Factors influencing the well-being of elderly population in home care mode and optimization research

Abstract

This study aims to explore the changes in well-being of the elderly population in the Guangdong-Hong Kong-Macao Greater Bay Area in terms of physical health, mental state, daily activity capability, and social interaction before and after receiving home care, as well as the main issues and challenges in the implementation of home care services. By collecting 800 valid responses through a self-designed questionnaire, dimensions including chronic disease management, daily activity capability, mental state, and social interaction were assessed. Data analysis was conducted using SPSS 26.0. The study found that the scores of the elderly in mental state and social interaction significantly improved after home care, while the scores for chronic disease management and daily activity capability slightly decreased. Additionally, the study explored the influence of different regions, genders, and economic levels on the effectiveness of home care. The results indicate that elderly individuals in the high-income group and economically developed cities showed more significant improvements in mental state and social interaction after home care, while those in the low-income group and economically disadvantaged areas showed less improvement in these aspects. Gender differences also manifested in the effectiveness of home care, with female elderly individuals showing more noticeable improvements in mental state and social interaction. These findings emphasize the necessity of developing personalized and diversified home care strategies to better meet the needs of elderly individuals from various backgrounds.

Introduction

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is experiencing a significant demographic shift as population aging accelerates. Although rapid economic development and improvements in medical care have contributed to extended life expectancy, these changes also intensify pressures on elderly care systems, particularly within a region characterized by pronounced cultural, institutional, and socio-economic heterogeneity^1,2. Differences across Hong Kong, Macao, and Guangdong shape distinct expectations, lifestyles, and resource accessibility for older adults, creating uneven elderly care demands and outcomes across the GBA^3,4. In this context, establishing a sustainable system that supports the well-being of older adults has become a core strategic objective for regional social governance.

Home care has emerged as a key model to address aging, as it allows older adults to maintain autonomy and emotional security in familiar domestic settings while receiving necessary support^5,6. Over the past decades, home care has evolved globally from informal family-based support to professional and diversified care models⁷. However, implementation patterns vary widely internationally due to differences in welfare regimes and social structures⁸. For example, Nordic countries incorporate home care into state-led welfare systems and emphasize professional medical support and social participation⁹, whereas the United States relies more heavily on private and nonprofit organizations¹⁰. China has formed distinctive family-centered home care approaches, such as the 9073 and 9064 models, which emphasize the primary role of families and communities while selectively integrating professional services¹¹. More recently, innovations such as “Internet + elderly care” and community-based medical–social integration have been proposed to further expand the scope of home care services^12–14.

Within the GBA, home care has transitioned from traditional family-driven support to complex hybrid models involving governments, communities, and private providers^15,16. Nevertheless, disparities in resource allocation, service quality, caregiver availability, and technological adoption remain obstacles to the development of equitable care systems^17–19. Understanding how home care affects the well-being of the elderly in the GBA therefore requires a conceptual structure that can capture both the diversity of service environments and the multidimensional nature of elderly well-being.

To achieve this, the present study draws on Aging Society Theory, Welfare Mix Theory, and Social Support Network Theory to construct an analytical framework for evaluating the impacts of home care. Aging Society Theory suggests that the well-being of older adults depends not only on maintaining physical health but also on supporting long-term functional capability in daily life. Welfare Mix Theory emphasizes that elderly care outcomes are shaped by the joint influences of families, governments, markets, and communities. Social Support Network Theory highlights the importance of emotional ties and social participation for psychological well-being in later life.

These theoretical perspectives converge to operationalize elderly well-being into four interrelated dimensions:

1. physical health (e.g., chronic disease management), representing the biological foundation of aging;

2. mental state, reflecting psychological resilience and emotional balance;

3. daily activity capability, indicating functional independence and self-care ability;

4. social interaction, representing connectedness and participation in social life.

Together, these dimensions capture the interplay of biological, psychological, functional, and social aspects of aging, offering a systematic foundation to evaluate the impact of home care.

Against this theoretical and practical backdrop, the purpose of this study is to investigate the influence of home care on the well-being of elderly individuals in the Guangdong–Hong Kong–Macao Greater Bay Area. Specifically, this research examines how elderly well-being changes before and after receiving home care across the four dimensions identified above and further analyzes heterogeneity in care outcomes by region, economic status, and gender. By integrating empirical evidence with a multidimensional theoretical structure, this study contributes to a deeper understanding of how home care functions in a highly diverse socio-economic environment. The findings aim to provide actionable insights for optimizing home care policies and service delivery, strengthening resource allocation, and promoting inclusive and high-quality aging support within the Greater Bay Area and beyond.

Data sources and research tools

Theoretical foundation

The present study draws on three complementary theoretical perspectives to construct a multidimensional analytical framework for understanding how home care influences elderly well-being in the Guangdong–Hong Kong–Macao Greater Bay Area. Rather than treating well-being as a single outcome, the combination of Aging Society Theory, Welfare Mix Theory, and Social Support Network Theory provides a systematic basis for operationalizing elderly well-being into four key dimensions—physical health, mental state, daily activity capability, and social interaction—which guide the research design, variable selection, and interpretation of empirical patterns. To further strengthen conceptual coherence, this study explicitly links these theories to the four analytical dimensions: Aging Society Theory underpins the dimensions of physical health and daily activity capability, Social Support Network Theory justifies the inclusion of mental state and social interaction, and Welfare Mix Theory explains how differences in institutional and care arrangements shape variations across all four dimensions. Together, these frameworks collectively substantiate why the study evaluates well-being through these specific four dimensions.

1. Aging Society Theory.

   Aging Society Theory emphasizes that population aging brings structural changes to social and health systems and highlights the need to sustain quality of life in later life amid rising longevity²⁰. The theory stresses two core aspects: maintaining physical health in the face of chronic disease and preserving functional independence necessary for daily living²¹. Accordingly, this study incorporates physical health (e.g., chronic disease management) and daily activity capability as two primary dimensions of elderly well-being. These dimensions reflect the theory’s central proposition that well-being in aging societies depends not only on medical support but also on the ability of older adults to function independently within their everyday environments. In the context of the Greater Bay Area, where life expectancy has increased and the prevalence of chronic conditions is rising, Aging Society Theory provides a theoretical rationale for examining how home care services influence these two dimensions.

2. Welfare Mix Theory.

   Welfare Mix Theory posits that social welfare outcomes arise from the interplay among the state, markets, nonprofit organizations, and families²². Home care systems therefore vary depending on how responsibilities and resources are distributed among these actors. In the Guangdong–Hong Kong–Macao Greater Bay Area, substantial differences in welfare regimes, service markets, public support, and family caregiving traditions lead to differentiated home care models across cities. Guided by this theory, the present research assumes that the effectiveness of home care is influenced by the capacity and coordination of multiple actors in the care ecosystem. Therefore, analyzing changes in daily activity capability and physical health across different regional and economic contexts helps reveal how different welfare configurations shape the performance of home care services. Welfare Mix Theory thus supports the comparative aspect of the study, linking variations in institutional arrangements to disparities in elderly well-being outcomes.

3. Social Support Network Theory.

   Social Support Network Theory highlights the importance of emotional support, interpersonal connections, and social participation for maintaining psychological well-being and physical health among older adults²³. From this perspective, home care functions not only as a service delivery approach but also as a mechanism for sustaining social interaction and preventing social isolation. Based on this theory, the study incorporates mental state and social interaction as essential dimensions of elderly well-being, as they capture the psychosocial foundations of quality of life in later life. Activities organized by caregivers, community initiatives, peer engagement opportunities, and continued family involvement can strengthen social networks, which in turn contribute to improved emotional stability and social participation. Social Support Network Theory therefore explains why home care services are expected to affect these two dimensions and provides the theoretical basis for measuring them.

By integrating Aging Society Theory, Social Support Network Theory, and Welfare Mix Theory, this study establishes a unified theoretical framework that supports its multidimensional assessment of elderly well-being. Aging Society Theory provides the basis for examining physical health and daily activity capability, Social Support Network Theory informs the inclusion of mental state and social interaction, and Welfare Mix Theory explains the heterogeneity of home care outcomes across different regions, economic groups, and family structures. Together, these theoretical pillars ensure that the four dimensions of well-being under investigation are not arbitrarily selected but grounded in established scholarly perspectives on aging, welfare provision, and social connectedness, thereby enabling a systematic and comprehensive exploration of how home care influences the well-being of elderly individuals within the socio-economic and cultural diversity of the Guangdong–Hong Kong–Macao Greater Bay Area.

