Long-Term Care Quality-of-Life Scale utility in community
Tracey McDonald PhD, MSc(Hons), BHA, Dip Ed, RN, RM |
Frances Russell BAppSc (Biomed), MPH
Faculty of Health Sciences, Australian Catholic
University, Sydney, New South Wales,
Tracey T.A. McDonald, Department of
Nursing, Midwifery & Paramedicine, Australian
Catholic University, PO Box 968, North
Sydney NSW 2059, Australia.
This study aimed to test the utility of the Long-Term Care Quality-of-Life assessment
scale within community home care contexts and to compare the scale against the
World Health Organization Quality-of-Life scale in terms of reliability and validity.
Both scales were administered concurrently to 109 older adults receiving home care.
Analysis revealed the Long-Term Care Quality-of-Life scale to have good test–retest
reliability, modest but acceptable internal consistency, and pairwise comparison
between the Long-Term Care Quality-of-Life and World Health Organization
Quality-of-Life scales' scores suggesting moderate-to-strong correlation of criterion
validity and comparability between scales. The results showed that the assessment
of individual perceptions of life quality within home care contexts can be monitored
and recorded, and that Long-Term Care Quality-of-Life scale monitoring in home and
residential care can identify opportunities for quality-of-life support and care conti-
nuity, even with transitions between care services and systems. The implications of
the present study lie in having access to a validated quality-of-life assessment scale
that can be used across care contexts to support evidence-based practice, continuity
of care, and acknowledgement of individual circumstances in services and care
community care, evidence-based practice, home care, long-term care, Long-Term Care
Quality-of-Life scale, quality-of-life assessment
General awareness of quality of life (QoL), a term first coined in the
early 20th century, has been of ongoing interest to service providers,
health professionals, patients, and their families since the 1960s
(Wood-Dauphinee, 1999). Researchers have refined the concept of
QoL and developed theoretical models to explain how individual mea-
sures, with methodologic rigor and practical applications, can fit within
care services’contexts (Henchoz et al., 2017). Borowiak and Kostka
(2004) note that policies and programs are increasingly focused on
finding ways to improve life quality, rather than just extending the
length of life. The increasing likelihood of an older person moving
between services to obtain care and support means that reliable tools
need to be available for the consistent assessment of their reactions
to their surroundings across all care contexts. Stakeholders also have
an interest in ensuring that government-funding subsidies are used
appropriately; therefore, most national funding systems include regu-
latory frameworks that assess clinical care quality, and more recently,
report on patient experiences of life quality because of where they
are and the services they receive.
The Long-Term Care QoL (LTC-QoL) scale was developed, tested,
and published to provide a life quality assessment suitable for people
Received: 19 May 2018 Revised: 10 May 2019 Accepted: 19 May 2019
494 © 2019 John Wiley & Sons Australia, Ltd Nurs Health Sci. 2019;21:494–500.wileyonlinelibrary.com/journal/nhs
living in residential care in Australia (McDonald, 2014). During its
development, the LTC-QoL scale underwent many iterations based on
input from clinicians and managers using the scale. All were closely
associated with the care of people with chronic comorbidities and dis-
abilities who were admitted for care, support, treatment, and protec-
tion. The scale provides clinicians and managers with individualized
information and reliable evidence to inform care planning, resource
allocation, and quality benchmarking of QoL support interventions
(McDonald & Shaw, 2019).
Since the release in 2006 of the LTC-QoL scale within Australia's
residential aged care sector, voluntary feedback from clinicians and
managers is that the scale provides a unique diagnostic opportunity
related to the integrity and strength of the five life-quality pillars
described in the scale: (i) social connection and activity; (ii) acting for
ourselves; (iii) supportive relationships; (iv) taking a positive outlook
on life; and (v) feeling safe and secure (McDonald, 2016). The LTC-
QoL monitors nine factors that can be managed to help the person
improve their level of contentment (Figure 1). As such, the LTC-QoL
scale is unique in delivering information to nurses and others who can
intervene to improve QoL for people with diverse care needs. Ettema,
Droes, de Lange, Mellenbergh, and Ribbe (2005) reported that many
QoL tools lose relevance in the presence of dementia; however, the
LTC-QoL scale was found to be valid, reliable, and reproducible,
irrespective of the dementia status of the older person (McDonald,
2014), and under strict conditions, proxy reporting was also valid.
