2. 5 Clinica della Memoria, Department of Neurological Sciences,
University of Rome “Sapienza,” Rome, Italy
6 Department of Neurology, Philipps-University, Marburg,
Germany
7 The Research Institute for the Care of Older People (RICE),
The RICE Centre, Royal United Hospital, Bath, UK
8 Division of Neurogeriatrics, Department of Neurobiology,
Care Sciences and Society, Karolinska Institute, Stockholm,
Sweden
9 Parc Santari Sant Joan de Déu, CIBERSAM, Universitat de
Barcelona, Sant Boi de Llobregat, Barcelona, Spain
A B S T RA C T
Background: We aimed to obtain a better understanding of how
different aspects of patient functioning affect
key cost and caregiver outcomes in Alzheimer’s disease (AD).
Methods: Baseline data from a prospective observational study
of community-living AD patients (GERAS)
were used. Functioning was assessed using the Alzheimer’s
Disease Cooperative Study – Activities of Daily
Living Scale. Generalized linear models were conducted to
analyze the relationship between scores for total
activities of daily living (ADL), basic ADL (BADL),
instrumental ADL (IADL), ADL subdomains (confirmed
through factor analysis) and individual ADL questions, and total
societal costs, patient healthcare and social
care costs, total and supervision caregiver time, and caregiver
burden.
Results: Four distinct ADL subdomains were confirmed: basic
activities, domestic/household activities,
communication, and outside activities. Higher total societal
costs were associated with impairments in all
aspects of ADL, including all subdomains; patient costs were
3. associated with total ADL and BADL, and
basic activities subdomain scores. Both total and supervision
caregiver hours were associated with total ADL
and IADL scores, and domestic/household and outside activities
subdomain scores (greater hours associated
with greater functional impairments). There was no association
between caregiver burden and BADL or basic
activities subdomain scores. The relationship between total
ADL, IADL, and the outside activities subdomain
and outcomes differed between patients with mild and
moderate-to-severe AD.
Conclusions: Identification of ADL subdomains may lead to a
better understanding of the association between
patient function and costs and caregiver outcomes at different
stages of AD, in particular the outside activities
subdomain within mild AD.
Key words: activities of daily living (ADL), ADCS-ADL,
Alzheimer’s disease, caregiver burden, costs, function,
supervision time
Introduction
Functional status in patients with Alzheimer’s
disease (AD) is usually evaluated by a patient’s
ability to undertake activities of daily living (ADL).
A number of subjective and performance-based
questionnaires have been developed to assess ADL
Correspondence should be addressed to: Dr Catherine Reed,
PhD, Global
Health Outcomes, Eli Lilly and Company, Erl Wood Manor,
Sunninghill
Road, Windlesham, Surrey GU20 6PH, UK. Phone: + 44-1276-
483243; Fax:
4. + 44-1276-483192. Email: [email protected] Received 30 Sep
2014;
revision requested 30 Nov 2014; revised version received 14
May 2015;
accepted 28 Jul 2015. First published online 26 August 2015.
in patients with AD (Marshall et al., 2012).
Such questionnaires usually comprise a list of
common activities that a person would, under
normal circumstances, be expected to perform
without difficulty. ADL are divided into basic ADL
(BADL), which are related to standard self-care
tasks (e.g. eating, using the bathroom, and bathing),
and instrumental ADL (IADL), which may not
be necessary for fundamental functioning but
allow independent living (e.g. housework, financial
management, and correct use of medications).
Whereas BADL tend to become impaired in the
http://dx.doi.org/10.1017/S1041610215001349
mailto:[email protected]
248 C. Reed et al.
moderate-to-severe stages of AD, the more complex
IADL are more likely to start to decline in the
earlier stages of the disease (Marshall et al., 2012).
Given the wide variation in tasks usually classified
as IADL, it has been suggested that a more in-depth
analysis of these tasks and how they associate with
one another could improve the clinical applicability
of ADL assessments (Brown et al., 2011; Marshall
et al., 2012).
A number of studies in patients with AD,
5. using a variety of ADL questionnaires, have found
ADL to be associated with key cost and caregiver
outcomes. Greater impairment in ADL has been
identified as an important predictor of total societal
costs across different countries (Gustavsson et al.,
2011); caregiver burden (Germain et al., 2009;
Kim et al., 2012; Haro et al., 2014); and informal
caregiver time (Germain et al., 2009; Haro et al.,
2014). Informal caregiver time, which includes
time spent assisting with BADL and IADL, and
supervision time (i.e. time spent protecting the
patient from dangerous events), has been identified
as a major component of societal costs of care
in patients with AD (Gustavsson et al., 2011;
Wimo et al., 2013). In addition, increase in more
subjective measures of caregiver burden (e.g. the
Zarit Burden Interview [ZBI]) is associated with
a faster time to institutionalization and death in
AD patients (Brodaty et al., 1993; Balardy et al.,
2005). Therefore, there is a need to expand our
understanding of the different factors comprising
ADL, and how these influence or are associated
with different outcomes. Although studies usually
report total ADL, BADL, or IADL scores (as in the
aforementioned studies), there may be individual
factors or groups of factors of ADL driving different
cost and caregiver outcomes at different stages of
the disease. To date, however, we have not been
able to identify any studies that have investigated
this.
The Alzheimer’s Disease Cooperative Study –
Activities of Daily Living Scale (ADCS-ADL) is
an informant-based, disease-specific assessment of
functional ability that has been widely used in
clinical trials of mild-to-moderate AD (Galasko
6. et al., 2005). A recent factor analysis of this
questionnaire used baseline data from the PLASA
(PLAn de Soin et d’aide dans la maladie
d’Alzheimer) study, a prospective randomized trial
comparing usual care with a non-pharmacological
intervention in patients with AD (Nourhashemi
et al., 2010). Results suggested that ADCS-
ADL questions could be grouped into four
subdomains: basic activities, domestic/household
activities, communication and engagement with
the environment activities, and outside activities
(the latter reflecting an individual’s ability to
independently function outside the home; Kahle-
Wrobleski et al., 2014). The aim of the current
hypothesis-generating study was to obtain a better
understanding of how patient function impacts
societal costs and caregiver outcomes by examining
the association between these outcomes and scores
for total ADL, BADL, IADL, and the four ADL
subdomains (confirmed by factor analysis) and/or
individual ADL questions. The study used baseline
data from a prospective observational study of
community-living AD patients (GERAS).
Methods
Patient and caregiver data
Patient data were obtained from the GERAS
study, an 18-month prospective, multicenter,
observational study, being conducted in France (N
= 419), Germany (N = 552), and the United
Kingdom (N = 526), of the routine care of
community-living patients with AD. Participants
were aged �55 years, with a Mini-Mental
State Examination (MMSE) score of �26, and
7. diagnosed with probable AD (National Institute
of Neurological and Communicative Disorders,
and Stroke and Alzheimer’s Disease and Related
Disorders Association criteria; McKhann et al.,
1984). The study design and methods have
previously been described in detail (Wimo et al.,
2013). All patients had to have a primary caregiver
willing to participate in the study and to undertake
responsibility for the patient for �6 months of
the year. The primary caregiver was an informal
caregiver who, according to the family, normally
took most responsibility for the day-to-day decisions
and provision of home care for the patient. All
patients (or their legal representative) and caregivers
were required to provide written informed consent,
and the study was approved by ethical review boards
in each country following country regulations.
Patients were stratified according to disease severity
at baseline using MMSE criteria based on the
UK guidelines (as reported previously in Wimo
et al., 2013): “mild AD severity” (MMSE = 21−26
points); “moderate AD severity” (MMSE = 15−20
points); “moderately severe/severe AD severity”
(MMSE <15 points).
In addition to patient and caregiver socio-
demographic data, other assessments carried out
at baseline included patient cognitive function
assessed using the MMSE, and patient functional
ability assessed using the ADCS-ADL (Galasko
et al., 2005). Caregivers completed the ZBI, a widely
used instrument for measuring subjective caregiver
burden in AD (Zarit et al., 1980). Information
on caregiver time during the month before the
8. ADL factors and cost and caregiver outcomes in AD 249
baseline visit was collected using the Resource
Utilization in Dementia (RUD) instrument (Wimo
et al., 1998). The RUD collects information on
time spent on informal care (separated into the
hours spent assisting with BADL, IADL, and
supervision time) and information on lost working
days. We investigated caregiver supervision time as
well as total caregiver time, as supervision time was
identified as the largest component of caregiver time
at baseline in the GERAS cohort (Wimo et al.,
2013; Haro et al., 2014). Caregiver supervision
time has also been found to contribute to both
caregiver burden and costs (Leicht et al., 2011;
Wimo et al., 2013; Haro et al., 2014). Moreover,
supervision time will have less overlap with the
basic and instrumental factors of ADL than the
other two aspects of caregiver time (time spent on
BADL and IADL). Although total societal costs
provide a reflection of the patient plus caregiver-
related costs of caring for a patient with AD, patient
healthcare and social care costs were selected as an
outcome because of their relevance to the healthcare
provider.
Confirmatory factor analysis of the
ADCS-ADL
The ADCS-ADL is a 23-item (6 BADL; 17
IADL) inventory developed as a rater-administered
disease-specific questionnaire. It is widely used to
assess functional ability in clinical trials in AD, and
is completed on behalf of the patient by his/her
caregiver (Galasko et al., 1997; 2005). The caregiver
is first asked, whether the patient has attempted
9. each specific ADL during the past four weeks. If
the patient did attempt the ADL, the caregiver is
asked to rate the patient’s performance level based
on a set of performance descriptions. Scores for each
item and the overall score for the tool are calculated.
The range for the total ADCS-ADL score is 0 to 78.
Separate scores can be derived for BADL (0 to 22)
and IADL (0 to 56).
