The expectations and influencing factors to choose institutional elder care for older person in the context of future disability: an empirical analysis in China based on Anderson’s health behavior model

Abstract

Background

Since entering an aging society, the trend of population aging in China has become increasingly intense. As the average life expectancy continues to rise, the number of older people who lack the ability to take care of themselves is also increasing. The growing number of disabled older people and the extension of their survival time after becoming disabled will increase the demand for elderly care services, especially specialized institutional care services. The purpose of this paper is to study the expectations of older people regarding future institutional care services in the event of incapacity and the factors that influence these expectations, in order to provide a basis for the development of elderly care organizations.

Methodology

Based on Anderson's health behavior model, an analytical framework was constructed for the expectations of the older people to choose nursing services from elderly care institutions in the situation of future disability. Using survey data from 1134 older people who live in communities of 15 cities of 12 provinces, China. The respondents were selected using stratified and random sampling methods. First, the cities in the country were divided into four regions based on their geographical locations. Then, 2–4 cities were selected from each region, 1–2 districts within each selected city, and some communities were randomly chosen within each district. In the selected communities, a list of older person aged 60 years and over was obtained through community registration information, and a certain number of these older person were randomly selected as survey participants. The survey was mainly conducted in the form of face-to-face questionnaires, and the online survey method was used only in distant cities, such as the Xinjiang Uygur Autonomous Region. After getting the data, descriptive statistics, correlation analysis and binary logistic regression methods were used to analyze the expectation of the older people to choose nursing services from elderly care institutions in the situation of future disability and its influencing factors.

Result

Only 38.3% of the respondents expressed willingness for institutional elder care in the context of future disability. The variables of age, education, number of children, income, health status, self-care level,whether the community provides elderly care services and health services have a significant positive impact on the willingness of the older people to receive institutional elder care in the situation of future disability. The results of the Model 1 showed that older individuals those without a spouse, and those with higher education levels were more willing to consider moving into a nursing home if they became disabled in the future. The results of Model 2 show that older person with fewer children, not living with their children, higher income, and lower access to community pension services are more likely to choose pension service institutions if they become disabled in the future. The results of Model 3 show that the poorer the health status of the older person, such as those suffering from severe or chronic diseases, the more willing they are to consider moving into a pension institution if they become disabled in the future. Additionally, older person with lower self-care abilities are also more likely to consider moving into a pension institution under the same circumstances.

Conclusion

Affected by a variety of factors, the older person's low acceptance of institutional care remains consistent even when future disability is considered. This situation provides the background and ideas for China's current research on promoting social care services. For example, the nursing institutions should consider factors such as the age, education leveland income of the older person when designing elderly care services. The government can lower the threshold for the older person to stay in nursing homes by providing subsidies, tax relief and other incentives. Besides, when promoting the development of socialized elderly care services, emphasis should be placed on integrating medical and care services in elderly care institutions and developing inclusive community home care services. At the same time, the government should strengthen publicity and education efforts to popularize scientific knowledge about elderly care to the public.

Introduction

Aging is an objective trend in global population development. Declining fertility rates and increasing life expectancy are two key factors driving this trend. Due to its large population base, the absolute scale of China's aging population is significant. Furthermore, the speed of China's aging process is notably rapid. It took only 24 years for China to transition from an aging society to a moderately aging one, starting from 1999. Moreover, China faces the challenge of "getting old before getting rich," as it has entered an aging society before reaching the economic status of high-income countries. At the present stage, China's demographic structure is in an important period of transformation, highlighted by the rapid development of population ageing and the obvious trend of ageing, with data from the seventh population census showing that China's older people population over the age of 60 has reached 264 million, accounting for 18.7 per cent of the total population [1], of which 35.8 million are over the age of 80, accounting for 2.54 per cent of the total population. Besides, the aging of China's population exhibits an urban–rural inversion, primarily driven by policy and economic factors. A large number of young rural laborers migrate to cities, leading to a higher degree of aging in rural areas compared to urban areas.

Along with the characteristics of the aging population, the proportion of older people suffering from chronic diseases as well as disability and dementia is increasing year by year, and the data shows that there are more than 40 million disabled and semi-disabled older people in the country. According to forecasts, by 2030 and 2050, China's disabled older people population will reach 61.68 million and 97.5 million respectively [2]. In the context of an aging population, government expenditures on pensions, health insurance, and other related areas are increasing. These expenditures include not only direct medical costs but also the costs of long-term care and other support services, leading to greater pressure on public finances and economic development. Furthermore, as older individuals generally require more medical care than younger ones, the growing number of older people will pose significant challenges to the healthcare and old-age care system. Under the intertwining effects of longevity, disability and incapacity, the issue of long-term care has become an urgent problem for the older people in China [3]. At the same time, however, due to the impact of the centralization of family structures and the separation of modern living styles, family care for the older people has gradually become "dysfunctional" [4], and socialized elderly care services are becoming a more and more important option for meeting their needs in old age.

As a key part of the social service system for the older people, institutional care is considered an important way to achieve long-term care and healthy aging for the disabled older people due to its professional services, complete facilities, safety and convenience [5]. This aligns with the trend in China's elderly care policy, which has shifted from primarily supporting individuals and families to promoting diversified development. This includes encouraging social capital to enter the elderly care service industry and supporting a service model that combines home care, community care, and institutional care. In August 2024, the "Decision of the Central Committee of the Communist Party of China on Further Comprehensively Deepening Reform and Promoting Chinese-Style Modernization" proposed to "deepen reforms in the field of elderly care services as a key component of improving the population development support and service system, and to enhance the policy mechanisms for the development of elderly care and the elderly care industry." It is evident that the development of institutional nursing services for the older person is closely tied to the strategic reform of China's pension industry and service system.

However, the different characteristics of the older people determine that their choice of elderly care will vary from person to person. For example, due to the economic foundation and the traditional concept of family care, the rural older person may have lower expectations for institutional nursing services compared to their urban counterparts. So, it is not yet known whether institutional care will be recognized and favored by the older people. This is because China has a profound family culture and traditional values that emphasize respecting the older person and caring for the young. These values have long influenced people's attitudes towards elderly care. In traditional Chinese culture, family members, especially children, are responsible for taking care of their old parents. Therefore, the traditional model of elderly care is largely family-based. However, with the development of the social economy, changes in population structure, the shrinking of family size, and increased occupational pressure, the aging problem in China has become increasingly prominent. This has prompted a shift from family-based care to institutional care. In recent years, the Chinese government has introduced a series of policy measures to promote the construction of an elderly service system. These measures have changed people's understanding of "filial piety." More and more people are beginning to realize that placing the older person in well-equipped nursing homes with professional services does not mean violating filial piety; rather, it provides a more comfortable and safe living environment for the older person.

