Search tips
Search criteria 


Logo of gerontLink to Publisher's site
Gerontologist. 2012 October; 52(5): 632–640.
Published online 2012 January 9. doi:  10.1093/geront/gnr137
PMCID: PMC3463417

Does Cognitive Impairment Influence Quality of Life Among Nursing Home Residents?

Kathleen Abrahamson, PhD, RN,*,1 Daniel Clark, PhD,2 Anthony Perkins, MS,3 and Greg Arling, PhD2


Purpose: We investigated the relationship between cognitive status and quality of life (QOL) of Minnesota nursing home (NH) residents and the relationship between conventional or Alzheimer’s special care unit (SCU) placement and QOL. The study may inform development of dementia-specific quality measures. Design and Methods: Data for analyses came from face-to-face interviews with a representative sample of 13,130 Minnesota NH residents collected through the 2007 Minnesota NH Resident Quality of Life and Consumer Satisfaction survey. We examined 7 QOL domains: comfort, meaningful activities, privacy, environment, individuality, autonomy, relationships, and a positive mood scale. We applied multilevel models (resident and facility) to examine the relationship between the resident’s score on each QOL domain and the resident’s cognitive impairment (CI) level and SCU placement after controlling for covariates, such as activities of daily living dependency, pain, depression or psychiatric diagnosis, and length of stay. Results: Residents with more severe CI reported higher QOL in the domains of comfort and environment and lower QOL in activities, individuality, privacy and meaningful relationships, and the mood scale. Residents on SCU reported higher QOL in the meaningful activities, comfort, environment, and autonomy domains but had lower mood scores. Implications: Our findings point to QOL domains that show significant variation by CI and thus may be of greatest interest to consumers, providers, advocacy groups, and other stakeholders committed to improving dementia care. Findings are particularly applicable to the development of NH quality indicators that more accurately represent the QOL of NH residents with CI.

Keywords: Quality of life, Nursing home, Special care unit, Cognitive impairment

Nursing home (NH) quality indicators (QIs) have been used widely for regulation, public reporting, and facility quality improvement. Yet, none of the QIs are designed specifically for residents who are cognitively impaired (Arling, Kane, Lewis, & Mueller, 2005 ). The QIs deal primarily with health conditions, functioning, and nursing services; they give little attention to quality of life (QOL) and resident satisfaction (RS), areas that are of great importance to both cognitively impaired and nonimpaired residents. Although some current QI’s point to care problems that are relevant to residents with dementia, such as physical restraints, psychotropic medications, functional decline, and continence, they do not specifically address the needs and experiences of residents with cognitive impairment (CI).

Though clinical outcomes and processes of care have historically been the primary measures of NH quality, there is an increasing body of literature addressing factors that influence NH residents’ overall QOL (R. A. Kane, 2001; R. A. Kane et al., 2003). However, the specific influence of CI on NH resident QOL remains underinvestigated. Our study examines the QOL of NH residents with CI through an investigation of the relationship between CI and resident QOL. It also compares QOL for residents on conventional and dementia special care units (SCUs). Findings have the potential to inform the development of dementia-specific quality measures (QMs) for use by both public and private NH quality initiatives.


Nursing home QIs are based upon data provided by the Minimum Data Set (MDS) and used by the Center for Medicare and Medicaid Services (CMS) for regulation as well as public reporting. Medicare’s web-based quality reporting system, Nursing Home Compare, presents information on 14 long-stay QMs for each of the nation’s 17,000 NHs. The NH Compare QMs are currently under review and may change. Neither the current QMs nor proposed new QMs (National Quality Forum, 2011) address the unique experience of residents with CI. Moreover, use of CI as a risk adjuster for several of the QMs may obscure differences in care processes and outcomes between residents with and without dementia, thus making it difficult for family members and caregivers of individuals with CI to choose the best care setting. Additionally, the QMs generally focus on the absence of negative health outcomes, such as fractures, falls, and decreased physical function. None of the QMs address the complexities of resident QOL, which is related to health and functioning yet represents a unique set of care domains (R. A. Kane, 2001). In a recent systematic review of NH QI by Castle and Ferguson (2010), QOL was absent from the list of measures, and there was limited attention to QOL as a policy-relevant outcome of care.