Data sources

Research subjects and method

This study aims to explore the well-being changes of elderly individuals in the Guangdong-Hong Kong-Macao Greater Bay Area under a home care model. To achieve this, we have designed a systematic and rigorous sampling and data collection scheme to ensure that the research subjects are highly representative and widely applicable. The study focuses primarily on four representative cities within the Greater Bay Area: Guangzhou, the Macao Special Administrative Region, Zhuhai, and Foshan. These cities differ significantly in terms of economic development levels, cultural backgrounds, resident compositions, and lifestyles. Therefore, by selecting communities from these four cities, we can comprehensively reflect the living conditions and care needs of the elderly under various socio-economic contexts.

First, regarding city selection, Guangzhou, as a typical metropolis, offers communities that exemplify a bustling and highly modern urban lifestyle. The communities in the Macao Special Administrative Region, on the other hand, combine unique historical and cultural heritage with distinctive urban characteristics, thereby reflecting the lives of elderly individuals in a multicultural environment. Meanwhile, Zhuhai and Foshan, as rapidly developing cities in recent years, showcase how elderly people adapt to urban transformation, shifting lifestyles, and evolving care services in the context of rapid economic growth. By selecting these four cities, our study strives to cover a diverse range of urban areas within the Greater Bay Area, ensuring that the findings are both broadly generalizable and representative.

In the specific process of sample selection, we first used a grid management system to delineate and screen communities within each city. In each city, we randomly selected 10 communities, each of which holds a certain degree of geographical representativeness and covers a range of economic levels, different resident structures, and diverse lifestyles. Subsequently, within each selected community, we randomly chose 50 households, resulting in a total of 2,000 households as the preliminary pool of potential research subjects. To guarantee the quality of the sample and the validity of the data, we set clear inclusion and exclusion criteria for all potential subjects. The inclusion criteria required that participants be aged 65 or above, have resided in the selected community for no less than three years, and have received home care services provided by the community at least once in the past year. The exclusion criteria eliminated elderly individuals who required long-term hospitalization due to major illnesses, those who were unable to communicate effectively due to cognitive impairment, hearing or vision disabilities, or language expression disorders, as well as individuals suffering from severe mental illnesses or those undergoing treatments that might significantly affect their psychological or physical health. Additionally, elderly individuals who planned to relocate from the community were also excluded. This rigorous screening process not only ensured the stability of the sample but also guaranteed the authenticity and continuity of the information collected during the data gathering process.

During the actual survey process, we employed a single-group pre-post study design to comprehensively capture the changes in well-being before and after the elderly began receiving home care services. Specifically, our research team conducted a baseline survey in the month when the elderly subjects first started receiving home care, thoroughly documenting their health status, quality of life, and other relevant variables. Then, after the subjects had continuously received home care services for 12 months, we conducted a follow-up survey on the same group of elderly individuals, thereby obtaining paired pre- and post-intervention data. This design allowed us to comparatively analyze the medium-term impact of home care on various dimensions of well-being, including physical, psychological, and social aspects. Data collection was primarily conducted using a structured questionnaire, and the same questionnaire was used in both the initial and follow-up surveys to ensure consistency and comparability of the data.

Out of the initial pool of 2,000 households, after preliminary screening and further verification, we ultimately distributed 1,000 questionnaires to the eligible households. Through stringent data recovery and cleaning processes, we finally obtained 800 valid pairs of pre- and post-test questionnaires, yielding an effective response rate of 80%. This response rate is quite considerable among the elderly population, indicating that the sample data are both reliable and representative. The primary reasons for dropout included withdrawal of consent, relocation from the community, health complications that prevented follow-up, and incomplete data submissions.

It should be noted that although the sample in this study is primarily drawn from urban communities and does not cover rural or remote elderly populations, the selected sample exhibits a high degree of diversity and representativeness in terms of gender ratio, age distribution, educational background, and economic status. Thus, the data from these 800 subjects not only provide a solid empirical basis for analyzing the impact of home care on the well-being of the elderly but also serve as a reference for the subsequent promotion and improvement of home care services in similar urban environments. In summary, the rigorous sample selection process, the multi-stage random sampling strategy, and the high questionnaire recovery rate all provide ample data support and theoretical foundation for the conclusions of this study, thereby enhancing the practical applicability and value of the research findings.

Description of home care services

The home care service model assessed in this study is an integrated, multi-tiered system designed to support the overall well-being of elderly individuals residing in the community. This model is structured around three primary components: daily living assistance, medical care services, and psychosocial support.

1. Program Structure: Daily living assistance provides support with routine tasks including bathing, dressing, meal preparation, and other activities of daily living. These tasks are primarily undertaken by family caregivers, who play a central role in maintaining functional independence among elderly individuals. Formal professional support is added through medical care services, such as health monitoring, chronic disease management, medication supervision, and scheduled consultations with healthcare professionals. Complementing these components, psychosocial support is delivered primarily through community-based initiatives, including organized social activities, recreational programs, intergenerational activities, and counseling services aimed at enhancing emotional well-being and social participation. These initiatives include organized social activities, recreational events, and counseling sessions, all aimed at enhancing emotional well-being and promoting social engagement. These three components map directly onto the outcome dimensions assessed in this study: daily living assistance corresponds to daily activity capability; medical services relate to physical health; while psychosocial support corresponds to mental state and social interaction.

2. Service Frequency: Home care services are delivered at varying intervals depending on individual needs. Family caregivers provide continuous daily support to maintain essential self-care and household functioning. Professional healthcare services are delivered on a weekly or bi-weekly basis based on personalized care plans, while community organizations typically schedule psychosocial programs on a weekly or monthly basis. This stratified frequency design ensures that urgent physical and functional needs receive uninterrupted support, while mental health and social needs are met through regular but non-intrusive engagement opportunities.

3. Duration: The intervention period in this study spans 12 months. Baseline data were collected when home care services commenced, followed by a post-assessment after one full year of continuous service delivery. This single-group pre-post design is well suited for capturing medium-term changes in elderly well-being. The 12-month timeframe also reduces bias from short-term fluctuations in physical or psychological status, offering greater validity in evaluating changes across the four dimensions of well-being.

4. Service Providers: The integrated home care model is jointly supported by three key actors: family members, community care organizations, and professional healthcare institutions. Family members provide personalized and continuous assistance; community organizations supplement informal care by offering social enrichment and community-based interventions; and professional healthcare providers deliver specialized medical services and periodic evaluations. The collaboration among these actors reflects the mixed-welfare structure of elderly care in the Greater Bay Area, where responsibilities for maintaining physical health, psychological resilie.

Overall, the home care service model evaluated in this study represents a balanced blend of informal and formal care. By leveraging the strengths of family support, community resources, and professional expertise, this model offers a comprehensive solution to meet the multifaceted needs of the aging population. This detailed description of the program structure, service frequency, duration, and service providers provides readers with a clear understanding of the nature and scope of the home care services being assessed.

Transparency and openness

This study upholds the principles of accessible and open research. To facilitate replication and further investigation, we hereby affirm that the de-identified data supporting our conclusions are available. These data can be accessed through the following link [E-mail: XXXXXX]. This initiative ensures that our research processes are transparent and that our findings can contribute significantly to the broader scientific community’s efforts in understanding the well-being of the elderly population in home care settings. This study was conducted with the approval of the Ethics Committee of XXXX. All participants signed an informed consent form. All experiments were conducted in accordance with the guidelines and regulations of the Declaration of Helsinki. Our procedures were developed to ensure the utmost respect for participant privacy and data protection, aligning with both legal and ethical standards.

Research tools

General information questionnaire

We utilized a general information questionnaire to collect basic demographic information from participants, covering key information such as age, gender, education level, marital status, and location. Specifically, we selected gender, location, and economic status as the main control variables in the study. Controlling for gender allows for a more accurate assessment of the impact of home care on elderly individuals of different genders, considering potential differences in needs and responses. Location as a control variable allows us to analyze and understand the impact of different geographical locations on the effectiveness of home care, considering socioeconomic differences and uneven resource distribution among regions. Additionally, incorporating economic status as a primary control variable and categorizing participants into high-income and low-income groups further enriches our analytical dimensions. This enables us to delve into how economic conditions affect the acceptance of home care and the effectiveness of care services for the elderly. Through meticulous collection of demographic data, we can provide a more comprehensive and in-depth analytical foundation for subsequent research.

