Research in Gerontological Nursing

Empirical Research 

A Capabilities Approach to Environmental Impact on Nursing Home Resident Quality of Life

Whitney Thurman , MSN, RN ; Tracie C. Harrison , PhD, RN, FAAN ; Shelley A. Blozis , PhD ; Michelle Dionne-Vahalik , MSN, RN ; Sharilyn Mead , RN


Nursing homes are the major provider of intermediate and long-term care outside of the hospital setting to individuals whose capacity for self-care is limited due to physical or cognitive impairments. Yet, despite their need for assistance, residents of nursing homes want to control their lives, set their routines, and do enjoyable things. The extent to which residents can maintain autonomy and dignity is important. The current study suggests an environmental gerontological framework, rooted in a capabilities approach, that can be used to consider environmental impact on quality of life in nursing homes. Using a cross-sectional survey of nursing home residents in Texas, environmental factors that might predict residents' quality of life as well as possible interactions of environmental factors and residents' characteristics that might predict well-being were examined. Environmental orientation and perception of social activities were important predictors of residents' quality of life, but geographic location and facility size were not important predictors.

[Res Gerontol Nurs. 2017; 10(4):162–170.]


Nursing homes are the major provider of intermediate and long-term care outside of the hospital setting to individuals whose capacity for self-care is limited due to physical or cognitive impairments. Yet, despite their need for assistance, residents of nursing homes want to control their lives, set their routines, and do enjoyable things. The extent to which residents can maintain autonomy and dignity is important. The current study suggests an environmental gerontological framework, rooted in a capabilities approach, that can be used to consider environmental impact on quality of life in nursing homes. Using a cross-sectional survey of nursing home residents in Texas, environmental factors that might predict residents' quality of life as well as possible interactions of environmental factors and residents' characteristics that might predict well-being were examined. Environmental orientation and perception of social activities were important predictors of residents' quality of life, but geographic location and facility size were not important predictors.

[Res Gerontol Nurs. 2017; 10(4):162–170.]

Nursing homes are the major provider of intermediate and long-term care outside the hospital setting for individuals whose physical or cognitive impairments limit their capacity for self-care ( Kane & Kane, 1995 ). Nursing home residents need assistance with activities of daily living as well as medical care; they are no longer able to maintain their quality of life within the community. Nevertheless, control over daily decision making remains an important aspect of residents' quality of life; self-empowerment within the home's environment remains important despite the need for assistance ( Duncan-Myers & Huebner, 2000 ). Nursing home residents want to set their routines, select their clothing, and do what they enjoy ( Agich, 2003 ; Kane & Kane, 2001 ). Nursing home personnel must deliver high-quality medical care while addressing necessities of daily life that include meals, social interactions, and personal hygiene, and they must do so in accord with regulations and policies ( Sherwin & Winsby, 2011 ). They must also balance residents' autonomy and dignity with the provision of an increasing array of complex medical, behavioral, and psychological therapies. To do this within a residential setting is fraught with tension that affects the resident's quality of life.

The current article suggests an environmental gerontological framework rooted in a capabilities approach ( Nussbaum, 2011 ; Sen, 1992 ) as a theoretical basis for considering influences on nursing home residents' quality of life. These influences are defined in terms of residents' desire for, access to, and satisfaction with social and functional environmental resources. This environmental gerontological framework is operationalized with an analysis of data collected in an in-person cross-sectional survey of quality of care and quality of life among nursing home residents, the biannual Texas Health and Human Services Commission's (HHSC) Nursing Facility Quality Review (NFQR).

Quality of Life in Nursing Facilities

In 1986, the Institute of Medicine's ( IOM; 1986 ) report, “Improving the Quality of Care in Nursing Homes,” recommended changes in regulatory policies and procedures to ensure that residents of nursing homes would receive satisfactory care. The IOM emphasized the “home” as opposed to the “nursing” component of nursing home care ( Koren, 2010 ). As a result, in 1987, the Nursing Home Reform Act created an explicit statutory requirement that services facilitate residents attaining and maintaining their highest possible well-being. Despite these statutory requirements, the meaning of well-being or quality of life for institutionalized frail older adults continued to be debated ( Agich, 2003 ). Seminal work by Kane et al. ( 2003 ) , however, conceptualized quality of life as a general construct that comprises 10 independent yet related domains: comfort, security, meaningful activity, relationships, functional competence, enjoyment, privacy, dignity, autonomy, and spiritual well-being. Quality of life for institutionalized older adults thus includes not only health but also satisfaction with their social and environmental status.