The current study was prompted by enquiries from LTC-QoL scale
users as to whether they could also use the scale within community
home care environments to monitor patients' reactions to transition
1.1 |Literature review
Most older Australians receive care in community settings and never
need residential care (Kendig, Browning, Pedlow, Wells, & Thomas,
2010). The Australian Government is responsible for “full funding, pol-
icy, management and delivery for a consistent and unified aged care
system covering basic home care through to residential care.”(Council
of Australian Governments, 2011, p. 53). The National Health Reform
Agreement also states that national and state governments share
“responsibility for providing continuity of care across health, aged care
and disability services to ensure smooth client transitions”(p. 54). The
trend toward home care is occurring internationally and it is expected
FIGURE 1 Long-Term Care Quality-of-Life scale
MCDONALD AND RUSSELL 495
that government spending will decrease with the movement of
patients from institutional to community/home care (Buttke, Cooke,
Abrahamson, Shippee, & Davila, 2018). Research supporting this trend
includes simulation models of patient flows within long-term care net-
works (Keno, 2017), as well as a focus on safety and care outcomes
for people funding their own community care (Kane, Davila, Shippee, &
Abrahamson, 2016). However, despite this policy direction, research
on monitoring the QoL experiences of people transitioning between
home care and government-subsidized residential care has been
Historically, researchers have used many different theoretical
frameworks and processes to examine QoL and have produced a
diversity of definitions and specialist perspectives. Unfortunately, this
range of approaches has delayed the operationalization of QoL as a
factor that can be identified and managed (Clark, Tucke, & Whitlatch,
2008; Felce & Perry, 1995). The approach we have taken centralizes a
person's self-perceived life quality as revealed through their reactions
to interventions delivered in accordance with their location and cir-
cumstances. The home care context is influenced by both functional
and existential variables. Life quality could depend upon such ele-
ments as dependency levels and cultural expectations of the person
and their family, the attitudes they hold toward life and aging, and
whether they are lonely.
International research into the influence of disease and disability
on life quality as well as economic analyses of care approaches has
produced a substantial body of knowledge from various perspectives
(Bulamu, Kaambwa, & Ratcliffe, 2015; Buttke et al., 2018; Castro,
Driusso, & Oishi, 2014; Lucas-Carrasco, 2012). It is generally accepted
that a person's ability to access home care should also be assessed.
Therapeutic strategies around QoL for older adults ought also to
include multi-disciplinary geriatric and psychosocial interventions
(Fassino et al., 2002). Assessments that link QoL with particular ill-
nesses are known as Health-Related QoL (HR-QoL) scales, and some
are used to calculate disease burden (Muldoon, Barger, Flory, &
Manuck, 1998). Most HR-QoL tools approach QoL as a phenomenon
that aligns with changes in physical and mental capacity because of
health changes. Such alignments do not always occur as expected; for
instance, the disability paradox described by Albrecht & Devlieger,
1999. HR-QoL tools are not necessarily appropriate for older adults
living with the functional decline of normal aging or even stabilized
chronic conditions. Kamitani et al. (2017) found that many existing
HR-QoL tools are inappropriate for people receiving home care,
because they live with many comorbid conditions that affect activities
of daily living and opportunities to socialize.
Outlook on life is important therefore, if a person's views of life
quality are assumed by others to be linked to their functional abilities,
it might accidentally trivialize the person's expectations of life and
undermine their self-determination and resilience. Castro et al. (2014)
reported that while changes in health due to aging can affect QoL, it
is how the older person responds to the aging process, rather than
their impairment, that is crucial when assessing QoL. Individually per-
ceived QoL focuses on how people view their own life quality, espe-
cially if facing personal challenges (Levasseur, Tribble, & Desrosiers,
2009). Therefore, if the assessment is to fully acknowledge a patient's
personal issues and lifestyle situations, their views about life and life
quality must be assessed using a reliable and appropriate scale.
