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International Psychogeriatrics: page 1 of 8 CInternational Psychogeriatric Association 2014
doi:10.1017/S1041610214000787
A Quick Test of Cognitive Speed: norm-referenced criteria for
121 Italian adults aged 45 to 90 years
...........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
Ferdinando Petrazzuoli,1,2 Sebastian Palmqvist,3Hans Thulesius,2Nicola Buono,1
Enzo Pirrotta,1Alfredo Cuffari,1Marco Cambielli,1Maurizio D’Urso,1
Carmine Farinaro,1Francesco Chiumeo,1Valerio Marsala1and Elisabeth H. Wiig4
1SNAMID (National Society of Medical Education in General Practice), Italy
2Department of Clinical Sciences in Malmö, Centre for Primary Health Care Research, Lund University, Malmö, Sweden
3Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Sweden
4Department of Communication Disorders, Boston University, Boston, Massachusetts, USA
ABSTRACT
Background: A Quick Test of Cognitive Speed (AQT) is a brief test that can identify cognitive impairment.
AQT has been validated in Arabic, English, Greek, Japanese, Norwegian, Spanish, and Swedish. The aim of
this study was to develop Italian criterion-referenced norms for AQT.
Methods: AQT consists of three test plates where the patient shall rapidly name (1) the color of 40 blue,
red, yellow, or black squares (AQT color), (2) the form of 40 black figures (circles, squares, triangles, or
rectangles; AQT form), (3) the color and form of 40 figures (consisting of previous colors and forms; AQT
color–form). The AQT test was administered to 121 Italian cognitively healthy primary care patients (age
range: 45–90 years). Their mean Mini-Mental State Examination (MMSE) score was 28.8 ±0.9 points (range
26–30 points). AQT naming times in seconds were used for developing preliminary criterion cut-off times for
different age groups.
Results: Age was found to have a significant moderate positive correlation with AQT naming times color
(r =0.65, p <0.001), form (r =0.53, p <0.001), color–form (r =0.63, p <0.001) and a moderate negative
correlation with MMSE score (r =–0.44, p <0.001) and AQT naming times differed significantly between
younger (45–55 years old), older (56–70 years old), and the oldest (71–90 years old) participants. Years of
education correlated positively but weakly with MMSE score (r =0.27, p =0.003) and negatively but weakly
with AQT color (r =–0.16, p =ns), form (r =–0.24, p =0.007), and color–form (r =–0.19, p =0.005). We
established preliminary cut-off times for the AQT test based on +1and+2 standard deviations according to
the approach in other languages and settings.
Conclusions: This is the first Italian normative AQT study. Future studies of AQT – a test useful for dementia
screening in primary care – will eventually refine cut-off times for normality balancing sensitivity and specificity
in cognitive diagnostics.
Key words: dementia evaluation, processing speed, cognitive impairment
Background
The clinical paradigms used to assess cognitive
function in elderly adults range from short screening
tests of memory to comprehensive behavioral
ratings by trained psychiatrists (Folstein et al.,
1975;Rosenet al.,1984; Molloy et al.,1991).
Correspondence should be addressed to: Dr Ferdinando Petrazzuoli, MD, MSc,
Centre for Primary Health Care Research, Lund University, Jan Waldenströms
gata 35, 20502 Malmö, Sweden. Phone: +46-00390823860032; Mobile:
+00393471273910. Email: ferdinando.petrazzuoli@med.lu.se. Received 5
Dec 2013; revision requested 18 Jan 2014; revised version received 26 Mar
2014; accepted 30 Mar 2014.
Some of the traditional measures of cognitive
status or decline show limitations in sensitivity for
differentiating normal from reduced or impaired
cognitive functioning (Duncan and Siegal, 1998;
Geerlings et al.,1999; Christensen, 2001; Burns
et al.,2002). Cognitive tests can also introduce
cultural, linguistic, and/or educational biases. The
finite nature of these scales, generally with point
scores ranging from 1 to 30, and relatively large
increments between points can make it difficult
to quantify gradual aberrations or positive changes
after medication (Palmqvist et al.,2010). The
processing-speed theory of cognitive aging proposes
2F. Petrazzuoli et al.
that slower speed of activating or processing
information is the key to cognitive decline rather
than the rate of information loss or decay
(Salthouse, 1996).
During the last decade, A Quick Test of
Cognitive Speed (AQT) (Wiig et al.,2002;
2003) has been used extensively in Sweden
to assess cognitive aging and decline associated
with dementia, including Alzheimer’s disease and
dementia with Lewy bodies (Andersson et al.,2007;
Palmqvist, 2011; Kvitting et al.,2013,p.68).