Although subsequent research has explored how to best measure quality of life and examined meaningful and influential factors, health-related quality of life measures still tend to focus on physical health and functional abilities ( Kelley-Gillespie, 2009 ). This neglect of social and environmental dimensions of well-being or quality of life can limit interventions to those that focus on residents' physical health. The current authors contend that the continued emphasis on physical health may come at the expense of residents' dignity and autonomy, and that it can be attributed at least in part to the use of models of acute and chronic care translated to the nursing facility setting. There is a need instead for frameworks that recognize residents as living within a residential, social, and environmental milieu. Quality of life must include the context of a resident's life prior to entering a nursing home as well as during nursing home residence.

Environmental Gerontological Framework

Individuals who live in a nursing home deserve and expect a life with dignity and autonomy ( Agich, 2003 ; Høy et al., 2016 ; Kane & Kane, 2001 ). An environmental gerontological capabilities framework can capture multidimensional influences on a resident's quality of life or well-being, including the extent to which that person retains his or her dignity and autonomy within and outside of the nursing home. The capabilities approach, first developed for use in the fields of human development and social justice ( Nussbaum, 2011 ; Sen, 1985, 1992 ), originated as a way of thinking about how advantaged or disadvantaged individuals may be and about how the quality of human lives might be assessed; Entwistle and Watt ( 2013 ) later applied it to person-centered care. The main concepts of any capabilities approach are functionings—individual's ways of being and doing, such as caring for one's family, spending time with friends, or being well-nourished—and capabilities, the real opportunities that an individual has to achieve a particular functioning ( Sen, 1985 ). Thus, capabilities do not refer exclusively to an individual's ability but also to social and environmental circumstances that shape an individual's capability to act.

Such an approach encourages an evaluation in which the outcome of interest is an individual's freedom to choose meaningful activities. To focus on capabilities as opposed to functionings in an assessment of quality of life avoids the imposition of particular ideals on others ( Entwistle & Watt, 2013 ). For example, a focus on the capability to be well-nourished (i.e., ensuring provision of nutritious and appropriate food choices) allows for the value that an individual might attach to religious fasting and the subsequent failure to be well-nourished, as opposed to the value of consuming the food, not to mention the subsequent attainment of the “functioning” of being well-nourished.

Ensuring that services are offered in such a way as to respect the individual's values is fundamental to a capabilities approach, and it reinforces the dignity and autonomy of the nursing home resident. Indeed, the importance of human dignity is inherent in a capabilities approach. Nussbaum ( 2011 ) has asserted that if an individual has sufficient physical health to acknowledge his or her own needs but is not empowered to exercise practical reason and planning, that person may lose his or her own unique human dignity. Respect for an individual's practical reason and ability to make choices about daily life is fundamental to human dignity, even if the individual requires assistance. Such respect is critical to understanding frail older adults and disabled individuals. Ensuring that everyone has a basic level of capability to pursue the things that they have reason to value is a bare minimum of respect for human dignity.

It has been asserted that nursing home residents' own appraisal of their lived experiences should be included in any assessment of their quality of life ( Kane et al., 2003 ; Rubinstein, 2001 ). But one must also consider the influence of the environment. The more competent an individual is in health and intelligence, the less influence his or her physical and social environment may wield ( Lawton, 1969 ). Conversely, a reduction in competence heightens the influence of external conditions. Given that more than 75% of nursing facility residents require assistance with activities of daily living ( Centers for Medicare & Medicaid Services [CMS], 2013 ) and that approximately two thirds have at least mild cognitive impairment ( CMS, 2013 ), the facility's environment must have a tremendous influence on residents' lives. Thus, in the current study, Lawton's ( 1969 ) environmental docility hypothesis was incorporated within a capabilities approach ( Nussbaum, 2011 ; Sen, 1992 ) to promote an understanding of the nursing facility environment as an extension of the home in relation to quality of life.