The baseline data of GERAS were used to
perform a confirmatory factor analysis (CFA) of the
previously mentioned factor analysis of the ADCS-
ADL conducted by Kahle-Wrobleski et al. (2014)
using baseline data from the PLASA study. Model
fit was assessed using the standardized root mean
square residual (SRMSR), the root mean square
error of approximation (RMSEA), and the Bentler
Comparative Fit Index (CFI). An acceptable fit was
determined by CFI >0.90 and RMSEA <0.10.
Generalized linear model analyses
Generalized linear models (GLMs) were used to
analyze the relationship between ADL scores (total
ADL, BADL, and IADL), scores for the ADL
subdomains confirmed through factor analysis, and
each of the following outcomes: total and caregiver
supervision time, total societal costs (defined as
patient healthcare and social care costs plus
caregiver informal care costs), patient healthcare
and social care costs (γ distribution with a log
link function), and the ZBI total score (normal
distribution with an identity link function). All
GLMs were run with country, patient age, MMSE
severity group, and caregiver relationship (spouse:
yes/no) as included factors. Model fit was assessed
10. through the Akaike Information Criterion (AIC)
and R2 statistics when adding ADL total score,
BADL and IADL scores, and the scores of the
confirmed subdomains. In addition, likelihood ratio
tests (LRTs) were performed on nested models
of the ADL factors to confirm the findings of
GLMs. If any of the ADL subdomains provided
an improved model fit to any of the outcomes,
we also looked at a model that included responses
to individual ADL questions. Full models for
GLMs are provided in Supplementary Table S1
(Table S1 is available as supplementary material
attached to the electronic version of this paper
at www.journals.cambridge.org/jid_IPG). To aid
interpretation of the coefficients from the GLM
γ distribution models (cost and caregiver time
outcomes), the percentage change in the mean cost
or mean number of caregiver hours per patient
for each unit change in the ADL variable is
reported; however, these are not adjusted for the
respective range in each domain or subdomain. To
aid interpretation of the coefficients from the GLM
normal distribution models (ZBI total score), the
change in ZBI score for each one-point change in
the ADL score being used is reported. In both cases
the percentage change associated with a one-point
change in ADL score was calculated as (exp(0 –
(exponential β-coefficient)) – 1) × 100.
As there are concerns about the ability of
ADCS-ADL to adequately capture functioning in
individuals with milder AD severity (Sacco et al.,
2012), we were interested in identifying factors of
ADL that may be particularly sensitive to change
in milder severity disease. Hence, for all five
outcomes the same GLMs described above were
11. run, including the following terms: country; patient
age; mild MMSE (yes/no); caregiver relationship;
ADL score; and a mild MMSE × ADL score
interaction term. The GLM models for the cost
outcomes included these terms: country; patient
age; number of patient co-morbidities; patient
experienced a fall; caregiver working for pay; mild
MMSE (yes/no); ADL score; and mild MMSE ×
ADL score interaction term.
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250 C. Reed et al.
Sensitivity analyses
Sensitivity analyses were conducted to test the
strength of individual questions identified from the
GLMs (e.g. would any of the other basic activities
questions substitute for the basic activities question
on bathing?).
Relationship between total ADL score and AD
severity
The relationship between total ADL score and
the MMSE baseline score was explored through
regression models, with ADL score as the
dependent variable and the MMSE score as the
independent variable. Similar models were run for
the two main domains (BADL and IADL) and the
subdomains confirmed through factor analysis, and
their relationship with MMSE score.
Missing data
Missing data were minimal (<1%) for all the
outcome measures (total and caregiver supervision
12. time, total societal costs, patient healthcare and
social care costs, and the ZBI total score). Sensitivity
analyses were conducted on the GLM models for
(1) total ADL and (2) BADL + IADL, where
missing data was only 2.4%. The results from
these models were consistent with the models
based on patients with no missing ADL items.
A sensitivity analysis was additionally conducted,
where patients with missing responses to specific
ADL questions were imputed. Three separate
analyses were performed: (1) missing question
responses were assumed to have a score of zero;
(2) missing question responses were assumed to
have the maximum score for that question; and
(3) a multiple imputation approach was used using
the Markov chain Monte Carlo methods. All three
sensitivity analyses were in agreement with the
primary CFA regarding the SRMSR, RMSEA,
and the Bentler CFI values. Hence, we conclude
that our findings are robust, and we assumed that
patients not included in the GLM models are
missing completely at random.
Statistical methods
Descriptive summary statistics are provided for the
baseline characteristics of patients and caregivers,
and of the outcomes of interest, overall and by
MMSE severity. Estimates (with 95% confidence
intervals) and p-values are presented for all GLM
analyses.
All analyses were performed using SAS version
9.2 (SAS Institute, Cary, NC, USA).
Results
13. The baseline characteristics of patients and
caregivers participating in the GERAS study across
all three countries have been reported in detail
(Wimo et al., 2013). Most patients participating in
GERAS were living in their own home with their
spouse as the main caregiver (Table 1). Patients
with more severe disease were less likely to be living
alone, and were more likely to be female and to have
a longer disease history.
Baseline data for all outcomes of interest – care-
giver burden (ZBI total score), total and caregiver
supervision hours, and cost outcomes (total societal
and patient healthcare and social care costs) –
increased with severity of the disease (Table 2).
Confirmatory factor analysis results
A CFA run on the overall GERAS data using
the factor pattern of the ADCS-ADL reported
by Kahle-Wrobleski et al. (2014) (which used
data from the PLASA study) suggested a good
fit with this analysis (model fit statistics for the
entire GERAS cohort were SRMSR = 0.049,
RMSEA = 0.060 and Bentler CFI = 0.92).
The CFA confirmed that ADL questions could
be grouped into the following four subdomains:
basic activities, domestic/household activities,
communication/engagement with the environment
activities, and outside activities (Supplementary
Table S2 and Supplementary Figure S1 are
available as supplementary material attached to the
electronic version of this paper at www.journals.
cambridge.org/jid_IPG). Similar “acceptable fits”
were seen between CFAs run using data from each
of the three MMSE severity groups and the factor
pattern generated by the PLASA analysis: mild
14. AD severity patients (SRMSR = 0.059; RMSEA
= 0.058; Bentler = 0.89); moderate AD severity
patients (SRMSR = 0.063; RMSEA = 0.055;
Bentler = 0.89); and moderately severe/severe AD
patients (SRMSR = 0.055; RMSEA = 0.060;
Bentler = 0.91). Based on the results from the
CFA, there was no evidence to suggest that the
subdomains identified from the PLASA study data
should not be considered when exploring the
relationship between ADL and outcome measures
in the GERAS patient population. Hence, the ADL
subdomains used in the GLM models were those
identified by the PLASA analysis.
GLM analyses results
Total societal costs was the only outcome found to
be associated with all ADL scores (total ADL,
BADL, and IADL) as well as all four confirmed
subdomains and some of the individual ADL
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ADL factors and cost and caregiver outcomes in AD 251
Table 1. Patient and caregiver characteristics at baseline
AD S E V E R I T Y
M O D E R A T E L Y O V E R A L L
C H A R A C T E R I S T I C M I L D M O D E R A T E S E V
E R E / S E V E R E p-V A L U E ∗ P O P U L A T I O N
...............................................................................................
...............................................................................................
15. ...............................................................................................
...............................
No. of patients 567 472 458 1,497
Age, years (mean [SD]) 77.3 (6.97) 77.8 (7.95) 77.6 (8.17) NS
77.6 (7.66)
Gender (% female) 47.8 57.2 61.1 p < 0.001 54.8
Time since diagnosis,
years (mean [SD])
1.7 (2.00) 2.1 (2.04) 3.1 (2.40) p < 0.001 2.2 (2.22)
MMSE (mean [95% CI]) 23.3 (23.2; 23.5) 17.9 (17.8; 18.1) 9.5
(9.1; 9.9) -a 17.4 (17.1; 17.7)
BADL (mean [95% CI])b 19.8 (19.6; 20.1) 18.3 (17.9; 18.6)
13.2 (12.7; 13.8) p < 0.001 17.3 (17.1; 17.6)
IADL (mean [95% CI])b 38.6 (37.6; 39.5) 29.9 (28.8; 31.1) 16.6
(15.5; 17.8) p < 0.001 29.2 (28.4; 29.9)
Total ADL (mean [95%
CI])b
58.5 (57.3; 59.6) 48.3 (46.9; 49.7) 30.0 (28.4; 31.6) p < 0.001
46.6 (45.6; 47.6)
Marital status,
married/cohabiting (%)
74.8 68.2 72.5 NS 72.0
Living in own home (%) p < 0.001
Alone 18.6 22.8 11.2 17.7
With spouse 75.3 68.8 73.1 72.6
With others 5.4 8.3 14.8 9.1
No. of caregivers 567 472 458 1,497
Age, years (mean [SD]) 68.1 (11.60) 66.7 (11.70) 67.0 (12.85)
16. NS 67.3 (12.03)
Gender (% female) 68.6 64.4 58.3 p < 0.05 64.1
Caregiver relationship (%) p < 0.05
Spouse 70.7 63.1 62.9 65.9
Child 23.5 28.8 29.8 27.1
Others 5.8 8.1 7.2 7.0
Notes: aNo statistical analysis performed.
bAssessed using the Alzheimer’s Disease Cooperative Study –
Activities of Daily Living Scale (ADCS-ADL).
∗ For comparison between AD severity groups (ANOVA for
continuous variables and Cochran–Mantel–Haenszel test for
categorical
variables).
“Mild” AD severity = MMSE 21–26 points; “moderate” AD
severity = MMSE 15–20 points; “moderately severe/severe” AD
severity =
MMSE < 15 points.
AD = Alzheimer’s disease; ADL = activities of daily living;
BADL = basic activities of daily living; CI = confidence
interval; IADL =
instrumental activities of daily living; NS = not significant (p �
0.05).
questions (Table 3). One-point lower ADL domain
and subdomain scores (signifying worse function)
were equivalent to higher total societal costs
(Table 3).
Patient healthcare and social care costs were
associated with total ADL and BADL but not IADL
scores, and with only the basic activities subdomain.
