Aging Clin Exp Res
DOI 10.1007/s40520-015-0413-5
ORIGINAL ARTICLE
Toward the processing speed theory of activities of daily living
in healthy aging: normative data of the Functional Activities
Questionnaire
Ondrej Bezdicek1,2 • Hana Stepankova1 • Lenka Martinec Novakova1,3
Miloslav Kopecek1
•
Received: 14 May 2015 / Accepted: 3 July 2015
Ó Springer International Publishing Switzerland 2015
Abstract
Background The aim of this study was to describe an
instrumental activities of daily living (IADL) measure:
Functional Activities Questionnaire (FAQ), which is often
used in clinical settings as a self- or informant-based
measure of IADL. However, the FAQ’s relationship with
age or education in healthy aging has not been investigated.
Methods FAQ and a neuropsychological battery were
administered to old and very old Czech adults (n = 540).
Participants met strict inclusion criteria for the absence of
any active or past neurodegenerative disorders.
Results FAQ is significantly dependent on age and education, but not gender. Younger subjects and those with
higher education have the lowest scores in the FAQ and
show a higher degree of functional independence. FAQ
moderately correlates with speed of processing, visual–
perceptual and executive functions measures (Trail Making
Tests, Stroop Test) and depressive symptoms, but not with
episodic memory (WMS-III logical memory). We present
normative percentile values for different age groups from
60 to 96 years of age.
& Ondrej Bezdicek
[email protected]
1
National Institute of Mental Health, Klecany, Czech Republic
2
Department of Neurology and Centre of Clinical
Neuroscience, First Faculty of Medicine and General
University Hospital in Prague, Charles University in Prague,
Kateřinská 30, 128 21 Praha 2, Czech Republic
3
Department of Anthropology, Faculty of Humanities, Charles
University in Prague, Praha 5, Czech Republic
Conclusions The present study shows conclusively that
IADL measures, such as FAQ, should not be used without
appropriate normative data, especially in very old adults.
Thus, it has the ability to differentiate functional dependence due to age-related decline from neurodegenerative
disease.
Keywords Activities of daily living Instrumental
activities of daily living Normal aging Normative data Questionnaire
Introduction
Activities of daily living (ADL) are a complex system of
activities required for continued functional independence.
They can be divided into basic ADL (BADL), including
bathing, personal hygiene, dressing, grooming, eating, and
toileting; and more complex tasks, instrumental ADL
(IADL), which include housekeeping, laundry, meal
preparation, medication management, shopping and transportation. Intact BADL are essential for health and safety
and IADL are necessary prerequisites of an active social
life [1–3].
ADL measurement has been shown fruitful in the
diagnostics of mild cognitive impairment (MCI) and
dementia. MCI is a construct for a stage or cognitive
status between normal aging and very early dementia [4].
None or minimal impairment in ADL based on clinical
interviews with the patient or informant are one of the
core criteria in MCI diagnostics [5] and ADL impairments
are an essential criterion when determining all-cause
dementia [6]. However, as noted by Sikkes et al. [7], data
on psychometric properties of ADL measurement instruments for dementia are insufficient and improvements
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Aging Clin Exp Res
regarding their validity, reliability and internal structure
are needed to justify their use in clinical settings. We
suppose that this improvement cannot be achieved without normative data studies on healthy aging adults. Normative data show the range of performance on a
particular instrument based on the performance of healthy
individuals stratified by age, education, gender and other
socio-demographic characteristics. These data establish
the standard against which individual performances can
be compared and are of critical importance for the
meaningful interpretation of questionnaire scores [8].
The Functional Activities Questionnaire (FAQ) was
originally developed by Pfeffer et al. [9] as a self-reported
questionnaire for the differentiation of functional independence in normal and demented adults. FAQ is composed of ten items; the ability to perform each activity is
rated from 0 (normal) to 3 (dependent). Scores range from
0 to 30 points. The original report describing the FAQ
used two different criteria: dependency (i.e., item
score = 3) in at least two categories of IADLs and a total
score C5 used in conjunction with a battery of neuropsychological testing [7]. A cutoff of 9 (dependent in 3
or more activities) is recommended to indicate impaired
function and possible cognitive impairment. The optimal
cutoff to distinguish between demented and non-demented
subjects ranges from C5 [10] to C8 points [11, 12]. This
is similar to the results of the Czech validation study of
FAQ on healthy adults, in which levels for psychometrically defined MCI (B-1.5 SD) would be [5 in self-report
and [3 in informant report, and in dementia (B-2.5
SD) C6 and [6 points [13]. FAQ had the highest discriminatory potential among other self-reported IADL
scales for the differentiation of subjects with dementia
from those without dementia [11]. FAQ was sensitive not
only in subjects with dementia due to Alzheimer’s disease
(AD), but also in MCI due to AD with high predictive
potential for the conversion from MCI to dementia [14–
16]. Even though FAQ was not originally developed as a
disease-specific and informant-based [7] measure, in
recent years it has been successfully applied to assess
MCI and dementia due to AD or other etiologies [15–17];
in addition, self- and informant-based versions were
successfully used with the replication of discrepancy
scores (informant-based score minus self-reported score)
in patients and healthy population [13, 15]. Based on
previous IADL findings, we wish to emphasize that
regardless of the measurement scale (for a review of
measurement properties and problems see [7, 18–20]),
there is still a lack of information about the influence of
very high age (85?) on self-reported IADL in normal
aging. Even though healthy older subjects restricted in at
least two IADL at baseline have a higher risk of dementia
10 years later (as measured by the Lawton scale [21]), the
123
issue of whether or not healthy older and very old adults
report some IADL deficits remains unclear.
