Caring perception questionnaire of the home-dwelling elderly: development and validation study
Population aging is a global issue where the proportion of elderly people is increasing. The UN projects that by 2050, 16% of the world’s population will be over 65, up from 11% in 2019 . In Mainland China, 264 million people were aged 60 and over in 2020, making up 18.7% of the population . The impact of aging varies by country due to differences in awareness, healthcare, and gerontological services. Japan has the highest elderly proportion, but other developing Asian countries may face greater challenges . Aging populations strain healthcare, pensions, and social services. Countries are responding with policies such as Singapore’s integrated long-term elderly care services  and Japan’s adjustments in pension and health services since 1950 . China is also adapting its policies to address increasing elderly care needs . Home-dwelling elderly deserve special attention. In China, elderly care includes family, institutional, and community support . To enhance care, China plans to focus on family care, community support, and supplementary nursing homes . Japan provides more home and community nursing services [ – ], while Finland improves care through better family caregiver training and the Finnish Care Classification [ – ]. Sweden manages home care through registries and supports the psychological needs of elderly individuals . While home-based care aligns with traditional values in China and is preferred by many elderly, current policies do not fully meet their needs . Research is mainly on hospice care, service quality, and disease prevention, with few studies on the experiences of home-dwelling elderly . In the 1980s, Jean Watson first introduced “humanistic care” in the book “Nursing: The Philosophy and Science of Care” . Watson defined caring as a loving interaction that supports physical, psychological, social, and spiritual health . With the global aging population increasing, there is growing focus on humanistic care for the elderly, encompassing unconditional love, understanding, and support . Existing studies, however, only look at family elderly with a single or partial source of care, such as family caregivers, self care, emotion and social network, life satisfaction and community services, and social support for the elderly [ – ]. There is still a lack of an overall evaluation system for the care perception of the elderly at home. While different tools have been developed to assess care recipients or care providers, no such tool has been developed to assess the caring perception for home-based elderly people. The care perception of elderly individuals presents a diverse range of characteristics. It includes the advantages of family support, but also faces challenges in areas such as care-giving systems, health management, and social support. This study aims to develop a tool to assess the care perceptions of home-dwelling elderly individuals. This tool will help understand their current care perceptions, enhance societal care-giving behaviors, and advance home care services. The questionnaire will address gaps in current assessment tools and offer insights for elderly care research. Practically, it will improve societal understanding of the elderly, facilitate humanistic care, and enhance their quality of life. Overall, the development and validation of this questionnaire will aid in exploring factors affecting care perceptions among home-dwelling elderly individuals. 