Weight design

We employed a questionnaire survey method to determine the relative importance of the following indicators: primary indicators including physical health and psychological and social well-being^24,25. Secondary indicators encompass chronic disease management, daily activity capability, mental state, and social interaction^26–29. These four secondary indicators were assessed using the Likert 5-point scale, with scores ranging from 1 (very unimportant) to 5 (very important)³⁰. The average score for each question was calculated to obtain the average importance score for each indicator. Subsequently, by dividing the average score of each indicator by the sum of average scores of all indicators, we calculated the relative weights of each indicator and standardized the weights to ensure their sum equals 1. This method intuitively and effectively captures respondents’ subjective views on the importance of each indicator, laying the foundation for further analysis.

Self-designed questionnaire

The self-designed “Guangdong-Hong Kong-Macao Greater Bay Area Elderly Home Care Well-being Assessment Questionnaire” is the core component of this study. Firstly, the Resident Assessment Instrument (RAI) for Long-Term Care Facilities, developed by Morris et al. in 1994, is used to assess the health and functional status of long-term care facility residents³¹. The Activities of Daily Living (ADL) scale, created by Sidney Katz and colleagues in the 1960s, primarily evaluates individuals’ ability to perform daily activities independently³². The Geriatric Depression Scale (GDS), designed by Yesavage et al. in 1983, is specifically used to assess depressive symptoms in the elderly³³. The SF-36 Health Survey, developed by Ware and Sherbourne in 1992, covers 8 dimensions of health status³⁴. Lastly, the Mini-Mental State Examination (MMSE), developed by Folstein et al. in 1975, is used to evaluate cognitive impairments³⁵. The questionnaire revolves around two primary indicators—physical health and psychological and social well-being, each of which is further divided into two secondary indicators. Specifically, the secondary indicators of physical health include chronic disease management and daily activity capability, while those for psychological and social well-being include mental state and social interaction. Eight questions are designed for each secondary indicator, totaling 32 questions, covering various aspects of elderly individuals in the home care environment. These questions are designed using the Likert 5-point scale, with scores ranging from 1 (very dissatisfied) to 5 (very satisfied). This scoring method enables us to quantify elderly individuals’ satisfaction and perceptions of home care services, with higher scores indicating higher levels of well-being in the respective dimensions.

Questionnaire reliability and validity test

Data entry and analysis were conducted using SPSS 26.0. The questionnaire data were weighted using the relative weights of each dimension (such as chronic disease management, daily activity capability, mental state, and social interaction) obtained through the questionnaire survey, multiplied by the corresponding scores of each dimension in the questionnaire. The weighted data, combined with the original scores and the importance of the respective parts, generated a comprehensive score reflecting the overall performance of respondents across the entire questionnaire. The overall Cronbach’s alpha for the questionnaire was 0.869, indicating good internal consistency reliability. The test-retest reliability was 0.870, also falling within the range of 0.8–0.9. The overall Kaiser-Meyer-Olkin (KMO) measure was 0.937, well above the threshold of 0.7, and the Bartlett’s sphericity test yielded a significance value of 0.000, less than 0.05, indicating a good fit for approximate chi-square, degrees of freedom, and significance. The results of the questionnaire reliability and validity test were satisfactory, allowing for the use of the survey data for empirical analysis. Normality test results indicated that the data followed a skewed distribution, hence Wilcoxon signed-rank test, Kruskal-Wallis H test, and Mann-Whitney U test were employed to analyze the data. These non-parametric statistical methods were selected because they do not assume a normal distribution of the data, making them ideal for analyzing skewed or ordinal data, which is common in survey responses. The Wilcoxon signed-rank test was used to compare score changes before and after home care in dimensions such as chronic disease management, daily activity capability, psychological state, and social interaction. This test was chosen because it is appropriate for paired, non-normally distributed data, enabling us to assess the median differences in scores over time reliably. The Kruskal-Wallis H test was applied to analyze differences in home care effects among different cities. This test is well-suited for comparing more than two independent groups without assuming normality, thereby providing a robust method to detect differences in central tendencies across diverse urban settings. The Mann-Whitney U test was used to explore score differences among different economic level groups. This test is ideal for comparing two independent samples when the data do not meet the assumptions required for parametric tests, ensuring that the conclusions regarding group differences are both reliable and valid. A significance level of p < 0.05 was considered statistically significant for all analyses.

Questionnaire evaluation, weighting methodology, and statistical analysis framework

Questionnaire evaluation

To ensure the scientific rigor and reliability of the instrument used in this study, we conducted a comprehensive psychometric evaluation of the self-developed “Guangdong-Hong Kong-Macao Greater Bay Area Elderly Home Care Well-being Assessment Questionnaire.” The evaluation focused on three dimensions: internal consistency reliability, test-retest reliability, and construct validity³⁶. Internal consistency reliability was assessed using Cronbach’s alpha. The overall alpha value for the 32-item scale was 0.869, indicating high reliability and homogeneity of the measurement items. This suggests that the questionnaire items are internally cohesive and reliably measure the same underlying constructs across the four domains. Test-retest reliability, calculated based on a subset of participants who completed the same questionnaire twice within a 2-week interval, was 0.870. This score demonstrates high temporal stability and suggests that the questionnaire yields consistent results over time. Construct validity was verified using the Kaiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity. The KMO value was 0.937, which is considered “excellent” and indicates that the data are suitable for factor analysis. Bartlett’s test yielded a significance value of p < 0.001, confirming the presence of underlying factor structures in the dataset. These psychometric results confirm that the questionnaire is a valid and reliable instrument for assessing changes in well-being among elderly individuals in a home care setting.

Composite scoring and weighting methodology

The composite well-being score was calculated using a weighted scoring approach that integrates subjective importance with empirical performance. Based on a prior weight design procedure (Sect. 2.3.2), each of the four secondary indicators—chronic disease management, daily activity capability, mental state, and social interaction—was assigned a relative weight derived from average Likert-scale importance ratings. The final score for each respondent was computed by multiplying each dimension’s score by its respective weight and summing the results. This method enhances interpretability by aligning final scores with participants’ perceived importance of different well-being components.

Statistical analysis strategy

To examine the effects of home care on well-being outcomes and explore differences across subgroups (e.g., cities, genders, income levels), we employed a suite of non-parametric statistical methods, as the normality tests indicated skewed data distributions for most dimensions. The statistical approach is structured as follows:

Wilcoxon Signed-Rank Test: Used for comparing paired scores (before and after home care) across the four dimensions. This non-parametric alternative to the paired t-test is robust for ordinal and skewed data, offering reliable median comparisons.

Kruskal-Wallis H Test: Employed to assess inter-group differences across multiple cities. As a rank-based test, it allows for comparison among more than two independent groups without assuming normality or equal variances.

Mann-Whitney U Test: Applied to compare two independent groups, particularly across gender and economic strata. This test identifies whether the distributions of scores differ significantly between subpopulations.

All statistical tests were conducted at a significance level of p < 0.05. These analyses were carried out using SPSS version 26.0, and results are reported alongside test statistics (e.g., Z-values, U-values, H-values) and exact p-values in the Results section.

This integrated statistical strategy ensures rigor in hypothesis testing and accommodates the ordinal, skewed nature of survey data—thereby enhancing the robustness and interpretability of the empirical results.

Results

Basic characteristics of survey participants

A total of 800 elderly individuals completed the survey. In terms of gender distribution, females accounted for a larger proportion, with 585 individuals (73.1%), while males numbered 215 individuals (26.9%). The age of the participants ranged from 65 to 90 years, with an average age of (74.26 ± 5.35) years. Regarding marital status, there were 464 married individuals (58%), 40 unmarried individuals (5%), 56 divorced individuals (7%), and 240 widowed individuals (30%). Regarding educational level, 560 individuals had a college education or below (70%), 192 individuals had a bachelor’s degree (24%), and 48 individuals had a master’s degree or above (6%) (Fig. 1).

Fig. 1.

Basic characteristics of survey participants.

