriprasong et al., 2009).

Social support, as measured by the Multidimensional Scale of Perceived Social Support (MSPSS), was developed by Zimet et al. (1988). With permission to use, this scale is composed of a 12-item scale from 1 to 7 (1= strongly disagree; 7= strongly agree). All items are positive. An example of a statement is “There is a special person who is around when I am in need.” The Cronbach’s alpha of this questionnaire in a previous study was 0.81 (Zimet et al., 1990), 0.84 for the previous Thai version (Wongpakaran et al., 2011), 0.91 for the pilot test, and 0.83 for this study. According to Wongpakaran et al. (2011), the confirmatory factor analysis of the MSPSS showed good model fit with comparative fit index (CFI) = 0.95 (good), Tucker-Lewis index (TLI) = 0.94 (good), and the root mean square error of approximation (RMSEA) = 0.05 (excellent).

Financial management, as measured by the Financial Management Behavior Scale (FMBS), was developed by Dew and Xiao (2011). The Thai version, composed of a 17-item scale with a 5-point rating scale (1= never; 5= always), was used with permission (Tiwasasit, 2020). An example of a statement is “Comparison shopped when purchasing a product or service.” The Cronbach’s alphas of this questionnaire in previous studies were 0.81 (Dew & Xiao, 2011) and 0.71 for the previous Thai version of the FMBS (Tiwasasit, 2020). In addition, the Cronbach’s alphas in the pilot and the current studies were 0.96 and 0.84, respectively. The exploratory factor analysis of the FMBS using the four-factor solution yielded the best-fitting and most parsimonious model, accounting for 59% of the total variance (Dew & Xiao, 2011).

Financial burden on family caregivers was measured by the Financial Burden in the Non-Communicable Disease Family Caregiver Scale, developed by researchers. This scale is composed of 15 items with a 4-point rating scale (1= very disagree; 4= very agree). The positive items remain the same while the negative items are reversed scores. An example of a statement is “You have enough savings to care for and promote your own health.” The Cronbach’s alphas in the pilot and the current studies (Thai version) were 0.96 and 0.81, respectively. The content validity of the instruments was evaluated by five experts in adult and gerontological nursing to ensure the appropriateness of the items for the Thai context. The Content Validity Index of this questionnaire was 0.90.

Data Analysis

The Statistical Package for the Social Sciences (SPSS) version 30 was used to analyze both descriptive (e.g., percentages, means, and standard deviations) and inferential (Pearson’s correlation and multiple regression (MR) analyses) statistics, including all required assumptions for these analyses.

Ethical Considerations

Ethical approval was given by the Human Research Ethics Committee of hospital A and the Institutional Review Board of hospital B. This study was conducted in accordance with the Declaration of Helsinki, as adopted by the World Medical Association. All potential participants had the right to know the purposes, risks, and benefits of the study. They could withdraw from the study at any time without the negative impacts of the treatment they received. Eligible participants who agreed to participate in the study would sign a consent form before an interview. All completed questionnaires were kept confidential and anonymous. Only the principal investigator and co-investigators could access the data, which were stored in numerical and aggregated form and protected by a secure password.

Results

One hundred twenty-four Thai stroke family caregivers were recruited from the internal medicine outpatient clinics at hospitals A (62 cases) and B (62 cases) in Bangkok, Thailand. However, when examining the normality of all involved variables, four cases were identified and removed due to extreme outliers, using diagnostic methods including boxplots (to visually identify extreme outliers), a Z-score threshold (greater than +3 or less than -3), and Mahalanobis distance evaluated against a Chi-square distribution with degrees of freedom equal to the number of predictors (p < .001).

Thus, only 120 cases were included in this study. Before conducting statistical analysis, family caregivers’ age, educational level, and income were examined across the two governmental tertiary care hospitals to identify differences. The results showed no significant differences in family caregivers’ age, educational level, and income. The ages of family caregivers ranged from 28 to 78 years (Mean = 52.13, SD = 11.37). Most participants were female (n = 91, 75.8%), children of dependent stroke survivors (n = 66, 55.0%), and married (n = 66, 55.0%). Many participants had a Bachelor’s degree (n = 50, 41.7%; the highest proportion in this study), with an average of 13.27 years of education (SD = 3.85).

