Development of a matching framework for voluntary services provided to home-dwelling older adults by nursing faculty and students based on the Kano model

Abstract

Background

As population aging accelerates, volunteer services provide meaningful community support for older adults. However, evidence is limited on how to align their needs with the service intentions of nursing faculty and students to develop appropriate frameworks.

Methods

Data were collected through self-designed demand-supply matching questionnaires from nursing faculty and students (March 26 - April 25, 2023) and older adults (May 24 - July 7, 2023) using convenience sampling.

Results

This study, based on the principle of demand-supply matching, identified volunteer service items that home-dwelling older adults expect to receive and that nursing faculty and students are not opposed to providing. These services span environmental support, physiological care, psychosocial support, and health-related behaviors. Through prioritization, a three-tiered demand-supply matching framework was established, consisting of basic services, expected services, and optional services.

Conclusions

This study applies the Kano model to explore the expectations of urban home-dwelling older adults and the service intentions of nursing faculty and students, identifying key commonalities and differences. Reverse attributes highlight the importance of respecting privacy, autonomy, and trust in volunteer services. The demand-supply matching questionnaire and service framework developed in this study can assist nursing faculty and students willing to volunteer by providing detailed evaluations and strategic guidance for selecting appropriate services and implementation order. This contributes to cultivating a professional, responsive nursing volunteer workforce and advancing China’s Healthy China strategic goals.

Clinical trial number

Not applicable.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12912-025-03456-4.

Background

Despite their unique advantages in addressing the challenges of population aging, community-based volunteer services for older adults have only recently gained attention and momentum [1, 2]. However, both domestic and international research remains limited. Existing studies have yet to thoroughly examine service models that can meet the needs of both service users and providers [3–5]. Previous research has predominantly examined the applicability and feasibility of volunteer services from a unidimensional supply-demand perspective, with limited consideration of the potential issues of inefficiency and misalignment arising from mismatched supply and demand [6, 7]. These issues severely constrain the further development of community volunteer services for older adults and may even lead to the wastage of public resources, highlighting the urgent need for in-depth research.

Older adults often have complex needs beyond basic care, including psychosocial and health-related concerns, which require support from trained volunteers [8–10]. Nursing professionals, with their health expertise and communication skills, are well-positioned to deliver such services [11, 12]. Studying the volunteer engagement of nursing faculty and students can help guide both professional and non-professional volunteers. Given the ongoing nursing shortage in China [13], this study focuses on nursing students and faculty to expand service reach and provide practical guidance for more effective participation.

Furthermore, while rural older adults face challenges such as geographic isolation and a lack of medical resources [14], urban older adults also experience multiple pressures and difficulties due to rapid urbanization and the evolving urban environment. For instance, most urban communities are composed of high-rise buildings rather than single-story houses, which increases the likelihood of social isolation and limits access to external support for older adults [15, 16]. According to statistics, the urban population aged 60 and above in China has reached 143 million, accounting for 54.0% of the total older population in the country [17]. Therefore, the situation and caregiving issues of urban older adults also warrant attention. Additionally, the majority of public eldercare services are concentrated in densely populated urban areas, making it more difficult to extend such resources to rural regions. This trend underscores the advantage of expanding volunteer services in urban areas, which facilitates the growth of volunteer teams and enhances the feasibility of services [18].

The Kano model, developed by Professor Noriaki Kano of the Tokyo Institute of Technology, is widely used to evaluate how different types of services influence user satisfaction [19]. It categorizes user needs into five types: basic needs, expected needs, excitement needs, indifferent needs, and reverse needs. Basic needs refer to services that users assume must be fulfilled; their absence causes strong dissatisfaction, though their presence does not significantly increase satisfaction. Expected needs are services that users clearly desire, and meeting them enhances satisfaction. Excitement needs refer to services that users do not anticipate but that create a positive experience, greatly increasing satisfaction. Indifferent needs have little impact on user satisfaction whether they are provided or not. Reverse needs refer to services that may lead to dissatisfaction if offered. Building on the Kano model, Professor Kano proposed a method for refining demand analysis through structured questionnaires, which can classify the attributes of each service item as a basis for demand categorization and screening. To further optimize customer satisfaction, Berger and others extended the Kano model by introducing a quantitative indicator, the Satisfaction Coefficient (Better-Worse coefficient), which expands the model from qualitative analysis to quantitative analysis [20]. In this study, the Kano model is primarily used to clarify the classification of service attributes expected by both the supply and demand sides, identify priorities and matching points, and provide a theoretical basis for developing a demand-supply matching framework suitable for nursing faculty and students.

