What Is Successful Aging? From Seniors’ Needs for a Happy and Meaningful Life to Moving into a Senior Living Community

Abstract

This study investigates the decision-making process behind moving into a senior living community. Prospective residents were asked to identify the most important qualities of a happy, healthy, and engaged life, so called successful aging. Our effort resulted in a scale with 27 items reflecting seniors’ needs for successful aging. Building upon the Andersen’s model to predict the medical service utilization, this study developed the Needs of Successful Aging-Enabling-Psychosocial (N-SEP) model. The results showed the needs for successful aging have a positive effect on prospective residents’ attitudes and subjective norms, which in turn affect seniors’ decision to move. In addition, enabling factors were found to increase the perceived control, leading to a decision to move. This study benefits both senior living practitioners and academics who are interested in studying this fast-growing field in the future.

1. Introduction

No matter how old one is or where one lives, there is an ultimate question that everyone asks oneself, “how can I live a happy, healthy, and engaged life?” This ultimate question may become even more serious when entering senior life. The aging population is growing rapidly in the world [1] because the boomers who take up a large portion of the U.S. (and world) population will be retiring or have already retired; the senior living industry is gaining momentum.

As the demand of senior living communities is increasing [2], it is important for senior living practitioners to invest their time and effort to understand the diversity and complexity of their customers, i.e., future residents. While the business model of senior living has existed for decades, the needs of their customers are least likely to remain the same. Given that the boomers have a much stronger purchasing power than other generations such as traditionalists (generation prior to the boomers), senior living practitioners’ mindsets of conducting business must change. Traditionally, the practitioners thought seniors move into senior living for only health purposes [3,4]. However, gerontology literature shows that seniors may have higher-level needs than simple physical (health) needs [5]. These higher needs must be understood for seniors’ successful aging. In particular, because of a large influx of new residents such as the boomers in the near future, it appears to be the perfect time to identify seniors’ higher-level needs that have been often neglected before. This study is undertaken to respond to the calls from hospitality academics and industry practitioners who urge more research on senior living [6].

A few studies have led senior living-related discussions in hospitality literature [2,7,8,9,10]. For example, Chaulagain and her co-authors [2,11] explored the factors affecting seniors’ relocation decisions to senior living communities by adopting the Theory of Migration [11] and reported the attributes that may satisfy senior residents in continuing care retirement communities. These prior empirical studies provide the foundation for the senior living researchers in hospitality and draw attention to the integration of various theories to further enrich the senior living literature. We hope to fill this gap in senior living literature within hospitality. As more and more senior living communities are becoming hotel-like, it is meaningful for more hospitality academics to engage in senior living research.

This study explores the perspectives of individuals approaching their senior years (within the next 5 to 10 years) to understand their vision of an ideal, fulfilling senior life, with the aim of informing senior living practitioners to align community operations with potential residents’ preferences. To achieve this, this study pursues three integrated objectives: (1) drawing on gerontological theories, develop a scale to measure seniors’ needs for successful aging, providing a foundation for empirical assessment; (2) build on Andersen’s Behavioral Model of Health Services Use to create the Needs of Successful Aging-Enabling-Psychosocial (N-SEP) model, which broadens the concept of needs to include healthy seniors’ psychosocial factors; and (3) analyze the N-SEP model using Structural Equation Modeling (SEM) to elucidate the decision-making processes influencing seniors’ choices to relocate to senior living communities. These objectives collectively bridge theoretical development and empirical analysis, offering actionable insights for senior living practitioners and contributing to gerontological research.

2. Theoretical Background and Proposed Model

2.1. Conceptualization of Successful Aging

Researchers have traditionally divided older people between those with disabilities or diseases (“pathologic”) and those free of disability or disease (“nonpathologic” or “healthy aging”). However, this categorization not only fails to acknowledge the heterogeneity within the latter category but also neglects the substantive potential that seniors can achieve through the aging process [12]. To address this shortcoming, Rowe and Kahn [13] made a distinction between healthy and successful aging. They described nonpathologic aging as “usual but high-risk” seniors and successful aging as “low-risk and high-functioning.”

There have been several definitions of successful aging since the 1990s [14,15,16]. One of the most broadly applied definitions originating from Rowe and Kahn’s [5] work identified three major components: (1) low probability of disease and disease-related disability; (2) high cognitive and physical functional capacity; and (3) active engagement with life. Taken together, these interrelated components present a holistic definition of successful aging as absence of disease, maintenance of functional capacities, and vigorous engagement with life (Figure 1). A low probability of disease is both the absence of disease itself and the absence of risk factors for disease. High functional capacities represent that a person is cognitively and physically capable of doing more than he or she actually does. Lastly, active engagement with life underscores two major areas: interpersonal relations (emotional support, direct assistance, and exchange of information) and productive activity (the creation of societal value whether paid or not).