One-point lower total ADL, BADL, and basic
activities subdomain scores were associated with
higher costs.
17. Both total caregiver hours and caregiver supervision
hours were associated with total ADL and IADL
scores as well as the domestic/household and
outside activities subdomains. One-point lower
ADL scores were associated with higher total
caregiver hours and higher caregiver supervision
hours. In contrast to caregiver supervision hours,
total caregiver hours also demonstrated associations
with BADL and the communication/engagement
with the environment subdomain. Neither outcome
was significantly associated with the basic activities
subdomain.
Caregiver burden (ZBI total score) was associated
with total ADL and IADL scores and with the
domestic/household, communication and outside
activities subdomains: lower ADL scores resulted
in significantly higher ZBI scores (signifying a
worsening of caregiver burden). There was no
association between this outcome and the BADL
score or the basic activities subdomain score.
In addition to comparing models through the
AIC, a sensitivity analysis was conducted, which
looked at nested models between the ADL factors.
The results of comparing the LRTs of these nested
models supported the conclusion on the benefit
of breaking down the ADL score into subdomains
(data not shown).
Some outcomes also showed a significant
association with specific individual ADL questions
(as shown in Table 3); in general, the model fit
18. 252 C. Reed et al.
Table 2. Caregiver and cost outcomes by AD severity at
baseline
AD S E V E R I T Y
M O D E R A T E L Y O V E R A L L
C H A R A C T E R I S T I C M I L D M O D E R A T E S E V
E R E / S E V E R E p-V A L U E ∗ P O P U L A T I O N
...............................................................................................
...............................................................................................
...............................................................................................
...............................
Total societal cost,a,b
(€/month)
1,325.6 (1,519.0) 1,884.1 (1,972.5) 2,908.5 (2,981.8) <0.001
1,984.9 (2,288.4)
Patient healthcare and social
care costs,a,b (€/month)
568.1 (1,009.5) 777.4 (1,281.3) 1,076.9 (1,775.6) <0.001 789.5
(1,381.2)
Total caregiver time,a
(h/month)
121.3 (171.8) 187.2 (212.5) 339.7 (254.9) <0.001 208.8 (231.3)
Caregiver supervision time
19. (h/month)
44.6 (110.6) 78.6 (144.4) 158.1 (180.5) <0.001 90.0 (152.9)
ZBI total score 24.7 (14.2) 29.4 (14.8) 34.1 (14.8) <0.001 29.1
(15.1)
Notes: Data are mean values ± SD.
aCaregiver time = number of hours for basic ADL + number of
hours for instrumental ADL + supervision time (capped at 720 h
per
month).
bCalculated using an opportunity cost approach taking into
account only productivity loss for working age caregivers and
lost leisure time
for retired people or those who never worked or stopped
working for reasons other than care of the patient. Unit costs for
caregiver time for
working caregivers: value of lost production time (based on
average wage). Non-working caregivers: value of lost leisure
time (based on
35% of average wage). Caregiver time was capped at 720 h (the
maximum number of hours in a month at 24 h/day and excluding
caregiver
supervision time). Costs were calculated for the month prior to
baseline. Total societal costs = patient healthcare and social
care costs +
caregiver informal care costs.
∗ For comparison between AD severity groups (Wald χ2 test
from generalized models for costs and caregiver time; for the
ZBI score,
p-values are taken from the type III sums of squares from the
generalized linear model).
“Mild” AD severity = MMSE 21–26 points; “moderate” AD
severity = MMSE 15–20 points; “moderately severe/severe” AD
severity =
20. MMSE < 15 points.
AD = Alzheimer’s disease; ZBI = Zarit Burden Interview.
was similar when any of these individual questions
were replaced with another question from the same
subdomain, showing that the individual questions
within a subdomain were largely interchangeable
(data not shown). Exceptions to this were seen only
in the total caregiver hours model, in which the
individual basic activities question, Q4 (bathing)
and the domestic/household activities questions,
Q6A (choosing clothes), Q7 (using the telephone),
Q11 (finding belongings), and Q13 (cooking), all
of which were significantly associated with total
caregiver hours, could not be replaced by other
individual questions.
Overall, a one-point lower IADL score (range
0–56) was associated with 2.2% higher total societal
costs, 4.4% higher total caregiver hours, 7.2%
higher caregiver supervision hours, and a 0.48
higher ZBI score. A one-point lower BADL score
(range 0–22) was associated with 3.4% higher total
societal costs, 3.2% higher patient healthcare and
social care costs, and 3.1% higher total caregiver
hours.
GLM analysis by AD severity group
There was a linear relationship between MMSE
scores and ADL scores in the total, BADL, and
IADL domains and all four subdomains (Supple-
mentary Figure S2 is available as supplementary
material attached to the electronic version of this
paper at www.journals.cambridge.org/jid_IPG),
with increasing cognition deficits reflecting greater
21. impairments in all ADL domains.
Sensitivity analysis identified several interactions
between outcomes and ADL scores that differed
according to MMSE severity (mild vs. moderate-
to-severe; Figure 1). Notably, there were significant
(p � 0.007) differences between the mild and
moderate-to-severe AD groups in associations
between: total societal costs and total ADL, IADL,
and the outside activities subdomain; both total
and caregiver supervision hours and total ADL,
IADL, and the outside activities subdomain; and
ZBI score and total ADL score. A one-point
lower outside activities ADL subdomain score was
associated with 6.9% higher total societal costs
in the mild AD severity group compared with
1.5% higher costs in the moderate-to-severe AD
group. Corresponding higher values for caregiver
total and supervision hours were 17.2% and 35.3%,
respectively, in the mild severity group and 6.1%
and 13.5%, respectively, in the moderate-to-severe
AD group. There was no significant interaction
between MMSE severity (mild vs. moderate-to-
severe) and patient healthcare and social care costs
(p = 0.50).
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A
D
L
fa
cto
23. 5
3
Table 3. Associations between ADCS-ADL scores and outcomes
(estimates from multivariate models)a
P A T I E N T
H E A L T H C A R E C A R E G I V E R
T O T A L S O C I E T A L A N D S O C I A L
b
T O T A L C A R E G I V E R S U P E R V I S I O N
C O S T S
b
C A R E C O S T S
b
H O U R S
b
H O U R S
b ZBI T O T A L S C O R E b
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...............................................................................................
...............................................................................................
................................................................
ADCS-ADLc (range)
Total ADL score
24. (0–78)
2.4% (2.2%, 2.7%)
p < 0.001
1.2% (0.8%, 1.5%)
p < 0.001
4.1% (3.6%, 4.6%)
p < 0.001
5.5% (4.4%, 6.6%)
p < 0.001
0.37 (0.32, 0.42)
p < 0.001
BADL score
(0–22)
3.4% (2.1%, 4.6%)
p < 0.001
3.2% (1.6%, 4.8%)
p < 0.001
3.1% (0.7%, 5.5%)
p = 0.010
0% (−4.4%, 4.6%)
p = 0.999
−0.004 (−0.23, 0.22)
p = 0.972
IADL score
25. (0–56)
2.2% (1.7%, 2.6%)
p < 0.001
0.6% (0.0%, 1.1%)
p = 0.052
4.4% (3.6%, 5.3%)
p < 0.001
7.2% (5.4%, 9.1%)
p < 0.001
0.48 (0.40, 0.56)
p < 0.001
ADCS-ADL subdomains
Basic activities subdomain (B)
(0–19)
3.5% (2.0%, 4.9%)
p < 0.001
4.9% (3.0%, 6.8%)
p < 0.001
1.2% (−1.5%, 3.9%)
p = 0.401
−4.0% (−8.8%, 1.2%)
p = 0.129
−0.08 (−0.34, 0.19)
p = 0.573
26. Domestic/household activities
subdomain (D)
(0–28)
1.9% (1.0%, 2.7%)
p < 0.001
−0.2% (−1.3%, 0.8%)
p = 0.692
4.6% (3.0%, 6.3%)
p < 0.001
7.5% (4.2%, 10.8%)
p < 0.001
0.39 (0.24, 0.55)
p < 0.001
Communication and engagement
with the environment
subdomain (C) (0–20)
2.1% (1.0%, 3.2%)
p < 0.001
0.5% (−0.8%, 1.9%)
p = 0.441
2.4% (0.3%, 4.4%)
p = 0.024
2.7% (−1.0%, 6.6%)
p = 0.156
0.63 (0.43, 0.84)
27. p < 0.001
Outside activities subdomain (O)
(0–11)
3.8% (2.0%, 5.7%)
p < 0.001
2.0% (−0.4%, 4.4%)
p = 0.098
11.0% (7.4%, 14.7%)
p < 0.001
23.3% (15.8%, 31.4%)
p < 0.001
0.43 (0.10, 0.77)
p = 0.011
Individual ADCS-ADL items NA
Q4 (bathing) (B) (0–3) 14.3% (8.3%, 20.6%)
p < 0.001
15.3% (7.5%, 23.7%)
p < 0.001
11.7% (1.6%, 22.8%)
p = 0.022
NA NA
Q6A (choosing clothes) (D)
(0–3)
na −7.8% (−12.0%,
28. −3.4%)
p < 0.001d
10.6% (2.8%, 18.9%)
p = 0.007
NA NA
Q6B (dressing) (B)
(0–4)
7.9% (3.4%, 12.6%)
p < 0.001
9.6% (3.6%, 16.0%)
p = 0.002
NA NA NA
Q7 (using the telephone) (D)
(0–5)
4.0% (0.7%, 7.3%)
p = 0.018
NA 9.5% (3.1%, 16.3%)
p = 0.003
23.2% (11.0%, 36.7%)
p < 0.001
0.72 (0.16, 1.27)
p = 0.012
Q8 (watching the television) (C)
(0–3)
29. 7.9% (3.4%, 12.6%)
p < 0.001
NA NA NA NA
Q9 (paying attention to
conversation) (C)
(0–3)
NA NA NA NA 1.50 (0.85, 2.16)
p < 0.001
Q10 (clearing the dishes) (D)
(0–3)
NA NA NA NA 1.20 (0.52, 1.89)
p < 0.001
2
5
4
C
.