In this study, social security insurance (n = 50, 41.7%) was the most common type of family caregiver health insurance. Most participants reported inadequate incomes (n = 70, 58.3%); however, more than 70% reported having financial support (n = 86, 71.7%). The average care time for family caregivers was 54.81 months (SD = 47.80). The average family caregiver’s income was 30,241.67 Thai baht/month (SD = 23,538.45). See Table 1.

Table 1.

Demographic Characteristics of Family Caregivers of Dependent Stroke Survivors (n = 120)

Variable	Frequency	Percent (%)
Age
Mean = 52.13 (SD = 11.37)
Range of age = 28 to 78 years
Gender
Male	29	24.2
Female	91	75.8
Relationship to the patient
Partner of stroke caregivers	27	22.5
Children of patients with stroke	66	55.0
Other relatives	27	22.5
Marital status
Single	45	37.5
Married	66	55.0
Separated	1	.8
Divorced	5	4.2
Widowed	3	2.5
Educational level
Year of education Mean = 13.27 (SD = 3.85)
Primary school	9	7.5
Secondary school	20	16.7
.High school	17	14.2
High vocational certificate	14	11.7
Bachelor’s degree	50	41.7
Master’s degree or higher	10	8.3
Type of family caregivers’ health insurance
Government insurance	20	16.7
Social security insurance	50	41.7
Universal healthcare insurance	43	35.8
Private insurance	3	2.5
Other insurance	4	3.3
Income adequacy
Not enough	70	58.3
Enough	50	41.7
Financial support
No support	34	28.3
Have support	86	71.7
Duration of care for family caregivers
Mean = 54.81 months (SD = 47.80)
Family caregivers’ income
Mean = 30, 241.67 baht/month (SD = 23,538.45)

Most dependent stroke survivors had universal healthcare insurance (n = 82, 68.3%), government insurance (n = 27, 22.5%), and other types of healthcare insurance (n = 11,9.2%).

Regarding family caregivers’ financial burden, the total mean score was 2.88 (SD = 0.45). In terms of percent agreement of family caregivers’ financial burden, family caregivers reported “strongly agree,” for the top three responses including having enough income to pay for their own non-medical expenses, such as travelling, vehicle, and fuel expenses (n = 63, 52.5%), having enough income to pay for non-medical expenses for family members, such as travelling, vehicle, and fuel expenses (n= 58, 48.3%), and food and other necessary products (n= 54, 45.0%). See Figure 1.

Figure 1.

Percent agreement of family caregivers’ financial burden: Strongly agree (n = 120)

Additionally, they reported the top three responses of percent agreements of family caregivers’ financial burden (agree), including having enough money to pay for their own treatment when being admitted to the hospital (n = 55, 45.8%), losing opportunities to earn income for caring and promoting their own health (n = 55, 45.8%), and having enough money to pay for their own medical care when not being admitted to the hospital (n = 54, 45.0%). See Figure 2.

Figure 2.

Percent agreement of family caregivers’ financial burden: Agree (n = 120)

Many family members (n = 46, 38.3%) disagreed about having enough money to pay for and promote the health of family members with chronic illnesses. They strongly disagreed that they received support for the health problems of family members with chronic illnesses from the involved healthcare unit (n= 55, 45.8%).

Regarding responses on family caregivers’ financial burdens, their income might be sufficient only for their basic daily living and family members, but not for covering healthcare costs. High healthcare costs for dependent stroke survivors in tertiary care hospitals could be different and varied due to various complex treatments that family caregivers might or might not know how to seek help for them.

Preliminary analyses were conducted to ensure that the data met the assumptions for correlational and MR analyses. In the Kolmogorov-Smirnov (K-S) test, only family caregivers’ financial management was not statistically significant, whereas the other involved variables were significant. Regarding skewness and kurtosis, all variables demonstrated acceptable ranges of skewness (-.950 to +1.382) and kurtosis (-.698 to +2.050). However, the normality test of residuals indicated a violation (p = 0.032). After identifying and removing four extreme outliers, the residuals were not significant (p = 0.05).

Consequently, only 120 participants were included for data analysis. Before running the correlational analysis, the assumptions of the level of measurement, normality, absence of outliers, and linearity were examined. They all met the assumptions. In the correlational analysis, except for the age and illness perception, all other involved variables were significantly associated with family caregivers’ financial burden (p < .01). See Table 2.