The reason for the popularity of successful aging is that it could be a precursor to several key outcomes, such as quality of and satisfaction with life, both of which ultimately promote health. Health promotion can increase exercise and improve diet among seniors, thus improving their cardiac morbidity and decreasing the risk of falls [18,19,20]. Previous studies revealed biomedical, psychosocial, or lay approaches, or combinations of these approaches to test successful aging (

Table 1. Five models of successful aging.

Biomedical model: Comprised summing of variables, number of diagnosed, chronic medical conditions, activities of daily living (ADL), no psychiatric morbidity

Broader biomedical model: Comprised summing of the above plus number of different social activities engaged in during past month (3+), as an index of social engagement

Social functioning model: Comprised summing of number of different social activities engaged in during past month (as above 3+), frequency of social contacts score, helped/supported in all 5 areas of life asked about

Psychological resources model: Comprised summing of self-efficacy score, best optimism score, plus items on sense of purpose: playing useful part; coping: facing up to problems, overcoming difficulties; self-esteem; feels has self-confidence and has self-worth

Lay model: Comprised summing of the above plus gross annual income (>around $10,422) and perceived social capital [rating of area facilities (e.g., transport, closeness to shops, services), area problems (e.g., crime, vandalism, graffiti, speed and volume of traffic, air quality), somewhere nice to go for a walk, feels safe walking alone during the day or night]

Source: [18,21,23].

). To evaluate how accurately these models of successful aging predict perceived quality of life, Bowling and Dieppe (2005) and Bowling and Iliffe (2006) [18,21] assessed these models using data from a British survey. The lay-based model emerged as the strongest predictor. However, differences were found between self-rating successful aging and Rowe and Kahn’s [5] criteria (absence of disease, functional capacities, and engagement with life). Comparison results show that 50.3% of participants aged 65 to 99 years described themselves as aging successfully but only 18.8% of the sample did under Rowe and Kahn’s criteria [22].

Seniors with chronic conditions and functional difficulties can still think of themselves as aging successfully. Reichstadt and colleagues [24] conducted a focus group study to define successful aging in a sample of community-dwelling older adults. They found the four themes of successful aging: (1) a positive attitude, realistic perspective, and the ability to adapt to change; (2) a secure and stable living environment, social support, and financial resources; (3) general physical health and wellness; (4) the continuing pursuit of stimulation and learning, a sense of purpose in life, and usefulness to society and to others. Moreover, they noted that older people consider psychosocial factors more important than genetics, longevity, function, and independence. In sum, lifestyle and a risk-free living arrangement, high functional promotion, and psychosocial essentials encapsulate successful aging [5,24].

Specialized living arrangements for seniors have existed in the United States for over 100 years. Religious and fraternal organizations initially provided care for older Americans who turned over their homes and assets to those organizations. After decades of development, the senior living sector became sophisticated. The senior living industry transitioned from a small niche market into a major specialized market. Some people have perceived senior living facilities as warehouses for those who are dying, without dignity, with limited medical support and care. However, today, “hotel-style” senior living communities promote successful aging and reject that conventional negative image.

2.2. Successful Aging and “Hotel-Style” Senior Living Community

“Homes for the aged,” residential settings for seniors with health problems, date to 1965 when Medicare and Medicaid were enacted. These institutions were the initial model of the modern nursing home [25]. After the term “assisted living” first appeared in a proposal to the State of Oregon in 1985, trade journals and industry practitioners sought alternatives to nursing homes [26]. According to Wilson’s [26] (p. 10) reflective review, this alternative living arrangement should reject the institutional feeling of a nursing facility and provide housing and on-site services. The modern senior living community should offer the following:

(1) A residential-style physical environment, pertaining to (a) a resident’s private space and (b) public community spaces shared by all residents;

(2) A service capacity for (a) delivering routine services—both those amenable to being scheduled and those that could not be scheduled and (b) specialized health-related services;

(3) An operating philosophy emphasizing resident choice and normal lifestyles related to (a) the governance of the resident’s time, space, possessions, and contacts in his or her private space; and (b) decisions about accepting or rejecting medical care and other health-related care and services.

Senior living communities were like hospitals in the past and the future ones will follow the cues of hotels [27]. With greater financial freedom through social security and pensions, seniors realized that moving into a senior living community could free them from the responsibility of household maintenance and offer the security of on-site health care. Through the 1970s and 1980s, a few retirement communities became facilities with grand lobbies and gracious public space, elegant dining, and concierge-type services. The entry of Hyatt and Marriott accelerated this change. Senior living leaders have begun to prepare the industry for retired baby boomers since the 1990s. Because boomers have significantly different expectations and tastes, they preferred the new community settings to the traditional retirement models [28]. Moreover, seniors not only expect a living arrangement that looks like hotels but look forward to the extraordinary experience that hospitality practitioners provide to their guests.