Under such circumstances, understanding the expectations of the older people for institutional care when they become disabled and the factors affecting them is an important basis for the rational layout of China's elderly care service planning and the development of socialized elderly care services. On this basis, this paper aims to explore the expectations and influencing factors of the older people when they become incapacitated, with a view to providing useful references for the layout and improvement of China's institutionalized elderly care services, especially the elderly care institutions that combine medical care and elderly care.

Literature review

Based on the criterion of whether or not the older people need the services provided by others or institutions other than their children, the way of old-age care can be divided into two types: family old-age care and socialized old-age care, and which kind of old-age care the older people will choose is the result of the combined effect of a variety of factors. Based on Anderson's health behavior model, the factors that affect the older person's choice of old-age care mode can be summarized into propensity factors, demand factors and enabling factors [6]. This is because the Anderson health service utilization model is a comprehensive theoretical framework, which initially tries to explain how and why individuals choose to use medical services. The model highlights a range of variables in three main categories: predisposing factors, need factors, and enabling resources. When applied to older people's choice of institutional care, these three categories can help us understand how older people decide whether to enter a nursing facility, It takes into account not only the characteristics of the older person themselves, but also various factors in the external environment. That is, corresponding to the older person's basic personal status (gender, age, occupation, etc.), health status (self-care degree, chronic disease, etc.), family status and socio-economic status (number of children, child support, living conditions, income level, etc.

With regard to the propensity factor, some scholars have pointed out that the widowed older people [7], the middle-aged people and low-aged older people [8], and the highly educated older people prefer the institutional care model [9, 10]. However, some scholars have come to the opposite conclusion, arguing that the spousal older people have a greater likelihood of choosing institutional care [7]. In terms of demand factors, established studies have found that older people with chronic illnesses and physical disabilities prefer institutional care [11, 12]. And that the willingness of older people to choose institutional care increases when they are unable to take care of themselves [13, 14], a survey on population ageing and pension options in Beijing shows that, among the parents of only one child who choose institutional care, 45.9 per cent of them choose to go to an institution just "when they are unable to take care of themselves" [15]. However, some studies have found the opposite: older people with lower levels of disability and better health are more likely to choose institutional care model [16].

In terms of enabling factors, a number of studies show that the older people with better economic conditions are more inclined to choose institutional care model [17–20]. And the more children and the more dutiful the children, the less likely the older people will choose institutional care model [21–23]. Older people living with their spouse, with their children or with their spouse and children are less likely to choose institutional care mode [24]. Older people living alone, empty nesters and those living with their children but in relatively poor housing conditions are more likely to opt for institutional care model [25–27].

Previous studies are richer in research on the factors influencing the older people's choice of pension mode, but there are still the following shortcomings:

1. Most of them focus on analyzing the factors influencing the older people's choice of pension mode in general, and there are fewer studies specifically focusing on the older people's expectations of the institutional care mode in the event of future incapacitation;

2. Most of the existing studies are based on the surveys of a single city in a small regional scope, and there are fewer studies based on the nationwide large samples, and the adaptability of the conclusions may be limited to a certain extent;

3. In terms of research methodology, the Anderson Health Behavior Model (AHBM) has been widely used in the field of public health and medical care, but it has been less used by scholars of demography and gerontology in China, who have mostly studied the influencing factors of the older people's choices of old-age care from the perspective of socio-demographics by using the binary or multivariate regression method.

In view of this, this study introduces the Anderson Health Behavior Model as a theoretical framework for analysis, conducts a nationwide survey on the older person's demand for elderly care services, analyses their expectations of institutional care in the event of future incapacity and the factors influencing them, and finally puts forward relevant policy recommendations, with the aim of rationally guiding the allocation of elderly care services and promoting the healthy development of the aging cause.

Data sources and methods

Data sources

A cross-sectional survey of the older person was conducted by the research team in 12 provinces of the China, including the Northeast, Eastern, Central and Western regions, from February to October 2020. First, those 60 years and older who were able and willing to answer the questions were included in our sample. Second, in order to make our samples as representative as possible, we used a multistage stratified sampling design. The 15 cities of 12 Province were used as primary sampling units. In addition, a face-to-face interview format was used during the survey to ensure that the older person understood the questionnaire correctly. A total of 1300 questionnaires were finally distributed. After removing the missing data, a total of 1134 valid samples were obtained (Table 1), and the questionnaire recovery rate was 87.2%.

Table 1.

Sample descriptive statistics

Variable name	Variable category	Ratio	Variable name	Variable category	Ratio
Sex	Male	42.5%	Marital status	Not married (single, divorced, widowed)	35.7%
	Female	57.5%
Age	60–69 years old	46.8%		At marriage	64.3%
	70–79 years old	22.7%
	≥ 80 years old	30.5%	Education level	Primary school and below	27.2%
Number of children	Zero	5.8%		Secondary school or junior college	51.4%
	One	44.6%		University	14.3%
	TWO	29.8%		Graduate student or above	7.1%
	≥ Three	19.8%	Level of self-care	Level of self-care	52.3%
Health status	Health	35.2%		Need occasional help	26.9%
	Chronic diseases	53.7%		Often need help	17.3%
	Severe disease (disability or dementia)	11.1%		Completely unable to take care of oneself	3.5%

Research method

Since older people services after disability cover healthcare services, this paper chooses Anderson's Health Behavior Model (AHBM), a theoretical model commonly used in the field of public health and wellness to explore the factors influencing the use of health services, as the basic theoretical framework.

The Behavioral Model of Health Services Use (BMHSU) was created by American scholar Ronald Anderson. Initially, the Anderson Behavioral Model of Health Services Use (BMHSU) takes individuals/families as the unit of analysis to explore the factors influencing the use of health services by individuals/families in different regions, including three first-level indicators: propensity, enabling resources, and need. Chinese scholars have appropriately adjusted the model variables based on the differences in regions, research objects, and research contents, as well as combining China's cultural traditions and research needs to adapt to China's development context [3, 28, 29].