This study was completed in 2022, with the primary research location in Wuhan, Hubei Province. Convenience sampling was used to conduct qualitative interviews with several urban elderly individuals living at home in Wuhan. The results, along with a literature review, were used to develop a pool of questionnaire items. Two rounds of Delphi expert consultations were conducted to finalize the first draft of the caring perception questionnaire of the home-dwelling elderly. Several experts involved came from six provinces in China. Then, a survey was conducted with elderly individuals living at home in four cities. The data from these questionnaires were analyzed to assess the reliability and validity of questionnaire, leading to the development of the final version of the questionnaire. Phase 1: Item generation Using search terms including “home-based elderly care"、"home-dwelling elderly"、 “urban elderly"、 “humanistic care"、 “care perception"、 “questionnaire"、"questionnaire development"、 “validation"、 “reliability and validity testing"、 “reliability analysis” and “validity analysis”, a comprehensive literature search was conducted across multiple databases (PubMed, Embase, Scopus, WOS, OVID, Web of Science). This search focused on literature related to humanistic care for home-dwelling elderly individuals, care services, and questionnaire development. A total of 50 English and 46 Chinese articles were analyzed to provide a foundation for designing the qualitative interview outline and constructing the item pool for the questionnaire. Convenience sampling was adopted to select 30 home-dwelling elderly people for a semi-structured interview. Additionally, the sample was drawn from diverse neighborhoods across Wuhan to capture a variety of living conditions and social backgrounds, thereby enhancing the diversity of perspectives. The inclusion criteria includes home-dwelling elderly aged 60 or above in the city of Wuhan, China; normal cognition, clear thinking, and general communication ability. These criteria helped ensure that the participants were representative of the target population and capable of providing meaningful and reliable responses. The following is the outline of the interview: What kinds of caring have you felt in your daily life? Please give some examples. When you suffer difficulties, who do you usually ask for help? How would you ask for help? Generally speaking, do you feel your caring needs are met? What difficulties or problems do you have at present? What kinds of caring and help do you want? The data from the interview was analyzed using NVIVO11.0. Based on the literature analysis and semi-structured interview, the item pool of the caring perception questionnaire of the home-dwelling elderly was initially formed. Phase 2: Delphi method and content validity Fifteen experts were invited to evaluate the items. In this study, experts were connected by email to screen the questionnaire items and give their suggestions. The expert correspondence questionnaire consisted of three parts: preface (research background and purpose), body part (the preliminary form of the care perception questionnaire for the home-dwelling elderly), and basic information of experts(personal information and questionnaire familiarity). After two rounds of consultation, opinions from experts reached a consensus. All items of the preliminary care perception scale of the home-dwelling elderly were listed, and experts were asked to explain their modification or deletion opinions. Likert 5-level scoring method being used, 1–5 points were assigned from “very unimportant” to “very important” for each item. The mean importance score ≥ 4.0 and Coefficient of Variation (CV) ≤ 0.25 were taken as the indicator screening criteria, and the items were supplemented, deleted or modified based on expert opinions. The most commonly used indicators for evaluating the content validity of a scale is the Content Validity Index (CVI), which includes two types: the item-level Content Validity Index (I-CVI) and the scale-level Content Validity Index (S-CVI), with the latter being the average of the former . The evaluation criteria were I-CVI ≥ 0.78 and S-CVI/Ave ≥ 0.80. The formula for calculating the authority coefficient (Cr) is Cr = (Ca + Cs)/2, in which Ca indicates the experts’ judgment criteria and Cs shows the degree of familiarity with each indication. The judgment criteria is based on four characteristics. If the expert authority coefficient exceeds 0.7, the authority level is considered high, and the scores and recommendations provided by the expert are more reliable. Phase 3: psychometric test Sampling and data collection The study was mainly carried on in Wuhan, Hubei Province(59.2%) and second and third-tier cities(39.1%) in China. The surveyed population was the elderly over 60 years old. Their choice of pension mode was a home-based pension, which could actively cooperate with the researchers’ investigation. They had no serious mental illness and were not in the terminal stage. They volunteered to participate in the study. The ethics department of the university authorized the study, and the person in charge of the community where the elderly lived was informed and cooperated with the study before questionnaire distribution. The survey tools included general demographic data and a formal draft of the care perception questionnaire. The sample size for factor analysis should be 5–10 times the number of items . The preliminary draft of the questionnaire contains 52 items according to the literature review and semi-structured interview. To ensure a sufficient sample size for robust statistical analysis, the convenience sampling method was employed for the survey. While convenience sampling is often associated with limitations such as potential selection bias, several steps were taken to enhance the reliability of the data. Participants were recruited from diverse geographic locations within the target population (home-dwelling elderly in Wuhan, China), and strict inclusion criteria (e.g., age 60 or above, normal cognition, and clear communication ability) were applied to ensure the sample’s relevance to the study objectives. A total of 260 questionnaires were collected, of which 238 were valid, with an effective rate of 91.54%. These valid samples were used for Item analysis, reliability analysis and exploratory factor analysis(EFA). To validate the questionnaire’s reliability, the second round of survey was conducted with home-dwelling elderly individuals using convenience sampling. A total of 290 questionnaires were collected, of which 260 were valid, with an effective rate of 89.66%. The survey data were used for confirmatory factor analysis(CFA). The large sample sizes, rigorous inclusion criteria, and geographic diversity of participants helped mitigate potential biases and strengthen the validity of the findings. The data collection methods included both online and paper questionnaires, each serving a specific purpose to ensure comprehensive and reliable data. The online questionnaires were published and managed by the researchers, who sorted and screened the responses to eliminate any submissions with significantly shorter completion times. Simultaneously, paper questionnaires were distributed by researchers who visited various communities where the elderly reside, allowing for direct interaction and assistance to participants, particularly those with limited digital literacy. By employing both methods on the same target population, we aimed to capture a more representative and diverse range of responses while maintaining consistency in questionnaire content and participant criteria. Data analysis The data obtained was imported into Excel and coded before the analysis. The methods used for the analysis were: item analysis, construct validity analysis and reliability analysis. IBM SPSS software version 26.0 and AMOS software version 24.0 were used to conduct the statistical analysis. Item analysis : (1) Critical ratio method: the differences between the two extreme groups (the top 27% of the total score of the scale was high, and the bottom 27% was low) were compared between groups by an independent sample T-test, and the items with P > 0.05 and critical ratio greater than 3.00 were retained. (2) Homogeneity test: the items with a significant product difference correlation coefficient ( P > 0.05) and a high correlation coefficient ( R > 0.4) were retained. (3) Cronbach’s α coefficient method: keep the dimensions and items with internal consistency α coefficient above 0.80; If an item is deleted and the internal consistency α coefficient of the dimension or total scores significantly increases, the item should be deleted. (4) Commonness and factor load: retain the items with commonness value ≥ 0.20 and factor load ≥ 0.45. Construct validity analysis : (1)The kaiser-Meyer-Olkin Measure of sampling (KMO) value was calculated. When the KMO value was greater than 0.50, the factor analysis can be carried out among item variables. (2) Bartlett’s spherical test was performed. When the significance probability value p < 0.05, it was suitable for factor analysis. (3) EFA was carried out. The principal component analysis was used for the factor extraction, and the maximum variance method-one of the orthogonal axis method was used for the factor rotation method. Test principles included: cumulative explanatory variation of extracted common factors is greater than 60%; Common factors include at least three items; It conforms to the test principle of gravel map and is easy to name. (4) To further verify the scale structure validity, 260 valid questionnaires from the second round of the survey were used for CFA to evaluate the model fitting degree. Reliability analysis : Internal consistency reliability: Cronbach’s α coefficients of the total amount table and each dimension were calculated. When corresponding Cronbach’s coefficients are greater than 0.9, the questionnaire’s or first-level index’s internal consistency reliability is good. Ethical consideration This study was approved by the University Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology. Informed consent was obtained from participants and the data collected were anonymous. 