For the framework, three constructs/concepts were developed and tested: (a) environmental factors, (b) quality of life, and (c) residents' characteristics. Environmental factors include not only physical structures but also the social dimensions of the nursing home, because the environment comprises “those contexts (situations) which occur outside individuals and elicit responses in them” ( Law, 1991 , p. 175). In the current study, environmental factors include socialization, rural or urban classification status, nursing facility size, and resident access to outdoor space.

Socialization/Social Activities

Lawton ( 1969 ) , who reported that opportunity for casual interaction was the most important factor in predicting socialization, theorized that the impact of the environment on socialization is a critical determinant of friendship in older adults. Engagement in social activities is an important predictor of quality of life in nursing homes ( Tak, Kedia, Tongumpun, & Hong, 2015 ). Positive social interactions contribute to thriving in nursing homes ( Bergland & Kirkevold, 2006 ), and social engagement is positively associated with psychosocial well-being, health, and survival ( Adams, Leibbrandt, & Moon, 2011 ). Evidence also suggests that social engagement is valued by older adults ( Litwin & Shiovitz-Ezra, 2006 ). Hence, access to a place where casual interactions may occur as well as access to social activities that facilitate those interactions are important for behavior modifications that may occur via social connectedness among older adults. The nursing home's environment should facilitate environmental opportunities for socialization by providing interactive habitats ( Lawton, 1969 ), and the individual's socialization within those habitats can lead to actions and further interactions, ultimately culminating in a sense of human dignity.

Rural/Urban Classification Status

Rural location has been associated with quality concerns; evidence suggests that nursing homes in rural areas are less likely than those in non-rural areas to achieve a 4-star or higher rating on quality ( Kang, Meng, & Miller, 2011 ; Lutfiyya, Gessert, & Lipsky, 2013 ). Research on end-of-life care in nursing homes suggests that residents of rural nursing homes receive less medical care at the end of life ( Gessert, Haller, Kane, & Degenholtz, 2006 ) and are more likely to report frequent pain ( Bolin, Phillips, & Hawes, 2006 ). Thus, geography may be an important predictor of quality of life in nursing homes residents, especially in light of health and health care disparities: rural communities across the United States have a greater proportion of frail older adults, placing rural residents at an increased likelihood of requiring nursing home care ( Jacobsen, Kent, Lee, & Mather, 2011 ).

Nursing Home Size

Evidence also suggests that nursing home size is an important predictor of outcomes. Larger facility size has been associated with poorer scores on quality of life measures ( Shippee, Hong, Henning-Smith, & Kane, 2015 ) and significantly associated with deficiency citations ( Flynn, Liang, Dickson, & Aiken, 2010 ). Similar to geographic location, facility size may be an important predictor of nursing home residents' quality of life.

Outdoor Space

Outdoor space is also beneficial for nursing home residents. Many residents never have the opportunity to leave facility grounds, and residents have indicated their appreciation of outdoor spaces for relaxation, activities, and interactions with others ( Whear et al., 2014 ). However, research has indicated that only one third of nursing home residents who are physically able to go outdoors actually do so ( Cutler & Kane, 2005 ). Spending time outdoors can have positive effects in a wide range of outcomes, including improved mood and sleep quality ( Detweiler et al., 2012 ).

Quality of Life

Commensurate with the capabilities approach, quality of life represents an individual's capability to pursue activities he or she has reason to value. Within this definition is the assumption that dignity is fundamental to quality of life and that it precedes the individual's ability to make meaningful choices or pursue meaningful activities.


In the current study, the environmental gerontological framework was applied in an analysis of nursing homes to identify environmental predictors of quality of life in nursing home residents and consider whether these predictors are stable among variable demographic characteristics. Environmental factors (e.g., rural/urban classification status, facility size, outdoor space, social activities) that might predict individual resident's quality of life (e.g., privacy, control), and environmental factors or residents' characteristics that might interact in predicting resident quality of life (e.g., privacy, control) were considered.

Study Population

The study included a sample of residents from Medicaid-certified nursing homes in the state of Texas that provide long-term, institutional care to those whose medical conditions regularly require the skills of licensed nurses. In 2013, the Texas legislature directed the Texas HHSC to assess satisfaction with quality of care and quality of life for individuals living in Medicaid-certified nursing homes in the state. In 2014, the HHSC awarded the second author of the current study (T.C.H.) the grant to begin data collection for the NFQR. The data were collected by RNs through chart reviews, interviews with nursing home residents or their families, and facility observation.