R
e
e
d
e
30. t
a
l.
Table 3. Continued.
P A T I E N T
H E A L T H C A R E C A R E G I V E R
T O T A L S O C I E T A L A N D S O C I A L
b
T O T A L C A R E G I V E R S U P E R V I S I O N
C O S T S
b
C A R E C O S T S
b
H O U R S
b
H O U R S
b ZBI T O T A L S C O R E b
...............................................................................................
...............................................................................................
...............................................................................................
...............................................................................................
................................................................
Q11 (finding belongings) (D)
(0–3)
31. NA NA 8.3% (1.3%, 15.8%)
p = 0.020
21.8% (7.8%, 37.7%)
p = 0.002
1.84 (1.20, 2.48)
p < 0.001
Q13 (cooking) (D)
(0–4)
5.7% (2.6%, 8.8%)
p < 0.001
NA 7.2% (1.5%, 13.2%)
p = 0.013
12.0% (1.7%, 23.3%)
p = 0.022
NA
Q16A (shopping) (O)
(0–3)
NA NA 15.1% (6.6%, 24.4%)
p < 0.001
32.0% (13.3%, 53.8%)
p < 0.001
NA
Q16B (paying) (O)
32. (0–1)
22.1% (10.8%,
34.6%)
p < 0.001
NA NA NA 3.21 (1.43, 4.99)
p < 0.001
Q17 (keeping appointments) (C)
(0–3)
5.8% (1.1%, 10.7%)
p = 0.015
NA 11.3 (1.9%, 21.5%)
p = 0.020
NA NA
Q18 (being left alone) (O)
(0–3)
NA NA 20.6% (12.2%, 29.6%)
p < 0.001
40.5% (23.3%, 60.2%)
p < 0.001
NA
Q20 (reading) (C)
(0–20)
NA NA NA NA 2.04 (0.93, 3.14)
p < 0.001
33. Q21 (writing) (C)
(0–3)
NA 6.8% (0.9%, 13.0%)
p = 0.023
NA NA NA
Q22 (performing hobbies) (C)
(0–3)
NA na NA NA 0.78 (0.18, 1.38)
p = 0.011
Q23 (using appliances) (D)
(0–4)
NA 5.0% (1.0%, 9.2%)
p = 0.014
NA NA NA
Notes: aResults for each outcome are generated from separate
GLMs, all run with country, patient age, MMSE severity group,
and caregiver relationship (spouse: yes/no) as included factors.
bFor continuous ADL variables, the percentage change (95%
confidence interval [CI]) in the mean cost or mean number of
caregiver hours per patient for each unit change of the ADL
score is
reported; positive values indicate higher cost/hours for lower
ADL scores (signifying worse function); however, these are not
adjusted for the respective range in each domain or subdomain.
In the
ZBI model, the estimate relates to the change in the ZBI total
score (95% CI) for each unit point change in ADL score;
34. positive values indicate greater caregiver burden for lower ADL
scores.
cAssessed using the ADCS-ADL.
dFactor goes in the opposite direction (i.e. lower costs are
associated with lower functional scores).
B = basic activities item; C = communication activities item; D
= domestic/household activities item; O = outside activities
item.
“Mild” AD severity = MMSE 21–26 points; “moderate” AD
severity = MMSE 15–20 points; “moderately severe/severe” AD
severity = MMSE < 15 points.
ADCS-ADL = Alzheimer’s Disease Cooperative Study –
Activities of Daily Living Scale; BADL = basic activities of
daily living; GLMs = Generalized Linear Model analyses; IADL
=
instrumental activities of daily living; NA = not applicable to
the model; ZBI = Zarit Burden Interview.
ADL factors and cost and caregiver outcomes in AD 255
Figure 1. (Colour online) Interactions between outcomes and
ADL scores that differed between MMSE AD severity (mild vs.
moderate-
to-severe) groups (sensitivity analysis); interactions that differ
significantly between AD severity groups are indicated using
bold p-values.
ADL = activities of daily living; BADL = basic activities of
daily living; IADL = instrumental activities of daily living;
MMSE = Mini-Mental
State Examination.
Discussion
35. This study found significant associations between
key cost and caregiver outcomes and components
of ADL (defined as total ADL, BADL, and IADL
scores, and the scores of four ADL subdomains
confirmed by factor analysis) using data from
the GERAS observational study in community-
based patients with AD. In particular, significant
associations were identified between total societal
costs (patient healthcare and social care costs
plus caregiver informal care costs) and caregiver
256 C. Reed et al.
total and supervision hours and the derived ADL
subdomain of outside activities. These differed
significantly between patients with mild AD and
those with moderate-to-severe AD, suggesting that
this subdomain may be potentially informative
in determining outcomes in patients with mild
AD.
Factor analysis of ADCS-ADL confirmed the
presence of a basic activities subdomain commen-
surate with the original BADL domain of the
ADCS-ADL questionnaire (Galasko et al., 2005),
and separated IADL into three distinct subdomains:
domestic/household, communication/engagement
with the environment, and outside activities. All
four subdomains showed a linear relationship with
MMSE score similar to that seen with the total
ADL, BADL, and overall IADL scores.
36. BADL and the basic activities subdomain
Lower BADL scores were associated with higher
total societal costs and, specifically, higher patient
healthcare and social care costs. This is supported
by the finding that the basic activities subdomain
was the only subdomain to show an association
with patient costs. Thus, a poor ability to self-
care had the greatest impact on patient health and
social care costs, possibly because such patients
require care from external sources (e.g. home
helps, district nurse visits, etc.), which have clear
cost implications. Few studies appear to have
investigated the specific contribution of BADL
impairment to patient costs. However, in a study
conducted by Zhu et al. (2006) in the United
States, increased impairments in both BADL and
IADL (assessed using the Blessed Dementia Rating
Scale) were associated with increases in patient
direct medical costs as well as informal care
costs.
Lower BADL and basic activities subdomain
scores were not directly associated with higher
caregiver supervision hours. This is perhaps
surprising, as less time spent on supervision was
significantly associated with fewer deficits in both
BADL and IADL in a previous analysis of the
GERAS baseline data (Haro et al., 2014). However,
Haro et al. (2014) analysis included additional
caregiver factors in the multiple linear regression
analyses, whereas our analysis used GLMs with γ
distributions.
A lower BADL score was associated with
higher total caregiver hours, but there was
no association between this outcome and the
37. basic activities subdomain. Given the overlap of
items comprising BADL and the basic activities
subdomain confirmed in the factor analysis
(which differ only in the questions relating to
choosing clothes [BADL] and being able to dress
[basic activities subdomain]), this finding appears
contradictory. However, the significant association
observed between total caregiver time and the
individual ADL item on choosing clothes (Table 3)
demonstrates the importance of this one item in its
contribution to the assessment of BADL.
A lower BADL score was not associated with
greater caregiver burden (as assessed using the
ZBI score). There was also no association between
caregiver burden and the basic activities subdomain
or any individual basic activities question. A number
of studies have reported a weak or no relation
between ADL in patients with dementia and the
perceived emotional burden of their caregivers
(Serrano-Aguilar et al., 2006; Campbell et al.,
2008). These findings therefore imply that poor self-
care in a patient does not add to the caregiver’s
emotional burden of caregiving, which appears to
contradict the previously mentioned association
between higher functional impairment and a higher
caregiver burden (e.g. Kim et al., 2012; Haro
et al., 2014). However, as BADL generally become
impaired in the moderate-to-severe stage of AD
(Marshall et al., 2012), it is possible that by the time
patients have progressed to this stage of the disease,
caregivers may have developed coping strategies
(Del-Pino-Casado et al., 2011) or have started
using informal and formal support services (Snyder,
2000), which may have influenced their experience
38. and outcomes related to care provision. It can
also be speculated that caregivers of patients with
BADL impairments, who have more severe AD,
have fewer expectations of the patient. Perhaps
also there is a differential subjective appraisal of
caring tasks, with more caregiving satisfaction being
associated with providing assistance for BADL
versus IADL. Additional work is needed to evaluate
these potential mechanisms.
Instrumental ADL
Instrumental activities of daily living were found
to be significantly associated with the total societal
costs of AD, caregiver burden, and total caregiver
time and supervision time. The lack of an
association between IADL and patient health and
social care costs may reflect the fact that all patients
enrolled in GERAS have caregivers to help manage
medication and comorbidities, which may minimize
such costs. Although few studies have investigated
associations between IADL and key outcomes in
patients with AD, those we identified were generally
supportive of our findings.
Handels et al. (2013) found IADL to be a key
determinant of societal costs of care of patients
with dementia or cognitive impairment, a finding
ADL factors and cost and caregiver outcomes in AD 257
in agreement with a study by Wattmo et al. (2013),
which showed that a slower decline in IADL was
associated with a longer time to the implementation
of community-based home-help services and its
39. associated costs.
Both ADL and IADL were found to predict
caregiver burden in an analysis by Kim et al. (2012);
however, the authors found caregiver burden to be
more strongly associated with deteriorating IADL
than with total ADL. Impairments in IADL were
identified as a predictor of the objective burden of
informal care (amount of time or costs spent on
informal care) in a systematic review involving ten
studies conducted in patients with dementia (Wolfs
et al., 2012). Lower IADL scores (commensurate
with worse function) were also associated with
a higher caregiver burden in previous analyses
of the GERAS study (Haro et al., 2014; Reed
et al., 2014) and in the ICTUS study, a European
longitudinal cohort study in patients with mild-
to-moderate AD (Germain et al., 2009). In the
previous GERAS analysis (Reed et al., 2014),
the relationship observed between functionality
(ADCS-ADL total score) and caregiver burden
in both adult–child and spousal caregivers in the
GERAS study was predominantly associated with
IADL rather than BADL for both caregiver–patient
relationship cohorts. These results are supported by
the finding in the current study that IADL, and not
BADL, was associated with caregiver supervision
hours.