There is evidence that resident QOL is a measureable and achievable outcome in NHs (R. A. Kane et al., 2003). R. L. Kane and colleagues (2004) found that though the majority of the variation in QOL between NH residents could be explained by individual characteristics, a pattern of scores emerged within facilities on the 10 examined QOL domains indicating the ability to differentiate between facilities on the basis of resident QOL. It is feasible to measure resident QOL and apply these findings to the evaluation of care provided by NHs.

Cognitive status alone or in combination with other factors can significantly influence an individual’s perception of QOL. Previous research suggests that QOL has potential to improve over time among NH residents (Lyketsos et al., 2003; Selwood, Thorgrimsen, & Orrell, 2005), yet when declines in QOL occur, they are often correlated with declines in cognitive status and mood disorders, such as depression (Hoe et al., 2009; Logsdon, Gibbons, McCurry, & Teri, 2002; Selwood et al., 2005). Sloane and colleagues (2005) found that QOL is strongly related to level of CI and activities of daily living (ADL) dependency, consistent with the finding of Anderson, Wittrup-Jensen, Lolk, Andersen, and Kragh-Sorensen (2004) that dependence upon others for assistance with ADLs negatively influences QOL. Evidence indicates that QOL among NH residents is improved by high levels of social engagement, a perception of life coherence or purpose, and the availability of purposeful activities (Degenholtz, Kane, Kane, Bershadsky, & King, 2006; Drageset et al., 2008; Moore, Delaney & Dixon, 2007; Zimmerman et al., 2005). The special programming on SCUs is intended to promote social engagement and activities that enhance resident’s perception of QOL (Gruneir, Lapane, Miller, & Mor, 2008; Holmes et al., 1990). On the other hand, SCUs are more likely to have residents with behavioral problems, depression, or other conditions that could diminish perception of QOL. Our analysis addresses this complexity by examining the relationship between SCU placement and resident QOL, although controlling for covariates, such as ADL dependency, pain, depression or psychiatric diagnosis, and length of stay.

QOL is a multidimensional and subjective construct, influenced by both individual and environmental factors. Evaluation of QOL among cognitively impaired NH residents poses particular challenges, given the potential for difficulties with communication, memory, and cognitive processing within this population. However, previous investigations have found that NH residents are reliable informants of their own QOL status, even in cases of CI (Brod, Steward, Sands, & Walton, 1999; R. A. Kane et al., 2003; Logsdon et al., 2002; Maslow & Heck, 2005; Mozley et al., 1999). Because QOL is inherently dependent upon individual perception, caregiver reports and clinical data are not adequate proxies for resident self-report assessment instruments (Degenholtz, Rosen, Castle, Mittal, & Liu, 2008; R. A. Kane et al., 2003; Logsdon et al., 2002; Mozley et al., 1999).

We utilized an established self-report instrument, the annual Minnesota Quality of Life/Resident Satisfaction (QOL/RS) survey (Vital Research, LLC, 2007), to assess multiple dimensions of QOL at the resident level across the entire population of nursing facilities in the state of Minnesota. We investigated patterns of resident QOL based upon both resident CI and placement on an SCU. The aim of our study was to assess the influence of CI and placement on an SCU on eight specific QOL domains, whereas controlling for clinical factors and functional status.


Data and Sample

Data for analyses came from the 2007 Minnesota Nursing Home Resident Quality of Life and Consumer Satisfaction Survey conducted in the Spring 2007. This survey, sponsored by the state of Minnesota, is administered annually by Vital Research, an independent survey organization, through face-to-face interviews with a representative sample of NH residents. Earlier research has shown that items measuring QOL can be reliably completed for residents with mild to moderate CI (R. A. Kane et al., 2003). Thus, the survey was administered to all NH residents except the most severely cognitively impaired and acutely ill as indicated by a cognitive performance scale (CPS) score of 6 (about 10% of residents), residents in medical isolation, and residents who refused or had a guardian who refused participation in the study.

The survey was conducted with a probability sample of residents selected from each of the approximately 390 NHs in the state of Minnesota. The sample frame consisted of facility residents at the time of the survey. A list of all licensed nursing facilities in Minnesota was provided to Vital Research by the Minnesota Department of Human Services. Interview staff then contacted each facility by telephone to schedule interviews. Facility administration provided interview staff with a list of all current residents 2 weeks prior to their interview date.