Nursing home residents located in the facility on the day of data collection and willing/able to answer survey questions were entitled to participate, regardless of cognitive status. Cognitively impaired participants have been included in previous research on quality of life in nursing homes ( Kane et al., 2003 ); they are thinking, conscious adults even though their consciousness may be fragile and their concerns may differ from individuals without cognitive impairment ( Diamond, 1986 ). If a resident was unable to provide consent but the resident's family was present and able to do so, the resident was included. If unable to consent to participate due to cognitive status and no family members were available for consent, the resident was not approached for questions. However, residents' charts were still reviewed to provide assessment of the facility's quality of care.

Individuals in the sample ranged in age from 18 to 108, with a mean age of 77.82 ( SD = 12.85 years ). Similar to national statistics, 65.6% were female, and 15.8% were Black individuals. However, Texas nursing homes have a smaller percentage of White residents (67.2% versus 76%) and a higher percentage of Hispanic residents (14.4% versus 5.2%). Less than 50% of the sample had lived in their current residence for 1 full year, 16.6% for 1 to 2 years, and approximately 3% for more than 10 years.

Data Collection

The NFQR's random sample comprised one to three residents from each facility. The CMS Minimum Data Set was used to establish a 6-month census for each nursing home, ranking facilities from smallest to largest according to bed capacity. The ranked list was divided into thirds: from the smallest third of facilities, one resident was sampled; from the middle third, two residents were sampled; and from the largest third, three residents were sampled.

The NFQR's measures—chart reviews, residents' or families' perceptions of quality of life, and RN observations of the facility environment—were selected from input to the HHSC from multiple committees of stakeholders. After local Institutional Review Board approval, 1,115 nursing home administrators within 11 Texas health regions were mailed letters stating that their facilities would be visited to administer the NFQR. The letters included the time period for visits and contact information for the primary investigator and HHSC for any follow-up questions. From March 2015 through January 2016, 21 RNs trained in research ethics, research methods, and consistency in data collection were assigned regions to visit, depending on the number of facilities to be evaluated in each region. Using a standardized program, RNs collected data on tablets loaded with items to be retrieved in all three areas of interest from every resident.

Upon arriving at the nursing home, RNs used randomized numbers to select potential participants based on alignment with the census roster. Residents had the option of refusing interviews, which occurred on eight occasions. If a resident refused, was unavailable due to hospitalization, or was on leave with family, or for any other reason not specified, a second set of random numbers was used to identify a different resident participant. Chart review data were collected from documentation in the resident's paper or electronic chart. The resident's identity was verified by staff, and the resident was then interviewed by the RN data collector in a private area in each facility. Facility-level data were entered separately for each resident. Each RN data collection point was monitored for reliability through ongoing duplication of facility visits, ongoing research office connection with each facility's administration, and review of RN data, including the time it took to collect data. These activities ensured reliable data for analyses.


Outcome Variable. To capture the opportunity freedom that is paramount in the capabilities approach, seven questions in the NFQR survey instrument were selected that were related to meaningful choice ( Table 1 ), which together constituted a scale for quality of life. The environmental gerontological framework seeks to understand the individual resident's meaningful opportunities for action and choice, as opposed to specific actions taken or decisions made. Each item was rated on a Likert-type scale ranging from 1 = always to 5 = never . Using Mplus version 7.4, an exploratory factor analysis with the seven items using oblique rotation suggested a two-factor structure (root mean square error or approximation = 0.022, confirmatory fit index = 0.998, Tucker Lewis Index = 0.995). Five of the seven items loaded on a factor that was labeled privacy , and the remaining two loaded on a factor that was labeled control . The estimated correlation between the two factors was r = 0.26; hence, there was no threat of multi-collinearity. These two factors were retained as separate dimensions of quality of life. Internal consistencies for the sets of items were examined using Cronbach's alpha, acceptable at 0.82 and 0.69, respectively. Given that the confirmatory factor analysis provided data that supported the theorized components and that the two components' alphas were similar to other acceptable validity analyses ( Rubright, Cary, Karlawish, & Kim, 2011 ), the authors are confident that these measures reflect the observed scores.