Comparison of weights across four dimensions

When analyzing the changes in elderly individuals’ perceptions of four key dimensions (chronic disease management, daily activity capability, mental state, and social interaction) before and after receiving home care, we identified a series of significant data trends revealing shifts in the importance attached to various aspects of quality of life. Firstly, the average score for chronic disease management declined from 4.35 to 3.89, and its weight decreased from 0.28 to 0.24. This marked decline suggests that after receiving home care, elderly individuals may place relatively less emphasis on chronic disease management and more on other dimensions such as psychological well-being and social interaction. One plausible explanation is that the comprehensive nature of home care services, which integrate family, community, and professional support, not only addresses specific health issues but also enhances overall well-being through improved daily living support and emotional care. Additionally, external factors—such as natural adaptation to chronic conditions, previous experiences with medical treatments, and evolving self-perceptions of health—may also contribute to the lower prioritization of disease management. Thus, while the decrease in chronic disease management scores likely reflects a beneficial rebalancing of focus toward broader aspects of quality of life, it is important to consider that these scores might also be influenced by factors beyond the scope of the home care services themselves. Next, we noticed a slight decrease in the weight of daily activity capability, decreasing from 0.25 to 0.24, with the average score decreasing from 3.92 to 3.74. This suggests that while elderly individuals perceive home care to have an impact on maintaining daily activity capability, it is not their primary concern. More significantly, in terms of mental state, the average score increased from 3.76 to 3.98, with the weight increasing from 0.24 to 0.26. On the dimension of social interaction, there was a significant increase, with the average score increasing from 3.47 to 4.25, and the weight increasing from 0.22 to 0.25 (Fig. 2). The significant improvement in these two dimensions clearly indicates that after receiving home care, elderly individuals place greater emphasis on mental health and social interaction. This may be because home care provides more emotional support and social opportunities, enabling elderly individuals to better maintain their mental health and social connections within the home environment. Overall, these data emphasize the importance of home care in the lives of elderly individuals, particularly in terms of mental health and social participation. The relatively lower attention paid to chronic disease management and daily activity capability, along with the heightened emphasis on mental state and social interaction, reflects their demand for an overall improvement in quality of life.

Fig. 2.

Comparison of weight changes across four dimensions.

Comparison of questionnaire scores across four dimensions

The changes in questionnaire scores across four dimensions before and after receiving home care among the elderly objectively demonstrate the specific effects of home care. The data shows that in terms of chronic disease management, the average score before home care was 6.48, which slightly decreased to 6.24 after care, although this decrease is statistically significant (P values are all 0), the magnitude of change is small. This may reflect the continued attention to chronic disease management under home care, although the focus may have shifted to more comprehensive improvement in quality of life. In contrast, the score for daily activity capability increased from 5.76 before care to 6.25 after care, with a Z value of -7.79, indicating a significant improvement, demonstrating that home care has a positive impact on improving the self-care ability and daily functionality of the elderly. The change in scores for mental state is more significant, increasing from 4.99 to 6.65, with a Z value of -20.60. This significant change emphasizes the important role of home care in improving the mental well-being of the elderly, possibly related to increased emotional support and social activities. In terms of social interaction, home care has a significant positive impact on the elderly. The score increased significantly from 4.68 before care to 6.56 after care, with a Z value of -22.28 (Fig. 3), indicating that home care significantly improves the social ability and participation of the elderly. This may be because home care provides more opportunities for social interaction, such as community activities and interest groups, thereby enhancing the social participation and satisfaction of the elderly. These data reveal the significant impact of home care on the quality of life of the elderly across different dimensions, particularly in improving mental state and social interaction.

Fig. 3.

Comparison of score changes across four dimensions.

Before home care, the overall questionnaire score for the elderly was 21.91 points. However, after receiving home care, this score significantly increased to 25.69 points (Fig. 4). This increase in score indicates a significant positive impact of home care on the overall quality of life for the elderly. With a Z value of -16.183, this change is highly significant. The P value is 0.000, further confirming the statistical significance of this change. This result emphasizes the importance of home care in improving the quality of life for the elderly. It may encompass improvements in various aspects ranging from physical health to psychological well-being and social interaction. It underscores the critical role of home care in the well-being of the elderly and how different intervention measures can enhance their overall quality of life.

Fig. 4.

Changes in overall questionnaire scores.

Contrasting regional disparities

Tables 1 and 2 provide comprehensive data for analyzing the score changes in various dimensions before and after home care in different cities, along with their comparisons. Specifically, Table 1 shows that after home care, the scores in Guangzhou increased by 1.114, 1.108, 2.489, and 2.496 points in chronic disease management, daily activity ability, psychological state, and social interaction, respectively. The score increments in Macau SAR were 0.488, 0.545, 2.057, and 2.055 points. Zhuhai and Foshan saw score increases of 1.162, 1.273, 0.863, and 0.873 points, and 1.136, 1.167, 0.771, and 0.773 points, respectively, in these four dimensions (Table 1). The statistical significance of score changes before and after home care was highly significant for all cities across the four dimensions, with Z values ranging from − 3.459 to -6.457 and P values being 0.000 in all cases, indicating statistically significant score changes. Particularly significant improvements were observed in psychological state and social interaction in Guangzhou and Macau SAR, possibly due to the advantages these cities have in social support, cultural activities, and the quality of home care services.

Table 1.

Differences within the region.

City	Statistical indicator	Chronic disease management	Daily activity capability	Psychological state	Social interaction
Guangzhou	Before home care	6.132	6.214	5.978	6.043
	After home care	7.246	7.322	8.467	8.539
	Z-value	− 5.724	− 5.638	− 6.457	− 6.391
	P-value (two-tailed)	0.000	0.000	0.000	0.000
Macau	Before home care	6.301	6.287	5.886	5.947
	After home care	6.789	6.832	7.943	8.002
	Z-value	− 4.913	− 4.876	− 6.118	− 6.055
	P-value (two-tailed)	0.000	0.000	0.000	0.000
Zhuhai	Before home care	6.359	6.416	6.121	6.189
	After home care	7.521	7.689	6.984	7.062
	Z-value	− 6.162	− 6.273	− 5.816	− 5.911
	P-value (two-tailed)	0.000	0.000	0.000	0.000
Foshan	Before home care	6.178	6.261	5.982	6.054
	After home care	7.314	7.428	6.753	6.827
	Z-value	− 5.936	− 6.167	− 5.771	− 5.673
	P-value (two-tailed)	0.000	0.000	0.000	0.000

Table 2.

Differences between regions.

	Dimension	Guangzhou	Macau	Zhuhai	Foshan	Kruskal-Wallis H(K) value	Degrees of freedom	Asymptotic significance (P-value)
Before home care	Chronic disease management	6.132	6.301	6.359	6.178	12.340	3	0.006
	Daily activity capability	6.214	6.287	6.416	6.261	11.211	3	0.010
	Psychological state	5.978	5.886	6.121	5.982	10.471	3	0.015
	Social interaction	6.043	5.947	6.189	6.054	11.982	3	0.007
After home care	Chronic disease management	7.246	6.789	7.521	7.314	15.473	3	0.000
	Daily activity capability	7.322	6.832	7.689	7.428	16.357	3	0.000
	Psychological state	8.467	7.943	6.984	6.753	18.022	3	0.000
	Social interaction	8.539	8.002	7.062	6.827	17.681	3	0.000

Table 2 reveals the score differences among different cities in these dimensions before and after home care. Before home care, the Kruskal-Wallis H (K) value for chronic disease management was 12.340, with 3 degrees of freedom and a P value of 0.006, indicating significant statistical differences in scores among the four cities in this dimension. Similarly, after home care, the significance of score differences increased, with the Kruskal-Wallis H (K) value for chronic disease management rising to 15.473 and the P value dropping to 0.000, suggesting more pronounced differences among cities after home care. These data suggest that although all cities showed improvement after home care, the extent of score improvement varied significantly among different cities. Guangzhou and Zhuhai showed particularly significant improvements in psychological state and social interaction, possibly reflecting the advantages of these cities in the effectiveness and accessibility of home care services. Despite lower score increases, Macau SAR and Foshan still exhibited significant improvements, indicating the positive impact of home care in these cities as well. Combining the data from Tables 1 and 2, we can conclude that home care services have a universal and significant effect on improving the quality of life for the elderly in terms of chronic disease management, daily activity ability, psychological state, and social interaction. Moreover, the differences in score improvements among cities may reflect disparities in resource allocation, service quality, social, and cultural structures in providing home care services.