In this study, the Anderson Health Behavior Model was slightly modified with the aim of adapting the model to the application of factors influencing the choice of institutional care services when the older people become disabled. Therefore, in the selection of independent variables, variables such as community service supply were added to the enabling factors of Anderson's model based on previous research. According to the classification of Anderson's Health Behavior Model, the influencing factors that may affect the willingness of the older people to choose institutional care in the future when they become disabled are classified into three categories: propensity factors, enabling factors, and demand factors in the data from the Survey on the Demand for Elderly Care Services of the Elderly in China.

What needs to be mentioned here is that, under the combined effect of many factors such as traditional cultural values, economic and social conditions, and personal preferences, the older person of China hold complex attitudes about whether to choose institutional care. In Chinese culture, the family is a very important social unit. Filial piety is one of the cores of Confucianism, emphasizing that children should respect and care for their parents. Therefore, in the minds of many Chinese, the older person living in a nursing home may be seen as a sign of filial impiety. Although the situation has improved with social development and changes in people's attitudes, family attitudes are still an important factor influencing whether older people choose to stay in nursing homes when they are disabled. Some older person may be afraid that staying in a nursing home will be misinterpreted by the outside world as a failure of their children to properly take care of their family members, thus damaging the social image of the whole family. As a result, they may hesitate even when professional nursing services are actually needed. Therefore, different cultures may significantly influence older adults' preferences and choices for institutional care in the event of future disability, which may have implications for the interpretation of the findings.

Analytical methods

Statistical analyses were performed using SPSS V.23.0. For categorical variables, p value was calculated using χ2 test. Binary logistic regression with an enter method was used to assess the influencing factors of the willingness to accept institutional care when the older people are disabled in the future.

Study design

Variable selection

The dependent variable in this paper is the expectation of institutional care when the older people are disabled. The expectations of the older people for institutional care when they become disabled are mainly driven by their personal wishes. In this regard, the "Survey on the Demand for Elderly Care Services in China" asked the question "Would you be willing to accept the services of elderly care institution when you are unable to take care of yourself?." This question was used to understand the willingness of institutional care mode of the older people when they become disabled. The variable was divided into two subvariables: willingness and unwillingness, and in the regression analyses, the variable was coded as "0 = unwillingness, 1 = willingness".

According to the descriptive statistics on the willingness of the older people to accept the services provided by elderly care institutions when they become disabled, the proportion of those who indicated that they were willing to accept the services provided by elderly care institutions when they become disabled was 38.3 per cent, while the proportion of those who were unwilling to do so was 61.7 per cent, with the reasons for unwillingness to accept the services including worries about safety (15.3 per cent), worries about the price being too high (28.5 per cent), worries about the quality of the services being poor (23.2 per cent), and worries about the service content is not sustainable (19 per cent). Moreover, 19.5 per cent of the older people said that when they were unable to take care of themselves, they looked to their spouses as their caregivers, 30.9 per cent to their children, 21.9 per cent to nannies and other professional domestic helpers, 36.2 per cent to professional caregivers, 50.7 per cent to nursing homes, 4.2 per cent to unpaid volunteers, and 5.2 per cent to older persons for mutual assistance.

The independent variable selected in this paper are divided into three parts: propensity factors, enabling factors and demand factors. (1) Propensity factors: variables such as gender, age, marital status, region, education level and occupation type of the older people were mainly selected for analysis. (2) mainly selected for analysis are variables such as the older people's marital status, number of children, intergenerational support, source of livelihood, whether the community provides life care services, whether the community provides medical services, and so on. (3) Demand factors: mainly selected variables such as the health status of the older people and the degree of self-care were analyzed. The definitions of the above variables are shown in Table 2.

Table 2.

The willingness of the older people to accept the services provided by the elderly care service institutions when they become disabled in the future

Index	Main variables	Variable category	Willing (%)	Unwilling (%)	X2	P
Propensity factors	Sex	Male = 1 Female = 2	69.8 71.4	30.2 28.6	0.348	0.555
	Age	60–69 years old = 1 70–79 years old = 2 ≥ 80 years old = 3	63.5 68.1 75.7	36.5 31.9 24.3	13.815	0.001
	Region	Eastern region = 1 Central region = 2 Western region = 3 Northeast region = 4	90.6 78.0 59.3 62.0	9.4 22.0 40.7 38.0	77.786	0.210
	Marital status	Not married (single, divorced, widow) = 1 At marriage = 2	61.3 46.8	38.7 53.2	28.715	0.000
	Educational level	Primary school and below = 1 Secondary school or junior college = 2 University = 3 Graduate student or above = 4	64.9 66.0 73.2 87.5	35.1 34.0 26.8 12.5	19.805	0.001
	Pre-retirement occupation	Public institutions = 1 State-owned or collective units = 2 Private enterprise = 3 Individual employment = 4 Farming occupation = 5	74.3 71.7 60.9 54.2 38.7	25.7 28.3 39.1 45.8 61.3	22.178	0.000
Demand factors	Health status	Health = 1 Long-term chronic disease = 2 Severe illness (disability, dementia) = 3	64.0 68.5 75.4	36.0 31.5 24.6	21.616	0.014
	Self-care degree	Full self-care = 1 Need occasional help = 2 Frequent need for help = 3 Completely unable to take care of themselves = 4	54.4 58.5 63.8 75.2	45.6 41.5 36.2 24.8	27.121	0.000
Enabling factors	Number of children	0 children = 1 1 child = 2 2 children = 3 ≧3 children = 4	66.7 69.6 73.2 70.7	33.3 30.4 26.8 29.3	1.793	0.617
	Whether live with children	Not living with children = 1 Living with children = 2	72.8 61.0	27.2 39.0	27.173	0.000
	Intergenerational support	Financial support = 1 Life care = 2 Emotional support = 3	67.5 62.8 54.2	32.5 38.7 45.8	5.667	0.129
	Income status	No income = 1 3000 yuan and below = 2 3000–5000 yuan = 3 5000–7000 yuan = 4 Over 7000 = 5	65.8 71.7 72.0 74.5 78.9	34.2 28.3 28.0 25.5 21.1	47.570	0.014
	Main source of income	Pension = 1 Child support = 2 Personal savings = 3 Government grants and others = 4	56.2 65.3 37.4 39.4	43.8 34.7 62.6 60.6	22.526	0.202
	Categories of medical insurance	Basic medical insurance for urban workers = 1	59.2	50.5	42.355	0.500
		Basic medical insurance for urban and rural residents = 2	31.0	38.3
		Medical insurance for critical illness = 3	14.1	4.7
		Publicly-funded medical care = 4	12.5	15.0
		Long-term care insurance = 5	2.0	3.7
		Commercial medical insurance = 6	12.5	14.0
	Whether the community provides elderly care services	Yes = 1 No = 2	61.1 49.8	38.9 50.2	23.124	0.000
	Whether health services are available in the community	Yes = 1 No = 2	59.4 40.9	40.6 59.1	29.183	0.013