A widely accepted approach to testing the reliability of a scale is
to compare it with another established scale (Von Steinbach,
Lischetzke, Gurny, & Eid, 2006). For comparison, we needed another
scale that centralizes a person's reactions to their situation and
remains valid across care levels and location boundaries. As no similar
scale could be found, we searched for one with characteristics in com-
mon with the LTC-QoL.
In 2006, The World Health Organization developed a survey to
assess generic life quality (WHOQOL-BREF) to “support epidemiologi-
cal research, clinical trials and for use in clinical treatment contexts”
(Skevington, Lofty, & O'Connell, 2004, p. 299). The WHOQOL-BREF
prioritizes the views of individuals about their circumstances and their
self-perceived health status. We selected the WHOQOL-BREF as a
validated scale against which we could test the LTC-QoL's robustness
within the community home care context. Prior to commencement of
concurrent testing of both scales, nurses employed in two community
home care contexts attended a 90 minute group training on the use
of both scales. Following data collection, the group met again to dis-
cuss any issues they wished to raise about the scales and the project.
1.2 |Study aims
The aims of the present study were to: (i) test the utility and reliability
of the LTC-QoL assessment scare within the community home care
context; and (ii) compare the performance of the LTC-QoL with the
WHOQOL-BREF in home care contexts.
The study incorporated two quantitative measures: (i) psychometric
validation of the LTC-QoL for community home care; and
(ii) comparison of LTC-QoL results with WHOQOL-BREF validity and
2.1 |Participants and setting
A priori determination of the sample size required to support statisti-
cal analysis was estimated to be 10 participants for each of the nine
questions in the LTC-QoL scale (Anthoine, Moret, Regnault, Sbille, &
Hardouin, 2014); that is, 90 participants each undergoing two concur-
rent assessments (LTC-QoL and WHOQOL-BREF) during two home
visits with the same nurse. Older adults approved to receive the home
care subsidy provided via the Australian Government Aged Care Act
1997 and admitted for home care were eligible to participate. To
maintain consistency with earlier validation of the LTC-QoL in resi-
dential aged care, no clients were excluded. Two metropolitan service
providers in Australia approved the study and allowed the researcher
access to clients and staff ( Table 1).
496 MCDONALD AND RUSSELL
2.2 |Ethical considerations
Ethics approval was granted by the home care service providers and
University Human Research Ethics Committee (HREC) (no. 2013
257N). The HREC-approved protocol was completed in December
2016. Formal consent was received from all participants. All recorded
data were de-identified and coded, and the results aggregated to fur-
ther protect the privacy of participants. No case could be identified by
location. Permission to use the WHOQOL-BREF was received from
World Health Organization Health Statistics and Health Information
2.3 |Data collection
The LTC-QoL and WHOQOL-BREF scales were used for each con-
senting client, collected by the visiting nurse during a scheduled home
visit, and checked for completeness by the supervising nurse. Both
assessments were repeated after 12 weeks for consistency with the
residential care protocol for LTC-QoL scale usage. All pairwise data
were collated, coded, deidentified, and combined before psychometric
analysis and comparison of scores.
2.4 |Data analysis approach: Testing for reliability,
validity, and sensitivity
Reliability of the LTC-QoL scale in home care contexts was assessed
using test–retest reliability and internal consistency measures. Test–
retest reliability is a measure of the stability of scores over time when
no change is expected in the concept of interest. A one way random-
effects model was used for inferences concerning P-value. The Bland–
Altman test (Bland & Altman, 1986) looked at the distribution of
differences in scores. It was assumed that differences were normally
distributed and that both the original test and the retest were from
the same distribution. Pairwise correlations were used to determine
whether any differences between the two tests were significant.