AQT has been used in research involving Arabic,
English, Greek, Japanese, Norwegian, Spanish,
and Swedish speaking adults (Wiig et al.,2002;
2003;2007; Jacobson et al.,2004; Warkentin
et al.,2005; Bruna et al,2007; Ijuin et al,2013;
Wigg and Al-Halees, 2013). The purpose of this
study was to obtain objective, quantitative AQT
processing-speed measures for cognitively healthy
Italian primary care patients to develop normative
data for cognitive screening in primary care. The
design replicates previous research with AQT (Wiig
et al.,2003; Nielsen et al.,2004; Andersson et al.,
2007; Warkentin et al.,2008).
A Quick Test of Cognitive Speed uses a
rapid-naming format to assess cognitive processing
speed and efficiency by measuring the amount of
time required to complete relatively simple tasks
with controlled input (Wiig et al.,2002;2003;
Nielsen and Wiig, 2011). The measures account
for reaction, retrieval, and response time as well
as time for making choice decisions and cognitive
set shifting. AQT measures are sensitive to small
changes in the time used for processing and
responding, and have been used to examine, among
others, the comparative effects on cognition of
Alzheimer’s disease and dementia with Lewy bodies
and individual responsiveness to Alzheimer’s dis-
ease’s specific medication (Warkentin et al.,2005;
Andersson et al.,2007; Warkentin et al.,2008;
Palmqvist et al.,2010; Palmqvist, 2011,p.62).
AQT has also proved useful in differentiating adults
with and without attention deficit hyperactivity
disorders (ADHD; Wiig and Nielsen, 2012).
A recent primary care study (Kvitting et al.,
2013) compared the Mini-Mental State Exam-
ination (MMSE) with the AQT and the Clock
Drawing Test (CDT) in dementia assessments and
showed that AQT in combination with MMSE had
a sensitivity of 91%. AQT sensitivity alone was
78%, MMSE 59%, and CDT 26%. The AQT
specificity of 67% was lower than that for CDT
88% and MMSE 91%, but AQT had the highest
negative predictive value of 69% (MMSE 61% and
CDT 46%). So a combination of AQT and MMSE
proved to be a quickly administered and suitable
instrument for primary care dementia screening.
A Quick Test of Cognitive Speed has shown
a high test-retest reliability (r =0.84 to 0.96)
with no significant gender differences or differences
caused by years of education after achieving literacy
(grades 8 and above; Wiig et al.,2002; Wiig et al.,
2003; Jacobson et al.,2004; Nielsen and Wiig,
2006). Previous studies have shown that AQT
times correlate positively with age, which is in
agreement with the fact that aging is associated
with slower cognitive speed (Jacobson et al.,2004;
Nielsen and Wiig, 2006; Wiig et al.,2007). Criterion
cut-off times (in seconds) for typical (less than
+1.0 SD), slower-than-typical (between +1.0 and
+2.0 SD), and atypical/pathological performance
(greater than +2 SD) were identical for English
and Swedish languages (Wiig et al.,2002;2003).
AQT can be administered and scored with minimal
training. These considerations prompted the
collection of normative AQT processing-speed and
efficiency measures from a representative sample of
cognitively healthy Italian primary care patients.
The objective of this study was to obtain
normative data for AQT color, form, and color–
form combination naming in Italian adults and
to develop culturally and linguistically appropriate
criterion cut-off times for typical, slower-than-
typical, and atypically slow processing speed.
Methods
Sample
Participants were patients who for any reason visited
one of the nine primary care physicians spread all
over Italy over a two-week period. The patients
were included consecutively. Only patients with
MMSE scores of 26–30 points were included.
Other criteria for inclusion were that the patients
lived independently, managed personal finances,
had not experienced recent changes in patterns of
eating, sleeping, general health, or mood, and had
no personal history of psychiatric or neurological
disorders or family history of early dementia.
Patients in nursing homes, or with psychiatric
disorders, requiring treatment or severe stages
of diseases which could interfere with cognitive
performance, such as severe chronic obstructive
pulmonary disease, severe chronic heart failure,
anemia, diabetes, impairment of visual perception,
were all excluded. However, patients with chronic
diseases but in a clinically stable condition determ-
ined by the primary care physician and unmodified
medication for the last six months were included.