About the Interpretation of variables

1. Region (The survey in the eastern region includes Qingdao City, Jinhua City, Guangzhou City, Beijing City, and Tianjin City; the survey in the central region includes Changsha City, Zhoukou City, and Pingdingshan City; the survey in the western region includes Chengdu City and the Xinjiang Uygur Autonomous Region; the survey in the northeastern region includes Changchun City, Dalian City, Shenyang City, Harbin City, and Jiamusi City)

2. Marital status (Unmarried status refers to being single, divorced, or widowed. Married status means currently being in a relationship with a partner)

3. Pre-retirement occupation (Organs and institutions: Usually refers to government departments, schools, hospitals, research institutes, and other public sectors or institutions. State-owned or collective units: Refers to enterprises or institutions that are owned and operated by the state or collective entities, such as state-owned enterprises and collective enterprises. Private enterprises: Refers to businesses that are privately owned and operated. These enterprises are not owned by the state or collective entities. Self-employed: Refers to small-scale business activities run by individuals or families, typically without employing others, such as small shops or workshops. Farming: Refers to activities involved in agricultural production, such as growing crops or raising poultry and livestock)

4. Self-care degree (The self-care degree of the older person, as an independent variable, refers to their physical self-care ability, which is assessed using the ADL (Activities of Daily Living) scale. The assessment covers various activities such as using public transportation, walking, cooking, doing housework, taking medication, eating, dressing, combing hair, brushing teeth, washing clothes, bathing, shopping, using the bathroom regularly, making phone calls, and managing personal finances. The rating scale is divided into four levels: 1 (completely able to do it), 2 (somewhat difficult and occasionally need help), 3 (often need help), and 4 (unable to do it)

5. Intergenerational support (In this study, intergenerational support primarily refers to the assistance provided by children to their old parents. This includes: Economic support: Children providing living and medical expenses for the older person. Life care: Children taking care of the older person’s diet and daily living, such as cleaning their rooms, cooking, and washing clothes. Emotional support: Children frequently accompanying the older person, contacting them by phone or WeChat to help alleviate psychological stress, anxiety, and loneliness)

6. Main source of income (There are four main sources of income that older adults may rely on. Pension: Refers to the pension insurance paid by the individual during the working period, resulting in a fixed income received on a monthly or annual basis after retirement. Child support: Refers to the financial help that retirees receive from their adult children, which can be in the form of monetary assistance or other material support. Personal savings: Refers to the private funds accumulated by individuals through savings and investments during their working life, which can be used to supplement their income after retirement. Government subsidies and others: Includes various welfare subsidies provided by the government in addition to pensions, such as social assistance, subsistence security, and medical subsidies, as well as income from other sources, such as rental income from rental properties and investment income)

7. Categories of medical insurance (Several common types of medical insurance in China include the following specific meanings. Basic Medical Insurance for Urban Employees: This type of medical insurance covers urban enterprise employees and is usually co-funded by both employees and their employers, providing basic medical security. Basic Medical Insurance for Urban and Rural Residents: This insurance covers both urban and rural residents and is primarily funded by individuals and the government, offering basic medical security for residents. Serious Illness Medical Insurance: This insurance mainly provides protection against major diseases and helps reduce the financial burden on patients who face high medical expenses. Free Medical Care: A medical security system primarily supported by government finances, originally designed to cover state workers and their families, and now gradually merging with the basic medical insurance for urban workers. Long-term Care Insurance: This insurance provides financial support for individuals requiring long-term care services, including but not limited to the older person and disabled. Commercial Medical Insurance: These are medical insurance products offered by commercial insurance companies that individuals can purchase according to their own needs, serving as a supplement to basic medical insurance)

8. Whether a community provides elderly care services (This refers to whether a community (usually a residential area or community unit) offers specialized services to older person. These services typically include daily living assistance, healthcare, cultural and recreational activities, psychological support, and emergency assistance. The goal is to help the older person enjoy their later years within the community and reduce the various life challenges they may face as they age)

9. Whether health services are available in the community (This means whether a community has the facilities or capabilities to offer health services. This includes having medical facilities such as hospitals, clinics, and health posts, as well as providing basic medical services like diagnosis and treatment of common illnesses, health consultations, vaccinations, and emergency aid. In short, this phrase asks whether the community can provide healthcare and medical support to its residents)

The results of the X² test showed that with regard to the propensity factor, the willingness of the older people to accept institutional care service in the event of future incapacity was correlated with the older people's age, marital status, type of occupation, and level of education (p < 0.05);In terms of demand factors, the willingness to accept institutional elderly care services in the event of future incapacity expressed by the older people was correlated with older people's health status and degree of self-care (P < 0.05); In terms of enabling factors, the willingness to accept institutional elderly care services in the event of future incapacity expressed by the older people was correlated with the older people's income status, the situation of living with children, and whether or not the community provides elderly care and medical services (P < 0.05), and the results of the analyses are shown in Table 2.

Model selection

What is the direction and degree of influence of predisposing factors, enabling factors, and need factors on the older person's choice of institutional care services when considering future disability? To address this problem, we developed the following three models.

According to the results of X² test, when P < 0.05, it means that the independent variable reaches the level of statistical significance and can be included in the regression model. In order to further verify the specific influence of the independent variables through cross-tabulation analysis on the willingness of the older people to choose institutional elderly care services when they become disabled in the future, three regression models are established based on the three indicators of propensity factor, demand factor, and enablement factor, so as to avoid errors in the results caused by a separate level of factors, and all the influencing factors affecting the willingness of the older people to choose institutional elderly care services are gradually included in the Logistic regression model.

In the empirical analysis, the willingness of the older people to receive the services supplied by the elderly service agencies at the time of incapacity was operated as a dichotomous variable, whose values were disordered and did not satisfy the requirements of the linear regression model for the dependent variable, so a binary logistic regression analysis model was used in the analysis.