The goal of the current cross-sectional study was to
identify differences in levels of self-reported IADL deficits
in older and very old (85?) Czech healthy adults to determine the influence of age on IADL in normal aging and to
present psychometric analysis of FAQ with normative
percentile values to support its use in clinical settings.
Methods
Participants
The current report is part of a longitudinal project [National Normative Study of Cognitive Determinants of
Healthy Aging (NANOK)]. We recruited a convenience
sample of independent senior volunteers through advertisements on the institutional website, at post offices and
general practitioners’ clinics; we used non-random quota
sampling in 12 of the 14 regions in the Czech Republic.
The numbers in each socio-demographic category were
balanced based on the previous normative study for older
adults (5-year age intervals; balanced ratios of women to
men and of lower to higher education; [22, 23]). Education classification was based on the lower education level
of 8–12 years of formal education and the higher education level (12 or more years; see Table 1). There were
predefined counts in each subgroup (1:1 for men/women
and education low/high). Inclusion criteria consisted of
age C60 years; exclusion criteria consisted of any neurodegenerative disease (e.g., dementia due to AD,
Parkinson disease, MCI due to AD), head trauma with
unconsciousness, stroke, alcohol or substance abuse history, current radiotherapy or chemotherapy, aphasia, epilepsy, major depression and/or other major psychiatric
disorders, unstable medical illness and/or uncorrected
visual or hearing disorder. Five hundred and sixty-eight
participants (aged 60–96 years) who met inclusion criteria
and provided informed consent were enrolled in the study.
To guard against including persons with emerging
dementia or MCI and differentiate the effect of physiological aging from the effect of pathological aging, an
FAQ additional exclusion criterion including a clinical
assessment in which having scores two standard deviations units (SD) below the entire sample in any two of the
following tests were applied: Trail Making Test, Part B
(TMT-B) and a composite score of verbal letter and
animal fluency or a high score obtained on the short
Geriatric Depression Scale (GDS-15; score C10). Using
these additional criteria, 14 participants were excluded. 14
other participants were excluded because Mini-Mental
State Examination (MMSE) or Montreal Cognitive
Aging Clin Exp Res
Table 1 Demographic data of the normative sample (N = 540)
Frequency
%
Age
60–64
81
15.0
65–69
77
14.3
70–74
91
16.9
75–79
84
15.6
80–84
98
18.1
85–96
109
20.2
501
92.8
39
7.2
Men
248
45.9
Women
Handedness
Right-handed
Other
Sex
292
54.1
Marital status
Single
13
2.4
With partner
23
4.3
Married
233
43.1
Widowed
214
39.6
Divorced
57
10.6
Lower
254
47.0
Higher
286
53.0
Education
Lower means a level of formal education as measured by the number
of years of schooling (8–12 years of formal education), higher means
college level or higher level of education (12 and more years with a
state graduation examination after the 12th year). Other in handedness left-handed, ambidextrous or retrained right-handed (is a person
who was born left-handed but was taught systematically to write with
his/her non-dominant right hand)
Assessment (MoCA) scores were not obtained. The final
sample consisted of 540 older adults (Table 1).
Materials and procedure
All participants completed a neuropsychological battery
including the FAQ. Participants underwent an individual
assessment in a professional’s office or at home according to
their preference. To assist with identifying early cognitive
impairment [24], the assessment protocol involved the MiniMental State Examination [25, 26] and Montreal Cognitive
Assessment [27, 28]. Other administered tests included the
Czech version of the Philadelphia Verbal Learning Test
[czP(r)VLT] [23], the Prague Stroop Test [29, 30], Geriatric
Depression Scale-15 items [31], letter and semantic fluency
tests [32], WAIS-III Digit Span and Digit Symbol Coding
subtest [33], Trail Making Tests, Parts A and B [34], the
Boston Naming Test, 30-item version [35] and the WMS-III
Logical Memory (LM) test (immediate and delayed recall of
the first story only [36]). The Institutional Review Board of
the National Institute of Mental Health/Prague Psychiatric
Center approved the study protocol.