In conclusion, research on volunteer services for older adults remains underdeveloped, and no clear framework exists to guide service content or structure. Volunteers still lack evidence-based answers to key questions such as “What services should be provided?” and “How should they be delivered?” This gap limits access for older adults in need and hinders quality-of-life improvements. Therefore, this study will prioritize urban home-dwelling older adults as the demand side and nursing students and faculty as the supply side for a supply-demand matching study, aiming to clarify the appropriate volunteer service projects and their implementation sequence for nursing professionals, providing practical guidance for the effective implementation of community-based volunteer services for older adults.

Methods

Design

The cross-sectional design was adopted to investigate the demand for volunteer services among home-dwelling older adults, as well as the intentions of nursing faculty and students to provide such services. Based on the findings, a supply-demand matching framework was developed using the Kano model.

Participants and setting

The study involved two distinct groups of research subjects: nursing faculty and students, and older adults. For the older adult participants, data were collected between May 24 and July 7, 2023, using a similar convenience sampling method. Eligible older adults were selected from four communities, one in each of the aforementioned cities. The inclusion criteria for older adults were: (1) aged 60 years or older; (2) currently residing in urban communities for over a year; (3) reporting a need for volunteer services; and (4) informed about the purpose and significance of the study and voluntarily agreeing to participate. The exclusion criterion was: the presence of communication barriers.

For the nursing faculty and students, data were collected between March 26 and April 25, 2023, using a convenience sampling method. Participants were selected from eight institutions, consisting of four undergraduate and four vocational colleges, located in four cities in central China: Wuhan, Ezhou, Zhengzhou, and Xinxiang. The inclusion criteria for nursing faculty and students were: (1) formal education and training in nursing; (2) currently engaged in relevant work or studies at the institution; (3) reporting a willingness to provide volunteer services for older adults; and (4) informed about the purpose and significance of the study and voluntarily agreeing to participate.

Samples

According to the sample size determination principles proposed by Hulland et al. in their study on the Kano model, the sample size should be at least 200 cases, which is 5 to 10 times the number of items in the main questionnaire [21]. The demand-supply matching survey used in this study contains 40 items. Considering that each item requires both positive and negative responses, along with a 10% invalid response rate, the required sample size for older adults is at least 444 cases (i.e., ).

For nursing faculty and students, the sample size calculation also needs to account for the proportion of those willing to participate in volunteer services. Based on pre-experiment results, it is expected that 76.7% of the nursing faculty and students will be willing to volunteer, with 100% of nursing faculty (4/4) and 73.1% of nursing students (19/26) expressing such willingness. After accounting for a 10% invalid response rate, the required sample size for nursing faculty and students should range from 608 to 1216 cases (i.e., ).

Instruments

A self-designed questionnaire was used to survey both older adults and nursing faculty and students. The questionnaire was divided into three sections: (1) Characteristics of older adults, including gender, age, education level, marital status, previous occupation, whether they live alone, number of children, monthly income, and health status; (2) Characteristics of nursing faculty and students, including gender, age, marital status, education level, occupation, type of institution, position, title, years of work experience, current grade level, and whether they are an only child; (3) Demand-supply matching questionnaire: Based on the qualitative research results extracted from both the supply and demand sides, and through reviewing relevant domestic and international books and literature, the research team conducted group discussions to comprehensively include volunteer service projects that meet the expectations of either party on the supply or demand side. Guided by the Omaha System’s problem classification scheme, the structure and content of the questionnaire were initially determined. Due to the unique design of the Kano model questionnaire, it is not suitable for traditional quantitative evaluation. Therefore, the development of this questionnaire solely employed the Delphi expert consultation method for qualitative evaluation. The resulting draft of the supply-demand matching questionnaire includes four dimensions: Environment (7 items), Physiological (6 items), Psychological-Social (12 items), and Health-Related Behaviors (15 items), totaling 40 items. Based on this, the wording of the items was adjusted to ensure the questionnaire’s applicability to both older adults and volunteers, ultimately resulting in two finalized versions of the questionnaire: one for older adults and one for volunteers. In this study, the Cronbach’s α coefficients for the surveys of older adults and volunteers were 0.922 and 0.954, respectively.