Individual Quality of Life Scale Items

Table 1 :

Individual Quality of Life Scale Items

Independent Variables. Because evidence suggests that they are predictors of quality of life of nursing facility residents, the following variables were included for environment and individual well-being: urban classification, facility size, residents' access to outdoor space, and social activities offered at the nursing facility.

For urban classification, the U.S. Department of Agriculture's set of rural–urban continuum codes was used; these codes range from 1 to 9, with large, metropolitan counties (>1 million residents) coded as 1, and completely rural areas, nonadjacent to urban areas (<2,500 individuals) coded as 9. For facility size, facilities were classified according to the CMS categories of <50 beds, 50 to 99 beds, 100 to 199 beds, and >199 beds. For the capability of access to outdoor space (as opposed to the functioning of spending time outdoors), the question from the NFQR that asked residents “Do you have access to outdoor spaces?” was used; response possibilities ranged from 1 = always to 5 = never .

Finally, three items from the NFQR measured the extent to which residents perceived activities as available and of interest, rather than the extent to which residents participated in the activities; these items were used to constitute a scale for social activities ( Table 2 ). This scale captured the capability of social activity as opposed to the functioning of being socially active. Each item was rated on a Likert-type scale ranging from 1 = always to 5 = never . These three items, assumed to represent an underlying measure of social activities, are henceforth referred to as social activities in the current models. Internal consistency for this item set was acceptable at 0.73.

Social Activities Scale Items

Table 2 :

Social Activities Scale Items

Cronbach's alpha is reported as a measure of scale reliability. In the current analysis (presented in the next section), a latent variable model was used, which made it possible to separate measurement error from variance and estimate relationships between the factor and other variables without the influence of measurement error in those scale items. Only a small number of items was used to measure the construct of quality of life, and fewer items can result in a less reliable scale. The latent variable approach allows for a model that helps maintain adequate reliability.

Data Analysis

The target sample of 1,560 adults living in Medicaid-certified nursing homes in Texas yielded data for 899 residents who lived in 581 nursing facilities. Regarding environmental factors that might predict individual quality of life in a nursing facility, a multilevel regression analysis with latent variables was estimated using Mplus version 7.4 because multiple residents living in the same facility were surveyed. The fact that some individuals shared the same home could result in correlated responses among residents living in the same facility. Multilevel regression accounts for dependencies in the data due to hierarchical data collections ( Raudenbush & Bryk, 2002 ); standard regression is not appropriate in such situations because that method assumes that individuals are independent. In addition, the multilevel regression included latent measures of the two aspects of resident quality of life (based on exploratory factor analysis), namely privacy and control, as well as a latent measure of social activities based on the three survey items relating to social activities. For interaction effects, the multilevel model was extended to include residents' characteristics along with environmental factors combined with the interactions between these variables. All resident-level predictors were centered on their respective grand means to obtain within-facility effects of these variables.


An average of 1.55 residents were sampled in each nursing home. Of the facilities surveyed, 75% were in metropolitan areas; 49.7% of these were in large urban areas with a population >1 million. The remaining one quarter of nursing homes were in nonmetropolitan areas, 21 of which were located in a completely rural area nonadjacent to a metropolitan area. The majority of nursing homes were classified as intermediate in size, with 52.5% having between 50 and 99 beds and 34.4% having between 100 and 199 beds. More than 50% of respondents indicated that they “always” had access to outdoor space at their respective nursing home.

In the first step of the data analysis, variables relating to the nursing home were evaluated as predictors of the two dimensions of quality of life (privacy and control). These variables were the facility's urban classification, facility size, access to outdoor space, and social activities. As shown in Table 3 , social activities (b = 0.147, standard error [SE] = 0.058, t = 2.52, p = 0.012 ) and access to the outdoors (b = 0.190, SE = 0.035, t = 5.44, p < 0.001 ) were positively related to privacy; and social activities (b = 0.654, SE = 0.135, t = 4.84, p < 0.001 ) and access to the outdoors (b = 0.140, SE = 0.056, t = 2.48, p = 0.013 ) were positively related to control. In other words, the capabilities of social activities and access to the outdoors were related to a resident's report of quality of life as expressed by both privacy and control. However, facility size or urban classification was not statistically related to the resident's privacy or control. Overall, the predictors accounted for 9% of the variance for privacy and 27% of the variance for control.