There are three challenges in the move from hotel-style (appearance focused) to hotel-substance (experience- or service-focused) senior living communities [29]. The first of these challenges is that the culture of retirement communities must change. The conventional concept of retirement communities is merely institutional and tends to care for the basic needs. However, hospitality services offer much more. To accommodate this emphasis, a senior living community with hospitality-substance must pamper and delight its residents by engaging them in residential life. The second challenge is that the hotel-like senior living community must adopt holistic services for a variety of residents. For example, residents of senior living communities often enjoy fine dining, travel, and entertainment, thus senior living operators must be able to serve these healthy and independent tenants and offer memorable and enriching experiences. The third challenge is that the management of hotel-like senior living communities must instill the work value that exceptional customer service comes from treating guests with dignity. Those who have a warm heart could do a better job in a workplace like senior living because they will feel fulfillment by making differences in others’ lives.

2.3. The Andersen Classic Health Care Model

Andersen’s (1995) [30] classic model is the most applied framework to understand the use of medical care. The model identifies the factors that affect the use of health services. The Andersen model postulates that the use of medical or health services can be influenced by predisposing characteristics, enabling resources, and needs (Figure 2). The model was initially designed to understand why families use health services and then adopted the individual as the unit of analysis. The original Andersen’s model [31] has been expanded with more predictors, such as the health care system and external environment, to enhance the explanatory power. Also, more specific outcomes, such as health status and consumer satisfaction, have been added to make the ultimate goal of health services more explicit. Andersen’s model emphasizes that the utilization of health services is a dynamic and recursive process.

Predisposing characteristics are the first component of the Andersen model. An individual’s propensity can predict their use of services; an individual’s characteristics affect their behavior throughout life, not only when they encounter specific episodes of illness. People may act toward health care utilization because of demographic, social-structural and attitudinal-belief influences. For example, an individual’s social status could affect their lifestyle, the physical and social environment associated with their behavioral patterns and consequently his or her use of health services.

The second component, enabling factors, are available means from individuals/families as well as communities. Enabling factors can permit individuals to satisfy a need or act on a value regarding health service utilization. These factors can be measured by resources, such as income, insurance, availability and accessibility of a regular source of care. The community can be an enabling factor because the characteristics of a community dictate the number of health professionals or facilities and the cost of health services. These variables could influence the local norms concerning how medical services should be practiced, and the values held by the community.

The third component is need based on the illness level. An individual or family will use health services only if there is a real or perceived illness. Need is directly associated with utilization of health services. Perceived illness can be measured by duration of disability, symptoms, and self-reported general state of health. Apart from the perception of illness, diagnosed illness can affect the use of services based on clinical judgment.

Bradley and her colleagues (2002) [3] expanded Andersen’s model through the focus group discussion with people older than 65. They reported long-term care may involve more routine personal tasks such as, but not limited to bathing, dressing, cooking, and shopping. This is different from the Andersen model that mostly applies to acute care. While the Andersen model identifies predisposing, enabling, and need factors as predictors of the medical (health) service use, it does not address how these three factors interact with each other. In comparison, Bradley et al. (2002) [3] found prosocial factors, defined as attitudes, social norms, and perceived control, play a crucial role in the use of a long-term care service. Also, they noted that the decision to use a long-term care service is chiefly dominated by need for care (illness) and psychosocial factors mediate (do not precede) the relationships between need/enabling factors and intention. Although their conceptual model may not fit in all types of service contexts, it offers a set of variables that are worth consideration and validation in the future. This study’s setting is senior living. To a large extent, long-term care is one of the essential services in senior living communities. Thus, Bradley et al.’s findings are useful for this study.

2.4. Proposed Needs of Successful Aging-Enabling-Psychosocial Model

Few studies have explored the decision-making process for relocating to senior living communities [3,32]. While Bradley et al. (2002) [3] integrated the Andersen model of health services use with the theory of planned behavior to conceptualize long-term care decisions, their framework remains unvalidated in the context of senior living. To address this gap, we developed the Needs of Successful Aging-Enabling-Psychosocial (N-SEP) model by extending the Andersen model, which primarily focuses on illness-driven health service utilization [33]. The Andersen model is limited in capturing proactive, non-medical decisions like relocation to senior living communities, which involves active, preventive choices by healthy seniors, unlike the passive care acceptance emphasized in Bradley et al.’s (2002) [3] long-term care application. The N-SEP model redefines “need” to include psychosocial and preventive motivations, aligning with seniors’ proactive planning for community living. We further examined the relationship between needs and enabling factors and hypothesized that needs and enabling factors influence psychosocial variables (attitudes, subjective norms, and perceived control), which in turn drive the intention to relocate to a senior living community. The proposed N-SEP model is presented in Figure 3.

Need has been extensively incorporated in the studies of health care (medical) services because need motivates an individual to use the service [3,30]. To heath care researchers, need is rather simple, derived by one’s illness. Senior living facilities offer more than a (short-term) medical service or room and board. Senior living facilities include a comprehensive supporting system for residents to stay healthy, active, and engaged in their (remaining) life. This study uses the need of successful aging rather than the need of curing illness. As mentioned before, successful aging signifies absence of disease or disability, active cognitive and physical functions, and engagement in life. Thus, an individual’s perception of what he/she needs for a happy, healthy, and engaged senior life will positively relate to his/her decision to move into a senior living community. As for the relationship between the needs for successful aging and enabling factors (e.g., financial support), the link is likely to be positive because stronger needs will demand more resources. The above logic leads us to the following hypotheses.