The finding in the current analysis that
IADL scores, and not BADL scores, impact on
caregiver burden may be indicative of a differential
relationship between this outcome and ADL.
The majority of the previously mentioned studies
reporting a weak or no relation between ADL in
patients with dementia and the perceived burden
40. of their caregivers (Serrano-Aguilar et al., 2006;
Campbell et al., 2008) assessed total ADL with
no breakdown of BADL or IADL. It is therefore
possible that their overall findings of no association
between ADL and caregiver burden masks a specific
association between this outcome and IADL.
IADL subdomains
Loss of ability of a patient with AD to communicate
contributes to caregiver burden (Snyder, 2000),
and this was reflected in our finding that a lower
communication subdomain score was associated
with a higher ZBI score. However, given that a one-
point lower communication subdomain score was
associated with only a 0.63 higher ZBI score (mean
score 29.1), this change is unlikely to be clinically
relevant. Lower communication subdomain scores
were also associated with higher total caregiver
hours and total societal costs, but not caregiver
supervision hours. However, supervision time is
typically not included in estimations of informal
caregiver costs, a major contributor to total societal
costs (Gustavsson et al., 2011; Handels et al., 2013;
Wimo et al., 2013).
Outside and domestic/household activities can be
seen as a representative of the level of a patient’s
independence. Both of these ADL subdomains were
associated with all outcomes, with the exception
of patient healthcare and social care costs, which
would imply that they are the most relevant
subdomains driving the IADL domain (patient
healthcare and social care costs were the only
outcome not associated with IADL). However, in
the analysis of interactions with AD severity groups
41. (mild vs. moderate-to-severe), only the association
between the outside activities subdomain and the
outcomes of total societal costs and caregiver
hours (supervision and total) differed significantly.
Hence, it would appear that the ADL outside
activities subdomain might better discriminate
these outcomes in patients with mild AD from
those with moderate-to-severe AD. In patients
with milder AD, therefore, it can be hypothesized
that measuring/monitoring their ability to function
independently outside the home may be more
useful than assessing overall IADL when assessing
functional ability or in monitoring functional
decline. As IADL impairments generally appear
earlier in the disease course than deficits in BADL,
we could speculate that this finding might also be
of value in assessing patients with mild cognitive
impairment (MCI). There is growing evidence that
patients with MCI have functional deficits in IADL
(Brown et al., 2011). However, not all patients with
MCI progress to AD. A better understanding of the
type and severity of IADL impairment may help
to identify patients in the very early stages of AD
and thus promote the earlier recognition of care
needs and the implementation of support services.
Such an understanding may also, therefore, affect
future policy and service development. Further
investigation of the outside activities subdomain
may be informative in this context.
Study strengths and limitations
One of the strengths of this study is the good
correlation between the CFA run on the overall
GERAS data using the factor pattern reported
in the PLASA study and the factors identified
by Kahle-Wrobleski et al. (2014) using data
42. from the prospective randomized PLASA study
(Nourhashemi et al., 2010). Similar correlations
were also apparent between the CFAs run using
data from each of the three MMSE severity groups
258 C. Reed et al.
and the factor pattern generated by the PLASA
analysis.
Other strengths of our analysis are that the
GERAS study data were obtained from a large AD
population characterized by a wide range of disease
severity. In contrast to the PLASA study factor
analysis (Kahle-Wrobleski et al., 2014), however, it
should be noted that data were missing for <1%
of patients in the GERAS study (Wimo et al.,
2013), whereas a limitation of the Kahle-Wrobleski
et al. (2014) study was that it was not possible
to include all participants in the analyses due to
missing baseline data in 35% of patients. Sensitivity
analyses found missing data to have no effect on the
results of the GLM models conducted in the current
study.
Limitations of this study include the fact that the
GERAS population was a clinic-based convenience
sample (not a population-based cohort) and
therefore not fully representative of a typical
AD patient cohort. In a population-based cohort,
patients having dementia tend to be diagnosed in
later stages of the disease, and families require more
information and psycho education to cope with the
consequences of the disease; hence, caregiver time
43. and costs may differ from this clinic-based cohort.
Baseline parameters were gathered by patient and
caregiver recall, and hence may be subject to
recall bias (Evans and Crawford, 1999). It should
also be borne in mind that the ADCS-ADL is a
subjective measure of a patient’s ability to perform
ADL, completed on behalf of the patient by
his/her caregiver. Caregivers have been shown to
underestimate the functional status of patients with
AD, especially with regard to IADL (Zanetti et al.,
1999), a finding related to the caregiver’s perceived
burden (Mangone et al., 1993).
The current factor analysis was based on baseline
(cross-sectional) data from the GERAS study. As
GERAS is a prospective study, it is intended that
the reliability of this analysis will be assessed using
longitudinal data when available.
Conclusions
Stratifying patients by their ability to carry out
subdomains of ADL may lead to a better
understanding of the association between patient
function and costs and caregiver outcomes at
different stages of AD. Assessment of the outside
activities subdomain in milder stages of the disease
in particular could be important for use in the
diagnosis of functional impairment within AD and
in the monitoring of disease progression; it may
provide a useful measure in clinical trials.
Conflict of interest
The GERAS study and this analysis were supported
by Eli Lilly and Company Limited. Mark Belger,
44. Catherine Reed, and Jeffrey Scott Andrews are
employees of Eli Lilly and Company Limited. Josep
M. Argimon, Giuseppe Bruno, Richard Dodel, and
Anders Wimo have received financial compensation
from Eli Lilly for participation on the GERAS
Advisory Board. Roy W. Jones, Bruno Vellas, and
Josep Maria Haro are consultants for Eli Lilly.
Description of authors’ roles
M. Belger was responsible for carrying out statistical
analysis and the statistical design of the analysis.
J.S. Andrews, J.M. Haro, C. Reed, and B. Vellas
contributed to the data analysis and drafting of the
paper. J.M. Argimon, G. Bruno, R. Dodel, R.W.
Jones, and A. Wimo critically revised the paper for
important intellectual content.
Acknowledgments
The authors wish to thank all investigators who
participated in the study. We would like to express
our gratitude to all patients and their caregivers
who participated in this study. The authors would
like to acknowledge Drs Gill Gummer and Deirdre
Elmhirst (Rx Communications, Mold, UK) for
medical writing assistance for the preparation of this
paper, funded by Eli Lilly and Company.
Supplementary material
To view supplementary material for this
article, please visit http://dx.doi.org/10.1017/
S1041610215001349.
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http://dx.doi.org/10.1007
http://dx.doi.org//s12603-014-0036-
0IntroductionMethodsPatient and caregiver dataConfirmatory
factor analysis of the ADCS-ADLGeneralized linear model
analysesSensitivity analysesRelationship between total ADL
score and AD severityMissing dataStatistical
methodsResultsConfirmatory factor analysis resultsGLM
analyses resultsGLM analysis by AD severity
groupDiscussionBADL and the basic activities
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and limitationsConclusionsConflict of interestDescription of
authors’ rolesAcknowledgmentsSupplementary
materialReferences
Rapid #: -10183329
50. CROSS REF ID: 1257683
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JOURNAL TITLE: Aging & mental health
USER JOURNAL TITLE: Aging and Mental Health
ARTICLE TITLE: Older adults’ influence in family care: how
do daughters and aging parents navigate differences in
care goals?
ARTICLE AUTHOR: Heid, Allison R.,
VOLUME: 20
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Older adults’ influence in family care: how do
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Allison R. Heid, Steven H. Zarit & Kimberly Van Haitsma
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Older adults’ influence in family care: how do daughters and
aging parents navigate
differences in care goals?
Allison R. Heid
a,b
*, Steven H. Zarit
b
and Kimberly Van Haitsma
53. c,d
a
New Jersey Institute for Successful Aging, Rowan University
School of Osteopathic Medicine, Stratford, NJ, USA;
b
Department of
Human Development and Family Studies, The Pennsylvania
State University, University Park, PA, USA;
c
College of Nursing, The
Pennsylvania State University, University Park, PA, USA;
d
The Polisher Research Institute, The Madlyn and Leonard
Abramson Center
for Jewish Life, North Wales, PA, USA
(Received 4 December 2014; accepted 4 May 2015)
Objective: This study seeks to address how older adults
influence their daily care when their preferences conflict with
those
of their adult daughter caregivers.
Method: Using a sample of 10 dyads (N D 20) of an older adult
and adult daughter, we utilize content analysis strategies to
analyze in-depth, semi-structured interview data with QSR
NVIVO to investigate how older adults influence their care,
how daughters respond to such efforts of influence, and how
dyads navigate differences in care goals.
Results: When there is agreement in goals, dyads report tasks
going well and both individuals’ requests are honored. When
54. there are differences in care goals, daughters most frequently
reason with their older parents, while parents walk away or
‘let go’ of their requests. Daughters report making decisions for
their parents for health or safety-related needs. However,
all dyads discuss differences in care goals, whereby parents are
perceived as insisting, resisting, or persisting in care.
Conclusion: Findings illustrate complex patterns of responses
by families when navigating differences in daily care goals
that carry important implications for research and the
development of dyadic-based family interventions.
Keywords: family caregiving; preferences; care influence;
qualitative
Introduction
As individuals age, they increasingly rely on the support
of others. Adult offspring often provide such support with
daily activities. However, children often express frustra-
tion around the fact that their older parents want to have
tasks done in their own way, even when it may compro-
mise their safety or well-being (Zarit & Zarit, 2007).
These situations often involve differences of goals. Yet,
there is little work to date on how families address older
adults’ preferences. Furthermore, work has yet to address
how older adults try to influence family members to get
55. the care they prefer and how family caregivers respond in
situations where preferences or goals differ. This study
takes a process-oriented approach to understanding such
phenomena in families.