Using search terms including “home-based elderly care"、"home-dwelling elderly"、 “urban elderly"、 “humanistic care"、 “care perception"、 “questionnaire"、"questionnaire development"、 “validation"、 “reliability and validity testing"、 “reliability analysis” and “validity analysis”, a comprehensive literature search was conducted across multiple databases (PubMed, Embase, Scopus, WOS, OVID, Web of Science). This search focused on literature related to humanistic care for home-dwelling elderly individuals, care services, and questionnaire development. A total of 50 English and 46 Chinese articles were analyzed to provide a foundation for designing the qualitative interview outline and constructing the item pool for the questionnaire. Convenience sampling was adopted to select 30 home-dwelling elderly people for a semi-structured interview. Additionally, the sample was drawn from diverse neighborhoods across Wuhan to capture a variety of living conditions and social backgrounds, thereby enhancing the diversity of perspectives. The inclusion criteria includes home-dwelling elderly aged 60 or above in the city of Wuhan, China; normal cognition, clear thinking, and general communication ability. These criteria helped ensure that the participants were representative of the target population and capable of providing meaningful and reliable responses. The following is the outline of the interview: What kinds of caring have you felt in your daily life? Please give some examples. When you suffer difficulties, who do you usually ask for help? How would you ask for help? Generally speaking, do you feel your caring needs are met? What difficulties or problems do you have at present? What kinds of caring and help do you want? The data from the interview was analyzed using NVIVO11.0. Based on the literature analysis and semi-structured interview, the item pool of the caring perception questionnaire of the home-dwelling elderly was initially formed. 

Fifteen experts were invited to evaluate the items. In this study, experts were connected by email to screen the questionnaire items and give their suggestions. The expert correspondence questionnaire consisted of three parts: preface (research background and purpose), body part (the preliminary form of the care perception questionnaire for the home-dwelling elderly), and basic information of experts(personal information and questionnaire familiarity). After two rounds of consultation, opinions from experts reached a consensus. All items of the preliminary care perception scale of the home-dwelling elderly were listed, and experts were asked to explain their modification or deletion opinions. Likert 5-level scoring method being used, 1–5 points were assigned from “very unimportant” to “very important” for each item. The mean importance score ≥ 4.0 and Coefficient of Variation (CV) ≤ 0.25 were taken as the indicator screening criteria, and the items were supplemented, deleted or modified based on expert opinions. The most commonly used indicators for evaluating the content validity of a scale is the Content Validity Index (CVI), which includes two types: the item-level Content Validity Index (I-CVI) and the scale-level Content Validity Index (S-CVI), with the latter being the average of the former . The evaluation criteria were I-CVI ≥ 0.78 and S-CVI/Ave ≥ 0.80. The formula for calculating the authority coefficient (Cr) is Cr = (Ca + Cs)/2, in which Ca indicates the experts’ judgment criteria and Cs shows the degree of familiarity with each indication. The judgment criteria is based on four characteristics. If the expert authority coefficient exceeds 0.7, the authority level is considered high, and the scores and recommendations provided by the expert are more reliable. 