Hypothesis 1.

Needs for successful aging will be positively related to the intention to move into a senior living community.

Hypothesis 2.

Needs for successful aging will be positively related to enabling factors.

Psychosocial factors consist of attitudes, social norms, and perceived control that are rooted in the theory of planned behavior [3]. Of three psychosocial factors, needs are expected to be positively associated with attitudes and social norms. As people get older, they realize family members cannot always look after them or they are far away, making seniors lonely or unhappy. To satisfy their need for a happy, healthy, and fulfilling life, senior living communities may emerge as an alternative, thereby developing a positive attitude towards senior living communities in seniors. Also, strongly met needs for successful aging being expressed by seniors may encourage close referents to think of senior living as a favorable, lasting option.

In addition to the direct effect of needs on one’s attitudes and subjective norms (H3 and H4), it is feasible to expect the indirect effects of needs on intentions to move through attitudes and subjective norms. Attitudes and subjective norms are well known as the proximal predictors of intentions [34]. Taking all these paths together (from needs to attitudes/subjective norms and from attitudes/norms to intentions), attitudes/subjective norms are expected to serve as mediators. Accordingly, we put forth the following hypotheses.

Hypothesis 3.

Needs for successful aging will be positively related to attitudes.

Hypothesis 4.

Needs for successful aging will be positively related to subjective norms.

Hypothesis 5.

Attitudes will mediate the relationship between needs for successful aging and the intention to move.

Hypothesis 6.

Subjective norms will mediate the relationship between needs for successful aging and the intention to move.

In line with the Andersen model, enabling factors (e.g., financial support, insurance, etc.) may have a direct influence on the intention to settle into a senior living community. However, the effects have been mixed. If formal and informal services are available, moving into an institutional facility will be low; but if financial resources are abundant, one is more likely to move into a senior living facility. Enabling factors can be associated with a psychosocial factor, perceived control. A good number of enabling factors will increase the feeling of perceived control and perceived control will further influence the intention to move. In other words, perceived control is expected to serve as a mediator between enabling factors and intentions to move. Based on the above rationale, we posit the following hypotheses.

Hypothesis 7.

Enabling factors will be significantly related to the intention to move into a senior living community.

Hypothesis 8.

Enabling factors will be positively related to perceived control.

Hypothesis 9.

Perceived control will mediate the relationship between enabling factors and the intention to move.

3. Methodology

3.1. Procedure to Identify Seniors’ Needs for Successful Aging and Enabling Factors

Building upon Andersen’s model, this study identified seniors’ needs for successful aging and enabling factors leading to their decision of moving into senior living communities. Specifically, the needs incorporated three essential elements of successful aging [5]. Along with the literature review, items were generated based on interviews with ten senior living managers and employees. Discussions with interviewees centered around the following questions:

1.

People may opt to stay in a senior living facility due to health benefits. What factors do you think are important for seniors to stay healthy?

2.

People may opt to stay in a senior living facility because it may help them to keep their mind and body active. What factors do you think are important to keep seniors’ mind and body active?

3.

People may opt to stay in a senior living facility to increase or maintain an active lifestyle. What factors do you think are critical for seniors to have an active lifestyle?

4.

What kind of support is required for people to achieve the above factors for their successful aging?

The questionnaire contains 11 items for staying healthy, 7 for keeping the mind and body active, and 9 for leading an active lifestyle (Appendix A). The supporting factors included financial support, help from family and friends, and help from other sources, such as social workers and the church community.

3.2. Measures

Needs for successful aging (27 items). Respondents were asked to think about their senior life after retirement and then provided their expectation of living senior life successfully. Specifically, the questionnaire consisted of items to stay healthy (e.g., “I might need help for nutrition and food services”), to keep mind and body active (e.g., “I might need activities that help me stay active mentally”), and to have an active lifestyle (e.g., “I might need activities that facilitate my needs to do meaningful and productive things”). Respondents rated the items on 7-point scales ranging from “very unlikely” to “very likely.”

Enabling factors (5 items). Enabling factors were constructed in a senior living context. One example for an enabling factor is “Please indicate the extent to which the financial support you may have in the future (retirement income, house, investment, savings, etc.) is adequate for your needs of successful aging.” Respondents provided their responses on a 7-point scale ranging from “not at all adequate” to “completely adequate.”

Proximal determinants of intention to move. The items of each determinant (attitudes—5 items, subjective norms—3 items, and perceived control—2 items) were developed based on a questionnaire on TPB [34,35,36]. For attitudes, respondents evaluated the common stem, “For me, moving into a senior living community sometime after retirement would be…” on five 7-point bipolar adjective scales, such as “good—bad,” “unpleasant—pleasant,” “harmful—beneficial.” Responses were aggregated to generate a rating of attitude. For subjective norms, three items were used (e.g., “People who are important to me want me to move into a senior living community sometime after retirement”). Respondents rated each item on a 7-point scale ranging from “definitely false” to “definitely true.” Two items assessed perceived behavioral control. Respondents rated, for example, “It is mostly up to me whether or not I move into a senior living community sometime after retirement,” on a 7-point scale, such as from “strongly disagree” to “strongly agree.”