Contrasting gender differences

Tables 3 and 4 provide a detailed perspective on how gender influences the effectiveness of home care across different dimensions and reveal significant differences between genders. In Table 3, the score increases for males in chronic disease management, daily activity ability, psychological state, and social interaction before and after home care are 1.362, 1.365, 0.458, and 0.464 points, respectively. For females, the score increases in the same dimensions are 1.182, 1.183, 2.780, and 2.824 points, respectively. The significant increase in scores for females in psychological state and social interaction suggests that home care services are particularly effective for females in terms of psychological and social support. This is also reflected in the Z values, with males having Z values of -3.459 and − 3.512 for psychological state and social interaction, respectively, while females have Z values of -6.784 and − 6.829, with P values of 0.000 in all cases, indicating statistically significant changes. Table 4 provides further details from the perspective of gender differences. Before home care, although the differences in scores between males and females in chronic disease management and daily activity ability were not significant (with P values of 0.215 and 0.304, respectively), females lagged slightly behind males in psychological state and social interaction (scores of 5.892 and 5.917 compared to males’ 5.940 and 5.973), although these differences were not statistically significant (with P values of 0.029 and 0.080, respectively). However, after home care, gender differences became more significant, especially in psychological state and social interaction dimensions. The score increases for females were significantly higher than those for males (P values less than 0.001), indicating that females may derive greater benefits in these dimensions after home care. Through the comparison of these two tables, we can conclude that home care services are universally effective in improving chronic disease management and daily activity ability, while gender differences become more pronounced in psychological state and social interaction after home care. Particularly for females, home care seems to provide more support in psychological and social aspects. The discovery of these gender differences can guide home care service providers to consider gender-specific needs in service design to ensure that all recipients maximize their benefits.

Table 3.

Comparison of differences before and after home care for males and females respectively.

Gender	Statistical indicator	Chronic disease management	Daily activity capability	Psychological state	Social interaction
Male	Before home care	6.184	6.256	5.940	5.973
	After home care	7.546	7.621	6.398	6.437
	Z-value	− 6.342	− 6.421	− 3.459	− 3.512
	P-value (two-tailed)	0.000	0.000	0.000	0.000
Female	Before home care	6.207	6.273	5.892	5.917
	After home care	7.389	7.456	8.672	8.741
	Z-value	− 5.943	− 6.013	− 6.784	− 6.829
	P-value (two-tailed)	0.000	0.000	0.000	0.000

Table 4.

Differences between genders in the same dimension.

	Dimension	Male	Female	Mann-Whitney U-value	Wilcoxon W-value	Z-value	Asymptotic significance (P-value)
Before home care	Chronic disease management	6.184	6.207	19,285	39,915	− 0.584	0.215
	Daily activity capability	6.256	6.273	19,170	38,030	− 0.442	0.304
	Psychological state	5.94	5.892	19,302	37,898	− 1.361	0.029
	Social interaction	5.973	5.917	19,472	38,105	− 0.637	0.080
After home care	Chronic disease management	7.546	7.389	19,450	39,750	− 0.754	0.453
	Daily activity capability	7.621	7.456	19,560	39,640	− 0.852	0.395
	Psychological state	6.398	8.672	18,701	39,540	− 5.954	0.000
	Social interaction	6.437	8.741	18,540	39,660	− 5.987	0.000

Contrasting differences in economic levels

Tables 5 and 6 provide detailed data on the score changes across four dimensions (chronic disease management, daily activity ability, psychological state, social interaction) before and after home care for elderly individuals in different economic level groups (high-income and low-income). From the data in Table 5, it can be observed that both high-income and low-income groups experienced significant improvements in scores across all four dimensions after home care. For instance, in chronic disease management, the score for the high-income group increased from 6.282 to 7.563, while for the low-income group, it increased from 6.157 to 6.841. In terms of social interaction, the score for the high-income group increased from 6.478 to 7.756, and for the low-income group, it increased from 6.356 to 7.038. This indicates that home care is universally effective in enhancing the well-being of elderly individuals, regardless of their economic status. The P values for all dimensions were 0.000, indicating statistical significance for these changes. However, Table 6 reveals significant differences between different economic levels. Before home care, the high-income group had slightly higher scores than the low-income group across all four dimensions, although these differences were relatively small, they were still statistically significant. For example, in psychological state, the score for the high-income group was 6.411, compared to 6.29 for the low-income group, with a P value of 0.042. Of particular note is that after home care, these differences became more pronounced. For instance, in daily activity ability, the scores for the high-income and low-income groups were 7.629 and 6.907, respectively, with a P value of 0.000, indicating a more significant increase in scores for the high-income group. These data suggest that while home care has positive effects on elderly individuals across different economic levels, elderly individuals in the high-income group seem to derive greater benefits from home care.

Table 5.

Comparison of differences before and after across different economic levels.

Economic level	Statistical indicator	Chronic disease management	Daily activity capability	Psychological state	Social interaction
High income group	Before home care	6.282	6.349	6.411	6.478
	After home care	7.563	7.629	7.692	7.756
	Z-value	− 5.312	− 5.389	− 5.466	− 5.543
	P-value (two-tailed)	0.000	0.000	0.000	0.000
Low income group	Before home care	6.157	6.224	6.29	6.356
	After home care	6.841	6.907	6.973	7.038
	Z-value	− 3.284	− 3.351	− 3.418	− 3.485
	P-value (two-tailed)	0.000	0.000	0.000	0.000

Table 6.

Comparison of differences between different economic levels.

	Dimension	High income group	Low income group	Mann-Whitney U-value	Wilcoxon W-value	Z-value	Asymptotic significance (P-value)
Before home care	Chronic disease management	6.282	6.157	20,482	39,418	− 1.984	0.047
	Daily activity capability	6.349	6.224	20,569	39,531	− 2.011	0.044
	Psychological state	6.411	6.29	20,655	39,645	− 2.038	0.042
	Social interaction	6.478	6.356	20,742	39,758	− 2.065	0.039
After home care	Chronic disease management	7.563	6.841	20,828	39,872	− 3.092	0.001
	Daily activity capability	7.629	6.907	20,915	39,985	− 3.119	0.000
	Psychological state	7.692	6.973	21,001	40,099	− 3.146	0.000
	Social interaction	7.756	7.038	21,088	40,212	− 3.173	0.000

Discussion

In-depth analysis of home care effects

Impact of home care on elderly physical health

The impact of home care on the physical health of the elderly is multifaceted³⁷. From the data, it can be observed that the score for chronic disease management slightly decreased after home care, from an average of 6.48 to 6.24. This may indicate a shift in service priorities. In traditional care models, chronic disease management is often a focal area, but in the home care environment, this focus may shift to a more comprehensive health care approach, including emotional support and social interaction. This transition may reflect a holistic care concept, emphasizing the importance of addressing the psychological and social well-being of the elderly alongside physical health. Based on the Welfare Mix theory, such a shift also demonstrates how formal and informal care systems can jointly contribute to the elderly’s well-being, balancing medical treatment with family-based and community-based care resources. This integration reflects the theoretical notion that the welfare of older adults is best achieved through the complementary interaction between state, market, and community actors. Therefore, the decrease in chronic disease management scores does not necessarily imply a decline in care quality but rather a reasonable adjustment in service priorities.

Moreover, the decline in chronic disease management scores should be interpreted in light of resource allocation and evolving care priorities within home care settings. For instance, caregivers may devote more time to emotional support and social engagement, thus inadvertently reducing the focused attention on regimented chronic disease interventions. From the perspective of the Aging Society framework, this reallocation aligns with the shift toward “active aging,” emphasizing autonomy, functional ability, and overall well-being rather than merely the management of disease. This shift could also reflect a growing understanding that mental health and social participation are central to sustaining overall well-being, ultimately influencing how caregivers balance clinical and non-clinical care tasks. In line with previous research³⁸, a comprehensive approach that weaves chronic disease management into broader psychosocial support strategies may be more effective in the long run. This also echoes the Social Support Network theory, which highlights the interdependence between emotional, instrumental, and informational support in promoting physical health outcomes among the elderly. Therefore, future care models might aim to integrate structured protocols for managing chronic conditions within a holistic, person-centered framework, thereby preserving necessary treatment regimens while still providing robust emotional and social support. Such an approach would mitigate the potential trade-off observed in our study and strengthen the long-term benefits of home care services for the elderly population. On the other hand, the improvement in daily activity ability, from an average score of 5.76 to 6.25, indicates that home care plays a positive role in enhancing the self-care ability of the elderly. This may be related to the attention to personalized needs in home care services, such as customized health exercise plans, nutritional guidance, and daily living skills training, enabling the elderly to better maintain and improve their daily activity ability³⁹. From the Welfare Mix perspective, the empowerment of elderly individuals through personalized services shows how market-based professional services and family support can be effectively combined to strengthen functional independence, fulfilling the multidimensional goals of modern eldercare systems.