Both short-stay (intended stay fewer than 30 days) and long-stay residents were sampled in proportion to their numbers in the facility. In facilities with fewer than 25 residents, interviews were attempted with each resident in the facility. In larger facilities, eligible residents were selected at random prior to the initiation of interviews. Each interviewer was provided with the randomly generated list of long-term residents in the facility that they could approach for an interview. Upon arrival in the facility, interviewers removed residents in isolation and residents whose guardian had declined participation from the list of potential respondents. Interviewers also randomly selected a predetermined number of short-stay residents (intended stay fewer than 30 days) from a current resident list in each facility. Interviews were conducted in the resident’s location of choice after the interviewer obtained resident permission to proceed. Of the 16,538 eligible residents, interviews were initiated with 14,381, a response rate of 87%. Completed interviews were obtained from 13,983 Minnesota nursing home residents (97% of initiated interviews were completed). The average number of completed interviews per facility was 36, with a range of 9–65 interviews within each facility (Vital Research, LLC, 2007). Additional information regarding survey methods can be found in the 2007 Vital Research final report to the Minnesota Department of Human Services.

The 2007 Minnesota Resident Satisfaction Survey contained 52 items addressing QOL as well as RS and mood. The QOL section of the survey contained 35 items with dichotomous yes/no responses adapted from the Nursing Home Quality of Life scale developed from a national study of NH residents conducted by R. A. Kane et al. (2003). Survey items covered QOL, RS, and mood. The 35 QOL items represented 10 dimensions based on the factor analysis by Kane and colleagues. For purposes of our study, we selected seven domains, where resident QOL scores differed significantly by CI in a bivariate analysis. The domains were comfort, meaningful activities, privacy, environmental adaptation, individuality, autonomy, and meaningful relationships. Domains excluded from the analysis were dignity, food enjoyment, and security. In addition, we constructed a mood scale representing positive affect. It was constructed from three of the nine items on the survey measuring mood (adapted from Brod et al., 1999). We found through a factor analysis that the three items tapping positive affect were distinct from the other six items tapping negative affect. The three items were felt peaceful, felt happy, and interested in things during the last 2 weeks, and the response categories were never, rarely, sometimes, and often. The QOL domain scales were calculated as the percentage of items that were answered yes and ranged from 0 to 100. The mood scale was calculated as a sum of the items comprising the scale; it ranged from 0 to 9 (Cronbach’s alpha = .63)

Measures of resident cognitive status, unit placement, and covariates were taken from the MDS assessment closest to the date of the survey. The CI level was based on the CPS (Morris et al., 1994), which ranges from 0 (intact) to 6 (very severely impaired). The SCU placement variable came from item P.1.n (Alzheimer’s/Dementia SCU) on the MDS 2.0. Functional level was measured from the ADL long form (Morris, Fries, & Morris, 1999) ranging from 0 to 28. Other covariates consisted of clinical conditions and demographic information. We selected covariates based upon prior research into the psychological status of NH residents as well as empirical analysis of the QOL data, that is, those variables found to be statistically significant in a multiple regression analysis of one or more QOL domains. They fell broadly into areas of mental health diagnoses (depression, schizophrenia, anxiety, and bipolar disorder), physical functioning (ADL, continence, aphasia, and hemiplegia), and pain or related diagnoses (cancer and arthritis). Selected covariates are likely to be related to increased dementia. By including these variables in our multi-level models, we controlled statistically for their effects, attempting to identify the independent relationship between CI and QOL. However, it is a study limitation that we cannot completely rule out the effects of resident characteristics that may covary with increased CI and influence perceived QOL.

The sample for this analysis was 13,107 NH residents. We elected to exclude 786 residents from the full sample of 13,983 because they had CPS scores of 5 (severe CI) or 6 (very severe CI). Six hundred and fifty-five (6%) of sample members resided on SCU.

In order to identify the independent relationships between CI and SCU placement and the QOL measures in our survey, we tested parallel multiple regression models, where each QOL domain and the mood scale was regressed on CI level, SCU placement, and covariates. We relied on multilevel models with a random effect for facility-level variation. The facility random effect helped to account for clustering of residents within the same facility. All other variables in the model were treated as fixed effects.


Table 1 shows the QOL scores, CPS, and other sample characteristics overall and by unit type. The percentage agreement for the seven QOL domains was consistently high, ranging from 71.0 for meaningful activities to 84.4 for environment. The mean mood score was 7.0 (SD = 2.0). The CPS scores indicated that 18.6% of the sample was cognitively intact, 16.0% borderline impaired, 22.1% mildly impaired, 37.6% moderately impaired, and 5.7% moderately severely impaired. In the bivariate comparisons, residents on SCUs had significantly higher perceived QOL in the comfort, activity, environment, and autonomy domains; however, they had a lower mean mood score. SCU residents also had significantly higher CPS scores, greater ADL dependency, and greater incontinence. They had lower perceived pain.