Data collection

The research team consists of the researchers and several other members (all graduate students majoring in nursing). All researchers underwent uniform training. For the data collection from older adults, before the survey began, the researchers contacted and obtained consent from the leaders of the communities where the survey was conducted or their supervising departments to ensure the smooth execution of the survey. Prior to the formal survey, the researchers conducted a pre-survey with 30 community older adults. Afterward, the researchers obtained the contact information and residential details of the older residents from the community management departments. Once the participants were confirmed to meet the inclusion and exclusion criteria, community staff accompanied the researchers to the participants’ homes. During the survey, the researchers neutrally and impartially read each item of the questionnaire. They supervised the questionnaire completion process and provided necessary explanations to ensure the quality of the responses. After the survey, the researchers promptly evaluated whether the questionnaires had been completed correctly.

For the data collection from nursing faculty and students, Before the survey began, the researchers contacted and obtained consent from the leaders of the hospitals and schools where the survey was conducted to ensure its smooth implementation. The electronic version of the questionnaire was created using Wenjuanxing (https://www.wjx.cn/). Subsequently, the researchers conducted a pre-survey with 30 nurses and 30 nursing faculty and students in phases. In the formal survey phase, the researchers sent the questionnaire QR code and informed consent form to the leaders of the schools or nursing colleges, who then forwarded them to the WeChat work groups of the nursing colleges. The teachers then distributed the questionnaires in the WeChat class groups. Both online and offline surveys followed the principles of anonymity and confidentiality. All participants in the study were required to sign an informed consent form.

Statistical analysis

Statistical analysis was conducted using SPSS 26.0 software. For continuous data, normally distributed data were represented by mean and standard deviation (SD), while skewed data were expressed as median [M (P25, P75)]. Categorical data were presented as percentages (%) and frequencies (n). In the Kano model analysis, demand attributes were statistically described using percentages (%) and frequencies (n). After categorizing the attributes of each item, the Better-Worse formula was used to calculate the weight of satisfaction and dissatisfaction for each service. The Better coefficient reflects the satisfaction index (SI), which corresponds to the “expectation” of a specific service and is related to the “desire” aspect. The Worse coefficient reflects the dissatisfaction index (DSI), which corresponds to the “dependency” on a specific service and is related to the “need” aspect [22] Both the Better and Worse coefficients range from 0 to 1. A two-dimensional matrix chart was then created based on the Better-Worse coefficients to further determine the priority ranking of the service items. The specific calculation formulas are as follows: SI = ; DSI = . To refine the ranking of the same attribute category, this study also introduced the average satisfaction coefficient (ASC), which is the average of SI and |DSI [23] The ASC indicator balances current user satisfaction with the potential impact of service improvement.

Results

For nursing faculty and students, a total of 931 questionnaires were distributed, and after excluding invalid responses, 804 valid questionnaires were included, resulting in a valid response rate of 86.4%. For older adults, a total of 456 questionnaires were distributed, with 421 returned, yielding a response rate of 92.3%. After excluding invalid responses, 409 valid questionnaires were included, resulting in a valid response rate of 89.7%.

General information of supply and demand parties

Among the 409 older adults included in the study, the age range was 60–94 years, with a median age of 68 (65, 74) years. Other details are shown in Appendix I.

Among the 822 nursing faculty and students included in the study, the age range was 15–78 years, with a median age of 20 (19, 21) years. The years of work experience ranged from 0 to 38 years, with a median of 10 (5, 15) years. Other details are shown in Appendix II.

Analysis of the supply and demand matching of volunteer service projects

The classification results of volunteer service project attributes based on the perceptions of 409 older adults with volunteer service needs showed that 13 items (32.5%) were expected attributes, 12 items (30.0%) were attractive attributes, 10 items (25.0%) were neutral attributes, and 5 items (12.5%) were reverse attributes. There were no essential attributes, as shown in Table 1.