Set the dependent variable as“y”, when the value is “1”, it means that the older people are willing to accept the services provided by the elderly care service institutions when they are disabled, and when the value is“0”, it means that the older people are unwilling to accept the services provided by the elderly care service institutions when they are disabled, where“P1”and“P0”respectively represent the probability that the older people are willing to choose the elderly service institutions to supply services when they are disabled, satisfying“P1 + P0 = 1”.“P1/P0” is the ratio of the probability of choosing elderly care service institutions to the probability of unwilling to choose elderly care service institutions to provide services when they are disabled, indicating that compared with the probability of unwilling to choose elderly care service institutions to provide services when disabled, the probability that the older people are willing to choose the elderly service institutions to provide services when disabled increase (positive value) or decrease (negative value).The “a” is a constant, and the “m”variables (independent or control variables) affecting “y” are denoted as “1x”, “2x”…,“mx”. Suppose the conditional probability that the older people are willing to choose elderly care institutions to provide services when they are disabled is “P”(y = 1 | X) = “Pi”, and “1-Pi”represents the probability that the older people are unwilling to choose elderly care institutions to provide services when they are disabled. Both of them are nonlinear functions consisting of a vector of independent variables (X). The baseline model for the non-linear regression is as follows:

1

Since the core variable of this paper is the probability that the older people choosing the care institutions to provide services in the event of future incapacity, which is a binary categorical variable, a binary Logistic regression model was used for the empirical analyses. A logarithmic transformation of Odds yields the following linear expression for the Logistic regression model:

2

In the second formulas“a”represents the constant term, “βi”is the coefficient of the independent variable, which represents the direction (positive or negative) and degree of the influence of the independent variable (“X”) on the older people's willingness to accept the services supplied by the elderly service institutions in the event of future incapacitation (“Y”). In Eq. 2, a represents the constant term,“βi” is the coefficient of the independent variable, which represents the direction (positive or negative) and the degree of influence of the independent variable (“X”) on the willingness to accept the services supplied by the elderly service institutions in the event of future incapacitation (“Y”); And the number of the independent variable is denoted by the letter “m”.

In order to analyze the direction and extent of the influence of propensity, demand and enabling factors on the willingness of the older people to accept the services provided by the elderly service agencies when they become disabled in the future, this paper constructs three models, model 1 only incorporates propensity factors, model 2 incorporates both propensity and demand factors, and model 3 incorporates both propensity, demand and enabling factors. By comparing the results of different models, the influence of some factors alone can also be obtained. The specific models are as follows:

3

4

5

Results

Through incorporates all the combined factors (propensity factor, enabling factor, demand factor) that may affect the willingness of the older people to accept the supply service of the elderly service institutions when they become disabled in the future into the model through stepwise regression one by one, we can observe whether the significance of the model and the related factors change when a new variable is added. In the third formulas, model (1) is the baseline model, which mainly examines the influence of propensity characteristic variable on the willingness of the older people to accept the supply service of the elderly service institutions when they become disabled in the future; in the fourth formulas, model (2) adds the demand factor variable on the basis of model (1), and mainly observes the influence of the demand factor on the willingness of the older people to accept the supply service of the elderly service institutions when they become disabled in the future; in the fifth formulas, model (3) adds the enabling factor variable on the basis of model (2), and observes the influence of the enabling factor on the willingness of the older people to accept the supply service of the elderly service institutions when they become disabled in the future.

Model testing evaluation

1. Multicollinearity test

The purpose of the multicollinearity test is to determine whether the explanatory variables are highly correlated. If the correlation between the variables is high, the regression results will be distorted, and their reliability will be compromised. When analyzing the test results, a higher variance inflation factor (VIF) indicates a higher correlation between the variables. Generally, if the VIF value is less than 10, it is considered to pass the multicollinearity test. If there is multicollinearity between the independent variables, it will often lead to an increase in the variance of the regression coefficients, so that the regression coefficients cannot pass the significance test. Therefore, before carrying out multiple Logistic regression, it is necessary to carry out the multicollinearity test on the 16 independent variables in this paper to ensure the reliability of the subsequent regression results. In this part, VIF (Variance Inflation Factor) will be used for the test of multicollinearity. It is generally believed that the larger the VIF, the higher the degree of linear correlation between the independent variables, and when the VIF is greater than 10, it is considered that there is multicollinearity.

As can be seen from the Table 3, the VIF values of the 16 independent variables designed in this paper are all much less than 10, so there is no multicollinearity among the independent variables, and the subsequent multiple regression analyses of the model can be carried out directly.

Table 3.

Multicollinearity test

Primary variable	VIF
Sex	1.317
Age	1.261
Area	1.171
Education level	1.671
Pre-retirement occupation	1.302
Health status	1.872
Self-care level	1.230
Marital status	1.562
The number of children	1.721
Whether to live with children	1.232
Intergenerational support	1.451
Income status	1.462
Main source of income	1.781
Categories of health insurance	1.124
Whether the community provides elderly care services	1.541
Whether health services are available in the community	1.675

• (2)Goodness-of-fit of the model

After verifying that there is no covariance problem between the independent variables, it is necessary to further verify the quality of the Logistic binary regression model, that is, to carry out the goodness-of-fit test, the higher the degree of fit, indicating that the correlation between the independent variables and the dependent variable is more consistent with the actual situation. This paper takes Anderson's health behavior model as the theoretical framework and constructs three models respectively, among which, Model III integrates all the independent variables to be studied in this paper, so provides the most comprehensive and complete explanation of the factors influencing the willingness to choose the long-term care model of the older people with disabilities, therefore, this paper takes the fitting results of Model III as a representative to illustrate the overall fitting effect of the research model in this paper.

As shown in Table 4, the Chi-square statistic of the model likelihood ratio is 763.817 with a degree of freedom of 34, and a Sig value of significance is 0.000, which is less than the test criterion of 0.05. So the model is significant at 5% level of significance, and the model is generally meaningful.

Table 4.

Model fitting information

The model	Fits the standard −2 times logarithmic likelihood value	Chi-square	likelihood ratio test df	Significance
Intercept only Final	2143.380 1187.024	763.817	34	0.000

Binary Logistic regression analysis of factors influencing older people's willingness to accept nursing facilities in the event of future disability.