Family care context
A growing body of evidence supports the need to provide
person-centered care to older adults, whereby the individ-
uals’ preferences and needs are placed at the center of
care delivery (Edvardsson, Varrailhon, & Edvardsson,
2014). However, less discussed is that the practice of pro-
viding person-centered care is embedded within the con-
text of aging, specifically, that older adults experience a
loss of physical and cognitive abilities and increasingly
rely on social support for managing daily tasks (Baltes,
Freund, & Li, 2005). Researchers drawing on different
perspectives, including sociological theory (Pescosolido,
1992), family systems (White & Klein, 2008), and dyadic
models (Berg & Upchurch, 2007) describe how adults
56. function within social systems and collaborate with others
when making decisions and responding to illness or dis-
ability. An individual interacts with a significant other or
supportive relative to develop joint coping responses
(Berg & Upchurch, 2007; Bodenmann, 1995; Krause,
2003). Person-centered care may arguably become dyad-
centered care, or family-centered care (Kuo et al., 2012),
and is shaped by the beliefs of both the individuals provid-
ing and receiving care.
Family members often step in to provide essential sup-
port to aging individuals across a diverse spectrum of
needs (Zarit, Femia, Kim, & Whitlatch, 2010). In such
instances, families are called to balance their needs with
their older relatives in care. Both an older adult and his/
her family member operate as individual complex systems
trying to achieve their own motivational goals in daily life
(Ford, 1994). For example, an older adult needs auton-
omy, competence, and relatedness, but so does his/her
57. family member (Deci & Ryan, 2000). Thus, families may
attempt to jointly cope with stressors, but one person’s
goals may not match the goals of the other partner sup-
porting care. In such cases, a clash of motivations may
ensue due to each person’s desire to achieve a different
goal (Ford, 1994). These conflicts in care likely carry
*Corresponding author: Email: [email protected]
� 2015 Taylor & Francis
Aging & Mental Health, 2016
Vol. 20, No. 1, 46�55,
http://dx.doi.org/10.1080/13607863.2015.1049117
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59. http://dx.doi.org/10.1080/13607863.2015.1049117
important implications for the experience of strain and
burden for the caregiver, or well-being outcomes for the
older adult; yet little is known about this micro-level pro-
cess in families.
Evidence highlights that as caregivers take on respon-
sibilities for a dependent older adult, they accrue great
power for persuasion and decision-making to influence
care (Pyke, 1999; Wilkinson, 2001), and that older adults’
own views are sometimes not taken into consideration
(i.e., Elliott, Gessert, & Peden-McAlpine, 2009; Persson
& W€asterfors, 2008). Particularly affected are those older
adults who must rely on help with instrumental or per-
sonal activities of daily living (IADLs or ADLs; Baltes,
1996; Harnett, 2010). As parents become more dependent,
children may become dominant in decision-making
(Cicirelli, 2006; Morgan & Hummert, 2000; Pratt, Jones,
Shin, & Walker, 1989) and/or children may influence care
60. decisions or encourage dependency of older adults in care
(Baltes, 1996).
Daughters, in particular, are a primary group of care-
givers for older adults. Often described as the sandwich
generation, they frequently experience competing roles in
caring for a parent and are at risk for compassion fatigue
(Day, Anderson, & Davis, 2014; Martire, Stephens, &
Townsend, 2000; Simpson & Carter, 2013). Furthermore,
unique tensions between mother�daughter dyads around
perceptions of aging and negotiating care have been docu-
mented (Fingerman, 1996; McGraw & Walker, 2004).
Yet, less is known about how daughters respond to older
adults’ attempts to direct their own behavior in care when
there are differences in care goals.
Responses to goal differences in care
More specifically, when there are goal differences in care,
daughters may define what is best for their relatives based
on their own assumptions and values. In some cases, this
presumption may not align with the older adults’ values
61. and caregivers may attempt to redirect their relatives’
behaviors. When an older adult attempts to act on a goal
and meets resistance from his/her caregiver (i.e., because
the caregiver has a different goal), the older adult may
attempt to influence care by resisting the caregiver’s sug-
gestion and insisting or persisting in acting on his/her origi-
nal goal, acting in a way that is commonly attributed to
stubbornness (Heid, Zarit, & Fingerman, 2015). If the older
adult persists in his/her preferred action or opinion, there is
likely to be a lack of collaboration in care (i.e., Berg &
Upchurch, 2007; Bodenmann, 1995; Krause, 2003). This
possibly frustrating sequence of behaviors may lead to rela-
tionship tension, relationship conflict, or decreased well-
being for the older adult or caregiver. Research has yet to
explore the process of how adult daughters respond when
they perceive an older adult acting in this way.
Present study
Given the number of daughter caregivers providing care
62. for older adults and the implications differences in care
goals may have for how families support each other, this
study seeks to expand our understanding of the process by
which older adults influence care, by conducting semi-
structured interviews with both daughter caregivers and
older adults. A better understanding of disagreements in
care and how older adults and caregivers navigate such
conflict may build our understanding of how to provide
family-centered care to older adults.
We focus on three primary research questions:
(1) How do older parents influence their care in families?
(2) How do daughter caregivers respond to such influ-
ence? and, (3) How do daughters and parents navigate
goal differences in daily care as a dyad, particularly when
a parent is perceived to insist, resist, or persist?
Method
Participants
A convenience sample of 10 dyads of an adult daughter
63. caregiver (aged 30�62) and her aging parent (two fathers;
eight mothers; aged 61�90) were recruited from a Short-
Term Rehabilitation Center between the months of Novem-
ber 2012 and February 2013 upon completion of a short-
stay visit for the aging parent. ‘Caregiver’ was loosely
defined as providing at least weekly assistance with inde-
pendent or personal activities of daily living to the older
parent to provide for a range of experiences. The older
adult was not required to be a certain age or have a specific
diagnosis, but was required to have no more than mild cog-
nitive impairment (as deemed by Center Staff of a 13, 14,
or 15 total score on the Brief Interview for Mental Status
(BIMS) cognition scale; Saliba et al., 2012). Given that a
specific diagnosis was not required, data were not system-
atically collected regarding reason for support; however,
participants shared reasons such as recovery from chemo-
therapy, a brain aneurism, or a recent fall. The daughters
and parents were not required to be living together but had
to be living in the community (i.e., not in institutional or
64. group living) upon the parent’s discharge from rehabilita-
tion (four dyads lived together in the sample). Study con-
sent and enrollment commenced approximately one month
after discharge from the Center. During recruitment,
14 families were referred, 13 screened eligible, and 10 par-
ticipated. Families who did not participate were no longer
eligible at scheduling (n D 1), did not return scheduling
calls (n D 1), or were no longer interested after screening
(n D 1). After 20 interviews, data reached saturation, no
new themes were emerging, and recruitment was stopped.
Procedure
Institutional review board approval was obtained. Partici-
pants (N D 20) individually signed a written consent to
participate and to have their interviews recorded. Parents
and daughters were interviewed separately at home or in a
place of their choosing without the presence of other indi-
viduals. In the case that family members needed to be
present, adjustments were made to meet the needs of the
participant (n D 1). The researcher conducted an open-
ended, semi-structured interview followed by a brief
65. Aging & Mental Health 47
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demographic questionnaire. To avoid any unintentional
bias on part of the interviewer, dyads were randomized to
have either the daughter be interviewed first or the parent.
For half of the dyads (n D 5), the daughter was inter-
viewed first, and for the other half, the parent was inter-
viewed first. Interviews were audio-recorded and
transcribed and lasted from 28 to 78 minutes.
Measures
Semi-structured interview
67. This study used a qualitative in-depth interview informed
by questions of Persson and W€asterfors (2008) in
interviewing nursing home caregivers about residents’
influence in care. Questions were translated from Swedish
to English, pared down, and adapted to include only ques-
tions related to study aims. Additional questions needed
to address the topic of goal differences were added. The
interview guide developed for the daughters was adapted
to create a parallel form for parents. The researcher used
follow-up questions to have respondents elaborate upon
answers. The order of questions was dependent on each
participant’s responses (see Table 1 for questions).
Demographic questionnaire
Participants were asked to indicate their age, race, marital
status, and highest level of education from 1 (less than
high school) to 6 (graduate degree). Gender of the parent
was coded as 0 (male) or 1 (female). Daughters were also
asked to rate their parents’ cognition using Pearlin’s
68. seven-item cognitive status scale (Pearlin, Mullan, Sem-
ple, & Skaff, 1990), as a check that individuals had no
more than mild cognitive impairment. Prior research has
found that this scale correlates highly with standard cogni-
tive screening tests (Aneshensel, Pearlin, Mullan, Zarit, &
Whitlatch, 1995). The seven items were: difficulty
remembering recent events, knowing the day of the week,
remembering his/her home address, remembering words,
understanding simple instructions, finding his/her way
around the house, and speaking sentences. Each item was
rated on a five-point scale from 0 (not at all difficult) to 4
(can’t do at all), and all items were summed to create a
total score of memory impairment. Parents were not self-
assessed for their cognitive impairment (see Table 2 for
descriptive statistics).
Data preparation and analysis plan
Data were transcribed and entered into QSR NVIVO 10, a
qualitative coding program (QSR International Pty. Ltd.).
69. Table 1. Interview questions for daughters.
1. First I’d like to understand a bit more about your caring
situation with your [RELATIVE]. Why are you currently
providing care for your [RELATIVE]?
2. What does a typical day in the life of caring for your
[RELATIVE] look like? Describe how you help your
[RELATIVE] on a given day.
3. When there are multiple people involved in making decisions
in daily life, we know that things can be difficult. Some
routines are established easily while others are not. We would
like to hear more about how this works in your relationship.
Describe one instance where you did see eye-to-eye with your
[RELATIVE].
4. Describe another instance when this has occurred.
5. Describe one past instance where you didn’t see eye-to-eye.
6. Describe one present instance where you don’t see eye-to-
eye.