Table 1.

Classification results of volunteer service project attributes based on older adults’ perceptions (n = 409)

Category	Service project	Frequency						Kano attribute
		A	O	M	I	R	Q
Environment	a1	133	55	22	127	62	10	A
	a2	154	64	18	132	32	9	A
	a3	150	72	27	119	33	8	A
	a4	128	48	15	126	76	16	A
	a5	132	67	25	125	54	6	A
	a6	176	116	27	65	14	11	A
	a7	76	32	21	73	195	12	R
Physiology	b1	132	61	12	147	49	8	I
	b2	119	65	17	138	64	6	I
	b3	67	22	31	137	144	8	R
	b4	170	80	17	116	18	8	A
	b5	120	51	25	157	48	8	I
	b6	124	52	19	142	55	17	I
Psychology - Society	c1	144	62	22	127	44	10	A
	c2	119	94	20	144	25	7	I
	c3	147	113	30	102	8	9	A
	c4	134	128	30	105	6	6	A
	c5	82	51	22	93	152	9	R
	c6	73	40	31	154	104	7	I
	c7	79	37	33	167	90	3	I
	c8	83	38	25	170	83	10	I
	c9	106	30	19	198	48	8	I
	c10	139	70	16	119	58	7	A
	c11	127	31	22	166	50	13	I
	c12	94	45	9	106	136	19	R
Health Related Behavior	d1	113	174	23	68	17	14	O
	d2	110	183	31	52	13	20	O
	d3	119	185	29	55	7	14	O
	d4	118	181	21	64	8	17	O
	d5	120	177	20	54	21	17	O
	d6	105	132	30	85	42	15	O
	d7	104	136	24	106	26	13	O
	d8	107	192	24	61	13	12	O
	d9	95	66	34	93	102	19	R
	d10	127	170	27	55	16	14	O
	d11	140	133	26	76	21	13	A
	d12	125	172	25	63	15	9	O
	d13	132	166	18	67	16	10	O
	d14	95	119	33	97	54	11	O
	d15	121	147	26	79	29	7	O

The classification results of volunteer service project attributes based on the perceptions of 822 nursing faculty and students with the willingness to engage in volunteer service showed that 25 items (62.5%) were expected attributes, 5 items (12.5%) were attractive attributes, and 10 items (25.0%) were neutral attributes. There were no essential attributes or reverse attributes, as shown in Table 2.

Table 2.

Classification results of volunteer service project attributes based on nursing students’ and faculty’ perceptions (n = 822)

Category	Service project	Frequency						Kano attribute
		A	O	M	I	R	Q
Environment	a1	149	215	110	317	27	4	I
	a2	117	195	125	347	33	5	I
	a3	144	296	119	242	18	3	O
	a4	144	252	117	287	19	3	I
	a5	131	336	127	216	10	2	O
	a6	126	324	112	248	8	4	O
	a7	148	289	101	268	12	4	O
Physiology	b1	171	210	98	317	21	5	I
	b2	158	189	95	337	37	6	I
	b3	78	115	101	421	95	12	I
	b4	120	274	120	288	17	3	I
	b5	142	305	75	286	12	2	O
	b6	115	303	107	277	16	4	O
Psychology - Society	c1	269	250	104	193	4	2	A
	c2	267	260	122	166	5	2	A
	c3	234	332	108	144	3	1	O
	c4	235	392	85	100	4	6	O
	c5	181	153	134	316	29	9	I
	c6	222	252	116	215	15	2	O
	c7	268	210	95	218	22	9	A
	c8	212	209	122	264	11	4	I
	c9	224	220	103	259	10	6	I
	c10	290	287	70	166	8	1	A
	c11	206	261	105	234	12	4	O
	c12	268	244	69	212	18	11	A
Health Related Behavior	d1	168	391	108	146	5	4	O
	d2	146	409	108	152	6	1	O
	d3	168	428	90	130	5	1	O
	d4	157	400	101	158	5	1	O
	d5	144	412	108	154	3	1	O
	d6	170	342	95	207	7	1	O
	d7	174	338	102	202	4	2	O
	d8	150	336	138	183	13	2	O
	d9	180	304	95	232	8	3	O
	d10	153	308	126	216	15	4	O
	d11	167	340	104	199	9	3	O
	d12	140	333	109	229	10	1	O
	d13	141	267	142	249	19	4	O
	d14	149	322	113	226	9	3	O
	d15	137	337	125	211	9	3	O