Sampling and data collection The study was mainly carried on in Wuhan, Hubei Province(59.2%) and second and third-tier cities(39.1%) in China. The surveyed population was the elderly over 60 years old. Their choice of pension mode was a home-based pension, which could actively cooperate with the researchers’ investigation. They had no serious mental illness and were not in the terminal stage. They volunteered to participate in the study. The ethics department of the university authorized the study, and the person in charge of the community where the elderly lived was informed and cooperated with the study before questionnaire distribution. The survey tools included general demographic data and a formal draft of the care perception questionnaire. The sample size for factor analysis should be 5–10 times the number of items . The preliminary draft of the questionnaire contains 52 items according to the literature review and semi-structured interview. To ensure a sufficient sample size for robust statistical analysis, the convenience sampling method was employed for the survey. While convenience sampling is often associated with limitations such as potential selection bias, several steps were taken to enhance the reliability of the data. Participants were recruited from diverse geographic locations within the target population (home-dwelling elderly in Wuhan, China), and strict inclusion criteria (e.g., age 60 or above, normal cognition, and clear communication ability) were applied to ensure the sample’s relevance to the study objectives. A total of 260 questionnaires were collected, of which 238 were valid, with an effective rate of 91.54%. These valid samples were used for Item analysis, reliability analysis and exploratory factor analysis(EFA). To validate the questionnaire’s reliability, the second round of survey was conducted with home-dwelling elderly individuals using convenience sampling. A total of 290 questionnaires were collected, of which 260 were valid, with an effective rate of 89.66%. The survey data were used for confirmatory factor analysis(CFA). The large sample sizes, rigorous inclusion criteria, and geographic diversity of participants helped mitigate potential biases and strengthen the validity of the findings. The data collection methods included both online and paper questionnaires, each serving a specific purpose to ensure comprehensive and reliable data. The online questionnaires were published and managed by the researchers, who sorted and screened the responses to eliminate any submissions with significantly shorter completion times. Simultaneously, paper questionnaires were distributed by researchers who visited various communities where the elderly reside, allowing for direct interaction and assistance to participants, particularly those with limited digital literacy. By employing both methods on the same target population, we aimed to capture a more representative and diverse range of responses while maintaining consistency in questionnaire content and participant criteria. Data analysis The data obtained was imported into Excel and coded before the analysis. The methods used for the analysis were: item analysis, construct validity analysis and reliability analysis. IBM SPSS software version 26.0 and AMOS software version 24.0 were used to conduct the statistical analysis. Item analysis : (1) Critical ratio method: the differences between the two extreme groups (the top 27% of the total score of the scale was high, and the bottom 27% was low) were compared between groups by an independent sample T-test, and the items with P > 0.05 and critical ratio greater than 3.00 were retained. (2) Homogeneity test: the items with a significant product difference correlation coefficient ( P > 0.05) and a high correlation coefficient ( R > 0.4) were retained. (3) Cronbach’s α coefficient method: keep the dimensions and items with internal consistency α coefficient above 0.80; If an item is deleted and the internal consistency α coefficient of the dimension or total scores significantly increases, the item should be deleted. (4) Commonness and factor load: retain the items with commonness value ≥ 0.20 and factor load ≥ 0.45. Construct validity analysis : (1)The kaiser-Meyer-Olkin Measure of sampling (KMO) value was calculated. When the KMO value was greater than 0.50, the factor analysis can be carried out among item variables. (2) Bartlett’s spherical test was performed. When the significance probability value p < 0.05, it was suitable for factor analysis. (3) EFA was carried out. The principal component analysis was used for the factor extraction, and the maximum variance method-one of the orthogonal axis method was used for the factor rotation method. Test principles included: cumulative explanatory variation of extracted common factors is greater than 60%; Common factors include at least three items; It conforms to the test principle of gravel map and is easy to name. (4) To further verify the scale structure validity, 260 valid questionnaires from the second round of the survey were used for CFA to evaluate the model fitting degree. Reliability analysis : Internal consistency reliability: Cronbach’s α coefficients of the total amount table and each dimension were calculated. When corresponding Cronbach’s coefficients are greater than 0.9, the questionnaire’s or first-level index’s internal consistency reliability is good. 

The study was mainly carried on in Wuhan, Hubei Province(59.2%) and second and third-tier cities(39.1%) in China. The surveyed population was the elderly over 60 years old. Their choice of pension mode was a home-based pension, which could actively cooperate with the researchers’ investigation. They had no serious mental illness and were not in the terminal stage. They volunteered to participate in the study. The ethics department of the university authorized the study, and the person in charge of the community where the elderly lived was informed and cooperated with the study before questionnaire distribution. The survey tools included general demographic data and a formal draft of the care perception questionnaire. The sample size for factor analysis should be 5–10 times the number of items . The preliminary draft of the questionnaire contains 52 items according to the literature review and semi-structured interview. To ensure a sufficient sample size for robust statistical analysis, the convenience sampling method was employed for the survey. While convenience sampling is often associated with limitations such as potential selection bias, several steps were taken to enhance the reliability of the data. Participants were recruited from diverse geographic locations within the target population (home-dwelling elderly in Wuhan, China), and strict inclusion criteria (e.g., age 60 or above, normal cognition, and clear communication ability) were applied to ensure the sample’s relevance to the study objectives. A total of 260 questionnaires were collected, of which 238 were valid, with an effective rate of 91.54%. These valid samples were used for Item analysis, reliability analysis and exploratory factor analysis(EFA). To validate the questionnaire’s reliability, the second round of survey was conducted with home-dwelling elderly individuals using convenience sampling. A total of 290 questionnaires were collected, of which 260 were valid, with an effective rate of 89.66%. The survey data were used for confirmatory factor analysis(CFA). The large sample sizes, rigorous inclusion criteria, and geographic diversity of participants helped mitigate potential biases and strengthen the validity of the findings. The data collection methods included both online and paper questionnaires, each serving a specific purpose to ensure comprehensive and reliable data. The online questionnaires were published and managed by the researchers, who sorted and screened the responses to eliminate any submissions with significantly shorter completion times. Simultaneously, paper questionnaires were distributed by researchers who visited various communities where the elderly reside, allowing for direct interaction and assistance to participants, particularly those with limited digital literacy. By employing both methods on the same target population, we aimed to capture a more representative and diverse range of responses while maintaining consistency in questionnaire content and participant criteria. 