Intention to move (3 items). Intentions were assessed by three items (e.g., “I want to move into a senior living community sometime after retirement”). Respondents provided their answers on a 7-point scale ranging from “strongly disagree” to “strongly agree.”

Control variables. Two control variables were added to rule out the possibility that respondents’ perception could be influenced by knowing someone close in a senior living community and/or by previously assisting someone with his/her decision to settle into a senior living facility. The first question was “Do you have any relatives, or anyone close who are now in a senior living facility?” The other question was “Have you been involved in anyone’s decision-making process of moving into a senior living facility?” In addition, demographic information was collected, including age, gender, race, education, marital status, current living arrangements, and income.

3.3. Data Collection Procedure and Common Method Variance

This study utilized a cross-sectional survey design, with data collected via a self-administered online questionnaire distributed through Qualtrics’ (2005) [37] panel service in the United States. Participants were screened for eligibility, with inclusion criteria requiring individuals to be aged 55 or older and not current residents of senior living communities, as the study targeted perspectives of potential future residents. Those under 55 or residing in senior living communities were excluded. Qualtrics’ panel service provided a convenience sample of eligible respondents, though specific details of the recruitment process and sample size estimation are unavailable due to the proprietary nature of the service. The sample size was determined to ensure sufficient statistical power for Structural Equation Modeling (SEM) analysis. Data were collected electronically, ensuring accessibility across the U.S., with respondents completing questions related to the Needs of Successful Aging-Enabling-Psychosocial (N-SEP) model.

To control common method variances, several approaches were used to ensure the quality of responses. First, attention filters were added to ask the respondent to answer in a certain way. For example, among all multiple-choice questions, one question was inserted to ask respondents to type in “senior” in the text block. Anyone who answered incorrectly was directed to the end of the survey, and responses were not included in the analysis. Second, there were several trap questions in the survey to catch individuals who were speeding or cheating. For example, “Please select Strongly Disagree for this statement.” Third, several questions were reverse worded and changed the direction of the scale. Fourth, forced response for every question was added to make sure respondents completed the entire survey. Fifth, the average duration to complete the survey was fifteen minutes. Those who finished in less than one-third of fifteen minutes were excluded from the analysis due to speeding. To address potential common method variance, we included Facebook Intensity [38] as a marker variable, which is theoretically unrelated to the substantive variables in this study, such as seniors’ decision-making for senior living communities [39]. Vaportzis et al. (2017) [39] suggest that social media engagement, like Facebook usage, primarily serves social connectivity purposes among older adults and does not influence their relocation decisions. The absence of significant relationships between Facebook Intensity and this study’s focal variables confirms that common method variance did not affect the results.

3.4. Statistical Analyses

The proposed model was tested to identify the significant predictors of intentions to move into a senior living community and the links among needs for successful aging, enabling factors, and the proximal determinants of intentions (attitudes, subjective norms, and perceived behavior control). The models were tested by structural equation modeling (SEM) using Mplus 6.0 [40]. As described in the Section 3.2, multiple indicators (items) were assigned to each study construct to ensure reliability and validity of the construct in SEM [41]. Maximum likelihood estimation with robust standard errors (MLR), which are robust to non-normal distribution of scores [41], was used. The model fit was assessed with sample size-independent fit indices, such as the comparative fit index (CFI), the Tucker–Lewis index (TLI), and the root mean squared error of approximation (RMSEA), because the chi-square test is oversensitive to sample size, minor deviations from normality, and minor model misspecifications. The acceptable and excellent model fit value for CFI and TLI are greater than 0.90 and 0.95, while the acceptable and excellent model fit value for RMSEA are smaller than 0.08 and 0.06 [41,42].

4. Results

4.1. Descriptive Statistics

The subjects’ (n = 377) average age was 66.27, with 25.20% over age 70 and 74.80% between 55 and 70. A total of 63.75% of subjects were women, 90.98% were non-Hispanic white, 60.50% were married or in a domestic partnership, and 60.48% lived with their spouse. About 68.97% of subjects had a total annual household income ranging from USD 20,000 to USD 79,999 (

Table 2. Demographic characteristics of samples (N = 377).