Development of the optimized project list

Based on the demand-supply matching analysis of classified perceptions of volunteer service attributes, and in order to enhance the service experience for older adults receiving assistance, this study excluded 10 indifferent attributes and 5 reverse attributes identified by older adults. Additionally, to ensure the acceptability of services among nursing faculty and student volunteers while still addressing the practical needs of older adults, reverse attributes identified by volunteers were excluded, but indifferent attributes were retained. After revision and screening, a total of 25 optimized volunteer service projects were finalized, covering four domains: six related to environmental support, one to physiological care, four to psychosocial support, and fourteen to health-related behaviors.

Calculation of the better-worse coefficient and two-dimensional matrix analysis

A quantitative analysis of the service project attributes was conducted using the Better-Worse calculation of the Kano model. The calculation results are shown in Table 3. Based on the Better-Worse coefficient results, the absolute value of Worse was used as the x-axis, and the Better value was used as the y-axis. The average values of |DSI| and SI were used as the origin of the coordinates. Two-dimensional matrix diagrams of volunteer service project attributes were drawn based on the perceptions of different groups. From Fig. 1, it can be seen that for nursing faculty and students, among all the service projects, 8 items fall in the first quadrant, 4 in the second quadrant, 7 in the third quadrant, and 6 in the fourth quadrant. From Fig. 2, it can be seen that for older adults, among all the service projects, 11 items fall in the first quadrant, 1 in the second quadrant, 10 in the third quadrant, and 3 in the fourth quadrant. The classification results of volunteer service project attributes based on the perceptions of different groups are shown in Table 4.

Table 3.

Better-worse coefficient calculation results

Category	Service project	SI	DSI	ASC	SI	DSI	ASC
		Nursing faculty and students			Older adults
Environment	a1	0.460	-0.411	0.436	0.558	-0.228	0.393
	a2	0.398	-0.408	0.403	0.592	-0.223	0.408
	a3	0.549	-0.518	0.534	0.603	-0.269	0.436
	a4	0.495	-0.461	0.478	0.555	-0.199	0.377
	a5	0.577	-0.572	0.575	0.570	-0.264	0.417
	a6	0.556	-0.538	0.547	0.760	-0.372	0.566
Physiology	b4	0.491	-0.491	0.491	0.653	-0.253	0.453
Psychology - Society	c1	0.636	-0.434	0.535	0.580	-0.237	0.409
	c3	0.692	-0.538	0.615	0.663	-0.365	0.514
	c4	0.772	-0.587	0.680	0.660	-0.398	0.529
	c10	0.710	-0.439	0.575	0.608	-0.250	0.429
Health Related Behavior	d1	0.688	-0.614	0.651	0.759	-0.521	0.640
	d2	0.681	-0.634	0.658	0.779	-0.569	0.674
	d3	0.730	-0.635	0.683	0.784	-0.552	0.668
	d4	0.683	-0.614	0.649	0.779	-0.526	0.653
	d5	0.680	-0.636	0.658	0.801	-0.531	0.666
	d6	0.629	-0.537	0.583	0.673	-0.460	0.567
	d7	0.627	-0.539	0.583	0.649	-0.432	0.541
	d8	0.602	-0.587	0.595	0.779	-0.563	0.671
	d10	0.574	-0.540	0.557	0.784	-0.520	0.652
	d11	0.626	-0.548	0.587	0.728	-0.424	0.576
	d12	0.583	-0.545	0.564	0.771	-0.512	0.642
	d13	0.511	-0.512	0.512	0.778	-0.480	0.629
	d14	0.581	-0.537	0.559	0.622	-0.442	0.532
	d15	0.585	-0.570	0.578	0.718	-0.464	0.591

Fig. 1.

Preferred volunteer service project list

Fig. 2.

Two-dimensional matrix of volunteer service project attributes based on perceptions of nursing faculty and students

Table 4.