The data obtained was imported into Excel and coded before the analysis. The methods used for the analysis were: item analysis, construct validity analysis and reliability analysis. IBM SPSS software version 26.0 and AMOS software version 24.0 were used to conduct the statistical analysis. Item analysis : (1) Critical ratio method: the differences between the two extreme groups (the top 27% of the total score of the scale was high, and the bottom 27% was low) were compared between groups by an independent sample T-test, and the items with P > 0.05 and critical ratio greater than 3.00 were retained. (2) Homogeneity test: the items with a significant product difference correlation coefficient ( P > 0.05) and a high correlation coefficient ( R > 0.4) were retained. (3) Cronbach’s α coefficient method: keep the dimensions and items with internal consistency α coefficient above 0.80; If an item is deleted and the internal consistency α coefficient of the dimension or total scores significantly increases, the item should be deleted. (4) Commonness and factor load: retain the items with commonness value ≥ 0.20 and factor load ≥ 0.45. Construct validity analysis : (1)The kaiser-Meyer-Olkin Measure of sampling (KMO) value was calculated. When the KMO value was greater than 0.50, the factor analysis can be carried out among item variables. (2) Bartlett’s spherical test was performed. When the significance probability value p < 0.05, it was suitable for factor analysis. (3) EFA was carried out. The principal component analysis was used for the factor extraction, and the maximum variance method-one of the orthogonal axis method was used for the factor rotation method. Test principles included: cumulative explanatory variation of extracted common factors is greater than 60%; Common factors include at least three items; It conforms to the test principle of gravel map and is easy to name. (4) To further verify the scale structure validity, 260 valid questionnaires from the second round of the survey were used for CFA to evaluate the model fitting degree. Reliability analysis : Internal consistency reliability: Cronbach’s α coefficients of the total amount table and each dimension were calculated. When corresponding Cronbach’s coefficients are greater than 0.9, the questionnaire’s or first-level index’s internal consistency reliability is good. 

This study was approved by the University Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology. Informed consent was obtained from participants and the data collected were anonymous. 

Item analysis Through the literature review and the results of the qualitative interview, the item pool of the questionnaire was constructed. The 6 s-level indexes under 3 first-level indexes including 52 items were built based on the distinct properties of each first-level index. The total items included 9 items for self-care, 21 items for family relative care, and 22 items for social care. The caring level of each subject can be adequately evaluated by calculating the scores of questionnaires. Delphi method For two rounds, suggestions from 15 experts were received. In the first round, 17 surveys were sent out, with 15 responses obtained, resulting in an 88% recovery rate. Fifteen surveys were sent out in the second round, and 12 responses were received. The experts are from Hubei, Henan, Guangdong, Fujian, Jiangsu and Sichuan provinces in China. Their research covers a wide range of fields, including humanistic care, clinical nursing, nursing management, medical humanities, and sociology. All of them have worked for more than 10 years, and hold intermediate-grade or above professional titles in China, as shown in Table . Correlation evaluation coefficient The authority coefficient of experts was calculated to be 0.92 in the two rounds, indicating the relatively high expert authority. Kendall’s W on the questionnaire was 0.196(X2 = 190.86, P < 0.01) in the first round. The C Vs of the items ranged from 0 to 0.23, with 0.140 being the average. Kendall’s W on the questionnaire in the second round was 0.196 (X2 = 190.64, P < 0.01). The C Vs of the items had a fluctuation range of 0-0.24, with an average of 0.110. Although Kendall’s W values for the two rounds of expert consultation were not particularly high, they were all significant, indicating that the expert scores were based and credible. The average C Vs of items had shrunk, indicating that expert differences had shrunk. Establishment of the second index system In each round, items were evaluated by calculating the average importance score and CV for second-level indexes and items. The revised questionnaire, incorporating these calculations, expert advice, literature review, and research group discussions, comprised three first-level indexes, six second-level indexes, and 43 items. Content validity The Clevis ranged from 0.44 to 1, and items with scores of less than 0.78 were removed. The overall S-CVI/Ave of the questionnaire was 0.89. The content validity was good overall. Table provides more information about this. Although the I-CVI of d1, d2, d3, and d4 lied between 0.67 and 0.75, the caring from the government such as some preferential policies like ticket reduction and subsidies, the facility-construction of fitness and entertainment, special channels or services for the elderly bring a lot of convenience to the old people’s life. For many old people who lack enough pensions, preferential policies from the government and communities can largely meet the practical needs of the elderly. Studies have found that elderly people are concerned about key basic services provided by the government, such as access to quality health care, whose well-being is also influenced by the quality of urban government services . In addition, many elderly people express an appeal for government services to meet their higher spiritual needs, such as building enough recreational and exercise facilities and places for elderly activities in the community. The I-CVI of f4 was 0.75 but was still retained owing to its significance. Psychometric analysis Sample characteristics A total of 550 elderly living at home answered the questionnaire, and 498 questionnaires were included in the study, with a 91% recovery rate. Table shows the main characteristics of this sample. The sample size of 498 included total samples for EFA and CFA. Item analysis The CR values of 43 items were all significant, ranging from 3.761 to 13.940( P <0.05), according to the calculation. This version of the questionnaire exhibited discrimination between the high and low-scoring groups on all of the items. In homogeneity, the correlation coefficient between a1 item, a3 item and the total score of the corresponding first-level index (self-caring index) was less than 0.4 (r1 = 0.380, r2 = 0.381), so these two items were deleted. The correlation coefficient between the b7 item and the total score of the corresponding first-level index (family and relative index) was 0.269, so this item was also deleted. As shown in Table . The commonness of all the items was over 0.20. Except that the factor load of a1, a2, a3, a4, a8 and b7 items was lower than 0.45, the load values of other items on the corresponding factor were > 0.45, as shown in Table . Therefore, a1, a2, a3, a4, a8 and b7 were deleted. Reliability analysis Internal consistency reliability analysis, Split-half reliability: The total Cronbach’s α was 0.945, while each first-level index’s Cronbach’s α ranged from 0.811 to 0.949. The overall split-half reliability was 0.805. Construct validity analysis The KMO value of the whole scale was 0.893 ( P < 0.001). The Bartlett spherical test revealed a substantial level of significance (X2 = 9704.073, P < 0.001). These indicated suitability for EFA. Six factors were limited to be extracted. The cumulative variance contribution rate was 69.02% > 60%, indicating that the structure validity was relatively good. The MSA values in the correlation matrix of reflected images ranged from 0.857 to 0.944, all of which were > 0.50. The load of items f2, f4, f7 and d4 on the two factors is > 0.40, and the difference value is > 0.20, so they were deleted. The items of g6 and g8 were divided into two factors, which of whom should be in the fifth factor, so these two items were deserted, as shown in Table . After a further screening of the items by EFA, the caring perception scale for the home-based elderly with 31 items in 6 dimensions was finally determined, as shown in Table . The goodness of fit of each dimension and item of the questionnaire was tested by CFA. The results showed that the chi-square test of goodness of fit of the scale model was χ2 = 1049.98. Chi-square value/degree of freedom (χ2/ DF) = 2.49 ( P < 0.05), non-standard fit index (TLI) = 0.91, incremental fit index (IFI) = 0.92, Comparison fitting index (CFI) = 0.92, root mean square error (RMSEA) = 0.07. The model fitting degree standard  was χ 2 degree of freedom ratio < 3.00, TLI, IFI, CFI > 0.90, RMSEA < 0.08. The load values of each item on the corresponding factors ranged from 0.54 to 0.97. According to the model fit standard, the questionnaire fitting index in this study met the requirements of fit. The model fitted well and had good structural validity. 