Mechanisms of improvement in psychological state and social interaction

The significant improvement in the psychological state and social interaction of the elderly due to home care reflects the profound impact of this service model on psychological and social dimensions. The psychological state score significantly increased from 4.99 to 6.65, and the social interaction score increased from 4.68 to 6.56, indicating not only the success of home care in providing emotional support and psychological comfort but also its effectiveness in promoting social engagement. These improvements may be attributed to the personalized services, friendly care environment, and provision of social and recreational activities for the elderly in home care. According to Social Support Network theory, the enhancement of social engagement and emotional well-being among the elderly is largely a result of strengthened interpersonal ties and community belonging. Home care creates opportunities for both formal and informal interactions, fostering emotional exchange and social reciprocity that reinforce mental health resilience. By creating a more home-like care environment, home care helps the elderly maintain social connections and a sense of participation in a comfortable and familiar setting. Social activities, such as community gatherings and interest groups, provide opportunities for the elderly to interact with others, enhancing their sense of social belonging and life satisfaction. Additionally, personalized care provided by home care services, such as customized activities tailored to the interests and needs of the elderly, further promotes their social participation⁴⁰. In terms of mental health, home care helps the elderly cope with issues such as loneliness, anxiety, and depression through regular mental health assessments, counseling services, and emotional support. Friendly caregivers provide emotional comfort and psychological support through daily communication and activities, which are crucial for improving the psychological well-being of the elderly. The success of home care in psychological and social dimensions is not only reflected in score improvements but more importantly, it improves the overall quality of life of the elderly by providing comprehensive and personalized support⁴¹. This finding also extends the Welfare Mix framework, demonstrating how public care services, voluntary organizations, and family support can be effectively interlinked to construct a hybrid support system for the elderly’s emotional and social needs.

Regional disparities analysis in the Greater Bay Area

Influence of economic development level on home care effectiveness

In the Greater Bay Area, there are significant regional disparities in the effectiveness of home care, largely influenced by the level of economic development. Economically developed cities such as Guangzhou and Macau demonstrate significant improvements in psychological state and social interaction. For instance, in Guangzhou, after home care, the average scores for psychological state and social interaction increased by 2.489 and 2.496 points, respectively. These improvements may be attributed to the higher level of economic development, richer social support resources, and more extensive social activities in these cities. Economic development brings better healthcare resources, professional caregivers, and diversified social activities, collectively promoting the well-being of the elderly in psychological and social aspects⁴². From the perspective of the Welfare Mix theory, such regional disparities reflect the uneven integration of public, market, and community resources across cities. Economically advanced regions are often able to establish a more balanced welfare mix, where government programs, private providers, and community organizations jointly contribute to the elderly’s well-being. In contrast, less developed areas may rely excessively on public or informal care, leading to structural limitations in service quality and accessibility. In contrast, regions with relatively lower levels of economic development may face more challenges in resource allocation and service quality. This may result in home care services in these areas failing to fully meet the psychological and social needs of the elderly, thereby affecting the improvement in these dimensions. This finding also aligns with the Aging Society framework, which emphasizes that economic inequality can deepen disparities in aging experiences—older adults in wealthier regions benefit more from institutional and social innovations that promote “active aging,” while those in less developed areas may encounter cumulative disadvantages in both physical and psychological health.

Role of culture and social structure

The culture and social structure of different cities in the Greater Bay Area have a significant impact on the effectiveness of home care. Taking the Macau Special Administrative Region as an example, its unique historical and cultural background and close-knit community network have a positive impact on home care for the elderly. In Macau, the improvement in psychological state and social interaction for the elderly is 2.057 and 2.055 points, respectively, possibly due to the close connections and spirit of mutual assistance in the Macau community culture. In such a social structure, home care is not only an extension of medical services but also a reflection of community support and cultural heritage⁴³. According to Social Support Network theory, these results illustrate how dense interpersonal ties and shared community norms can strengthen the psychosocial dimensions of elderly care. The presence of cohesive neighborhood relationships enhances informal support exchanges—such as emotional comfort and instrumental help—thereby amplifying the psychological benefits of home care. Through community activities and festive events, the elderly in Macau have more opportunities for social interaction, contributing to their psychological well-being and sense of social belonging⁴⁴. Guangzhou, as a relatively developed city economically, shows significant improvements in psychological state and social interaction for the elderly after home care, with scores increasing by 2.489 and 2.496 points, respectively. As a culturally diverse metropolis with abundant social resources and activities, Guangzhou provides extensive opportunities for social interaction for the elderly, significantly enhancing their social interaction scores. The cultural tradition of Guangzhou emphasizes mutual assistance within families and communities, which may further enhance the social support network provided by home care services, positively impacting the psychological well-being of the elderly⁴⁵. From the Welfare Mix perspective, this pattern indicates that cultural norms and community participation serve as informal welfare mechanisms that complement formal institutional care. When family support, community engagement, and professional services are effectively integrated, they form a hybrid welfare system capable of addressing not only medical needs but also emotional and social well-being. Zhuhai and Foshan show relatively modest improvements in these two dimensions. The improvements in psychological state and social interaction in Zhuhai are 0.863 and 0.873 points, respectively, while in Foshan, these improvements are 0.771 and 0.773 points, respectively. Although these cities are rapidly developing economically, they may have differences in social support and community participation compared to Macau. This indicates that while the level of economic development is important, social and cultural factors also play a crucial role in home care for the elderly. The role of culture and social structure in home care cannot be ignored. The cultural characteristics, community structure, and degree of social participation in different cities all influence the effectiveness of home care, especially in dimensions such as psychological well-being and social interaction⁴⁶. Therefore, considering the cultural and social characteristics of each region is essential when formulating and implementing home care plans. Future policies should draw upon the Welfare Mix framework to design localized, culturally embedded home care systems that combine public resources with community-based initiatives, thus promoting a more equitable and culturally responsive care environment across the Greater Bay Area.

Gender differences in home care

Differences in needs between male and female elderly in home care

Research data reveal significant differences in needs and responses between male and female elderly during the home care process. Women show much greater improvements in psychological state and social interaction dimensions compared to men. Specifically, the average score for women in psychological state increased from 5.892 to 8.672, an increase of 2.78 points, and in social interaction from 5.917 to 8.741, an increase of 2.824 points. In contrast, men only saw a slight increase in psychological state by 0.458 points, from 5.940 to 6.398, and in social interaction by 0.464 points, from 5.973 to 6.437. This indicates that women’s needs in psychological and social dimensions are more satisfied during home care. Women may place greater emphasis on social connections and emotional support, which are precisely what home care services can effectively provide. According to the Social Support Network theory, women’s higher gains in psychological and social well-being can be understood through their stronger inclination toward maintaining interpersonal ties and emotional exchanges. Home care environments provide a structured platform for such interaction, enabling women to convert social participation into tangible emotional benefits. Conversely, men’s relatively weaker social connectedness and smaller social networks may limit the psychosocial impact of home care interventions, reflecting gendered disparities in access to emotional and relational resources. When exploring the differences in needs between male and female elderly in home care, various factors must be considered, including social and cultural factors, physiological, psychological, and behavioral characteristics⁴⁷. Firstly, social and cultural factors greatly influence the behavioral patterns and expectations of male and female elderly. Women typically play a more active role in social and emotional communication, reflected in their higher demand for social activities and psychological support in home care, while men may lean towards independent and task-oriented activities with relatively lower demand for direct emotional communication. From a physiological perspective, male and female elderly have different physical structures and health issues, which also influence their needs for home care services⁴⁸. For example, women may be more concerned about age-related health issues such as osteoporosis or arthritis, while men may focus more on the management of heart disease or diabetes. Therefore, home care services need to provide appropriate attention and intervention for gender-specific health issues. At the psychological and behavioral level, male and female elderly cope with stress and manage emotions differently. Women may tend to express and process emotions through social interaction, while men may rely more on independent problem-solving or distraction methods. This requires home care services to adjust methods and strategies for providing psychological support based on gender differences. Additionally, gender differences may also affect the lifestyle and hobbies of the elderly⁴⁹. Certain activities or hobbies may be more common among men or women, so home care services should consider these differences when providing entertainment and leisure activities. For example, activities provided for elderly women may focus more on community participation and creative expression, while elderly men may prefer physical activities or skill-related activities. From the Welfare Mix perspective, recognizing these gender-specific preferences underscores the importance of diversified service provision through multi-actor collaboration—government, market, and community sectors should jointly deliver gender-sensitive programs that cater to varied psychosocial and physical needs. Such pluralistic arrangements ensure equity in service outcomes and promote inclusive aging. Considering these multifaceted factors is crucial for optimizing home care services. By understanding and meeting the specific needs of elderly individuals of different genders, home care services can effectively improve their quality of life, particularly in terms of psychological well-being and social interaction.