Maximum Likelihood Estimates (Standard Error) of Environmental Factor Effects on Resident Well-Being

Table 3 :

Maximum Likelihood Estimates (Standard Error) of Environmental Factor Effects on Resident Well-Being

In first considering the addition of residents' characteristics (i.e., age, gender, length of stay, and non-White ethnicity) without the interactions, statistical tests suggested that the dimension of privacy was higher for residents who did not identify as White (b = 0.137, SE = 0.060, t = 2.27, p = 0.023 ). None of the other residents' characteristics were related to either privacy or control. As shown in Table 4 , when the model was extended to include interaction effects, statistical tests suggested that none of the residents' characteristics interacted with other residents' characteristics or environmental factors and none of the environmental factors interacted with other environmental factors as predictors of residents' quality of life. The type of facility or demographic characteristics of the residents did not predict quality of life.

Maximum Likelihood Estimates (Standard Error) of Environmental Factor and Resident Characteristic Effects on Resident Well-Being

Table 4 :

Maximum Likelihood Estimates (Standard Error) of Environmental Factor and Resident Characteristic Effects on Resident Well-Being


To the current authors' knowledge, this is the first study to use an environmental gerontological framework grounded in a capabilities approach to analyze nursing homes. This framework emphasizes individual values and beliefs as well as environmental factors in determining quality of life, grounded in the concept that individuals in a nursing home are an extension of the broader community. The findings of the current study suggest that when quality of life is considered in terms of an individual's capability to pursue meaningful activities, environmental factors may be more vital than individual demographic characteristics. Although studying quality of life in nursing home residents is not novel, the current study is the first with an environmental gerontological framework using a capabilities approach, which suggests implications for further study, especially with respect to residents' desire to know they can access the outdoors for feelings of privacy and control.

The immediate environment, not the extended classification of the environment as indicated by the urban–rural classification, made a difference in the latent estimation of quality of life. This finding is important because geographic location, including rurality, is frequently cited as a concern and has been associated with poorer outcomes in clinical quality and quality of life in nursing homes ( Kang et al., 2011 ; Lutfiyya et al., 2013 ; Phillips, Hawes, & Williams, 2003 ). In addition, no relationship was found between facility size and individual quality of life. This finding is also significant because previous research has indicated that facility size is an important predictor of nursing home quality ( Shippee et al., 2015 ). From an environmental gerontological perspective, it seems that geographic location and facility size cease to be important predictors of quality of life.

In the current study, perceived access to outdoor space was significantly and positively related to control and privacy, which is important for an understanding of quality of life in the nursing home. According to Marquardt and Schmieg ( 2009 ) , the outdoors can serve as a cognitive map that orients an individual to his or her surroundings. As autonomy is threatened, owing to loss of home and routine, knowledge of the self in relation to the outdoor environment can be pivotal to reorientation and wayfinding. A perspective that extends the importance of privacy and control to perceptions of access to the outdoor space should be a reminder that the nursing home is a community where individuals have come to reside while needing assistance, rather than an institutional setting for medical treatment.

Social activities were also a significant predictor of quality of life, given the capabilities approach. Previous research has indicated that finding out what matters to residents of nursing homes and what helps them feel fulfilled is central to determining their quality of life ( Dewar & Nolan, 2013 ; Tolson, Dewar, & Jackson, 2014 ). Findings from the current study support the notion that individual values and beliefs are important. The ability of older adults in long-term care to maintain independence and be involved in activities is also important to their quality of life ( Sullivan & Asselin, 2013 ). But the current findings challenge the assumption that residents must actively participate in social activities. From the environmental gerontological perspective, the perception that social activities are available to the individual (i.e., residents' perception that they have the capability to pursue meaningful activities) has a significant relationship with quality of life.


As with any research study, limitations must be acknowledged. The cross-sectional nature of the survey limits the ability to determine causal relationships, and the NFQR survey instrument was not designed from a capabilities perspective. The survey was designed to capture quality of life based on stakeholders' input regarding service needs and expectations. Therefore, the outcome variable measuring individual quality of life was not validated for use with the newly developed framework. Nevertheless, the statistical analyses regarding the outcome variable indicate sufficient reliability for the current study.