Through the literature review and the results of the qualitative interview, the item pool of the questionnaire was constructed. The 6 s-level indexes under 3 first-level indexes including 52 items were built based on the distinct properties of each first-level index. The total items included 9 items for self-care, 21 items for family relative care, and 22 items for social care. The caring level of each subject can be adequately evaluated by calculating the scores of questionnaires. 

For two rounds, suggestions from 15 experts were received. In the first round, 17 surveys were sent out, with 15 responses obtained, resulting in an 88% recovery rate. Fifteen surveys were sent out in the second round, and 12 responses were received. The experts are from Hubei, Henan, Guangdong, Fujian, Jiangsu and Sichuan provinces in China. Their research covers a wide range of fields, including humanistic care, clinical nursing, nursing management, medical humanities, and sociology. All of them have worked for more than 10 years, and hold intermediate-grade or above professional titles in China, as shown in Table . Correlation evaluation coefficient The authority coefficient of experts was calculated to be 0.92 in the two rounds, indicating the relatively high expert authority. Kendall’s W on the questionnaire was 0.196(X2 = 190.86, P < 0.01) in the first round. The C Vs of the items ranged from 0 to 0.23, with 0.140 being the average. Kendall’s W on the questionnaire in the second round was 0.196 (X2 = 190.64, P < 0.01). The C Vs of the items had a fluctuation range of 0-0.24, with an average of 0.110. Although Kendall’s W values for the two rounds of expert consultation were not particularly high, they were all significant, indicating that the expert scores were based and credible. The average C Vs of items had shrunk, indicating that expert differences had shrunk. Establishment of the second index system In each round, items were evaluated by calculating the average importance score and CV for second-level indexes and items. The revised questionnaire, incorporating these calculations, expert advice, literature review, and research group discussions, comprised three first-level indexes, six second-level indexes, and 43 items. 

The authority coefficient of experts was calculated to be 0.92 in the two rounds, indicating the relatively high expert authority. Kendall’s W on the questionnaire was 0.196(X2 = 190.86, P < 0.01) in the first round. The C Vs of the items ranged from 0 to 0.23, with 0.140 being the average. Kendall’s W on the questionnaire in the second round was 0.196 (X2 = 190.64, P < 0.01). The C Vs of the items had a fluctuation range of 0-0.24, with an average of 0.110. Although Kendall’s W values for the two rounds of expert consultation were not particularly high, they were all significant, indicating that the expert scores were based and credible. The average C Vs of items had shrunk, indicating that expert differences had shrunk. 

In each round, items were evaluated by calculating the average importance score and CV for second-level indexes and items. The revised questionnaire, incorporating these calculations, expert advice, literature review, and research group discussions, comprised three first-level indexes, six second-level indexes, and 43 items. 

The Clevis ranged from 0.44 to 1, and items with scores of less than 0.78 were removed. The overall S-CVI/Ave of the questionnaire was 0.89. The content validity was good overall. Table provides more information about this. Although the I-CVI of d1, d2, d3, and d4 lied between 0.67 and 0.75, the caring from the government such as some preferential policies like ticket reduction and subsidies, the facility-construction of fitness and entertainment, special channels or services for the elderly bring a lot of convenience to the old people’s life. For many old people who lack enough pensions, preferential policies from the government and communities can largely meet the practical needs of the elderly. Studies have found that elderly people are concerned about key basic services provided by the government, such as access to quality health care, whose well-being is also influenced by the quality of urban government services . In addition, many elderly people express an appeal for government services to meet their higher spiritual needs, such as building enough recreational and exercise facilities and places for elderly activities in the community. The I-CVI of f4 was 0.75 but was still retained owing to its significance. 