Table 1.
Characteristics of Study Nursing Residents Overall and by Unit Type

Table 2 shows the QOL domain scores, mood score, and other characteristics by level of CI. There were significant differences by CI in all the QOL domain scores. Compared with the cognitively intact (CPS = 0), the cognitively impaired residents scored higher in the comfort domain but lower in all the other QOL domains and in mood score.

Table 2.
QOL and Resident Characteristics by Level of Cognitive Impairment

The multiple regression models for the QOL domains and mood are presented in Table 3. After adjusting for demographics, functional limitations, and disease status, level of CI remained associated with all eight QOL scales. As CI increased, resident QOL decreased in the domains of privacy, individuality, relationships, and mood. For the activities and autonomy scales, those residents who were cognitively intact (CPS = 0) had significantly higher QOL scores than those with even mild impairment. Residents with mild and moderate CI (CPS score of 2 or 3) had significantly higher comfort scores than residents who were either cognitively intact or more severely impaired. Conversely, perception of environmental adaptations was the only domain for which those with increased levels of CI reported increased levels of QOL. Moderately or moderately severely cognitively impaired (CPS = 3 or 4) residents had significantly higher scores in the environmental adaptations domain. The positive relationship between SCU residence and QOL domains remained significant after controlling for CI, ADL dependency, and other covariates likely to influence perceived QOL. Interestingly, residents on traditional units had significantly higher positive mood scores.

Table 3.
Regression Models of Cognitive Impairment, SCU Placement, Clinical Covariates, and QOL Domains


As we hypothesized, CI was significantly related to all the seven QOL domains and mood scores, even after controlling for covariates likely to be associated with both CI and QOL. Residents with more severe CI reported higher QOL in the domains of comfort and environment and lower QOL in activities, individuality, privacy and meaningful relationships, and the mood scale. The Minnesota NH Resident Satisfaction Survey (Vital Research, LLC, 2007) is unique in that it directly measures NH resident perceptions of their own life quality. Because previous research has indicated that cognitive decline often precipitates declines in QOL, the finding that CI was associated with lower QOL in many of the domains was not unexpected. However, the positive relationship between CI and resident perception of comfort and environmental adaptation was surprising. Perhaps, items measuring comfort and environmental adaptations are tapping into the physical components of QOL and aligning most clearly with the current QIs and regulatory priorities (health conditions, level of ADL function, and nursing services). The other dimensions relate mainly to social (activities, privacy, and meaningful relationships) or psychological (individuality and mood) components of QOL, areas that are complex, highly individual in nature, and challenging to address within the limitations of institutional structures. The more CI alters social relationships, self-concept, and emotion the greater its potential impact on social and psychological domains. In any case, our findings indicate that QOL is a multifaceted concept that requires investigation through the measurement of multiple domains and that the relationship between QOL and CI is complex.

Our study has implications for the assessment and public reporting of facility QOL scores. For the majority of QOL domains, facilities admitting more CI residents run the risk of lowering their mean QOL scores. This would suggest the need to adjust for CI and other relevant covariates when estimating facility QOL. The Minnesota QOL Report Card Scores, which are published each year, have an adjustment for CI. In reports prepared for Minnesota nursing facilities, facilities are informed of their observed (unadjusted) and adjusted scores. Facilities focusing on QOL in the Minnesota NH pay for performance system can rely on the adjusted scores so as not to penalize providers admitting CI residents. There is no adjustment for SCU status. Such an adjustment could bias scores against providers who had effective dementia SCUs that improved their QOL scores. Interestingly, updates to MDS 3.0 encourage resident interviews for data collection, especially in regards to domains that are highly pertinent to QOL, such as resident mood, in an effort to more accurately assess resident QOL (Center for Medicare and Medicaid Services, 2011). Nonetheless, MDS 3.0 lacks specific QOL items representing the range of domains that are in the Minnesota Resident QOL survey.

The study also points to QOL dimensions—activities, individuality, privacy and meaningful relationships, and autonomy—that are of particular salience to CI residents and their families and could be the focus of facility quality improvement efforts. Facilities with successful SCUs may serve as models for quality improvement. The specialized physical and social environments of the SCU are meant to address the needs of residents with cognitive or behavioral difficulties (Gruneir et al., 2008; Holmes et al., 1990). Examples of environmental modifications found on many SCUs that could potentially increase resident QOL include specialized staff training, noise reduction programs, frequent use of private rooms, smaller unit sizes, increased availability of natural light, and flexible resident routines (Day, Carreon, & Stump, 2000; Holmes et al., 1990).