Optimization of service strategies for gender differences

Taking gender differences into account, the optimization strategies for home care services should be more detailed and personalized. According to research data, women show significant improvements in psychological state and social interaction after home care, with scores increasing from 5.892 to 8.672 and from 5.917 to 8.741, respectively. In comparison, men show smaller increases in scores in these two dimensions, with psychological state increasing from 5.940 to 6.398 and social interaction from 5.973 to 6.437. These data suggest that women may respond more positively to home care in psychological and social aspects, while men may have more pronounced needs in other areas. For elderly women, home care services should emphasize emotional support and social activities. This can be achieved by organizing regular community activities, interest groups, and social gatherings, while providing opportunities for psychological counseling and emotional communication⁵⁰. For example, establishing health clubs or reading groups specifically for elderly women encourages them to share experiences and emotions, enhancing their sense of community belonging. Drawing on the Social Support Network theory, such collective activities strengthen emotional connectedness and perceived belonging, which are central to mental health among older adults. These activities also facilitate the reciprocal exchange of support among peers, thereby reinforcing the informal care dimension of the welfare system.

For elderly men, home care services should focus more on enhancing physical health and daily activity capabilities. This can be achieved by providing customized exercise plans, healthy diet advice, and functional training. Additionally, considering that men may prefer independent and goal-oriented activities, skill development workshops or personal projects such as gardening, model making, or computer skills training can be set up. General strategies for both genders are also important; for example, regular health check-ups and personalized medical plans are essential for all elderly individuals⁵¹. In this process, maintaining good communication and coordination with healthcare providers is equally important to ensure that home care services align with the overall health plans of the elderly. From the Aging Society perspective, gender-sensitive home care is not merely a service refinement but a structural requirement in responding to demographic transitions. It reflects an adaptive welfare response to an aging population that recognizes diversity in aging trajectories and promotes inclusive well-being for both men and women. By implementing the above strategies, home care services can better meet the specific needs of elderly individuals of different genders, thereby enhancing the effectiveness of services and satisfaction of the elderly.

Analysis of the impact of economic levels on home care effectiveness

Impact of economic disparities on home care effectiveness

Research data indicate significant differences in the improvement of various aspects of well-being among elderly individuals receiving home care in groups with different economic levels. The high-income group shows higher increases in scores for chronic disease management, daily activity capability, psychological state, and social interaction compared to the low-income group. For instance, the high-income group’s score for chronic disease management increased from 6.282 before home care to 7.563, while the low-income group’s score increased from 6.157 to 6.841. This difference may reflect the importance of economic conditions in accessing high-quality care resources, as the high-income group may have easier access to higher standards of medical services, customized health plans, and more extensive social activities. Further analysis reveals that the high-income group’s improvement in psychological state and social interaction after home care is particularly significant, possibly due to their broader social networks, better awareness of mental health, and pursuit of a high-quality lifestyle⁵². From the perspective of the Welfare Mix theory, these disparities highlight how the combination of market capacity, public policy, and community resources jointly determines the accessibility and quality of home care. High-income groups often benefit from a market-oriented welfare subsystem that provides diversified and high-end services, whereas low-income groups rely more heavily on the public and community-based components of the welfare mix. This imbalance explains the uneven improvement in well-being and underscores the need for redistributive mechanisms within mixed welfare models to ensure equitable care outcomes. These factors combined enable elderly individuals in the high-income group to experience a more comprehensive improvement in well-being from home care. In contrast, although the low-income group also benefits from home care, their improvement in psychological and social aspects may not be as significant due to resource constraints.

Economic sensitivity of home care strategies

Based on the above findings, the development of home care strategies needs to pay closer attention to the impact of economic levels on the needs of elderly individuals. For the high-income group, strategies may need to focus more on providing diversified and high-quality services, such as offering more mental health support, social activities, and personalized health management plans^53,54. Additionally, considering their potential openness to new technologies and innovative services, efficiency and quality of care can be enhanced by introducing smart health monitoring tools and online consulting services. For the low-income group, strategies should prioritize the accessibility and quality of basic healthcare while providing necessary emotional support and opportunities for social interaction. Governments and community organizations can play a greater role in resource allocation, such as providing subsidies, establishing community care centers, and organizing community activities to enhance social participation and psychological well-being among this group. Informed by Welfare Mix theory, such differentiated strategies must be supported by a multi-actor governance model in which state, market, and community sectors collaborate to fill resource gaps. Public subsidies and nonprofit initiatives can complement market-oriented services, ensuring that home care remains not only an individual benefit but also a component of collective social welfare. This pluralistic welfare configuration is essential in aging societies to reduce inequality in health and care outcomes. Furthermore, home care service providers should consider adopting more cost-effective approaches, such as small-scale community support groups and telephone/video consultation services, to enhance service coverage and sustainability. From the Aging Society framework, the economic sensitivity of home care reflects broader demographic transitions, where financial capacity increasingly mediates access to dignified aging. Economic-level targeting in service design, therefore, becomes a structural response to population aging—seeking to balance efficiency with social justice in long-term care delivery.

Reflections on internal validity and research design constraints

One notable limitation of this study is the reliance on a single-group pre-post design without a control group. While this design enabled us to measure changes in key dimensions of elderly well-being—such as chronic disease management, daily activity ability, psychological state, and social interaction—over time, it also presents challenges to internal validity. Without a control group, it is difficult to conclusively attribute the observed changes solely to the home care intervention. External factors such as natural disease progression, seasonal influences, or other concurrent social and economic changes could also contribute to these shifts, thereby confounding our ability to isolate the effect of the intervention. Furthermore, the before-and-after design raises potential threats including maturation effects and regression to the mean. Maturation effects imply that improvements might occur simply as a natural consequence of time, independent of the intervention. Similarly, regression to the mean might explain some of the observed changes if individuals with initially extreme scores move closer to the average over time. Although our rigorous sampling strategy and data collection procedures were implemented to minimize these confounding factors, these inherent limitations cannot be completely ruled out. Despite these design constraints, the study remains valuable from a practical standpoint. The significant improvements observed in psychological state and social interaction, for example, align with the anticipated benefits of a comprehensive home care service that integrates family, community, and professional support. These findings provide useful insights into the potential of home care models to enhance the overall quality of life among the elderly, especially in rapidly aging urban settings like those in the Guangdong-Hong Kong-Macao Greater Bay Area.

Beyond internal validity, it is also important to acknowledge potential limitations in external validity, or the generalizability of the findings. The sample for this study is concentrated in the Guangdong-Hong Kong-Macao Greater Bay Area, a region characterized by relatively high economic development, urban density, and mature social service systems. Consequently, the patterns of improvement observed here may not fully represent the experiences of elderly individuals living in less developed or rural areas, where social support structures, healthcare accessibility, and cultural expectations surrounding home care may differ significantly. Therefore, caution should be exercised when extending these conclusions to other regions or countries. Future research should incorporate more diverse samples across varying socioeconomic and cultural contexts to test the robustness and universality of the results. Comparative studies among different provinces or cross-regional analyses could help identify how local welfare systems, family structures, and policy environments influence the effectiveness of home care models. Such efforts would strengthen the external validity of the research and contribute to a broader understanding of aging and care dynamics across different social settings. To address these limitations in future research, we recommend incorporating a control group or employing a randomized controlled trial (RCT) design. Such approaches would enable a more definitive causal inference by isolating the impact of home care services from other external influences. Additionally, future studies could utilize longitudinal designs with multiple follow-up points to better capture the trajectory of change over time.

Moreover, expanding future analyses beyond the Greater Bay Area will help determine whether the positive effects of home care identified here are context-specific or part of a more generalizable trend applicable to wider aging populations. In this way, the study can contribute not only to regional policy design but also to theoretical advancements in understanding how socioeconomic and institutional factors shape the delivery and outcomes of home care services.