7. Are there instances that your [RELATIVE] chooses to ignore
something that you feel would make (his/her) life better, safer,
or easier?
8. When you interact with your [RELATIVE], do you ever feel
that your [RELATIVE] insists on doing things (his/her) own
way even if it puts (him/her) at risk?
Note: Parallel questions were asked of the parent. Where the
word
‘RELATIVE’ appears, the interviewer substituted ‘mother’ or
‘father’
70. when speaking with parents, and ‘daughter’ when speaking with
parents.
Table 2. Sample descriptives.
Daughters Parents
M (SD) N (%) M (SD) N (%)
Age 51.20 (10.10)(range: 30�62) � 79.20 (9.09)(range: 61�90)
�
Caucasian � 10 (100.0) � 10 (100.0)
Marital status
Married/partner � 6 (60.0) � 4 (40.0)
Divorced � 3 (30.0) � 1 (10.0)
Never married � 1 (10.0) � 0 (0.0)
Widowed � 0 (0.0) � 5 (50.0)
Education 5.50 (0.85) � 4.30 (1.06) �
High school graduate � 0 (0.0) � 3 (30.0)
Some college � 2 (20.0) � 2 (20.0)
College graduate � 1 (10.0) � 4 (40.0)
Graduate degree � 7 (70.0) � 1 (10.0)
Employed � 8 (80.0) � �
Memory problems � � 1.90 (1.66) �
Note: N D 10 daughters and 10 parents; M D mean, SD D
standard deviation; N D number of participants.
48 A.R. Heid et al.
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Transcripts were read to produce a base coding-tree for
both daughters and parents, initially using broad codes.
The coding schemes were then expanded as common
responses were identified throughout the process of analy-
sis to add codes increasing in specificity according to the
responses provided. Content analysis strategies were then
used to code the manifest content with the developed
themes regarding how parents influence their care, how
daughters respond to such efforts of influence, and how
dyads navigate differences in care goals (Graneheim &
Lundman, 2004). Each interview was coded indepen-
dently and then compared to his/her family member’s
73. responses to examine dyadic responses in daily life. Two
additional trained assistants coded a random subset of
interviews to ensure stability, reproducibility, and accu-
racy in application of the developed coding tree (n D 9;
�80% agreement). Discrepancies between coders were
discussed and resolved by agreement to ensure utilization
of a consistent coding structure. Responses by theme were
tallied for purely descriptive purposes to develop a sense
of frequency within the sample.
Results
Findings highlight how older parents influence care,
daughters’ responses to parents’ influence, and dyadic
responses to navigating goal differences. When there is
agreement in goals, dyads report tasks going well and
both individuals’ requests are honored. When there are
differences in care goals, daughters most frequently rea-
son with their older parents, while parents walk away or
‘let go’ of their requests. However, all dyads discuss dif-
ferences in care goals, whereby parents are perceived as
74. insisting, resisting, or persisting in care, and differential
patterns of response were evident.
Parents’ influence
The perceptions of older parents’ involvement in care
tasks and decision-making on a daily basis varied across
individuals, from deciding how to do most of their own
care tasks to only making decisions in a couple of areas
(i.e., dressing, waking). All participants cited that parents
were involved in deciding how to spend their time. Partic-
ipants almost universally referenced a need for the parent
to experience independence or autonomy in making deci-
sions and completing daily tasks (n D 9 parents; n D 10
daughters).
Well I know that she has to let go of me, you know, that I
have to be independent. You know I see a lot of women
my age…who are very much dependent on their children
and that I never want to be (Parent, 1118).
Dyads reported that daughters and other individuals
(i.e., siblings) also made some decisions or that decisions
were made jointly (i.e., medical decisions). In these
75. instances, parents relied on their daughters or others for
their expertise:
I’m pretty much the decision maker and she knows even
though she’s very independent and she likes to be able to
make all of her decisions. She knows that it’s in her best
interests to have me navigate everything (Daughter,
1111).
Parents’ reliance on others was not perceived to limit
their abilities, but rather as a support.
Within these daily decisions, dyads reported things
going well when there was agreement in care goals or tasks.
Now, for instance, yesterday she took all my winter
clothes…Last year I did it all myself, I took all the sum-
mer ones out on the bed, put all the winter ones in, folded
the other ones, put them away. This year, she brought the
boxes in and I said, ‘I can’t do that.’ ‘I know you can’t!’
[Laughs] (Parent, 1103).
When dyads had different goals (e.g., different percep-
tions on where the parent should live, the temperature of
the room, the social activities of the parent), however, the
responses and influence of the parent varied across fami-
lies and circumstances. The most common strategies that
76. dyads (both parents and daughters) described were parents
‘letting go’ (n D 82 citations) and ‘continuing to act on
one’s own impulses’ (n D 58 citations). Other response
strategies used included getting upset, arguing, brainstorm-
ing a solution, getting someone else to talk to the other
individual, using humor, waiting to talk about it another
day, and rewording the request (see Table 3 for a summary
of strategies discussed). Thus, when there was conflict,
parents were described as influencing care by being more
passive and relinquishing their request, but also through
active attempts to persist in their behavior or opinions.
Daughters’ responses to parents’ influence
In the face of differences in daily goals, daughters were
most frequently described by dyads as ‘reasoning with
their parent’ or ‘letting go.’ These behaviors were primar-
ily viewed as responses that were meant to honor the ‘best
interests’ of their parents.
He tried [to stand up on his own] at the beginning when he
came home but I think he, now he realizes that all of us
are looking out for his best interests. And he’s not fighting
it like he was before (Daughter, 1117).
77. Daughters further discussed that they responded dif-
ferentially to their parent when faced with a conflict
depending upon the scenario and context. Daughters
talked of their need to preserve the health or safety of their
parents. In these situations, daughters reported stepping in
to make decisions in the face of differences in goals (n D
9 daughters).
Things related to safety or personal hygiene, like needing
the bathroom, and no he’s not just going to soil his pants
like that and things related to therapy. Like if the therapist
needs him to move his arm even though it hurts, or his
leg, or exercises, those things I try not to give up on…
Anything else I think should be negotiable or like pick
your battles (Daughter, 1108).
Aging & Mental Health 49
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Table 3. Response strategies employed by daughters and parents
when experiencing goal differences in daily care.
Response strategy Daughters Parents
Total
citations
in the sample
Let it go or
apologize, and
walk away
71 (n D 17) 82 (n D 19) 153
Okay step away from this one [Laughs]
(Daughter, 1113)
I let it go…I don’t worry about things I can’t
change, only what I can (Parent, 1115)
Reason with other
or talk it out
96 (n D 17) 37 (n D 16) 133
I said, ‘…even in an emergency I can’t even get
there, you know in a short amount of time.’ So
there has to be somebody 7 days a week and
there has to be somebody 4 days double time
80. and that’s what…the nurses have assessed
(Daughter, 1111)
Well she’s a type who needs an explanation. She
needs an intellectual discussion (Parent, 1106)
Continue to act on
own ideas or
behaviors
49 (n D 13) 58 (n D 14) 107
We just keep butting heads it doesn’t get nasty.
It doesn’t get mean. It just gets like whose
going to hold their ground the longest
(Daughter, 1117)
Sometimes she’ll say, ‘Oh you don’t have to wear
that. Wear something better.’ ‘No, I don’t want to
wear something better.’ But I end up wearing
what I want (Parent, 1103)
Argue or yell 24 (n D 12) 37 (n D 12) 61
Maybe I didn’t when I was little, but I’m not
little anymore, so I do [argue/yell] (Daughter,
1119)
We actually sort of had a…blow up this weekend…I
was kind of blind-sighted when she started to
basically yell at me that I hadn’t come over or
something you know, early enough to help her
(Daughter about parent, 1116)
Get upset 21 (n D 10) 25 (n D 17) 46
She’s not happy (Parent about daughter, 1118) Well, I kind of
81. said a few things and I cried and got
upset and she was upset (Parent, 1104)
Brainstorm a new
strategy to
accomplish
request
12 (n D 8) 12 (n D 6) 24
I’m like, ‘Yea, but not really, let’s look at it’…
And say, ‘Well, so if you’re out on, you know
you’re going to be out on Tuesday, your
doctor’s appointment’s two hours, check the
movie schedule the day before, maybe you go
from the doctor’s office to the movies’
(Daughter, 1112)
With the bathroom, the concession was he now uses
the potty seat in the hallway or in the den or
wherever he is, that was his concession, because
he was saying by the time I get upstairs I don’t
have to go anymore (Daughter about parent,
1117)
Wait and ask
again later or
another day
12 (n D 7) 8 (n D 4) 20
I mean I just walk away from it until the next
morning and then just start over again
(Daughter, 1119)
82. Well I just kind of let it slide, but I know it is going
to come up again because it’s the same problem
and you know it hasn’t been solved (Parent, 1105)
Use humor to
distill tension
7 (n D 3) 6 (n D 4) 13
And this time around, [I] just made a joke, ‘Oh
okay, good you could use a third or fourth
short sleeve blue blouse, I’ll put it in the short
sleeve blue blouse section of the closet,’ you
know and so we’re both laughing, joking, it’s
funny (Daughter, 1107)
Sometimes we’ll make like little jokey comments
about, you know, ‘Boy that was a lot of noise, and
I was biting my tongue’ (Parent, 1104)
Re-word the
request
differently
8 (n D 4) 1 (n D 1) 9
I just try to do it in a way that I remind her or I
just make a suggestion and she’s more
receptive to that then somebody telling her,
‘You need to do this and you’re not doing
this’ (Daughter, 1113)
She’ll try to keep bringing it up and then we just
keep pushing it back down (Daughter about
parent, 1109)
83. Get someone else
to ask
6 (n D 3) 0 (n D 0) 6
It’s almost like she has to validate what I say…
Like I was making her walk, like she didn’t
really need exercise. Well when the therapist
came and said, Yea, this is not far and there’s
no reason why you can’t maneuver this,
’cause you’re going to make that knee stiffer
than you’ll never be able to walk again’
(Daughter, 1101)
Note: Numbers in each cell represent the frequency the strategy
presented in the transcripts; the values for n represent the
number of transcripts the
response strategies were cited in for daughters or parents
respectively. Each comment is followed with a descriptor of
whether a daughter or parent made
the remark and within which dyad the individual was from.