Demographics	Proportion
Male	36.87%
Female	63.13%
Non-Hispanic white	90.98%
Non-Hispanic black	4.77%
Hispanic	1.86%
American Indian or Alaska Native	0.80%
Asian or Pacific Islander	1.59%
High school	45.36%
Associate’s degree	20.69%
Bachelor’s degree	21.75%
Master’s or doctoral degree	12.20%
Single, never married	12.20%
Married or domestic partnership	60.48%
Widowed	10.34%
Divorced or separated	16.98%
Living alone	25.99%
Living with spouse	59.95%
Living with other relatives	12.20%
Living with non-relatives	1.86%
Less than USD 20,000	13.26%
USD 20,000 to 39,999	29.44%
USD 40,000 to 59,999	22.81%
USD 60,000 to 79,999	16.71%
USD 80,000 to 99,999	6.63%
USD 100,000 to 149,999	8.49%
USD 150,000 or more	2.65%

).

Table 3. Measure correlations, means, and standard deviations.

Measures	Intention	Attitudes	Norm	Control	Need	Enabling	FBI
Attitudes	0.62 ***
Norm	0.77 ***	0.57 ***
Control	50 ***	0.49 ***	0.50 ***
Need	0.42 ***	0.33 ***	0.41 ***	0.16 **
Enabling	−0.021	0.13	0.02	0.44 ***	−0.25 ***
FBI	0.09	0.06	0.06	−0.02	0.9	−0.06
Mean	2.91	4.16	2.59	3.97	4.20	4.07	3.19
SD	1.50	1.51	1.39	1.67	1.21	1.41	2.12

Note: Need: needs of successful aging, Norm: subjective norms, Control: perceived behavioral control, Enabling: enabling factors, FBI: Facebook Intensity (marker variable). *** p < 0.001. ** p < 0.01.

reports the means, standard deviations, and inter-correlations of all variables. Several correlations among focal variables were significant and in the expected direction. Subjects reported a moderate level of intention to move into a senior living community (M = 2.91, SD = 1.5), quite positive perception of moving into senior living sometime in the future (M = 4.16, SD = 1.51), and low social pressure (M = 2.59, SD = 1.39). Their feeling of controlling the decision was moderately high (M = 3.97, SD = 1.67), while they also projected a high level of future need (M = 4.20, SD = 1.21) and enabling sources (M = 4.07, SD = 1.41) to support their later years.

4.2. Measurement Model

The measurement properties of the proposed model were evaluated by running confirmative factor analysis (CFA). To improve the model fit, items with a factor loading lower than 0.60 were dropped. The six-factor CFA model exhibited a good fit with the data (CFI = 0.911. TLI = 901; and RMSEA = 0.078). Composite reliability, an indicator of the shared variance among observed variables, was used to present the internal reliability of all constructs in this study [43] (Fornell & Larcker, 1981). Construct reliabilities for all six latent constructs (five constructs of interests and one marker variable) are well above the recommended value of 0.7 [44]. Standardized factor loading ranged from 0.61 to 0.99 and was statistically significant (p < 0.001) (

Table 4. Results of CFA.

Items	Standardized Factor Loadings	Standard Error	t-Value
Intention
Intent1	0.934	0.008	39.440 ***
Intent2	0.968	0.006	Fixed
Intent3	0.882	0.013	31.684 ***
Attitudes
Attitude1	0.903	0.012	Fixed
Attitude2	0.899	0.012	28.540 ***
Attitude3	0.806	0.020	21.551 ***
Attitude4	0.908	0.011	28.381 ***
Attitude5	0.797	0.021	21.474 ***
Norm
Norm1	0.737	0.027	17.526 ***
Norm2	0.871	0.016	26.573 ***
Norm3	0.906	0.015	Fixed
Control
Control1	0.768	0.040	Fixed
Control2	0.747	0.040	10.273 ***
Need
Health1	0.841	0.016	24.058 ***
Health2	0.823	0.017	22.501 ***
Health3	0.897	0.011	27.933 ***
Health4	0.879	0.013	27.145 ***
Health5	0.756	0.023	20.061 ***
Health6	0.894	0.011	30.037 ***
Health7	0.814	0.018	23.037 ***
Health8	0.901	0.011	Fixed
Health9	0.863	0.014	26.757 ***
Health10	0.880	0.012	27.192 ***
Health11	0.896	0.011	29.707 ***
Active1	0.807	0.019	22.709 ***
Active2	0.783	0.021	21.815 ***
Active5	0.729	0.025	18.884 ***
Active6	0.769	0.021	20.267 ***
Active7	0.662	0.029	15.792 ***
Engage5	0.638	0.031	15.437 ***
Engage6	0.606	0.033	14.140 ***
Engage7	0.627	0.032	14.940 ***
Enabling
Enable2	0.663	0.052	7.244 ***
Enable3	0.803	0.056	Fixed
FBI(MV)
FBI1	0.959	0.006	54.102 ***
FBI2	0.863	0.014	32.333 ***
FBI3	0.870	0.013	33.166 ***
FBI4	0.988	0.005	Fixed

Note: Need: needs of successful aging, Norm: subjective norms, Control: perceived behavioral control, Enabling: enabling factors, FBI: Facebook Intensity, MV: marker variable.*** p < 0.001.