Classification results of volunteer service project attributes based on the perceptions of different groups

Category	Service project	Kano attribute classification
		Nursing faculty and students	Older adults
Environment	a1	I	I
	a2	I	I
	a3	I	I
	a4	I	I
	a5	M	I
	a6	M	A
Physiology	b4	I	I
Psychology - Society	c1	A	I
	c3	A	I
	c4	O	I
	c10	A	I
Health Related Behavior	d1	O	O
	d2	O	O
	d3	O	O
	d4	O	O
	d5	O	O
	d6	A	M
	d7	O	M
	d8	M	O
	d10	M	O
	d11	O	O
	d12	M	O
	d13	I	O
	d14	I	M
	d15	M	O

Framework for matching the volunteer service needs of home-dwelling older adults with the supply of nursing personnel volunteer services

In this study, the process of developing the supply and demand matching framework follows the core principles of the Kano model. According to priority order, essential attributes (M), expected attributes (O), and attractive attributes (A) should be satisfied in sequence, while neutral attributes (I) are ignored and reverse attributes (R) are excluded. However, considering that the neutral attributes identified by nursing faculty and students might be services expected by older adults, these attributes were intentionally retained. Additionally, due to the limitations of the traditional Kano model in determining the priority of services within the same category, this study also incorporated the ASC (Attribute Satisfaction Coefficient) index to rank the importance of different classifications. Based on the preliminary classification and screening of volunteer service projects in the previous section, and the Better-Worse coefficient calculation results, the study further summarized and identified supply and demand matching points that maximize the interests of both sides, which led to the creation of the service framework.

Each service framework consists of three service levels: basic service layer, expected service layer, and optional service layer. In the basic and expected service layers, project ranking prioritizes the attribute classification based on the perceptions of older adults, and is then refined according to the ASC index. For the optional service layer, project ranking prioritizes the attribute classification based on the perceptions of nursing faculty and students, and is then refined according to the ASC index. Based on the above analysis, the final supply and demand matching framework includes 3 basic services, 12 expected services, and 5 optional services. These are shown in Figs. 3 and 4.

Fig. 3.

Two-dimensional matrix of volunteer service project attributes based on perceptions of older adults

Fig. 4.

Supply-demand matching framework for volunteer services provided by nursing faculty and students to home-dwelling older adults

Discussion

Commonalities and differences in perceptions between supply and demand sides

This study, using demand-supply matching analysis based on the Kano model, identifies both commonalities and differences in how urban home-dwelling older adults and nursing faculty and students perceive the attributes of volunteer service programs. Firstly, neither group identified any service attributes as must-have features, likely because volunteer services are not typically viewed as essential compared to paid services [24, 25]. Additionally, volunteers tend to focus on complementary tasks rather than core tasks [26].

In terms of differences, only older adults group identified five reverse attributes: providing admission consultation for nursing homes, assisting with bathing, wiping, laundry delivery, helping to improve family relationships or mediate conflicts, celebrating important holidays or birthdays, and guiding the use of online medical services. These services were generally unpopular among older adults, possibly because they involve personal or bodily privacy and lack trust-building [27–29]. This indicates that older adults prioritize privacy protection, personal independence, and avoidance of sensitive services. However, other studies have shown that social workers can effectively help older adults reintegrate into various networks and access material, social, and healthcare resources through sensitive interpersonal interactions, advocacy, and educational support [30]. Additionally, research indicates that home-dwelling older individuals have unmet needs for telemedicine [10, 31]. Therefore, volunteers should avoid these sensitive areas to prevent resistance from older adults, thereby improving their service experience, while still providing related services when appropriate and permitted.

Even after excluding the reverse attributes, some services considered indifferent by nursing personnel may still reflect the expectations of older adults. Considering the voluntary nature of volunteer services [32] and the positive impacts of work calling on both personal and organizational levels in recent years [33], these attribute projects can be incorporated as supplementary options within volunteer services. This study ultimately developed a preferred project list comprising 25 items. It was found that both supply and demand favor volunteer service projects focused on health-related behaviors and environmental improvements, whereas services related to physiological and psychosocial aspects received lower approval, with most projects not accepted by either group. This result aligns with a large-scale, multi-center study in the United States, which confirmed that home-dwelling older individuals have the greatest need for telemedicine and healthcare [31]. Similarly, a retrospective study found that home-dwelling older adults have unmet needs in healthcare, food safety, and remote services [10]. A study in Ghana also highlighted unmet needs for older adults in social interactions, environment, healthcare, and dietary health [9]. However, there is limited research on the physiological needs of older adults, suggesting a general lack of recognition for basic living services by both supply and demand sides. Consequently, the provision of such services should be minimized in actual service delivery.