Based on the theoretical framework constructed in the previous paper, this paper incorporates the three characteristic factors of Anderson's health behavior model into the unordered multicategorical logistic regression model, and observes the changes in the overall model after the incorporation of different characteristic factors into the regression by using the stepwise regression analysis method. Model I considers the influence of propensity factors on the willingness of the older people to accept elderly care institutions when they become disabled in the future, model II adds enabling factors on this basis, and model III considers the influence of propensity factors, enabling factors and demand factors on the willingness of the older people to accept elderly care institutions when they become disabled in the future, and the regression results of the three models are shown in the Table 5.

Table 5.

Logistic regression analysis of factors influencing the willingness of older people to accept nursing institutions in the event of future disability

Variable	OR
	Model 1	Model 2	Model 3
Age (60-69years old)
70-79years old	1.264***	1.318**	1.287**
≥ 80 years old	1.457***	1.512**	1.493**
Marriage (not married)
At marriage	0.762***	0.821	0.783
Education level (primary and below)	1.018***	1.124***	1.578***
secondary school or junior college	1.649**
University	1.982***	1.682**	1.432**
Postgraduate and above		2.315***	2.013**
Pre-retirement occupation (public institutions)
State-owned or collective units	0.815	0.716	0.927
Private enterprise	0.562	0.524	0.423
Individual employment	0.613	0.569	0.716
Farming occupation	0.223	0.362	0.217
Number of children (Zero)
One		0.796***	0.742***
Two		0.643***	0.603***
≧Three		0.432***	0.453***
Live with children (Yes)
No		1.546***	1.457
Intergenerational support (financial care)
Life care		0.833	0.581
Emotional support		0.545	0.372
Income status (no income)
3000 yuan and below		1.754***	1.653***
3000 to 5000 yuan		1.985***	1.874***
5000–7000 yuan		2.932***	2.656***
More than 7000 yuan		3.763***	3.432***
The community provides elderly care services (Yes)
No 1.573*** 1.724***
The community provides elderly health services (Yes)
No 1.642** 1.875**
Health status (Health)
Chronic disease			1.935***
Severe illness (disability, dementia)			2.874***
Degree of self-care (full self-care)
Occasionally need help			1.021***
Often need help			1.575***
Completely unable to take care of oneself			1.873***

Note: Values are Exp(B) values; The independent variableis the reference group in parentheses

^*p < 0.1

^**p < 0.05

^***p < 0.01

After univariate analysis, the statistically significant propensity factors included in Model I include age, marital status, pre-retirement occupation, and education level. And the enabling factors included in Model II include the income status of the older people, the number of children, intergenerational support, the situation of living with children, and whether or not the community provides elderly care services and medical care, although the differences between the number of children and intergenerational support were not found to be statistically significant, they are generally considered to be independent variables that are closely related to the dependent variable, so the two variables are also included in the regression equation. The demand factors that should be included in Model III include the health status and degree of self-care of the older people.

1. The influence of propensity factors

In the Table 5, Model Ⅰ is a propensity factor model, which mainly considers the influence of demographic characteristics on the willingness of the older people to choose elderly care service organizations when they become incapacitated in the future, in which the three variables of age, marital status and education have a significant influence on the willingness of the older people. In the age factor, the likelihood of choosing an elderly care service institution in the event of future incapacity is 1.264 times higher for those aged 70–79 than for those aged 60–69, and the likelihood of choosing an elderly care service institution in the event of future incapacity for those aged 80 or older is 1.457 times higher than for those aged 60–69, which means that the older people get, the more likely they will choose elderly care service organizations.

With regard to the marital factor, the married older people are 0.762 times more likely to choose an elderly care facility in the event of future incapacity than those who are not married, suggests that the older people with spouses are more likely to consider relying on their partner's care in the event of future disability.

About the factor of education level, the likelihood of the older people with secondary school or junior college education to choose an elderly care facility when they become disabled in the future is 1.018 times higher than that of the older people with primary school education, the likelihood of the older people with university education to choose an elderly care facility when they become disabled in the future is 1.649 times higher than that of the older people with primary school education, and the likelihood of the older people with postgraduate education to choose an elderly care facility when they become disabled in the future is 1.982 times higher than that of the older people with primary school education, indicating that the higher the level of education, the stronger the acceptance of the older people to the elderly care institution.

This phenomenon reflects the significant influence of educational background on the attitudes and expectations of older person in selecting care services for future disability. Specifically, older adults with postgraduate education showed higher expectations than their peers without a primary school diploma when considering potential dependence on institutional care services in the future. Firstly, older people with higher educational backgrounds generally have higher socioeconomic status and greater access to resources. This is because they tend to have better career development opportunities and a stronger economic foundation, which enables them to afford higher quality services. Therefore, when considering their care needs in old age, this group may tend to seek or expect more professional, comfortable, and even personalized care environments and services. Secondly, older people with higher educational backgrounds may have better health awareness and access to information. Well-educated individuals usually have a stronger understanding of health management and can obtain relevant knowledge about elderly care services through various channels. This makes it easier for them to understand the various options available in the market and their advantages and disadvantages, resulting in a clearer and higher standard of demand. Finally, older people with higher educational backgrounds may have better personal values and a higher pursuit of quality of life. As education levels improve, people's requirements for quality of life also increase. For some highly educated older person, even in the case of physical decline, they still hope to maintain a high standard of living, including living conditions, food quality, and spiritual and cultural activities. This means that institutions providing elderly care services need to pay attention to the different needs of various customer groups and adjust their service content and modes accordingly to meet these diversified requirements. From the perspective of policy-making, the government and relevant management departments should be aware that there are different levels of elderly care needs in society. More inclusive and targeted support measures need to be introduced to promote the development and improvement of the entire elderly care service system.

The results for the variable of pre-retirement occupation in the study did not meet the criteria for statistical significance (P < 0.05). This indicates that the type of occupation before retirement did not have a significant effect on the model's prediction. In other words, the elderly person's pre-retirement occupation did not influence their willingness to choose institutional care when considering future disability.

• (2)The influence of enabling factors

In the Table 5, Model Ⅱ introduces the variables of enabling factors on the basis of Model Ⅰ, and the variables of age and education level which were significant in Model Ⅰ are still significant in Model Ⅱ, and the direction of their influence remains basically unchanged, only the variable of marital status changes from significant to non-significant. Among the enabling factors, the variables of the number of children, whether they live with their children, income status, whether the community provides elderly care services, and whether the community provides medical services all have a significant effect on the willingness of the older people to choose elderly care services when they become disabled in the future.