Comprehensive optimization strategies for home care services

Application of innovative technologies in improving the quality of home care

With the continuous advancement of technology, technology plays an increasingly important role in the field of home care. Remote health monitoring systems, such as wearable devices and smart home technologies, have begun to change traditional home care service models. These technologies not only enable real-time monitoring of the health status of the elderly, such as heart rate, blood pressure, and activity levels, but also predict health risks through data analysis, thereby achieving early intervention. For example, wearable devices can monitor the activity patterns and sleep quality of the elderly, while smart home systems can detect emergencies at home, such as falls or abnormal behavior⁵⁵. The application of these technologies not only improves the efficiency of home care but also enhances the personalization and preventive nature of the services, helping to increase the sense of security and independence of the elderly. The application of information and communication technologies also provides more social and psychological support opportunities for the elderly. Through video calls, social media, and online health communities, the elderly can stay connected with family, friends, and healthcare providers, thereby reducing loneliness and social isolation. The application of these technologies not only improves the social lives of the elderly but also enhances the overall quality of home care.

Improvement of home care policies and resource allocation

Based on research findings, a series of improvements are needed for home care policies and resource allocation in the Guangdong-Hong Kong-Macao Greater Bay Area. Firstly, policymakers should consider increasing investment in home care services, especially in terms of human resources and technical equipment. This includes providing professional training and development opportunities for caregivers to ensure they have the necessary skills and knowledge to provide high-quality services. At the same time, investment should be made in research and development of technologies related to home care, such as developing more advanced remote health monitoring systems and smart home devices, to improve the efficiency and effectiveness of services⁵⁶.

Policies should also focus on improving the accessibility and equity of home care services. This means ensuring that all elderly individuals, regardless of their economic status or place of residence, have access to high-quality home care services. Rather than proposing generic Public-Private Partnerships (PPP), future reforms should emphasize the refinement and localization of existing models already active within the Greater Bay Area. A notable example is the Macau approach, in which the government provides funding and policy support while non-governmental organizations (NGOs) serve as the primary delivery agents for elderly services. This structure effectively leverages local civil society capacity while maintaining administrative oversight. To further improve regional home care delivery, it is essential to enhance coordination between municipal governments and standardize cross-border service frameworks. Particular focus should be given to addressing inefficiencies stemming from fragmented resource allocation, information silos, and inconsistent service quality among cities⁵⁷.

We therefore recommend optimizing current PPP frameworks by integrating the following elements: (1) the development of interoperable digital platforms that connect service providers across jurisdictions; (2) establishing unified outcome-based funding and evaluation mechanisms; and (3) institutionalizing collaborative planning structures that allow for shared workforce training, technology procurement, and regional service scaling. This model would not only enhance resource efficiency but also avoid the duplication of systems already in place, ensuring that policy innovation builds upon rather than replaces functional elements of existing local practice.

Development of intelligent and personalized home care services

The future development direction of home care services should focus on innovation and improvement of service models. On the one hand, service providers should consider adopting more flexible and personalized care plans to meet the diverse needs of the elderly. For example, designing customized care plans based on the health status, interests, and lifestyles of the elderly⁵⁸. On the other hand, cross-disciplinary cooperation should be strengthened, such as collaboration between healthcare, social services, and technology fields, to provide more comprehensive and coordinated care services⁵⁹. For example, the application of artificial intelligence and big data in home care. Additionally, attention should be paid to the impact and needs of home care for special groups, such as the elderly with cognitive impairments or chronic diseases. Through continuous innovation and research, home care services will be continuously optimized to better meet the needs of the elderly and provide them with a higher quality of life.

Conclusion

This study delves into the impact of home care on the quality of life of the elderly, covering various aspects such as physical health, psychological well-being, and social participation. The results indicate that home care significantly improves the overall quality of life of the elderly, particularly in the dimensions of psychological status and social interaction. Elderly individuals receiving home care not only experience improvements in physical health but also show significant enhancements in psychological well-being and social participation. These findings underscore the importance of home care in addressing the challenges of aging populations and enhancing the quality of life of the elderly. The effectiveness of home care extends beyond traditional health management to include meeting the emotional and social needs of elderly individuals. This is particularly evident in female elderly individuals, whose needs in psychological and social aspects receive more attention and satisfaction. Furthermore, the analysis of regional differences suggests that the economic, cultural, and social structures of different cities have a significant impact on the effectiveness of home care, especially in terms of psychological well-being and social interaction. For instance, elderly individuals in Guangzhou and the Macao Special Administrative Region show more significant improvements in these two dimensions after receiving home care, which may be attributed to the more developed social support systems and abundant social activities in these cities. These findings provide valuable insights and recommendations for the future optimization of home care services. With the exacerbation of population aging, attention and support for the well-being of the elderly will become a key component of social development. Providing more personalized and comprehensive care services can not only improve the quality of life of the elderly but also create a more harmonious and compassionate society. Overall, this study emphasizes the multidimensional effects of home care in enhancing the quality of life of the elderly, offering valuable guidance for future care services.

Based on these findings, we propose several actionable strategies for policymakers and practitioners:

1. Strengthen Public-Private Partnerships: Encourage collaboration between government agencies, private institutions, and nonprofit organizations to pool resources, harmonize service standards, and ensure consistent quality of care. This approach helps bridge gaps in funding and expertise while promoting a shared vision of holistic elderly care.

2. Enhance Training and Professional Development: Invest in comprehensive training programs for caregivers that encompass both clinical skills (e.g., chronic disease management, basic medical knowledge) and psychosocial competencies (e.g., communication, mental health support, cultural sensitivity). Well-trained caregivers are essential for delivering personalized services attuned to the diverse needs of the elderly population.

3. Integrate Technology for Remote Support: Build upon the “Internet +” model by exploring telemedicine, remote health monitoring, and virtual social engagement platforms. These technologies can supplement in-person services, especially in regions with limited access to specialized care, and foster sustained social connections for isolated individuals.

4. Foster Community-led Activities and Mental Health Services: Encourage local community centers and organizations to develop and maintain social clubs, volunteer groups, and counseling programs tailored to seniors’ interests and cultural backgrounds. Such activities help mitigate loneliness and strengthen mental well-being.

5. Customize Services Based on Regional Differences: Recognize and accommodate varying cultural, economic, and social factors when developing care protocols. For instance, in economically advanced regions like Guangzhou, resources might be allocated toward sophisticated social programs, while in less-developed areas, scaling up basic medical services and caregiver training could be prioritized.

6. Promote Sustainable Funding and Policy Support: Establish long-term financial and policy frameworks that support flexible home care models. This can include subsidies for low-income seniors, tax incentives for private providers, and clear guidelines for integrated medical-community services. Such measures ensure that home care remains both accessible and effective.

Limitations

Despite achieving certain theoretical and practical results, this study still has some limitations. Firstly, the study sample mainly comes from specific cities in the Guangdong-Hong Kong-Macao Greater Bay Area, which may not fully represent the situation of home care in other regions of China. Therefore, the universality and applicability of the research results may be limited. Secondly, due to the limitations of the research design, this study did not delve into the specific implementation process and operational details of home care services, which may affect a comprehensive understanding of the effectiveness of home care. Additionally, the study mainly focused on changes in the physical health, psychological status, and social interaction of the elderly, with insufficient exploration of other potentially affected areas such as economic status, family relationships, and community participation. Future research should consider broader samples, including elderly individuals from different regions with diverse economic and cultural backgrounds, to enhance the universality and applicability of the research results. Furthermore, research should delve into the specific implementation details of home care, including the professional capabilities of service providers, the diversity of service content, and the degree of personalization, to comprehensively assess the effectiveness of home care. Additionally, research should also focus on the impact of home care on the economic status, family relationships, and community participation of the elderly to gain a more comprehensive understanding. In conclusion, despite providing valuable insights for the optimization of home care services, this study still needs to overcome these limitations in future research to further promote the development of this field.

Author contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication. The ideas and data appearing in the manuscript have not been disseminated before (e.g., at a conference or meeting, posted on a listserv, shared on a website).

Funding

The authors received no funding for this work.

Data availability

Data is provided within the manuscript. Data storage path “E-mail: glxmsremix@gdmu.edu.cn”.

Declarations

Ethics approvals

This study was conducted with the approval of the Ethics Committee of Guangdong Medical University. All participants signed an informed consent form. All experiments were conducted in accordance with the guidelines and regulations of the Declaration of Helsinki.

Competing interests

The authors declare no competing interests.