The Czech FAQ was translated from the original [9] and
validated on a sample of the Czech population (self- and
informant-based report including test–retest reliability [13]
and percentile values on healthy adults). The validity study
established that the FAQ is a suitable instrument for selfand informant-based IADL measurement and may routinely be used in the assessment of IADL and in further
research of IADL in clinical settings.
Statistical analyses
As the FAQ total scores were skewed (skew of 2.15) with
a high incidence of zero values (49.6 %), we decided to
analyze the data with non-parametric methods: Wilcoxon
rank sum test for comparing two samples (effect of
gender or education) and Spearman’s rank correlation
coefficients for evaluating relationships with continuous
variables (age and other test measures). Because the high
incidence of ties may affect the non-parametric method,
we considered two additional statistical approaches. The
a-level for testing significance was set to 0.05. All analyses were performed in R [37].
Results
The influence of demographic variables
The majority of participants obtained a total score of 0 (268
participants, 49.6 %). The mean score was 2.43 (median = 1,
SD = 4.17,
75 %-quantile = 3,
90 %-quantile = 8,
max = 18). The FAQ score increased with age (Spearman
q = 0.348, p \ 0.001). When we aggregated the participants
into groups by 5-year age intervals, reflecting the recruitment
scheme, we found the scores across age groups significantly
differed [Kruskal–Wallis v2(5) = 81.7, p \ 0.001]. In a post
hoc analysis, we compared the scores in neighboring age
groups, and the only significant difference was between the
oldest two groups (80–84 vs. 85?; Wilcoxon W = 3273.5,
p \ 0.001 after Bonferroni correction for five comparisons).
We found no effect of gender (men: mean = 2.78, median = 1; women: mean = 2.13, median = 0; Wilcoxon
W = 39,066, p = 0.09). In accordance with our classification
of normative data into older (60–74), old (75–84) and very old
(85?), a re-analysis of group differences provided the same
results [Kruskal–Wallis v2(2) = 81.4, p \ 0.001] [38, 39] and
in a post hoc analysis there were significant differences
between all three age groups (p \ 0.001 after Bonferroni correction for two comparisons).
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Aging Clin Exp Res
Regarding education, subjects with higher education
obtained lower scores (education high: mean = 1.86,
median = 0; low: mean = 3.07, median = 1; Wilcoxon
W = 43,726, p \ 0.001).
Correlations with other tests of cognitive functioning
We tested the relationship of FAQ with other cognitive
measures (see Tables 2, 3). We found significant correlations with the Mini-Mental State Examination (MMSE)
and Montreal Cognitive Assessment (MoCA). Further
significant and medium correlations were found between
FAQ and Philadelphia Verbal Learning Test (PVLT), Trail
Making Test (TMT), Prague Stroop Test (PST), WAIS-III
Symbol Digit Coding and semantic verbal fluency (animals). Correlations with other tests were significant, but
low. Interestingly, the correlation with the WMS-III Logical Memory Immediate and Delayed Free Recall was nonsignificant. Also a medium significant correlation between
FAQ and the depressive symptoms scale (GDS-15) was
notable. To show that the correlations between FAQ and
some tests of cognitive functioning are not dependent on
depressive symptoms measured by GDS-15, we also present partial correlations between the selected tests of cognitive functioning and the FAQ (Table 2). To show what
happens if only those with non-zero values are considered
(Table 2), we see that the correlations with speed of processing an executive functions measures remain the same
or are even higher and still highly significant. To prove that
people with FAQ = 0 (i.e., no IADL impairment), when
being uncertain about the effect of having highly skewed
scores with the majority being zero, a pattern of better
cognitive performance (Table 3) with highly significant
differences in most of the tests of cognitive functioning
was shown.
Because the high incidence of ties may affect the nonparametric method, we added two additional approaches.
First, we ran an alternative parametric analysis for the effects
of age, gender and education and found identical pattern of
significance in the results. Second, we calculated correlations with other test outcomes with and without the zero
FAQ scores and report how it affected results (Table 2).