Sample characteristics A total of 550 elderly living at home answered the questionnaire, and 498 questionnaires were included in the study, with a 91% recovery rate. Table shows the main characteristics of this sample. The sample size of 498 included total samples for EFA and CFA. Item analysis The CR values of 43 items were all significant, ranging from 3.761 to 13.940( P <0.05), according to the calculation. This version of the questionnaire exhibited discrimination between the high and low-scoring groups on all of the items. In homogeneity, the correlation coefficient between a1 item, a3 item and the total score of the corresponding first-level index (self-caring index) was less than 0.4 (r1 = 0.380, r2 = 0.381), so these two items were deleted. The correlation coefficient between the b7 item and the total score of the corresponding first-level index (family and relative index) was 0.269, so this item was also deleted. As shown in Table . The commonness of all the items was over 0.20. Except that the factor load of a1, a2, a3, a4, a8 and b7 items was lower than 0.45, the load values of other items on the corresponding factor were > 0.45, as shown in Table . Therefore, a1, a2, a3, a4, a8 and b7 were deleted. Reliability analysis Internal consistency reliability analysis, Split-half reliability: The total Cronbach’s α was 0.945, while each first-level index’s Cronbach’s α ranged from 0.811 to 0.949. The overall split-half reliability was 0.805. Construct validity analysis The KMO value of the whole scale was 0.893 ( P < 0.001). The Bartlett spherical test revealed a substantial level of significance (X2 = 9704.073, P < 0.001). These indicated suitability for EFA. Six factors were limited to be extracted. The cumulative variance contribution rate was 69.02% > 60%, indicating that the structure validity was relatively good. The MSA values in the correlation matrix of reflected images ranged from 0.857 to 0.944, all of which were > 0.50. The load of items f2, f4, f7 and d4 on the two factors is > 0.40, and the difference value is > 0.20, so they were deleted. The items of g6 and g8 were divided into two factors, which of whom should be in the fifth factor, so these two items were deserted, as shown in Table . After a further screening of the items by EFA, the caring perception scale for the home-based elderly with 31 items in 6 dimensions was finally determined, as shown in Table . The goodness of fit of each dimension and item of the questionnaire was tested by CFA. The results showed that the chi-square test of goodness of fit of the scale model was χ2 = 1049.98. Chi-square value/degree of freedom (χ2/ DF) = 2.49 ( P < 0.05), non-standard fit index (TLI) = 0.91, incremental fit index (IFI) = 0.92, Comparison fitting index (CFI) = 0.92, root mean square error (RMSEA) = 0.07. The model fitting degree standard  was χ 2 degree of freedom ratio < 3.00, TLI, IFI, CFI > 0.90, RMSEA < 0.08. The load values of each item on the corresponding factors ranged from 0.54 to 0.97. According to the model fit standard, the questionnaire fitting index in this study met the requirements of fit. The model fitted well and had good structural validity. 

A total of 550 elderly living at home answered the questionnaire, and 498 questionnaires were included in the study, with a 91% recovery rate. Table shows the main characteristics of this sample. The sample size of 498 included total samples for EFA and CFA. 

The CR values of 43 items were all significant, ranging from 3.761 to 13.940( P <0.05), according to the calculation. This version of the questionnaire exhibited discrimination between the high and low-scoring groups on all of the items. In homogeneity, the correlation coefficient between a1 item, a3 item and the total score of the corresponding first-level index (self-caring index) was less than 0.4 (r1 = 0.380, r2 = 0.381), so these two items were deleted. The correlation coefficient between the b7 item and the total score of the corresponding first-level index (family and relative index) was 0.269, so this item was also deleted. As shown in Table . The commonness of all the items was over 0.20. Except that the factor load of a1, a2, a3, a4, a8 and b7 items was lower than 0.45, the load values of other items on the corresponding factor were > 0.45, as shown in Table . Therefore, a1, a2, a3, a4, a8 and b7 were deleted. 

Internal consistency reliability analysis, Split-half reliability: The total Cronbach’s α was 0.945, while each first-level index’s Cronbach’s α ranged from 0.811 to 0.949. The overall split-half reliability was 0.805. 

The KMO value of the whole scale was 0.893 ( P < 0.001). The Bartlett spherical test revealed a substantial level of significance (X2 = 9704.073, P < 0.001). These indicated suitability for EFA. Six factors were limited to be extracted. The cumulative variance contribution rate was 69.02% > 60%, indicating that the structure validity was relatively good. The MSA values in the correlation matrix of reflected images ranged from 0.857 to 0.944, all of which were > 0.50. The load of items f2, f4, f7 and d4 on the two factors is > 0.40, and the difference value is > 0.20, so they were deleted. The items of g6 and g8 were divided into two factors, which of whom should be in the fifth factor, so these two items were deserted, as shown in Table . After a further screening of the items by EFA, the caring perception scale for the home-based elderly with 31 items in 6 dimensions was finally determined, as shown in Table . The goodness of fit of each dimension and item of the questionnaire was tested by CFA. The results showed that the chi-square test of goodness of fit of the scale model was χ2 = 1049.98. Chi-square value/degree of freedom (χ2/ DF) = 2.49 ( P < 0.05), non-standard fit index (TLI) = 0.91, incremental fit index (IFI) = 0.92, Comparison fitting index (CFI) = 0.92, root mean square error (RMSEA) = 0.07. The model fitting degree standard  was χ 2 degree of freedom ratio < 3.00, TLI, IFI, CFI > 0.90, RMSEA < 0.08. The load values of each item on the corresponding factors ranged from 0.54 to 0.97. According to the model fit standard, the questionnaire fitting index in this study met the requirements of fit. The model fitted well and had good structural validity. 