Table 2.

Correlational Analysis Between the Involved Variables and the Family Caregivers’ Financial Burden of Dependent Stroke Survivors (n = 120)

Involved variables	r	p-value
Age	.063	.496
Educational level	.498	<.01
Income	.581	<.01
Illness perception	-.150	.145
Social support	.391	<.01
Financial management	.678	<.01
Non-medical costs	.369	<.01

Before running the MR analysis, the assumptions of linearity (no zero correlations), independence of residuals checked by Durbin-Watson test (an acceptable range from 1.5 to 2.5), the K-S test for normality (p = .05), no multicollinearity (the tolerance > 0.1 and the variance inflation factors or VIF < 10), and homoscedasticity (Breusch-Pagan test with p-value = 0.787) were checked. All assumptions were met.

The MR analysis examined the involved predictors of financial burden on family caregivers. The MR model was statistically significant, F(7, 112) = 27.185, p < .01, with an explained R² of 62.9% and an adjusted R² of 60.6%, accounting for the variance in the family caregivers’ financial burden. According to Cohen’s (1988) recommendation, an R² value above 0.26 is considered large for the MR model. This finding explained 60.6% of the variance in family caregivers’ financial burden, considered highly acceptable, especially in behavioral science research.

After all predictors were entered into the regression equation using the enter method, except for family caregivers’ illness perception and non-medical costs, all other predictors were found to be significant for family caregivers’ financial burden. Family caregivers’ financial management was the most robust predictor (β = .449; p-value < 0.01). Age (β = .290; p-value < 0.01), social support (β = .233; p-value < 0.01), educational level (β = .210; p-value < 0.05), and family caregivers’ income (β = .170; p-value < 0.05) were also significant predictors of the family caregivers’ financial burden. See Table 3.

Table 3.

Multiple Regression (MR) Analysis of Financial Burden on Family Caregivers (n= 120)

Predictor variable (Model 1)>	Unstandardized coefficients B	Standard errors (SE)	Standardized coefficients β	t	p-value
Age	.011	.003	.290	4.544	<.01
Edu	.025	.010	.210	2.248	<.05
Income	.000	.000	.170	2.115	<.05
IP	-.066	.133	-.030	-.491	.624
SS	.147	.040	.233	3.664	<.01
FM	.390	.068	.449	5.703	<.01
NMC	.000	.000	.020	.311	.756

Note. Edu= educational level; IP= illness perception; SS= social support; FM= financial management; NMC= non-medical costs.

Discussion

The findings of this study showed that most family caregivers were female and were dependent stroke survivors’ children. This supports a previous study (Aslan & Altuntas, 2024) reporting that most females were primary caregivers of dependent stroke survivors due to socio-economic and cultural factors. This is relevant to previous literature among international countries, such as China (Fan et al., 2023), India (Menon et al., 2017), Saudi Arabia (Tunsi et al., 2025), European countries (Palacios-Galvez et al., 2025), and Canada (Kokorelias et al., 2020). Additionally, most Thai females are responsible for full-time care of family members with chronic diseases, including stroke (Bui et al., 2026; Kongkar et al., 2019). This is common in Thailand because the cultural value of “gratitude” for caring for ill parents has been inculcated in younger generations (Balthip et al., 2022), thereby helping them grow into competent and responsible adults.

Most family caregivers in this study held a Bachelor’s degree. This is not surprising because the Thai educational system encourages Thai people to pursue higher education (ASEM Education Secretariat, 2020). Additionally, many family caregivers had social security healthcare insurance despite reporting insufficient incomes. It is possible that the healthcare support provided by the Thai Social Security Office for individuals is insufficient, as the costs of care for chronic illnesses vary significantly.

On average, most family caregivers in this study earned approximately 30,000 Thai baht per month ($900 USD/month), which should be sufficient. However, the range of earnings among them varied widely and does not guarantee their costs of living in Bangkok, Thailand, making it difficult to have sufficient income to support ill family members, especially dependent stroke survivors. When considering family caregivers’ income in Japan and China, the trends are similar to those in this study. In Japan, family caregivers are expected to cover long-term care expenses. Furthermore, lower household incomes and the costs of long-term care significantly increase family caregivers’ financial burden (Honda et al., 2025). In China, family caregivers have to manage and pay for the care of patients with chronic diseases. They also lose working hours to earn incomes, leading to serious financial burdens (Miao et al., 2026). Thus, insufficient income among family caregivers across countries results in financial burdens.