The current study's results indicate that an environmental gerontological perspective grounded in the capabilities approach can provide a useful framework for the evaluation of nursing home quality. This framework's expansive view of outcomes reflects what individuals say they value in life and appreciate in service provision. In a nursing home—in Kane's ( 1990 ) terms, an accidental community—where individuals from diverse demographic and social backgrounds reside together, the values and beliefs of individual residents may be overlooked. The environmental gerontological framework presented in the current study recognizes that capabilities are significantly shaped by environmental factors and individual values and beliefs. The results of this study warrant further investigation into the quality of life of nursing home residents using an environmental gerontological framework.


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Individual Quality of Life Scale Items

Survey Questions
Privacy Component
  • Can you find a place to be alone when you wish?
  • Can you make a private phone call?
  • When you have a visitor, can you find a place to visit in private?
  • Can you be together in private with another resident (other than your roommate)?
  • Do people knock first and wait for an answer before coming into your room?
Control Component
  • Can you choose your daily schedule (e.g., when to getup, when to eat, when to go to sleep)?
  • Can you choose when and how to bathe?

Social Activities Scale Items

Survey Questions
• Outside of religious activities, do you have enjoyablethings to do at the nursing facility?
• Does the nursing facility offer organized activities?
• Do you enjoy the organized activities here at the nursing facility?

Maximum Likelihood Estimates (Standard Error) of Environmental Factor Effects on Resident Well-Being

Resident Quality of Life
Predictor Privacy t a p Value b Control t a p Value b
Social activities 0.147 (0.058) 2.52 0.012 0.654 (0.135) 4.84 <0.001
Access to outdoors 0.190 (0.035) 5.44 <0.001 0.140 (0.056) 2.48 0.013
Facility size 0.088 (0.053) 1.67 0.096 −0.009 (0.075) −0.12 0.91
Urban classification 0.011 (0.017) 0.63 0.53 −0.004 (0.023) −0.19 0.85

Maximum Likelihood Estimates (Standard Error) of Environmental Factor and Resident Characteristic Effects on Resident Well-Being

Quality of Life
Predictor Privacy t a p Value b Control t a p Value b
Male 0.037 (0.058) 0.63 0.53 −0.093 (0.095) −0.98 0.33
Age 0.004 (0.004) 1.06 0.29 −0.001 (0.006) −0.184 0.85
Non-White ethnicity 0.137 (0.060) 2.27 0.023 −0.004 (0.097) −0.039 0.97
Length of stay 0.005 (0.008) 0.67 0.51 −0.005 (0.013) −0.38 0.71
Social activities 0.107 (0.046) 2.31 0.021 0.505 (0.109) 4.61 <0.001
Access to outdoors 0.187 (0.035) 5.35 <0.001 0.144 (0.061) 2.36 0.018
Facility size 0.087 (0.055) 1.60 0.109 −0.016 (0.075) −0.21 0.83
Urban classification 0.014 (0.017) 0.79 0.43 −0.004 (0.023) −0.16 0.88

Ms. Thurman is PhD Candidate, Robert Wood Johnson Foundation Future of Nursing Scholar, and Dr. Harrison is Associate Professor of Nursing, University of Texas at Austin School of Nursing, and Ms. Dionne-Vahalik is Director, Quality Monitoring Program and Initiatives, Medicaid Chip Division, and Ms. Mead is Nurse III, Quality Monitoring Program, Texas Health and Human Services Commission, Austin, Texas; and Dr. Blozis is Professor of Psychology, Department of Psychology, University of California, Davis, Davis, California.

The authors have disclosed no potential conflicts of interest, financial or otherwise. The Nursing Facility Quality Review was funded by the 2013 Texas Legislature and awarded through the Quality Monitoring Program of the Texas Health and Human Services Commission (Principal Investigator, T.C.Harrison; Contract UTA16-000895). Support for this article was provided in part by the Robert Wood Johnson Foundation. The views expressed herein do not necessarily reflect the views of the Foundation. Editorial support with manuscript development was provided by the Center for Excellence in Long-Term Care, the Cain Center for Nursing Research, and the Center for Transdisciplinary Collaborative Research in Self-Management Science at the University of Texas at Austin School of Nursing.

Address correspondence to Whitney Thurman, MSN, RN, PhD Student, University of Texas at Austin School of Nursing, 1710 Red River Street, Austin, TX 78701; e-mail: .

Received: February 03 , 2017
Accepted: June 15 , 2017


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