Table 2 Spearman correlations of FAQ with other tests of cognitive functioning in all subjects (N = 540) and without FAQ = 0 (N = 268)
Spearman q (N = 540)
czP(r)VLT-12 list A trial 1–5
20.209
czP(r)VLT-12 Long delay free recall
20.207
TMT-A
TMT-B
0.363
0.321
Partial correlation
0.422
0.251
p
Spearman q (N = 268)
\0.0005
20.143
\0.0005
20.145
\0.0005
\0.0005
0.469
0.368
p
Change
0.125
sig ) ns
0.125
sig ) ns
\0.0005
\0.0005
sig ) sig
sig ) sig
WMS-III LM immediate recall
20.020
0.648
20.019
0.757
ns ) ns
WMS-III LM long delayed recall
20.071
0.194
20.074
0.678
ns ) ns
MMSE
20.208
\0.0005
20.234
0.001
sig ) sig
MoCA
20.242
\0.0005
20.146
0.125
sig ) ns
PST-D
0.412
0.431
\0.0005
0.433
\0.0005
sig ) sig
PST-W
0.411
0.460
\0.0005
0.443
\0.0005
sig ) sig
PST-C
0.372
0.329
\0.0005
0.414
\0.0005
sig ) sig
0.069
20.066
0.678
ns ) ns
20.318
\0.0005
20.343
\0.0005
sig ) sig
BNT-30
20.098
SF (animals)
20.364
SF (plants)
20.263
\0.0005
20.169
0.054
sig ) ns
LF (P)
20.177
\0.0005
20.120
0.193
sig ) ns
LF (S)
20.191
\0.0005
20.209
\0.0005
sig ) sig
WAIS-III DS forward
20.211
\0.0005
20.316
\0.0005
sig ) sig
0.001
20.134
0.138
sig ) ns
\0.0005
\0.0005
20.351
0.234
\0.0005
0.001
sig ) sig
sig ) sig
WAIS-III DS backward
20.163
WAIS-III digit symbol coding
GDS-15
20.359
0.379
20.259
czP(r)VLT-12: Philadelphia (Repeatable) Verbal Learning Test Czech version; TMT: Trail Making Test (TMT—A and B, time in seconds);
WMS: Wechsler Memory Scale, LM: Logical Memory; Immediate and Delayed recall (0–25 points); MMSE: Mini-Mental State Examination
(0–30 points); MoCA: Montreal Cognitive Assessment (0–30 points); Prague Stroop Test (PST; time in seconds; D = dots, W = words,
C = interference condition); Boston Naming Test (BNT-30); Semantic and Letter fluency (animals ? plants and letters P ? S = total word
count); Wechsler Adult Intelligence Scale, Third Revision Digit span forward (0–16 points) and backward (0–14); brief Geriatric Depression
Scale (GDS-15, 0–15 points). Partial correlations are parametric contrary to Spearman q. Correlation values with corresponding p \ 0.0005 are
printed in bold. sig ) ns means change in significance level a B 0.05 after excluding those with FAQ = 0 (no IADL impairment)
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Aging Clin Exp Res
Table 3 A comparison between the cognitive performance in FAQ = 0 (N = 268) and FAQ C 1 (N = 272)
Median (FAQ = 0)
Median (FAQ C 1)
p (uncorrected) Wilcoxon signed rank test
38
35
\0.0005
8
7
\0.0005
44.5
56
\0.0005
112
152
\0.0005
10
10
0.699
9
8
0.199
MMSE
28
27
\0.0005
MoCA
26
24
\0.0005
PST-D
14
18
\0.0005
PST-W
19
22
\0.0005
PST-C
BNT-30
35
29
44
29
\0.0005
0.046
SF (animals)
22
17
\0.0005
SF (plants)
17
15
\0.0005
LF (P)
14
13
\0.0005
LF (S)
14
12
0.001
WAIS-III DS forward
8
8
0.001
WAIS-III DS backwards
6
5
0.001
50
40
\0.0005
1
3
\0.0005
czP(r)VLT-12 list A trial 1–5
czP(r)VLT-12 long delay free recall
TMT-A
TMT-B
WMS-III LM immediate recall
WMS-III LM long delayed Recall
WAIS-III digit symbol coding
GDS-15
czP(r)VLT-12: Philadelphia (repeatable) Verbal Learning Test Czech version; TMT: Trail Making Test (TMT—A and B, time in seconds);
WMS: Wechsler Memory Scale, LM: Logical Memory; Immediate and Delayed recall (0–25 points); MMSE: Mini-Mental State Examination
(0–30 points); MoCA: Montreal Cognitive Assessment (0–30 points); Prague Stroop Test (PST; time in seconds; D = dots, W = words,
C = interference condition); Boston Naming Test (BNT-30); Semantic and Letter fluency (animals ? plants and letters P ? S = total word
count); Wechsler Adult Intelligence Scale, Third Revision Digit span forward (0–16 points) and backward (0–14); brief Geriatric Depression
Scale (GDS-15, 0–15 points)
Item analysis of the FAQ
Mean item scores are shown in Table 4. The lowest scores
were found in items 5–8 (range 0.09–0.14 on 0–3 scale).