Internal consistency is a measure of the extent to which scale items
measure the same concept. Internal consistency was measured using
Cronbach's alpha (Cronbach, 1951; McDowell & Newell, 1987; Nun-
nally & Bernstien, 1994), inter-item correlations, and reliability
Validity was assessed using criterion validity; that is, the extent
to which the LTC-QoL scores related to an established scale for a
similar concept (in this case the WHOQOL-BREF scale). Pairwise
correlations between the total scores of the WHOQOL-BREF and
the LTC-QoL scales were produced. A sensitivity analysis was also
conducted by removing any questions that had poor test–retest
reliability. All reliability and validity outcomes were reproduced in
this dataset. Values of P< .05 were considered statistically signifi-
cant. All analyses were conducted using Stata MP for Mac (ver-
In total, 109 (43.6%) agreed to participate and were provided with
information and assurances of privacy and confidentiality. Participants
were assessed using the LTC-QoL and WHOQOL-BREF scales. In
terms of sex, 70.6% were female and 29.4% were males. The mean
age was 81 years (Table 1).
TABLE 1 Participant demographics
1 (N = 77)
2 (N = 32)
(N = 109)
Age, years, mean
79.6 (9.0) 86.6 (7.5) 81.6 (9.2)
Female, n(%) 59 (76.6%) 18 (56.3%) 77 (70.6%)
Australian 31 (40.3%) –– 31 (28.4%)
English 9 (11.7%) –– 9 (8.3%)
Other 30 (39.0%) –– 30 (27.5%)
Missing 7 (9.1%) 32 (100%) 39 (35.8%)
Dementia, n(%) 1 (1.3%) 6 (18.8%) 7 (6.4%)
SD = standard deviation.
TABLE 2 Test–retest reliability of the
Long-Term Care Quality-of-Life scale in
community care setting
Question Correlation Mean difference 95% CI Cases lying within 95% CI (%)
1 .163 .037 −1.402, 1.475 103/109 (94.5)
2 .901 −.009 −1.055, 1.037 104/107 (97.2)
3 .921 −.028 −1.067, 1.012 105/108 (97.2)
4 .887 −.055 −.991, .881 93/109 (85.3)
5 .892 −.064 −1.056, .927 103/109 (94.5)
6 .853 −.046 −1.417, 1.325 105/109 (96.3)
7 .865 −.102 −1.085, .882 102/108 (94.4)
8 .814 −.167 −1.405, 1.071 105/108 (97.2)
9 .900 −.101 −.959, .757 91/109 (83.4)
CI = confidence interval.
MCDONALD AND RUSSELL 497
3.1.1 |Test–retest reliability
Good correlation (>.80) was found between the first and second tests
for all but the first LTC-QoL scale question: “Participated in social
activities”(Table 2). The mean difference in initial and subsequent
tests was not significantly different from zero for any case, suggesting
that knowledge gained from doing the first assessment did not affect
answers for the second assessment (Bland & Altman, 1986).
3.1.2 |Internal consistency
Modest but acceptable reliability (Cronbach's alpha .76) was observed
for the overall scale. Compared to other items on the scale, question
2“Participated in self-care activities”performed less well, with item-
retest correlations being somewhat lower. However, removal of ques-
tion 2 did not improve the overall alpha significantly, so it was
retained by users as a guide to clinical follow up. Inter-item correla-
tions were low (≤.3), suggesting that the scale has no underlying cor-
related dimensions in this context (Table 3).
Pairwise correlation between the LTC-QoL and WHOQOL-BREF
scale total scores was .59 (P< .001), indicating moderate-to-strong
correlation and psychometric comparability between the two scales;
that is, the two scales delivered similarly reliable scores for the same
participant with the same assessor on both the test and retest
3.3 |Sensitivity analysis
We repeated our analysis removing question 1 to see if the assump-
tion of less relevance held true; however, internal consistency
(Cronbach's α.72) and criterion validity (pairwise correlation .55,
P< .0001) were not altered; therefore, the question was retained.