Overall, the mean financial burden score of 2.88 out of 4 indicated a medium financial burden for family caregivers. This is possible because every Thai person receives health insurance based on eligibility criteria in Thailand. However, when examining the subscales, many participants reported insufficient incomes to promote the health of family members with chronic illnesses. In addition, they felt they had lost an opportunity to earn income to cover their own expenses. Furthermore, they also did not receive support from the involved health care unit. These findings indicate that family caregivers need financial management and social welfare assistance. Healthcare providers should support family caregivers. For example, preparedness for a long-term care program from hospital to home for dependent stroke survivors should include financial issues with management to be considered to tailor effective health goals for both family caregivers and dependent stroke survivors.

In the MR analyses, family caregivers’ financial management was the most robust predictor of family caregivers’ financial burden, followed by age, social support, educational level, and family caregivers’ income. These findings mean that family caregivers’ financial management was crucial in alleviating their financial burden. A US study supports this relationship showing that cost-of-care links, which were considered financial management, helped reduce significant financial burden for family caregivers (Edward et al., 2023). Additionally, another US study supports this study reporting that family caregivers’ age (older age) was significantly associated with less financial burden (Hart et al., 2025). Furthermore, several previous Chinese studies support this finding, indicating that financial coping strategies or social support were associated with caregivers’ financial burden in patients with chronic illnesses (Wang et al., 2025; M. Zhang et al., 2024). Household income also predicts family caregivers’ financial burden among patients with chronic illnesses (M. Zhang et al., 2024). These findings show that while age, income, and educational level shape a family’s initial financial burden, effective financial management and social support can reduce the financial burden of stroke care.

However, family caregivers’ illness perceptions and non-medical costs were not significant predictors of their financial burden. It is possible that most family caregivers who took care of dependent stroke survivors had no serious stages (e.g., mild diabetes, hypertension, dyslipidemia) of the disease, making them less likely to perceive their own invisible illnesses. Notably, the IPQ-R used to measure illness perceptions yielded a low Cronbach’s alpha. This is possible because the IPQ-R is originally a multi-attribute construct designed to measure illness perceptions (both physical and mental health threats) in persons with chronic illnesses. However, when examining the subscales of the IPQ-R among family caregivers of dependent stroke survivors with no serious illnesses, the reliabilities for the timeline in the acute/chronic phase, emotional perception, and personal control ranged from 0.54 to 0.63. This could mean that family caregivers might not perceive some attributes as significant concerns or active problems, making the total construct of reliability difficult to achieve high internal consistency across these attributes. Due to incomplete data on non-medical costs, some family caregivers struggled to fully track or recall all daily out-of-pocket expenses. This incomplete report affected the outcome of the study.

The findings of this study strongly support the bidirectional relationship concept (Isik et al., 2019), indicating that caregiver burden arises from interactions among patient- and caregiver-related factors. In this study, the patient-related factor creates a financial burden on households and interacts with caregiver-related factors, which directly influence family caregivers’ financial burden.

When looking at correlational analysis, age was not significantly related to family caregivers’ financial burden while it was a significant predictor of family caregivers’ financial burden in the MR analysis. Additionally, the non-medical cost was significantly related to family caregivers’ financial burden but was not a significant predictor of it. This is possible because in the correlational analysis, age might lack a direct correlation. However, its emergence as a significant predictor in the MR model suggests that its effect was previously masked by other socioeconomic factors. Conversely, the non-medical costs were significantly correlated with financial burden. However, they lost their predictive power in the MR model, likely due to incomplete data.

Furthermore, the MR model explained 60.6% of the total variance, demonstrating that family caregivers’ economic outcomes are not shaped by isolated predictors but rather by the dynamic interplay between caregivers’ and patients’ related factors. However, 39.4% of the variance remained unexplained. This unexplained variance could be additional critical unmeasured variables, such as family caregivers and dependent stroke survivors’ daily living activities, the duration of care and specific clinical complications of dependent stroke survivors, and family caregivers’ debts. Adding these variables might help explain better predictors in the future.