The aim of our analysis was to investigate the relationship between CI and QOL among nursing residents residing on both conventional and SCU. Our findings provide insight into the complex nature of QOL within nursing facilities as well as the influence of placement on a specialized dementia unit. Additional research is needed to further investigate our finding that residents with increased levels of CI reported higher QOL in the domains of comfort and environmental modification yet lower QOL in the other five domains. Though the Minnesota Resident Satisfaction Survey is unique in that it asks residents directly to report perceptions of their environment, more in-depth qualitative methodology may be required to assess the positive relationship between CI and some QOL domains. Additionally, though our findings demonstrate a relationship between SCU placement and resident QOL, it is yet unclear what specific modifications found on SCU have the strongest influence on resident QOL. Further research is needed to assess the effect of environmental modifications on the QOL of those residing on specialized units. Organizational factors such as staffing, ownership type, and leadership style may have considerable influence on resident QOL. However, inclusion of these factors would have significantly expanded the scope of our study. Future research should expand upon our findings to address the influence of organizational characteristics on QOL.

Current NH QIs do not specifically address the needs of residents with CI, limiting their applicability to the decisions of family caregivers regarding NH quality and selection. Our findings have the potential to inform the development of dementia-specific QMs that better represent the experiences of NH residents with and without CI as well as for use by family caregivers, public reporting systems, and private NH quality initiatives.


This work was supported by the Alzheimer ’ s Association Investigator Initiated Research Grant Program (IIRG-07-59504) and was supported in part by P30AG024967 from the National Institute on Aging.