The overall purpose of the present study was to see if the LTC-QoL
scale could be used in home care contexts and be available to follow
the person from home to residential care or vice versa, providing a
consistent monitoring of life quality factors. Our results for commu-
nity home care contexts indicate that the LTC-QoL scale has modest
but acceptable reliability (Nunnally & Bernstien, 1994), although lower
than that reported in the original residential care validation analysis
(McDonald, 2014). Test–retest reliability for the LTC-QoL scale
showed strong correlations between initial and subsequent testing for
all questions, except the one on social activities. This was not an unex-
pected result, as opportunities for social activity differ in different
Home care environments have similarities with residential living,
but with some notable differences (Hwang, Liang, Chiu, & Lin, 2003).
In a study of hospital outpatients, home-dwelling patients were con-
cerned about recent life events, housing, financial status, and social
isolation (Bilotta et al., 2010). While recovering from acute illnesses,
TABLE 3 Internal consistency of the Long-Term Care Quality-of-Life scale (Cronbach's α)
Question Observations Sign Item-test correlation Item-retest correlation Inter-item correlation Alpha
1 109 + .68 .56 .25 .72
2 108 + .43 .25 .30 .77
3 109 + .50 .34 .28 .76
4 109 + .58 .43 .27 .75
5 109 + .56 .41 .27 .75
6 109 + .72 .61 .24 .72
7 109 + .61 .47 .26 .74
8 108 + .60 .46 .26 .74
9 109 + .61 .47 .26 .74
Total .27 .76
FIGURE 2 Correlation between total scores of LTC-QoL and
WHOQoL- BREF scale. Pairwise correlation: .59 (P<.001)
498 MCDONALD AND RUSSELL
participants were mostly concerned about their ability to live at home
with chronic health issues (Kane et al., 2016). Care and support deliv-
ered in a person's home requires engagement with external health
and other home services at pre-arranged times, leaving most of the
day relatively unstructured compared with residential living.
In the current study, home-dwelling patients showed very similar
demographic characteristics to the cohort that participated in the
2014 validation study. To preserve consistency with the earlier valida-
tion study, assessors followed cues devised for question 1 based on
social participation opportunities in residential living. It was antici-
pated that differences in daily routines, self-determination, and types
of assistance available at home would affect scoring among
community-dwelling participants. Following the study, nurses involved
in the data collection developed an alternative set of behavioral cues
for question1 that more accurately describe social activities at home.
Their feedback was that question 1 provides a useful guide to QoL
interventions and they want it retained in the scale.
In terms of comparison of results between the two scales, partici-
pants' responses corresponded for questions on similar topics in both
surveys. This alignment, confirmed by pairwise comparison, estab-
lishes the LTC-QoL scale as equally reliable as the WHOQOL-BREF
scale, despite some differences in questions. The WHOQOL-BREF
scale is psychometrically suitable for assessing people undergoing
time-limited treatments and tests. Differences within home care for
an older cohort of people living with communication and self-care lim-
itations limit the specificity of the scale, despite it being regarded as a
standard against which other scales might be compared to establish
validity (Von Steinbach et al., 2006).
Survey burden is an important consideration for all involved in
monitoring care services. For the older client, lengthy surveys asking
inappropriate questions can be tedious. While generic satisfaction sur-
veys might satisfy a broader management purpose (Gabriel & Bowling,
2004; Felce & Perry, 1995), surveys containing items that many older
people regard as irrelevant increase survey time. Hwang et al. (2003)
reports that the WHOQOL-BREF takes 11 minute on average to self-
complete and that questions relating to sexual activity and work
capacity are frequently left unanswered. Wood-Dauphinee (1999)
reported that people “do not tolerate long questionnaires, especially if
they are repeated at regular intervals”(p. 358). The ability to express
one's views is also an issue for those in long-term care, where their
input might be limited by cognitive decline and dementia-causing ill-
nesses. Following the current study, verbal feedback from the nurses
who administered both scales was that the LTC-QoL scale was much
faster and more easily completed than the WHOQOL-BREF scale.
4.1 |Study limitations
A convenience sample that might not be representative of the total
population of older Australians receiving home care was selected
because options were limited to organizations that had implemented
LTC-QoL scale assessments and home care nurses being willing to
undertake a considerable amount of work associated with collecting
data using concurrent scales over 6 months. Sample attrition is also a
consideration for this age cohort, making it impossible to retest partic-
ipants following the data-collection period. As the focus of the study
was the testing of the LTC-QoL scale within a new context, rather
than replication of the original psychometric validation of the scale,
some aspects of the previous validation were not repeated.