In terms of psychosocial aspects, although older adults generally hold a neutral attitude toward most projects, nursing faculty and students universally consider these services highly necessary, reflecting older adults’ insufficient attention to mental health issues. However, from a professional standpoint, as long as these services are not perceived as aversive by older adults, they should still be fully considered and actively implemented. Regarding health-related behaviors, both groups show a high level of interest and willingness to accept these services, making them the primary area for nursing students’ volunteer activities. This study used Better and Worse coefficients from different groups to create two two-dimensional matrices, helping to identify an effective service framework and establish clear priorities. According to the Kano model’s design principles, basic needs should be fully satisfied first, followed by performance needs, and finally efforts should be made to fulfill the excitement needs of service recipients [34]. Incorporating the ASC coefficients, this study further identified demand-supply matching points that maximize mutual benefits, forming a demand-supply matching framework. It is important to emphasize that the Better coefficient reflects the extent to which the presence of a service increases satisfaction, while the Worse coefficient indicates the extent to which its absence causes dissatisfaction. Therefore, services with both high Better and Worse values are generally not only well-received but also essential, and should be prioritized in volunteer service planning. For example, services such as Traditional Chinese Medicine (TCM) health consultations and medication management assistance showed high Better and Worse coefficients in this study, indicating that these services are highly expected by older adults and their absence may lead to dissatisfaction. These findings provide empirical evidence for a more rational allocation of volunteer service resources.

Interpretation and implications of the demand-supply matching framework

The foundational service layer of this framework includes three essential services as identified by older adults: guiding TCM health maintenance, improving sleep issues, and providing health consultations via WeChat or telephone. Although TCM health maintenance is not a professional strength for most nursing faculty and students and poses challenges such as knowledge gaps and operational difficulties, it remains a fundamental and indispensable service for older adults [35]. TCM emphasizes holistic regulation, prevention-oriented, and personalized approaches, which highly align with the growing health needs of older adults. Through methods such as differential diagnosis and treatment, herbal adjustments, acupuncture, and massage, TCM can alleviate common chronic conditions, insomnia, joint pain, and other symptoms in older adults, thereby improving their quality of life. Moreover, TCM’s concepts of “harmony between heaven and humans” and “yin-yang balance” help older adults achieve physical and mental harmony, promoting psychological comfort and tranquility, which positively impacts overall health [36]. Therefore, volunteers should continue to prioritize providing this service and enhance their knowledge and skills in TCM through ongoing training. Secondly, addressing prevalent sleep problems among older adults should be a priority [37]. Finally, given that older adults often encounter daily life difficulties, it is essential to encourage volunteers to maintain long-term contact and provide continuous online support and guidance. This helps enhance older adults’ sense of security and trust in volunteer services. Previous research shows that regular telephone follow-ups help students maintain sustained contact with older adults, assess their outcomes, and collect feedback effectively. This not only helps engage some older adults, who may feel grateful and voluntarily join the volunteer team, but also expands the potential and coverage of the community support network [38].

In the expected service layer, aside from the environmental aspect of “providing timely responses and support,” the remaining projects focus on health-related behaviors. This indicates that promoting health-related behaviors remains a key strategy for nursing faculty and students to improve service quality, such as guiding medical visits and assisting with medication management. However, the environmental factor of “providing timely responses and support” is equally important, as it encompasses not only health-related aspects but also various potential needs of older adults. To achieve comprehensive optimization, it is necessary to strengthen health behavior initiatives while also enhancing environmental support, ensuring that older adults receive timely and reliable assistance in health services. This balance will not only improve older adults’ satisfaction and service experience but also promote the sustainable and effective operation of services, ultimately maximizing mutual benefits and achieving truly human-centered service goals. Additionally, the framework provides optional service options, which, although not prioritized by older adults, are widely recognized by nursing faculty and students. Therefore, in actual service delivery, once the basic and expected service needs of older adults have been met, optional services may be considered based on individual preferences and specific contexts. This approach helps ensure a more comprehensive and well-structured service strategy. For instance, when designing a semester-long volunteer service program for students, initial training should focus on foundational service modules within the framework (e.g. sleep guidance, remote health consultations). As the program progresses, optimized and supplementary services can be gradually incorporated based on community feedback and practical feasibility.