The correlations with total scores corrected for the item
score ranged from 0.39 to 0.57. The internal consistency of
the FAQ scale was Cronbach a = 0.88.
Normative data in the Czech population of older
adults
In Table 5, we present percentile values for three different
age groups [38, 39] from 60 to 96 years of age to show the
prominent influence of age on IADLs in a healthy aging
population.
Discussion
The current study aimed to describe the psychometric
properties of FAQ and document any age-related decline in
IADL in healthy older and very old adults. We found that
FAQ was significantly dependent of age and education, but
not gender. The higher the subject’s age, the more were the
deficiencies found in IADL. Similarly, the lower the subject’s education, the less functional was the independence
found in older adults.
One of the key goals in our study was to expand
knowledge about the age-related decline in IADL in healthy aging. First, this issue is theoretically important and
could be linked with processing speed theory of healthy
cognitive aging [40], one of the major contemporary theories of healthy aging. Speed deficit theory supposes that
cognitive deficits reflect a general reduction in the speed of
cognitive processes due to age-related decline and that
cognitive performance is degraded when processing is slow
because the products of early processing may no longer be
available when later processing is complete (i.e., relevant
operations cannot be successfully executed) [40, 41]. If
IADL are significantly mediated by speed of processing,
then FAQ, as an IADL measure, should correlate with
some basic speed of processing measures even in healthy
aging. The present study corroborates this hypothesis: We
found that FAQ has medium correlations with PST,
semantic verbal fluency, WAIS-III Digit Symbol Coding
and TMT-A and TMT-B, which is in accordance with
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Aging Clin Exp Res
previous longitudinal studies in non-demented persons
[42]. However, none of these test measures can be taken as
purely ‘‘speed of processing’’ indicators; they all measure a
wide range of visual–perceptual and executive functions as
well. Especially the subtests TMT-B and PST-C are considered strongly driven by executive functions, engaging
especially set shifting and inhibition [43, 44]. Furthermore,
FAQ has low, but still highly significant correlations with
measures of general cognitive functioning, such as MMSE
Table 4 Item analysis of the FAQ
q (scale-item)
Item
M
SD
Min
Max
1
0.285
0.697
0
3
0.520
2
0.409
0.790
0
3
0.570
3
0.291
0.735
0
3
0.568
4
0.254
0.610
0
3
0.503
5
0.093
0.359
0
2
0.448
6
0.169
0.509
0
3
0.474
7
0.111
0.407
0
3
0.424
8
0.139
0.469
0
3
0.429
9
0.298
0.611
0
3
0.394
10
0.380
0.830
0
3
0.541
Spearman correlations (q) show the correlation of an item score with
the FAQ total score corrected for the particular item
The highest and lowest scale–item correlations are printed in bold
M mean, SD standard deviation
Table 5 Normative percentile
values of the FAQ based on
self-report in older and very old
adults
or MoCA or memory functioning measures, such as
czP(r)VLT-12 (total capacity to learn and delayed retention). On the other hand, neither Immediate, nor Delayed
Recall in WMS-III Logical Memory correlated with FAQ.
More importantly, these correlations remained stable even
after partializing the influence of depressive symptoms and
even after excluding those with FAQ = 0 (i.e., subjects
without IADL impairment). This finding provides a
response to the idea what happens if only those with nonzero values are considered? We see that there is no change
in the correlations after their exclusion and they are even
slightly higher. This finding is further supported by the
highly significant differences between those with FAQ = 0
(no IADL impairment) and those with FAQ C1 (slight
problems with some IADL activities). The subjects with no
IADL impairment are significantly better in tests of cognitive functioning and have lower level of depressive
symptoms. Again, these include measures pertaining to
speed of processing and executive functions measures,
such as TMT-A, TMT-B, PST-D, PST-W, PST-C, SF
(animals), SF (plants) and WAIS-III Digit Symbol Coding.
Item analysis is essential for establishing content
validity of the scale [45] as it furnishes us with information
on how each item relates to overall FAQ performance. We
found that overall FAQ scale–item correlations can be
characterized as discriminating (range 0.394–0.570) with
all items reaching the standard cutoff of [0.3. None of the
FAQ raw score
60- to 74-year-old (N = 249)
75- to 84-year-old (N = 182)
85? year-old (N = 109)
0
100
100
100
1
38
52
75
2
20
35
67
3
13
26
57
4
8
21
54
5
5
15
47
6
4
15
41
7
8
3
2
12
9
38
36
9
1
8
32
10
0
8
30
11
0
6
28
12
0
6
25
13
0
4
21
14
0
3
19
15
0
3
16
16
0
2
10
17
0
1
6
18
0
1
2
19
0
0
0
20
0
0
0
Percentage values were rounded to an integer
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Aging Clin Exp Res
items had a negative value or failed to correlate with the
total FAQ score, thus suggesting that FAQ can be considered a content-validated questionnaire.