). In addition, the average variance extracted (AVE) for each factor is higher than 0.50. These provided the evidence that all constructs showed convergent validity. Correlations among factors were all lower than 0.80, indicating the discriminant validity among constructs in this study [41]. Discriminant validity was established using a procedure suggested by Fornell and Larcker [43] According to Fornell and Larcker [43], the average variances extracted by the indicators corresponding to each of the six factors were computed and compared with the highest variances that each factor shared with the others in the model. Results showed that factors exhibited discriminant validity because the average variance extracted for each factor was greater than the highest shared variance (

Table 5. Scale properties of the six latent factors.

Construct	Composite Reliability	Coefficient Alpha	Average Variance Extracted	Highest Shared Variance
Intention	0.95	0.95	0.86	0.58
Attitudes	0.94	0.94	0.75	0.40
Norm	0.90	0.88	0.75	0.58
Control	0.73	0.73	0.57	0.25
Need	0.97	0.97	0.64	0.18
Enabling	0.70	0.67	0.54	0.19
FBI (MV)	0.96	0.96	0.85	0.01

Note: Need: needs of successful aging, Norm: subjective norms, Control: perceived behavioral control, Enabling: enabling factors, FBI: Facebook Intensity, MV: marker variable.

).

4.3. Tests of the Effects of Common Method Variance

Besides the procedural remedies described earlier, to address potential common method variance problems originating from a single data source (for details, refer to [45]), this study utilized the confirmatory factor analysis (CFA) marker technique [46,47,48]. The fits of the two nested models (“no marker model” vs. “marker model”) were compared. No significant differences were found between the two models, revealing common method variance is not a concern in this study (see the results of analyses,

Table 6. Model fit and goodness-of-fit indices.

Model	χ2	df	CFI	TLI	RMSEA
(a) No marker (structural) model	2023.27	706	0.912	0.903	0.070
(b) Marker (structural) model	1983.72	668	0.912	0.897	0.072

Models (a) and (b) do not significantly differ from each other regarding the model fit (nested χ²_diff, ns; [χ²_diff = (2023.27 − 1983.72) = 39.55; df = (706 − 668) = 38]).

).

4.4. Hypotheses Testing

4.4.1. Effects of Needs of Successful Aging

To predict the intention to move into a senior living community, the proposed model, including needs for successful aging and enabling factors, was tested by SEM analysis (Figure 4). Needs for successful aging had a significant effect on attitudes (β = 0.329, p < 0.001) and subjective norms (β = 0.457, p < 0.001). However, there was no significant relation between needs and intention. As expected, needs were negatively related to enabling factors (β = −203, p < 0.01). Therefore, Hypothesis 1 was not supported; Hypotheses 2, 3, and 4 were all supported.

The bootstrap method was employed to estimate the indirect effects of attitudes and subjective norms mediating the relationship between needs and intentions (

Table 7. Indirect effects.

Indirect Effect	Bootstrap Mean	SE	p-Value	95%CI
Effects from Need to Intention
Need->Attitudes->Intention	0.100	0.024	0.000	0.059–0.155
Need->Norm->Intention	0.312	0.049	0.000	0.227–0.425
Need->Enabling->Control->Intention	−0.015	0.007	0.033	−0.038–−0.005
Need->Enabling->Intention	0.019	0.013	0.146	0.000–0.055
Effects from Enabling to Intention
Enabling->Control->Intention	0.076	0.031	0.015	0.028–0.159

). The bootstrap method is a more powerful approach than the Sobel test [49] and the three-step multiple regression approach [50] to estimate mediation or indirect effects. For this study, the bootstrap process was repeated 2000 times. Results show significant indirect effects of needs on intention through attitudes (bootstrap mean = 0.100, 95% CI = 0.059–0.155), subjective norms (bootstrap mean = 0.312, 95% CI = 0.227–0.425), and enabling factors and perceived behavioral control (bootstrap mean = −0.015, 95% CI = −0.038–−0.005). Due to the nonsignificant relationship between needs and intention, there was mediation between needs and intention. Thus, Hypotheses 5 and 6 were supported.

4.4.2. Effects of Enabling Factors

Enabling factors were positively related with perceived behavioral control (β = 0.409, p < 0.001). But there was no significant relation between enabling factors and intention. The results do not support Hypotheses 7 and support Hypotheses 8. Using the bootstrap method to detect mediated effects, analysis found significant indirect effects of enabling factors on intention via perceived behavioral control (bootstrap mean = 0.076, 95% CI = 0.028–0.159). Since there were no significant direct effects between enabling factors and intention, perceived behavioral control mediated the association, supporting Hypothesis 9.

5. Discussion

In a need-driven marketplace, fulfilling customers’ needs is essential to bridge the gap between customers and service providers. For senior living operators to be successful, the three components of needs for successful aging must be satisfied to accommodate current and future customers. Most respondents belong to baby boomers in this study. With boomers gradually replacing the silent generation—also known as traditionalists—as potential customers for senior living communities, the results of this study show the importance of embracing the concept of successful aging, likely even more important to future residents, baby boomers. This implies the industry practitioners should operate the appropriate programs, ranging from a well-balanced meal plan to physical activities and to social activities. In addition, if residents can create a friendly atmosphere among themselves and make friends with other residents, they may feel more satisfied with their life in a senior living community.