Numbers reflect random values given to each dyad for readers
to be able to link responses of
daughters and parents within a single family.
50 A.R. Heid et al.
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Daughters considered health and safety as paramount
needs in care, while parents did not talk about their need
for safety. A few parents referenced their concern about
the risk of having an accident (n D 3 parents), but more
were concerned about being a burden to their daughters
(n D 6 parents).
That’s the hardest part, being a burden. I used to drive
myself; I used to go to the market, now I can’t do any of
that (Parent, 1115).
In these instances, parents talked about letting their
requests go to avoid adding stress to their daughters’ lives.
Dyadic responses to navigating goal differences and per-
ceived persistence, insistence, or resistance
All 20 participants described instances of goal differences
in daily care and specifically cited an example of the par-
ent being perceived as insisting and/or persisting in their
86. ways or opinions in attempting to accomplish a care goal,
or acting in a way that is commonly attributed to stub-
bornness. Dyads described such instances in regard to
daily care needs, such as parents insisting on doing physi-
cally challenging activities, personal care, or not changing
spending habits, as well as larger decisions such as mov-
ing to a new location or using a safety device. There were
dyad-to-dyad differences in how these behaviors were
navigated. Two examples are presented in Figure 1.
Figure 1 first depicts an instance where a daughter
describes the older parent as making a request (i.e., act-
ing), but the parent’s request is then met with resistance
on part of the daughter, and the parent reacts to assert her
intentions. At this stage, the daughter attempts to reason
with her parent and the parent relinquishes her request.
However, in the second instance, we see a process
whereby the older parent acts, meets some resistance, so
then reacts, whereby the child reasons with the parent, but
87. then the older adult continues to act on her own impulses.
In this latter case, the child then lets go of her request and
the elder’s goal is met. Ultimately to resolve conflicts,
dyads referenced that one or the other individual walked
away from the situation or let go of one’s request in order
to reach a resolution (n D 63 citations).
The interviewer did not prompt dyad members to
reflect on scenarios that the other person mentioned. How-
ever, in examining within dyad accounts around naviga-
tion of everyday goal differences, some families did
mention the same scenario. In these instances, daughters
and parents described similar response strategies to the
conflict (i.e., brainstorming a new solution) but also some
differences in interpretation by listing additional strategies
used (i.e., parent continued insistence).
A lot of times it’s too hot or it’s too cold back there. I’ve
tried to do different things to make adjustments but…she
wants to put in a certain type of air conditioning unit.
Now that’s in the front of our house and my husband and
I have certain reservations about that. So that’s a point of
conflict where you know she’ll try to keep bringing it up
88. and then we just keep pushing it back down. I’ve tried to
get a portable unit; it made too much noise… She tries to
justify how it can be done to try to make it fit within our,
you know, accepting it. ‘Oh, well we can hide the unit in
the landscaping,’ and we’re just like, ‘No’ (Daughter,
1120).
We considered putting an air conditioner in here but it
would be the air conditioner where there would be another
little unit outside… And my son-in-law, didn’t really…
want that on the house… and I was like, ‘Geez, I didn’t
know that.’ So, then we started to explore other avenues,
so it wasn’t a problem, you know it was just a disagree-
ment that was you know averted because I didn’t realize
he was against having that put on… .We even got…this
portable air-conditioner thing that you put water on and
put water in (Parent 1120).
Figure 1. Example patterns of responses to goal differences in
care.
Example 1: She’ll say, ‘Oh well you know, can’t you go to the
library and get me these books?’ And I said, ‘Mom I can’t go
because I
need to, you know the weather’s turned bad, I need to go get
some food and things like that.’ Like she may not realize what’s
going on
outside to drive in, and I’ll say, ‘The library’s in the total
opposite direction.’ Like so, if I explain things to her, she’s
pretty much,
‘Right’ (Daughter, 1101).
Example 2: Well when they talked to me about going home,
about leaving rehab I said, ‘I’m going home.’ And she said,
‘No, you’re not,
you’re going to my house.’ And I said, ‘You know I’m not, I’m
going home.’ And I came home (Parent, 1118).
Note: Resistance refers to a difference in care goals.
89. Aging & Mental Health 51
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Discussion
This study sought to articulate how older adults influence
their daily care, how adult daughters respond to such
influence, and how family dyads navigate differences in
care goals. The findings demonstrate the difficulties older
parents and their adult daughters experience when navi-
gating care issues and the complex patterns of response
these individuals employ on a day-to-day basis in manag-
91. ing care. The results further our understanding of how
families respond to differences in care goals and carry
implications for how we can support families in providing
person-centered, or family-centered care, to older
relatives.
First, older parents appear to most commonly influ-
ence their care with adult daughters by being involved in
daily decision-making, finding agreement with their
daughter, and through passive response strategies in the
face of conflict (i.e., letting go of their request). In line
with previous work, parents in this study varied from one
another in their desire to be involved in decision-making
(Bastiaens, Van Royen, Pavlic, Raposo, & Baker, 2007;
Flynn, Smith, & Vanness, 2006). However, almost all par-
ticipants expressed the importance of maximizing the
parent’s independence and involvement in care. Parents
further influenced care when their requests were in agree-
ment with their daughters, a finding similar to that of Har-
92. nett (2010) with caregivers in nursing homes. When
parents and daughters had a shared goal, requests were
honored through collaboration. However, when faced
with differences in care goals, parents’ active attempts to
overtly achieve a goal-based outcome were often met
with reasoning by the daughter for why their behavior
should be reconsidered. Parents faced choices in these
instances of whether to continue to act on their goal or to
step back to avoid further conflict. In such instances,
parents most frequently described a process of stepping
back and letting their request go.
At first glance, such responses by parents of letting
their requests go to allow their daughters’ requests to be
honored seemingly relinquishes parents’ influence.
Daughters have great power in decision-making (Pyke,
1999; Wilkinson, 2001), and therefore may be using that
power to influence their parents’ actions and adjust their
parents’ goals. However, in line with the lifespan theory
93. of control and previous research, this strategy may repre-
sent an older adult’s attempt to assert secondary control in
a tense situation, relinquishing their attempts to overtly
control the outcome and instead relying on cognitive reap-
praisals of the situation to reconcile the difference in their
goals and the outcome (Heckhausen & Schulz, 1995). In
this regard, indirect control strategies, such as letting go,
could be viewed as a way to remain in control. Haley
(1963) describes similar situations where one person in a
relationship has less power than the other, but is able to
exert control through a paradoxical communication, i.e.,
by saying ‘I give you control,’ the person in effect retains
control. Findings are consistent with prior work that dem-
onstrates that older people are more likely to use loyalty
strategies than younger adults when faced with
relationship conflict (Birditt & Fingerman, 2005), and that
older adults often expect families to make long-term care
decisions as a means of extended autonomy (High, 1988).
94. Thus, it may be an adaptive strategy by older adults to
step away from tension when there are differences in
goals.
However, further work is needed to examine differen-
ces in definitions of what a resolution is or means or the
salience of a given goal for a given person. For older
adults, their use of passive or indirect response strategies
may carry a different meaning for them than it does for
daughters or may seem preferable in some instances more
so than others. Older parents may fear a loss of a relation-
ship with family members, particularly adult daughters
who are providing assistance, and therefore have the goal
of keeping the ‘waters smooth’ or ‘being easy,’ particu-
larly when a goal is low in importance (N. Pope, personal
communication, 7 November 2014). While an initial goal
for older adults may be a specified outcome (i.e., to have a
book picked up from the library), upon meeting resis-
tance, their goals may actually change to just wanting to
95. have a positive interaction with their daughters, thereby
changing their action and request. The initial pushback on
their first goal may no longer matter to older adults and
not carry implications for diminishing their requests.
Regardless, the evidence suggests that older adults use
more passive, indirect ways of influencing care outcomes,
as compared to a more active, reasoning approach used by
daughters. These findings carry implications for future
research, everyday care decisions, and complex negotia-
tions by dyads such as end-of-life decisions (Black et al.,
2009; Ditto et al., 2001).
Second, the finding that daughters cite a ‘best inter-
ests’ perspective is interesting as it may offer a rationale
for family caregivers’ actions. On a situation-by-situation
basis, daughters appear to practice flexibility in determin-
ing if the perceived negative outcome outweighs the pos-
sible benefit of the older adult making his/her own
decision. This is in contrast to evidence found with formal
96. caregivers, where the ‘best interest’ is often defined by the
institution’s rules to preserve safety and institutional effi-
ciency (Ulsperger & Knottneurs, 2011). When there are
differences in goals and daughters believe that a health or
safety-related issue is involved, they step in. This is con-
sistent with previous research that daughters influence
their mothers’ care with major health, finance, and hous-
ing decisions (Pratt et al., 1989) and that the use of more
direct communication strategies by daughters is perceived
as more effective for addressing older adults’ behaviors
(Morgan & Hummert, 2000). Yet, we do not know
whether parents agree with this action � is it a response
by daughters based in worry to assure health and safety or
do parents also admit it is needed? More work is needed
to clarify the resolution in these instances in order to
determine whether both persons’ needs and values are
being honored in care.
Given that the literature demonstrates significant dis-
crepancies within families in understanding older adults’
97. preferences (i.e., Reamy, Kim, Zarit, & Whitlatch, 2011),
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the findings here support a need to determine what the
older adult would define as his or her own ‘best interests.’
If older adults also value preservation of their lives, then
daughters are helping to buffer against those environmen-
tal risks. But if older adults put precedence on the value of
doing as much as possible for as long as possible, over
length of life, room for intervention exists, as the process