The purpose of this study was to develop a questionnaire to measure the caring perception level of the home-dwelling elderly, from themselves, their family relatives and social surroundings. Multiple methods were used in the investigation to provide adequate rationality and accuracy about the credibility, and breadth of applicability of the content involved, the homogeneity and reasonable structure of the scale, covering wide literature reading, in-depth interviews, the Delphi method, and statistical analysis. The 15 experts from diverse fields across China ensured the questionnaire’s authority and standardization. The questionnaire underwent multiple revisions for clarity and ease of use, and its length was suitable for clinical application. Four methods were used for item selection, achieving a Cronbach’s α coefficient > 0.9, indicating reliability and consistency. Content validity indices were 0.78-1 at the item level and 0.89 at the scale level. Overall, the questionnaire was rigorously developed, which could be effective for evaluating elderly care perceptions. The analysis of the results produced three first-level indexes: self-caring, family and relative caring, and social caring. Family and relative caring, with twelve items, highlights both cohabiting and non-cohabiting family members’ roles, emphasizing respect and daily care. Social caring is divided into three factors: government assistance (material, non-material, and facilities), personal social relationships (friends and neighbors), and non-social relationships (healthcare organizations and volunteers), all contributing to elder support and well-being. Each secondary factor derived from the internal logic of the project content corresponded well with the results of the EFA and effectively reflected the elderly caring perception. This indicates that the initial compilation of the second-level indexes was reasonable. A more detailed analysis of these second-level indexes will be provided in future discussions when using this tool. One aspect that lowers older people’s quality of life is health issues. Although older people may experience health issues that require greater care, their tendency to seek assistance is so low that they frequently lack access to existing medical services . Additionally, geriatric mental health requires self-preservation. The creation of personal interests, which many older people rarely seek, can be considered as one component of the performance of life enjoyment in the situation of gradual decrease in physical function. A hobby can increase life expectancy in the elderly and aid with negative feelings . The items in this questionnaire provide a comprehensive assessment of health care and spiritual care for the elderly. The family has traditionally been a key domestic caregiver for the elderly, with recent recognition of the benefits of inter-generational care . Three second-level factors made up the social area. Government subsidies and material assistance ensure a basic standard of living for elders, reduce stress, and improve comfort and pleasure through supportive policies . Previous studies have found that the health needs of the elderly are diverse, manifesting in areas such as daily living, psychological comfort, social interaction, and medical services . The caring perception questionnaire can help understand the caring needs of the elderly living at home, identify differences in care perceptions among different individuals, and develop more targeted healthy aging policies, thus providing personalized intervention measures aligned with the goals of the United Nations healthy aging initiatives. These initiatives emphasize the importance of addressing the multifaceted needs of older adults to promote their well-being, independence, and social participation. By aligning with the UN’s vision, the development of this questionnaire not only provides a tool for understanding the needs of the elderly population but also offers theoretical support and practical guidance for achieving healthy aging goals, particularly in the context of home-based care. This scale will make it easier to comprehend how humanistic care is currently perceived, increase public awareness of humanistic care for older adults living at home, and advance the growth of the senior care industry. Designed with as few items as possible to represent comprehensive connotations, the humanistic care perception scale focuses on the caring sources and behaviors that significantly impact the elderly. It can help promote humanistic care services that align with the UN healthy aging initiatives, which advocate for inclusive, equitable, and person-centered care systems. By addressing the unique needs of home-dwelling elderly individuals, this scale contributes to fostering a supportive environment that enhances their quality of life, social engagement, and overall health, thereby supporting the broader objectives of healthy aging as outlined by the UN. This study also has certain limitations. Firstly, we did not use test-retest methods to assess the stability of the questionnaire. Although the questionnaire validation process was relatively comprehensive, its reliability and validity over time need to be tested in further research. Secondly, the use of convenience sampling may lead to a bias in the research results, as the non-random sample size could cause result distortion. Additionally, the study locations were primarily in Wuhan and several other second- and third-tier cities, which may limit the generalizability of the developed questionnaire to the elderly population. Finally, Two methods of online questionnaire and paper questionnaire were used for data collection. The deviation of questionnaire results caused by the two data collection methods may lead to the inaccuracy of research results. To further promote the application of this tool, future research should be conducted in a broader range of regions within China and in other countries. 

This study developed a caring perception questionnaire of the home-dwelling elderly through a literature review, qualitative research, and the Delphi method, and tested its reliability and validity through a formal survey. The results indicated that the scale has good reliability and validity. The developed questionnaire includes 3 dimensions and 31 items, and can serve as a tool for assessing the caring perception among home-dwelling elderly individuals, providing a basis for research on humanistic care for this population. 