Limitation

This study has several limitations. First, nursing faculty and students were analyzed as a single group in this study, given their joint participation in community-based volunteer services for older adults. Although subgroup data for faculty and students were collected separately, detailed comparative analyses were not presented in this manuscript due to space constraints. Detailed subgroup-specific data are available upon request from the authors. Second, the supply and demand participants involved in this study were all from relatively developed cities in central China, with no data collected from rural areas, towns, or less-developed regions, which limits the generalizability of the findings. Third, this study excluded older adults with significant communication impairments to ensure that responses accurately reflected participants’ personal intentions. However, this approach may have led to the omission of high-need groups, such as those with cognitive impairments, thereby limiting the representativeness and generalizability of the findings. Future research should explore alternative approaches, such as proxy responses from family members, structured observations, or assistive technologies, to better capture the assistance needs of these vulnerable populations. Lastly, the demand-supply matching framework developed in this study is only an initial attempt and requires further empirical validation across diverse populations.

Conclusions

This study reveals both commonalities and differences between the expectations of urban home-dwelling older adults regarding volunteer service programs and the service intentions of nursing faculty and students. Notably, the reverse attributes identified by the majority of older adults suggest that certain services should be avoided by volunteers, highlighting the importance of respecting privacy, autonomy, and building trust in volunteer programs. The dual survey tools developed in this study—the demand-supply matching questionnaire and the corresponding demand-supply matching framework—offer valuable support for optimizing volunteer services. The resulting service framework is hierarchical, comprehensive, and focused, providing specific strategic guidance for nursing faculty and students to meet the needs of China’s aging society. By prioritizing services such as Traditional TCM health maintenance, sleep improvement, and continuous health consultations, and emphasizing health-related behaviors and environmental support as key service attributes, nursing education can integrate targeted training to equip faculty and students with the necessary skills and knowledge. This approach not only addresses the immediate home-based health needs of older adults but also aligns with the development trends of modern nursing practices, which focus on personalized and preventive care. In addition, future studies may further explore how cultural and socio-economic factors affect the applicability of this framework, in order to identify potential differences in needs and expectations among older adults in diverse geographic settings, thereby enhancing its practical value and robustness. In summary, this study provides a preliminary framework for effectively aligning the volunteer services of nursing faculty and students with the diverse needs of older adults. It promotes the collaborative development of educational institutions and community services, enhancing the relevance of nursing education. These efforts contribute to the cultivation of a more responsive and professional nursing volunteer workforce and advance the process of addressing population aging and achieving China’s Healthy China strategic goals.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Author contributions

1. Substantial contributions to conception, design: Lei Huang, Weihong Yang, Lina Wang, Yan Lin, Peng Wang, Fengjian Zhang, Lulu Liao. 2. Acquisition, analysis, and interpretation of data: Lei Huang, Pei Wang, Xiang Sun, Yue Yao, Rui Chen, Shuyao Hui. 3. Drafting the manuscript: Lei Huang. 4. Revising it critically for important intellectual content: Lei Huang. 5. Final approval of the version to be submission: Yilan Liu, Chunyan Guan.

Funding

This study was funded by the Henan Provincial Science and Technology Key Research and Development Project (project No. 252102320196).

Data availability

I declare that all data and materials are available from the corresponding author upon reasonable request.

Declarations

Ethics approval and consent to participate

The research protocol has been approved by the Medical Ethics Committee of Tongji Medical College, Huazhong University of Science and Technology (Ethical review No. S053). Before the implementation of the study, the purpose and significance of the research were explained in detail to all participants, and their informed consent was obtained to ensure that participation was voluntary and anonymous, with the option to withdraw at any time. All methods were carried out in accordance with the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.