As suggested by Sikkes et al. [7] for the psychometric
analysis of IADL questionnaires, these measures can also
be taken as indicators of the convergent and divergent
validity of FAQ: the influences of IADL are paradoxically
not dependent on the classical episodic memory measures
(WMS-III LM).
We see that FAQ is preponderantly dependent on the
speed of processing and visual–perceptual rather than more
executively driven measures, such as TMT-A (vs. to a
lesser extent on TMT-B) or PST-D or W (vs. to a lesser
extent on PST-C interference condition) and Digit Symbol
Coding (the faster the speed of processing, the better is the
functional independence) and that this correlation remains
even after controlling for the influence of depressive
symptoms. From the presented percentile values, we see
that functional independence declined due to age especially
in very old adults (85?) and that it is a finding that needs to
be highlighted (80–84 vs. 85? groups differ significantly in
comparison to other age groups and the re-analysis based
on three age groups 60–74, 75–84, 85? provided identical
results). Furthermore, depressive symptoms also seem to
play a significant role in the degree of functional independence, as depressive symptoms show a similar association with FAQ as speed of processing and executive
functions measures.
To our knowledge, no previous study has shown so
conclusively that IADL declines with age in healthy aging
adults and that IADL measurement requires normative data
to differentiate functional dependence due to normal aging
from functional dependency due to the onset of brain
neurodegenerative processes. Moreover, IADL seem to be
significantly related to several classical speed of processing
and executive functions measures independent of depressive symptoms. Overall, the data seem to support a processing speed deficit theory of healthy aging in IADL.
The present study has several limitations. We do not
show informant-based report values in FAQ. Patient’s
caregivers in clinical settings provide such a report and
clearly healthy older persons do not need a caregiver.
Healthy adults are considered a reliable source of information on themselves and data from self-reports are routinely used in psychometric studies [31, 46]. Informantbased FAQ reports are needed when the patient is suffering
from anosognosia of his/her functional deficits and the
informant is the only person who can deliver valid information on IADL of the person [7, 13]. Second, our study
offers no information on minimal important change (MIC),
which is considered substantial in the psychometric analysis of IADL questionnaires [7]. Third, we do not show a
receiver operating characteristic of FAQ in a clinical
population; however, we suppose that the information
about FAQ’s clinical validity on dementia due to AD or
mild cognitive impairment is well documented [15].
Fourth, a volunteer sample could create potential biases
and limit the applicability of our findings to normal age
range. Fifth, our normative data apply only to a population
of old or very old Czech adults.
Conclusions
The current cross-sectional study conclusively shows that
there are significant age-related declines in IADL as measured by FAQ in healthy aging. On the other hand, education seems to have a protective influence on IADL in older
age. We presented percentile values for different age groups
to minimize the influence of age on IADL measurement and
showed item analysis to add missing psychometric information regarding the internal consistency of FAQ. Moreover, we showed that IADL are interconnected with speed
of processing and executive function measures independent
of depressive symptoms in healthy aging, and related these
characteristics to the speed-processing theory of healthy
aging. In conclusion, FAQ can be considered a brief and
content-validated tool with adequate psychometric properties and normative data for the measurement of IADL.
Acknowledgments The authors thank all the external administrators (Eva Biedermannova, Pavla Davidova, Lenka Freharova, Marketa Holubova, Karolina Horakova, Adela Jencova, Olga Kozicka,
Lenka Malkova, Jiri Michalec, Barbora Mnukova, Vlasta Novotna,
Klara Patlichova, Jana Pecinkova, Lucie Prazakova, Ilona Sedmidubska, Lenka Sreibrova, Nina Sterbova, Tomas Vacha, Martin
Vaverka, Zuzana Velkoborska, Michaela Viktorinova, and Tomas
Vilimovsky) and Jiri Lukavsky for his statistical analysis.
Funding The work was supported by grants from the Internal Grant
Agency of Ministry of Health of Czech Republic under grant number
IGA MZCR NT 13145-4/2012 and by the project ‘‘National Institute
of Mental Health (NIMH-CZ)‘‘, under grant number ED2.1.00/
03.0078, and the European Regional Development Fund. LMN is
supported by Charles University Research Centre (UNCE 204004)
and the Ministry of Education, Youth and Sports – Institutional
Support for Longterm Development of Research Organizations—
Charles University, Faculty of Humanities (project PRVOUK P20).