In the variable of the number of children, the likelihood of the older people with one child choosing an elderly care facility in the event of future incapacitation is 79.6 per cent of the likelihood of the older people without children, the likelihood of the older people with two children choosing an elderly care facility in the event of future incapacitation is 64.3 per cent of the likelihood of the older people without children, and the likelihood of the older people with more than three children choosing an elderly care facility in the event of future incapacitation is 43.2 per cent of the likelihood of the older people without children, indicating that the more children they have, the less likely the older people will choose an elderly care facility in the event of future incapacity. In the variable of whether or not they live with their children, those who do not live with their children are 1.546 times more likely than those who lived with their children to choose elderly care facility in the event of future disability.

About the variable of income, the likelihood that the older people with income of 5,000–7,000 RMB will choose an elderly care facility in the event of future disability is 2.932 times than that of the older people with no income, and the likelihood that the older people with an income of 7,000 RMB or more will choose an elderly care facility in the event of future disability is 3.763 times than that of the older people with no income. This means that the higher the income, the more likely it is that an older people will choose an elderly care facility in the event of future disability.

In the variable of whether or not the community provides elderly care service, the older people who cannot enjoy elderly care services in the community are 1.573 times more likely to choose an elderly care facility when they become disabled in the future than the older person who can enjoy elderly care service in the community. In the variable of whether the community provides health care services, the older person who cannot enjoy health care services in the community are 1.642 times more likely to choose an elderly care facility when they become disabled in the future than the older person can enjoy health care services in the community. This indicates that the availability of elderly care service and medical resources in the community has a significant positive effect on the older people's choice of an elderly care facility when they become disabled in the future, and the more abundant the care service and medical resources in the community, the less likely the older people will choose elderly care facility when they become disabled in the future.

In addition, the results of Model Ⅱ showed that the variable of pre-retirement occupation still did not meet the standard of statistical significance (P < 0.05). Similarly, the variable of intergenerational support also did not meet the standard of statistical significance (P < 0.05). This indicates that both pre-retirement occupation and intergenerational support had no significant impact on the model's prediction. In other words, the type of occupation before retirement and intergenerational support did not affect the willingness of older person to choose institutional care when considering future disability.

• (3)The influence of demand factors

In the Table 5, Model III introduces demand factors based on Model II, including the variables of health status and degree of self-care of the older people. From the regression results, it can be seen that most of the significant variables in the first two models are still significant and remain in the same direction, only the variable of living with children becomes no longer significant. Among the demand factors, health status has a significant effect on the willingness of the older people to choose an elderly care facility in the event of their future disability, those who suffering from long-term chronic diseases being 1.935 times more likely to choose an elderly care facility in the event of their future disability than those who are healthy, and those suffering from serious illnesses being 2.874 times more likely to choose an elderly care facility in the event of their future disability than those who are healthy.

In addition, the level of self-care had a significant effect on the willingness of the older people to choose an elderly care facility in the event of future disability. The older people who occasionally needed help being 1.021 times more likely to choose an elderly care facility in the event of future disability than those who were completely self-care, the older people who often needed help being 1.575 times more likely to choose an elderly care facility in the event of future disability than those who were completely self-care, and those who were completely unable to take care themselves being 1.873 times more likely to choose an elderly care facility in the event of future disability than those who were completely self-care.

In addition, the results of Model III showed that the variable of pre-retirement occupation still did not meet the standard of statistical significance (P < 0.05). Similarly, the variables of intergenerational support and marital status also did not meet the standard of statistical significance (P < 0.05). This indicates that the three variables—pre-retirement occupation, intergenerational support, and marital status—had no significant impact on the prediction of Model 3. In other words, after accounting for all predisposing, enabling, and demand factors, the type of occupation prior to retirement, level of intergenerational support, and marital status had little effect on the willingness of older person to choose institutional care when considering future disability.

It should be noted that this survey only collected data at one point in time, so it cannot reflect the change trends of variables over time. Additionally, due to resource constraints such as money and manpower, it is difficult to obtain a large enough sample size to meet ideal research needs. These limitations may result in findings that are constrained by the data collection method or sample size. Therefore, caution is required when interpreting and applying these results.

Discussion

From the results of the questionnaire correlation analysis, it can be seen that: (1) among the propensity factors, the older people's age, marital status, type of occupation, and education level have a correlation with the older people's willingness to accept institutional care services when they become disabled in the future; (2) among the enabling factors,, the older people's income status, the situation of living with their children, and whether or not the community provides elderly care services and medical care have a correlation with the older people's willingness to accept institutional care services when they become disabled in the future; (3)among the demand factors, the older people's health status, the degree of self-care have a correlation with the older people's willingness to accept institutional care services when they become disabled in the future. In a word, It is found that age, education level, number of children, income status, community provision of old-age care and medical services, health status, and self-care degree are all significantly correlated with the older person's willingness to choose old-age service institutions when they are disabled in the future. However, intergenerational support has no significant relationship with the choice intention. This is the difference between this study and previous studies. Based on the characteristics of the sample, the author believes that this conclusion is realistic and reasonable. In traditional Eastern culture, Chinese older person always adhere to the intergenerational concept of 'downward tilt.' Especially in contemporary society, where children face too much pressure to raise grandchildren and high workplace pressure, older person are more reluctant to bother their children. Therefore, when considering future care, they do not think too much about how much help their children can provide for them.

From the results of the regression analysis of the questionnaire, it can be seen that:

1. In the model Ⅰ, there is a significant relationship between the three variables and the willingness of the older people to accept institutional care services when they become disabled in the future. Among them, the older people with older age, no spouse and a higher level of education are more willing to accept institutional care services in the situation of future disability;

2. In Model Ⅱ, the variables of age and education are still significant, the variables of the marital status changes from significant to insignificant. However, the marital status variable changed from significant to non-significant. This change is possibly because the addition of the number of children and residence status variables reduced the effect of the spouse in caregiving. Living with children may increase the sources of care services for the elderly, as more family support becomes available. The greater the number of children, the greater the possibility of access to care services, which leads to a reduction in the older person's dependence on spousal care. Consequently, the marital status variable became insignificant. Additionally, when the variables of economic income, community care services, and accessibility of medical services were added to Model 2, the increase in external nursing support also reduced the older person's dependence on internal family care resources when disabled. This further contributed to the change in the marital status variable from significant to insignificant. Among the enabling factors, the variables of the number of children, whether living with children, income status, whether the community provides elderly care services and health care services all have a significant relationship with the willingness of the older people to choose an elderly care facility when they become disabled in the future. Among them, the older people with fewer children, not living with children, higher income, and the community does not provide elderly care and medical services are more willing to accept institutional care services in the situation of future disability;