Now that the LTC-QoL scale can be reliably used in residential and
community aged care, it supports the continuity of assessment and
QoL intervention planning for clients moving from one service to
another or moving between higher or lower levels of long-term
care across contexts. The availability of a single scale that can be
used across service settings supports evidence-based care and services.
The LTC-QoL scale enables services to monitor and assist older adults
transitioning between services as they adapt to changing circumstances.
Theimplicationsofthisresearchliein clinician and manager access to a
QoL scale that legitimizes interventions to strengthen elements of QoL
and maintain those that are robust. The results can be used to inform
management and clinical practice, and to benchmark care interventions
geared to enhancing life quality.
The LTC-QoL scale has acceptable test–retest reliability, good internal
consistency, and criterion validity for use with older people living in a
community home care setting. It is reliable for use across residential
and community-based aged care. Good correlation between our scale
and the WHOQOL-BREF scale establishes validity. Our results show
that the continuity of assessment and understanding of individual per-
ceptions of their own life quality within context can be monitored and
recorded. The evidence gathered can be used to identify aspects of cli-
ent reactions that could benefit from supportive interventions as they
transition through different levels of the care system.
Study design: T.McD.
Data collection: T.McD. and F.R.
Data analysis: T.McD. and F.R.
Manuscript writing and revisions for important intellectual content:
The authors thank Belinda Butcher and Jane Hutchinson for statistical
advice and assistance, and the residents, staff, and managers of
ANZAC Village and Calvary Silver Circle Community Care, Australia.
Tracey McDonald https://orcid.org/0000-0002-2470-733X
MCDONALD AND RUSSELL 499
Albrecht, G. L., & Devlieger, P. J. (1999). The disability paradox: High qual-
ity of life against all odds. Social Science in Medicine,48(8), 977–988.
Anthoine, E., Moret, L., Regnault, A., Sbille, V., & Hardouin, J. (2014). Sam-
ple size used to validate a scale. Health and Quality of Life Outcomes,
Bilotta, C., Bowling, A., Case, A., Nicolini, P., Mauri, S., Castelli, M., &
Vergani, C. (2010). Dimensions and correlates of quality of life
according to frailty status. Health Quality of Life Outcomes,8
Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing
agreement between two methods of clinical measurement. Lancet,1
Borowiak, E., & Kostka, T. (2004). Predictors of quality of life in older peo-
ple living at home and in institutions. Aging (Milano),16(3), 212–220.
Bulamu, N. B., Kaambwa, B., & Ratcliffe, J. A. (2015). Systematic review of
instruments for measuring outcomes in economic evaluation within
aged care. Health Quality Life Outcomes,13(179), 1–23.
Buttke, D., Cooke, V., Abrahamson, K., Shippee, T., & Davila, H. (2018).
Statewide model for assisting nursing home residents to transition
successfully to the community. Geriatrics,3(2), 1–27.
Castro, P. C., Driusso, P., & Oishi, J. (2014). Convergent validity between
SF-36 and WHOQOL-BREF in older adults. Rev Saúde Pública,48(1),
Clark, P. A., Tucke, S. S., & Whitlatch, C. J. (2008). Consistency of informa-
tion from persons with dementia: An analysis of differences by ques-
tion type. Dementia,41(3), 293–304. London, Sage.
Council of Australian Governments. (2011). National Health Reform Agree-
ment. Retrieved from http://www.federalfinancialrelations.gov.au/
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests.
Ettema, T. P., Droes, R. M., de Lange, J., Mellenbergh, G. J., & Ribbe, M. W.
(2005). A review of quality of life instruments used in dementia. Qual-
ity of Life Research,14, 675–686.
Fassino, S., Leombrunia, P., Daga, G. A., Brustolin, A., Rovera, G. G., &
Fabris, F. (2002). Quality of life in dependent older adults living at
home. Archives of Gerontology & Geriatrics,35(1), 9–20.