Strengths and Limitations

This study demonstrates the value of developing a new questionnaire, “the Financial Burden in Non-Communicable Disease Family Caregiver Scale,” with good internal consistency and acceptable content validity. This questionnaire helps assess the financial burden on family caregivers of dependent stroke survivors. It can also be applied to other patients with other chronic conditions. Furthermore, the additional questionnaires used in this study demonstrate high reliability and validity, thereby strengthening the outcomes of the study.

However, this study had several limitations. First, this study was a cross-sectional study. The relationships between the predictors and family caregivers’ financial burden were measured at a single point in time and did not follow up on each family caregiver’s financial burden over time. Second, participants were recruited from two governmental tertiary care hospitals in Bangkok, Thailand which might limit the generalizability of the findings to private tertiary care hospitals. Third, the IPQ-R questionnaire might be more feasible to administer to populations with severe symptoms or serious comorbidities. Finally, comprehensive direct medical cost data could not be extracted from the hospital databases due to strict privacy regulations under the Thai Personal Data Protection Act.

Implications for Practice

The findings suggest that preparedness for long-term care should include financial management to achieve health goals for both family caregivers and dependent stroke survivors. Healthcare providers, such as nurses, should assess the financial burden during follow-up visits to tailor support.

In terms of financial management, nurses, multidisciplinary teams, and involved organizations or policy makers should systematically collaborate to design structured discharge protocols that address financial matters and illness treatment. Preparing families for the long-term transition from hospital to home requires implementing structured financial counseling, facilitating access to public welfare benefits, and organizing community-based nursing follow-up support to monitor and alleviate the ongoing financial burden on family caregivers.

Recommendations for Future Research

Based on the findings and limitations of this study, several recommendations for future research are proposed. First, future studies should employ longitudinal designs to track the trajectory of financial burden and economic impacts over the long-term course for family caregivers. Second, researchers should incorporate broader socioeconomic and clinical parameters, such as family caregivers’ and dependent stroke survivors’ activities of daily living, the duration of care, specific clinical complications, and family caregivers’ debts, to examine the unexplained variance not accounted for to the current predictive model among dependent stroke survivors. Finally, because this study developed the new questionnaire of the “Financial Burden in Non-Communicable Disease Family Caregiver Scale,” future research should validate it with other chronic disease populations in private or community hospitals.

Conclusions

This study highlights that dependent stroke survivors’ family caregivers faced a significant financial burden. The family caregiver’s financial management was the strongest factor in reducing the financial burden. Other predictors, including age, educational level, income, and social support, also played important roles in financial burden. The family caregivers’ financial burden should thus be a top priority for the organization or the national healthcare policy, with a focus on supporting them. The bidirectional relationship concept was appropriate for guiding explanations of how patient and family caregiver factors affected family caregivers’ financial burden. Healthcare providers should go beyond medical treatment and offer financial education and long-term support programs for family caregivers. With improved financial management, the financial burden could be reduced, thereby improving the overall quality of care for dependent stroke survivors.

Footnotes

Acknowledgments

This study was conducted at the Faculty of Medicine Ramathibodi Hospital, Mahidol University and the Faculty of Medicine Vajira Hospital, Navamindradhiraj University. Our sincere gratitude goes to all participants and staff for their valuable support and contributions to this research study.

ORCID iDs

Surachet Boonchokanan

Sirirat Leelacharas

Jiraporn Lininger

Ethical Considerations

This study received approval from the Human Research Ethics Committee, Faculty of Medicine Ramathibodi Hospital, Mahidol University (COA. No.MURA2023/785) and the Institutional Review Board, Faculty of Medicine Vajira Hospital at Navamindradhiraj University (COA. No.021/2567). All procedures were conducted in accordance with the principles outlined in the Helsinki Declaration, and informed consent was obtained from all participants.

Author’s Contribution

S.B. and S.L. initiated and conceptualized the study. S.B. and S.L. conducted the research design and measurements. S.B. collected and secured data. S.B. and S.L. checked, analyzed, interpreted data, discussed and critiqued the results based on theories. S.B. and S.L. completed all references. S.B. and S.L. wrote and edited all parts of the manuscript. S.B., S.L., and J.L. reviewed and approved the final version of the manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The dataset generated and analyzed during the current study is available from the corresponding author upon a reasonable request.*

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