Compliance with ethical standards
Conflict of interest The authors have no conflict of interest to
declare.
Ethical approval All procedures performed in studies involving
human participants were in accordance with the ethical standards of
the institutional and/or national research committee and with the 1964
Helsinki declaration and its later amendments or comparable ethical
standards.
Informed consent Informed consent was obtained from all participants for being included in the study.
123
Aging Clin Exp Res
References
1. Katz S, Ford AB, Moskowitz RW (1963) Studies of Illness in the
aged—the index of ADL—a standardized measure of biological
and psychosocial function. JAMA 185:914–919
2. Lawton MP, Brody EM (1969) Assessment of older people: selfmaintaining and instrumental activities of daily living. Gerontol
9:179–186
3. Galasko D, Bennett D, Sano M (1997) An inventory to assess
activities of daily living for clinical trials in Alzheimer’s disease.
The Alzheimer’s Disease Cooperative Study. Alzheimer Dis
Assoc Disord 11:S33–S39
4. Petersen RC (2004) Mild cognitive impairment as a diagnostic
entity. J Intern Med 256:183–194
5. Grundman M, Petersen RC, Ferris SH (2004) Mild cognitive
impairment can be distinguished from Alzheimer disease and
normal aging for clinical trials. Arch Neurol 61:59–66
6. McKhann GM, Knopman DS, Chertkow H (2011) The diagnosis
of dementia due to Alzheimer’s disease: recommendations from
the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 7:263–269
7. Sikkes SA, de Lange-de Klerk ES, Pijnenburg YA (2009) A
systematic review of instrumental activities of daily living scales
in dementia: room for improvement. J Neurol Neurosurg Psychiatry 80:7–12
8. Lezak MD, Howieson DB, Bigler ED et al (2012) Neuropsychological Assessment, 5th edn. Oxford University Press, Oxford
9. Pfeffer RI, Kurosaki TT, Harrah CH Jr (1982) Measurement of
functional activities in older adults in the community. J Gerontol
37:323–329
10. Castilla-Rilo J, López-Arrieta J, Bermejo-Pareja F (2007)
Instrumental activities of daily living in the screening of dementia
in population studies: a systematic review and meta-analysis. Int J
Geriatr Psychiatry 22:829–836
11. Juva K, Mäkelä M, Erkinjuntti T (1997) Functional assessment
scales in detecting dementia. Age Ageing 26:393–400
12. Mejia S, Gutiérrez LM, Villa AR (2004) Cognition, functional
status, education, and the diagnosis of dementia and mild cognitive impairment in Spanish-speaking elderly. Appl Neuropsychol 11:196–203
13. Bezdicek J, Lukavsky, Preiss M (2011) Functional Activities
Questionnaire, Czech Version—a validation study. Cesk Slov
Neurol N 74:36–42
14. Albert SM, Michaels K, Padilla M (1999) Functional significance
of mild cognitive impairment in elderly patients without a
dementia diagnosis. Am J Geriatr Psychiatry 7:213–220
15. Tabert MH, Albert SM, Borukhova-Milov L (2002) Functional
deficits in patients with mild cognitive impairment: prediction of
AD. Neurology 58:758–764
16. Devanand DP, Liu X, Tabert MH (2008) Combining early
markers strongly predicts conversion from mild cognitive
impairment to Alzheimer’s disease. Biol Psychiatry 64:
871–879
17. Lima-Silva TB, Bahia VS, Nitrini R (2013) Functional status in
behavioral variant frontotemporal dementia: a systematic review.
Biomed Res Int 2013:837120
18. Avlund K (1997) Methodological challenges in measurements of
functional ability in gerontological research. A review. Aging
(Milano) 9:164–174
19. Demers L, Oremus M, Perrault A (2000) Review of outcome
measurement instruments in Alzheimer’s disease drug trials:
psychometric properties of functional and quality of life scales.