This study reveals three mediational routes to increase the feasibility of seniors’ moving into a senior living community. The first two routes are initiated by seniors’ needs for successful aging. In detail, seniors’ own needs influence (1) their attitudes as well as (2) the voice of important referents (e.g., family and friends), which in turn leads to the intention to move into senior living. The first route encourages senior living practitioners to reach out to potential residents by various means to show services they will receive in the community. Messages should be delivered to potential customers by emphasizing the product of senior living. If important referents (second route) can accurately detect a senior’s needs, these referents will advocate the option of services in senior living. Industry practitioners should strive to educate the public about seniors’ multiple needs and about how well senior living communities can gratify those needs.

The third mediation route is rooted in enabling factors. Specifically, enabling factors have a positive influence on perceived behavioral control, and then perceived behavioral control positively influences the intention. For those who believe they possess more financial resources and/or can obtain more assistance from family, friends, social workers, and other sources, they feel more strongly that they have control over the decision-making process. Industry practitioners must understand this influential role of resources on a senior’s decision. In the future, they may want to consider incorporating more flexible options, preferably with lower costs, in their business portfolio.

Although the negative relationship between needs and enabling factors may initially seem counterintuitive, it can be explained. Individuals with greater needs for successful aging may perceive themselves as having fewer resources, such as financial support, or assistance from family, friends, or social workers. Within Andersen’s behavioral model, enabling factors are typically expected to facilitate greater utilization of health or social services. However, prior studies, for example [51], have also documented cases where the relationship operates in the opposite direction. While the present findings do not replicate those exact pathways, this prior evidence provides a potential rationale for our unexpected result, suggesting that higher perceived needs may correspond with lower perceptions of available enabling resources.

To align senior living communities with the needs of baby boomers and facilitate their transition, policies should promote comprehensive programs addressing successful aging through balanced nutrition, physical activities, and social engagement; launch targeted public education campaigns to inform potential residents and their referents about community benefits; offer flexible pricing or financial assistance to enhance accessibility for seniors with varying resources; and address the needs–resources gap by collaborating with community organizations to provide resource navigation or subsidies for seniors with higher perceived needs but fewer resources.

6. Limitations and Future Research

This study developed a measure for the needs of successful aging to test the proposed model. Due to the limited sample size, full-scale validation studies have not yet been conducted. Items were generated around three commonly accepted facets of successful aging. While the scale was not intended to be exhaustive, it provides a foundation for future research in this area as the senior living industry continues to evolve and diversify.

One limitation of this study is that items with factor loadings below 0.60 were removed to improve model fit. Although this approach is methodologically appropriate, it may have reduced the breadth of content validity. Future studies should consider incorporating a broader set of indicators to ensure more comprehensive construct coverage. We encourage scholars in senior living research to refine and strengthen this scale by adding items and dimensions that capture the full range of residents’ needs.

The proposed model as a whole should also be further validated. Future research could replicate the model across different types of senior living communities (e.g., independent living, assisted living, and memory care), among populations with higher care needs, and within shifting demographic trends (e.g., a transition from predominantly non-Hispanic White residents to increasing proportions of Hispanic residents in the U.S.). Additional research should also test the model across diverse cultural contexts and employ longitudinal, multi-method approaches, extending beyond the present study’s reliance on self-report measures and single-session data collection.

In particular, the unexpected negative relationship between needs and enabling factors warrants further investigation. While prior studies have largely focused on residents or prospective customers, little research has examined employees working within the senior living sector. Considering the industry’s reliance on long-term, relationship-based care, the role of employees is critical. Future research could explore important questions such as which individuals are most likely to choose, thrive, or remain in this profession, and what qualities are most predictive of long-term fit.

From a broader perspective, the senior living industry is both substantial and often framed in a relatively negative narrative. Concepts such as “success” and “aging,” however, may be defined and interpreted differently across cultural contexts. Future research could refine these constructs by incorporating culturally grounded perspectives. Doing so may contribute to building a more inclusive and positive narrative around aging and senior living, with meaningful implications for both academic scholarship and industry practice.

7. Concluding Remarks

The growth of the aging population is alarming with the prolonged life expectancy. We urge our society to give serious thought to this demographic shift and be prepared. Luckily, the number of senior living communities are increasing, albeit on a small scale, offering older adults an alternative place to settle in when they are old. We, the authors, modified Andersen’s original model by changing the focal outcome behavior from the utilization of medical services to settling into a senior living community. Seniors’ needs for successful aging and enabling factors (e.g., financial support and other resources) serve as two key determinants of moving into a senior living community. Successful aging goes beyond physical and cognitive health. The seniors want to be engaged in their life just like they were when they were younger. We hope this study provides insights into what older adults desire in their remaining life and stirs up interest in hospitality scholars’ senior living research.