Felce, D., & Perry, J. (1995). Quality of life: Its definition and measurement.
Research Developmental Disability,16(1), 51–74.
Gabriel, Z., & Bowling, A. (2004). Quality of life from the perspectives of
older people. Ageing & Society,24(5), 675–691.
Henchoz, Y., Botrugno, F., Cornaz, S., Büla, C., Charef, S., & Santos-
Eggimann, B. (2017). Determinants of quality of life in community-
dwelling older adults: Comparing three cut-offs on the excellent-to-
poor spectrum. Quality of Life Research,26(2), 283–289.
Hwang, H. F., Liang, W. M., Chiu, Y. N., & Lin, M. R. (2003). Suitability of
the WHOQOL-BREF for community-dwelling older people in Taiwan.
Age and Ageing,32(6), 593–600.
Kamitani, H., Umegaki, H., Okamoto, K., Kanda, S., Asai, A., Maeda, K., …
Kuzuya, M. (2017). Development and validation of a new quality of life
scale for patients receiving home-based medical care. Geriatrics & Ger-
ontology International,17, 440–448.
Kane, R. A., Davila, H., Shippee, T., & Abrahamson, K. (2016). Housing and
assisted living issues for non-medicaid nursing home residents
returning to the community. Seniors Housing & Care Journal,4(1),
Kendig, H., Browning, C., Pedlow, R., Wells, Y., & Thomas, S. (2010).
Health, social and lifestyle factors in entry to residential aged care: An
Australian longitudinal analysis. Age and Ageing,39, 342–349.
Keno, H. A. (2017). Patient flow modeling in the long-term care network.
Purdue University, Indiana, Proquest Number: 10257503 (doctoral
Levasseur, M., Tribble, D., & Desrosiers, J. (2009). Meaning of quality of
life for older adults: Importance of human functioning components.
Archives of Gerontology & Geriatrics,49(2), 91–100.
Lucas-Carrasco, R. (2012). Reliability and validity of the Spanish version of
the World Health Organization-Five Well-Being Index in elderly. Psy-
chiatry Clinical Neurosciences,66(6), 508–513.
McDonald, T. (2014). Measurement features of a long-term care quality of
life (LTC-QoL) assessment scale. Care Services Management,7(3),
McDonald, T. (2016). Supporting the pillars of life quality in long term care.
Journal of Religion, Spirituality & Aging,28(3), 149–167.
McDonald, T., & Shaw, D. (2019). Benchmarking life quality support inter-
ventions in long-term care using the Ltc-Qol system. Journal of Nursing
and Health Sciences,21(2), 239–244. https://doi.org/10.1111/nhs.
McDowell, I., & Newell, C. (1987). Measuring health: A guide to rating scales
and questionnaires. New York, NY: Oxford University Press.
Muldoon, M. F., Barger, S. D., Flory, J. D., & Manuck, S. B. (1998). What
are quality of life measurements measuring? British Medical Journal,
Nunnally, J. C., & Bernstien, I. H. (1994). Psychometric theory (3rd ed.).
New York, NY: McGraw-Hill.
Skevington, S. M., Lofty, M., & O'Connell, K. A. (2004). The World
Health Organization's WHOQOL-BREF quality of life assessment.
A report from the WHOQOL Group. Quality of Life Research,13(2),
The WHOQOL Group. (1998). Development of the World Health Organi-
zation WHOQOL-BREF Quality of Life Assessment. Psychological Med-
Von Steinbach, N., Lischetzke, T., Gurny, M., & Eid, M. (2006). Assessing
quality of life in older people: Psychometric properties of the
WHOQOL-BREF. European Journal of Ageing,3(2), 116–122.
Wood-Dauphinee, S. (1999). Assessing quality of life in clinical research.
Clinical Epidemiology,52(4), 355–363.
How to cite this article: McDonald T, Russell F. Long-Term
Care Quality-of-Life Scale utility in community home care.
Nurs Health Sci. 2019;21:494–500. https://doi.org/10.1111/
500 MCDONALD AND RUSSELL