J Geriatr Psychiatry Neurol 13:170–180
123
20. Lindeboom R, Vermeulen M, Holman R (2003) Activities of
daily living instruments: optimizing scales for neurologic
assessments. Neurology 60:738–742
21. Pérès K, Helmer C, Amieva H (2008) Natural history of decline
in instrumental activities of daily living performance over the
10 years preceding the clinical diagnosis of dementia: a
prospective population-based study. J Am Geriatr Soc 56:37–44
22. Ivnik RJ, Malec JF, Tangalos EG et al (1990) The AuditoryVerbal Learning Test (AVLT): norms for ages 55 years and
older. Psychol Assess J Consult Clin Psychol 2:304–312
23. Bezdicek O, Libon DJ, Stepankova H (2014) Development,
validity, and normative data study for the 12-word Philadelphia
Verbal Learning Test [czP(r)VLT-12] among older and very old
Czech adults. Clin Neuropsychol 28:1162–1181
24. Steenland NK, Auman CM, Patel PM (2008) Development of a
rapid screening instrument for mild cognitive impairment and
undiagnosed dementia. J Alzheimers Dis 15:419–427
25. Štěpánková H, Nikolai T, Lukavský J et al (2015) Mini-mental
state examination—Czech normative study. Cesk Slov Neurol N
78/111:57–63
26. Folstein MF, Folstein SE, McHugh PR (1975) ‘‘Mini-mental
state’’. A practical method for grading the cognitive state of
patients for the clinician. J Psychiatr Res 12:189–198
27. Nasreddine ZS, Phillips NA, Bédirian V (2005) The Montreal
Cognitive Assessment, MoCA: a brief screening tool for mild
cognitive impairment. J Am Geriatr Soc 53:695–699
28. Bezdicek O, Balabanova P, Havrankova P (2010) A comparison
of the Czech version of the Montreal cognitive assessment test
with the mini mental state examination in identifying cognitive
deficits in parkinson’s disease. Cesk Slov Neurol N 73:150–156
29. Troyer AK, Leach L, Strauss E (2006) Aging and response
inhibition: normative data for the Victoria Stroop Test. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 13:20–35
30. Bezdicek O, Lukavsky J, Stepankova H et al (2015) Prague
Stroop Test: a valid tool for Parkinson’s Disease Mild cognitive
impairment subtyping and normative data in older adults. J Clin
Exp Neuropsychol. doi:10.1080/13803395.2015.1057106
31. Yesavage JA, Brink TL, Rose TL (1983) Development and validation of a geriatric depression screening scale—a preliminaryreport. J Psychiatr Res 17:37–49
32. Nikolai T, Štěpánková H, Michalec J et al (2015) Verbal fluency
tests - Czech normative study for older persons. Cesk Slov Neurol
N 78/111:292–299
33. Wechsler D (2010) Wechslerova inteligenčnı́ škála pro dospělé:
Hogrefe—Testcentrum
34. Bezdicek O, Motak L, Axelrod BN (2012) Czech Version of the
Trail Making Test: normative data and clinical utility. Arch Clin
Neuropsychol 27:906–914
35. Mack WJ, Freed DM, Williams BW (1992) Boston naming test:
shortened versions for use in Alzheimer’s disease. J Gerontol
47:P154–P158
36. Wechsler D (2011) Wechslerova zkrácená paměťová škála—
WMS-IIIa. Hogrefe—Testcentrum, Praha
37. R.C.T. R: A language and environment for statistical computing.
R Foundation for Statistical Computing (2014). http://www.Rproject.org/
38. Evans DA, Funkenstein HH, Albert MS (1989) Prevalence of
Alzheimer’s disease in a community population of older persons.
Higher than previously reported. JAMA 262:2551–2556
39. Garfein AJ, Herzog AR (1995) Robust aging among the youngold, old-old, and oldest-old. J Gerontol B Psychol Sci Soc Sci
50:S77–S87
40. Salthouse TA (1996) The processing-speed theory of adult age
differences in cognition. Psychol Rev 103:403–428
Aging Clin Exp Res
41. Dennis NA, Cabeza R (2008) Neuroimaging of healthy cognitive
aging. In: Craik FIM, Salthouse TA (eds) Handbook of aging and
cognition, 3rd edn. Erlbaum, New Jersey, pp 1-54
42. Dodge HH, Du Y, Saxton JA (2006) Cognitive domains and
trajectories of functional independence in nondemented elderly
persons. J Gerontol A Biol Sci Med Sci 61:1330–1337
43. Kane MJ, Engle RW (2003) Working-memory capacity and the
control of attention: the contributions of goal neglect, response
competition, and task set to Stroop interference. J Exp Psychol
Gen 132:47–70
44. Arbuthnott K, Frank J (2000) Trail making test, part B as a
measure of executive control: validation using a set-switching
paradigm. J Clin Exp Neuropsychol 22:518–528
45. Nunnally JC, Bernstein IH (1994) Psychometric Theory. Third
edn. McGraw-Hill, Inc., New York
46. Knight RG, McMahon J, Green TJ (2004) Some normative and
psychometric data for the geriatric depression scale and the
cognitive failures questionnaire from a sample of healthy older
persons. N Z J Psychol 33:163–170
123