3. In the model III, the variables of age, education, the number of children, the income status, the community to provide elderly care and medical services, the state of health, and the degree of self-care have a significant relationship with the older people when they are disabled in the future on the willingness to choose the elderly care service. In Model III, only the variable of living with children becomes no longer significant, which may be due to the substitution effect of the newly introduced health demand factor on its influence, indicating that the older people who cannot take care of themselves and have poorer health conditions have a greater demand for institutional care services. When physical health and independence are not taken into account, older persons living with children may receive basic care services. However, when physical illness and reduced independence are considered, older persons with chronic and serious illnesses have higher expectations of institutional care services in the event of future disability. The worse their physical health and independence, the higher their expectation of institutional care services. Older person in such conditions are more in need of specialized institutional care services. Additionally, because young people in contemporary China face greater pressure to raise children and compete in the workplace, the older person are less likely to rely on their children for nursing care in the event of future disability. As a result, the variable of living with children changes from significant to insignificant after taking into account the health demand factor.

Besides, the limitations of this study can offer valuable suggestions for future research. For example, in future studies, longitudinal studies can be conducted to track changes in the older person's expectations of institutional care over time. Additionally, research can focus on different sub-groups' expectations of institutional care and their influencing factors, as well as the impact of interventions aimed at improving the older person's acceptance of institutional care.

Conclusion

On the whole, it can be seen from the above study that the older people do not have a strong willingness to choose institutional care services when they become disabled in the future. The variables of age, education level, number of children, income, community provision of old-age care and medical services, health status, and self-care degree were significantly correlated with the older person's willingness to choose old-age service institutions when disabled in the future. Therefore, the nursing institutions should consider factors such as the age, education level, and number of children of the older person when designing elderly care services. This approach aims to provide a more professional, comfortable, and even personalized care environment and services for the older person with higher education levels and economic income. At the same time, the government and social organizations can lower the threshold for older people to stay in nursing homes by providing subsidies and tax relief, especially for low-income older people. Additionally, private capital should be encouraged to invest in the field of elderly care, thereby increasing the diversity of service supply.

Given that health status and self-care ability are important factors affecting the choice of institutional care services for older people in the event of future disability, governments should focus on improving the level of primary health care services and promote the development of integrated healthcare institutions. This will ensure that older people have easy access to the medical services they need. In addition, the government should strengthen publicity and education, popularizing scientific knowledge about elderly care through various channels. This can help change the traditional misconception that living in a nursing home means being abandoned, creating a positive social atmosphere where more older person are willing to accept professional care services. Furthermore, for the majority of older person living at home in the community, there should be a focus on developing inclusive community-based home care services. A comprehensive service platform combining community medical care and integrating medical and daily care service resources should be established.

Moreover, the study shows that the older people in China have great expectations for family care, so while developing socialized elderly care services, we should also pay attention to promoting filial piety, improving relevant family policies, repairing and consolidating the traditional function of family care, and supporting family members to provide daily care and nursing services for the older people. In addition, the establishment of elderly care institutions should take into account the acceptability of the older people at all income levels, rather than just building high-end elderly care institutions, and should focus on the quality and continuity of the services provided by elderly care institutions, which is the key to the development of elderly care institutions.

Previous studies on the older person's willingness to accept institutional care and the factors affecting their care decisions have shown that age, marital status, income level, occupation type, health status, number of children, intergenerational support, and accessibility of elderly care services all influence their choice of nursing services. These findings are consistent with most variables in this study. However, this study found that pre-retirement occupation and intergenerational support did not significantly impact older adults' willingness to choose institutional care in the event of future disability, which is something we need to pay attention to.

Besides, this study is different from other studies in sample selection, data collection and analysis methods. First, this study was conducted on a national scale, which means it is more broadly representative. Such samples give a better picture of the country as a whole than studies that are confined to specific regions or populations, helping to spot more general trends. Secondly, in terms of data collection, Anderson's health behavior model is used as a theoretical framework to guide the design of data collection tools. Questionnaire content may be constructed around various variables mentioned in the model, which makes the data directly relevant to the research purpose. Finally, in terms of analysis methods, using Anderson health behavior model as the main analysis framework, combined with regression analysis, can help to identify the multi-level factors affecting the dependent variables and their interactions.

Limitations of the study

This paper explores older people's expectations of institutional care in the event of future disability and the factors that influence them, based on the Anderson Health Behavior Model. However, there are still some shortcomings in this study. For example, with regard to data selection, the number of samples selected for the community was limited due to time constraints. Secondly, regarding the selection of independent variables, this paper only considers the most influential aspects that people generally believe, but does not include some potential more detailed factors, especially the selection of factors influencing individual demand is not comprehensive enough.

Biographies

Yuanyuan Heng

Holds a PhD in Social Security with research and teaching interest in geriatric health and Health Policy Management. She has 8 years of researching experience in this area. She is currently a teacher at the School of Social Work at Henan Normal University.

Yujuan He

She is a laboratory technician at the Clinical Skills Training Centre of Xinxiang Medical University. She has 2 years of working and researching experience in health policy area.

Zhaojun Meng

is a teacher at the School of Social Work at Henan Normal University, he has been engaged in research in this field for 2 years.

Authors’ contributions

Y.H. responsible for the design of model,drafted the manuscript and involved in critically revising the manuscript for important intellectual content. Y.He. responsible for the design of the study, analyzed and explained the data. Z. M. consulted during the analysis and interpretation process. All the authors read and approved the final manuscript.

Funding

This research was funded by Science and Technology Department of Henan Province (Soft Science Research project), grant number 232400410251. This research was funded by Philosophy and Social Sciences Office of Henan Province, grant number 2023CSH033.

Data availability

The data are not publicly available due to restrictions, their containing information that could compromise the privacy of research participants but data can be made available from the Corresponding Author on reasonable requests. The email address is: 13639638357@163.com.

Declarations

Ethics approval and consent to participate

The data was obtained by the author in February to October 2020 in 12 provinces of the China. This study included experimental procedures were passed the review of the ethics organization of Henan Normal University. We confirmed that informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.