  • Andersen CK, Wittrup-Jensen KU, Lolk A, Andersen K, Kragh-Sorensen P. Ability to perform activities of daily living is the main factor affecting quality of life in patients with dementia. Health and Quality of Life Outcomes. 2004;2:52–59. doi:10.1186/1477-7525-2-52. [PMC free article] [PubMed]
  • Arling G, Kane RL, Lewis T, Mueller C. Further development of nursing home quality indicators. The Gerontologist. 2005;45:147–156. doi:10.1093/geront/45.2.147. [PubMed]
  • Brod M, Stewart AL, Sands L, Walton P. Conceptualization and measurement of quality of life in dementia: The dementia quality of life instrument (DQoL) The Gerontologist. 1999;39:25–35. doi:10.1093/geront/39.1.25. [PubMed]
  • Castle NC, Ferguson JC. What is nursing home quality and how is it measured? The Gerontologist. 2010;50:426–442. doi:10.1093/geront/gnq052. [PMC free article] [PubMed]
  • Center for Medicare and Medicaid Services. MDS 3.0 for nursing home and swing bed providers. 2011 Retrieved November 16, 2011, from
  • Day K, Carreon D, Stump C. The therapeutic design of environments for people with dementia: A review of the empirical research. The Gerontologist. 2000;40:397–414. doi:1093/geront/40.4.397. [PubMed]
  • Degenholtz HB, Kane RA, Kane RL, Bershadsky B, King KC. Predicting nursing facility residents’ quality of life using external indicators. Health Services Research. 2006;41:335–357. doi:10.1111/j.1475-6773.2005.00494.x. [PMC free article] [PubMed]
  • Degenholtz HB, Rosen J, Castle N, Mittal V, Liu D. The association between changes in health status and nursing home resident quality of life. The Gerontologist. 2008;48:584–592. doi:10.1093/geront/48.5.584. [PubMed]
  • Drageset J, Nygaard HA, Eide GE, Bondevik M, Nortvedt MW, Natvig GK. Sense of coherence as a resource in relation to health-related quality of life among mentally intact nursing home residents—A questionnaire study. Health and Quality of Life Outcomes. 2008;6:85–93. doi.10.1186/1477-7525-6-85. [PMC free article] [PubMed]
  • Gruneir A, Lapane KL, Miller SC, Mor V. Are special care units really special? A new look at an old question. Journal of the American Geriatrics Society. 2008;56:199–205. doi:10.1111/j.1532.5415.2007.01559.x. [PubMed]
  • Hoe J, Hancock G, Livingston G, Woods B, Challis D, Orrell M. Changes in the quality of life of people with dementia living in care homes. Alzheimer Disease and Associated Disorders. 2009;23:285–290. doi:10.1097/WAD.0b013e318194fc1e. [PMC free article] [PubMed]
  • Holmes D, Teresi J, Weiner A, Monaco C, Ronch J, Vickers R. Impacts associated with special care units in long-term care facilities. The Gerontologist. 1990;30:178–183. doi:10.1093/geront/30.2.178. [PubMed]
  • Kane RA. Long-term care and a good quality of life: Bringing them closer together. The Gerontologist. 2001;41:293–304. doi:10.1093/geront/41.3.293. [PubMed]
  • Kane RA, Kling KC, Bershadsky B, Kane RL, Giles K, Degenholtz HB, et al. Quality of life measures for nursing home residents. Journal of Gerontology: Biolological Sciences and Medical Sciences. 2003;58A:240–248. doi:10.1093/Gerona/58.3.M240. [PubMed]
  • Kane RL, Bershadsky B, Kane RA, Degneholtz HH, Liu J, Giles K, et al. Using resident reports of quality of life to distinguish among nursing homes. The Gerontologist. 2004;44:624–632. doi:10.1093/geront/44.5.624. [PubMed]
  • Logsdon RG, Gibbons LE, McCurry SM, Teri L. Assessing quality of life in older adults with cognitive impairment. Psychosomatic Medicine. 2002;64:510–519. doi: 0033-3174/02/6403/0510. [PubMed]
  • Lyketsos CG, Gonzales-Salvador T, Chin JJ, Baker A, Black B, Rabins P. A follow-up study of change in quality of life among persons with dementia residing in a long-term care facility. International Journal of Geriatric Psychiatry. 2003;18:275–281. doi:10.1002/gps.796. [PubMed]
  • Maslow K, Heck E. Dementia care and quality of life in assisted living and nursing homes: Perspectives of the Alzheimer’s association. The Gerontologist. 2005;45:8–10. doi:10.1093/geront/45.suppl_1.133. [PubMed]
  • Moore K, Delaney JA, Dixon MR. Using indices of happiness to examine the influence of environmental enhancements for nursing home residents with Alzheimer's disease. Journal of Applied Behavior Analysis. 2007;40:541–544. doi:10.1901/jaba.2007.40-541. [PMC free article] [PubMed]
  • Morris JN, Fries BE, Mehr DR, Hawes C, Phillips C, Mor V, et al. MDS cognitive performance scale. Journal of Gerontology: Medical Sciences. 1994;49:M174–M182. [PubMed]
  • Morris JN, Fries BE, Morris SA. Scaling ADL’s within the MDS. Journal of Gerontology: Medical Sciences. 1999;54A:M546–M553. doi:10.1093/geronj/49.4m174. [PubMed]
  • Mozley CG, Huxley P, Sutcliffe C, Bagley H, Burns A, Challis D, et al. Not knowing where I am doesn’t mean I don’t know what I like: Cognitive impairment and quality of life responses in elderly people. International Journal of Geriatric Psychiatry. 1999;14:776–783. doi:10.1002/(SICI)1099-1166(199909)14:9<776::AID-GPS13>3.0.CO;2-C. [PubMed]
  • National Quality Forum. National voluntary consensus standards for nursing home care: A consensus report. Washington, DC: Author; 2011.
  • Selwood A, Thorgrimsen L, Orrell M. Quality of life in dementia—A one-year follow-up study. International Journal of Geriatric Psychiatry. 2005;20:232–237. doi:10.1002/gps.1271. [PubMed]
  • Sloane PD, Zimmerman S, Williams CS, Reed PS, Gill KS, Preisser JS. Evaluating the quality of life of long-term care residents with dementia. The Gerontologist. 2005;45:37–49. doi:10.1093/geront/45.suppl_1.37. [PubMed]
  • Vital Research, LLC. Implementation of the 2007 Consumer Satisfaction and Quality of Life Survey in Minnesota Nursing Homes: Final Report to the Minnesota Department of Human Services. Los Angeles, CA: Author; 2007.
  • Zimmerman S, Sloane PD, Williams CS, Reed PS, Preisser JS, Eckert JK, et al. Dementia care and quality of life in assisted living and nursing homes. The Gerontologist. 2005;45:133–146. doi:10.1093/geront/45.suppl_1.133. [PubMed]

Articles from The Gerontologist are provided here courtesy of Oxford University Press