We started with 128 presumably cognitively
healthy primary care patients, 57 women and 71
men, with no memory or cognitive complaint either
self-reported or reported by close relatives who
A quick test of cognitive speed in Italians 3
Table 1. Characteristics of participants and AQT test results in cognitively normal Italian primary care patients
GROUP I (n =30) GROUP II (n =46) GROUP III (n =45)
AGE 45–55 YEARS AGE 56–70 YEARS AGE 71–90 YEARS
............................................................................................................................................................................................................................................................................................................................
Age in years, mean ±SD 50.3 ±3.2 62.7 ±4.4 78.8 ±4.9
Women, n (%) 15 (50) 19 (41) 18 (40)
Men, n (%) 15 (50) 27 (59) 27 (60)
AQT color (seconds) 21.4 ±2.7 24.9 ±3.7 29.5 ±5.1
Range 18–29 18–33 24–49
AQT form (seconds) 25.9 ±4.1 28.1 ±4.0 32.5 ±4.5
Range 14–33 19–40 23–45
AQT color–form (seconds) 42.2 ±4.4 49.9 ±8.2 58.8 ±10.4
Range 33–50 35–77 46–90
MMSE (points) 29.2 ±0.7 28.9 ±0.8 28.3 ±0.8
Range 28–30 27–30 26–30
Education in years, mean ±SD 12.7 ±3.6 12.9 ±3.8 11.0 ±3.6
Range 8–21 8–19 8–18
were contacted and interviewed. Seven patients
were subsequently excluded because they met the
exclusion criterion of being in a severe stage of
a chronic disease. All the 121 enrolled patients
(52 women and 69 men) were fully literate and
responded to a verbal questionnaire of well-being,
family history of dementia, and past and present
medical history. Their age ranged from 45 to 90
years (mean (M) =65.6 year, SD =12.1 years).
All were native speakers of Italian, resided in Italy,
and had completed 8 to 21 years of education
(M =12.2 years; SD =3.7 years). Their MMSE
scores ranged from 26 to 30 points (M =28.8; SD
=0.9). See Table 1 for demographics stratified by
age groups.
Measurements
The AQT color, form and color–form processing-
speed tests were administered in Italian to all
participants. Short familiarization trials were done
to establish adequacy and consistency in naming
the stimuli. AQT consists of three separate
naming tasks. Of these, color naming (e.g., red)
and form naming (e.g., circle) provide single-
dimension naming measures that account primarily
for reaction, retrieval, and response time. The third,
color–form combination naming (e.g., red circle)
measures reaction, retrieval, and response time as
well as time for co-articulation and shifting cognitive
set (alternating between naming colors and forms;
Figure 1; Wiig et al.,2002).
Procedures
Nine primary care physicians, trained by the main
investigator, administered the AQT processing-
speed tests to their patients. Participants were
tested during routine visits to their primary care
physician. The order of administration was fixed
with color naming tested first, then form naming,
and last color–form naming. It should be noted
that in Italian the word “tondo” (round) was used
instead of the geometric reference “cerchio,” (circle)
since the latter is more difficult to pronounce in
rapid sequence. The total naming time for each
test plate with 40 visual stimuli was recorded with
a digital stopwatch in seconds and fractions of
seconds, beginning with voice onset. For clinical
purposes and ease of administration and scoring,
the examiner did not record the first three naming
errors.
Statistical analysis
Descriptive statistics were conducted using SPSS
Statistics for Windows Version 21.0 (IBM Corp,
Armonk, NY, USA). The AQT scoring times of the
three age groups are illustrated in the box plot graph
(Figure 2) and show the presence of both extreme
and mild outliers. Extreme outliers were defined as
those whose data points were above or below Q3
(upper interquartile range) ±3×IQR (interquartile
range), and mild outliers were those whose data
points were above or below Q3 ±1.5 ×IQR,
but were not extreme outliers. The outliers were
examined and these all proved to meet the inclusion
criteria. To achieve normality, all naming time
measures in seconds were transformed to log normal
(ln) measures for further statistical analysis. One-
way ANOVA tested the significance of difference
in naming–time means (ln) between each age
group and between women and men. Correlation
coefficients (Pearson’s r) explored relations between
individual ages and years of education and AQT
(ln) measures. Measures of variability (SDs) were
used to establish preliminary criterion cut-off time
4F. Petrazzuoli et al.
Figure 1. A sample of AQT. Each original test contains 40 figures. The patient is instructed to quickly name the color of each figure on the
first test (AQT color), the form on the second test (AQT form), and the color and form on the third test (AQT color–form).
Figure 2. Naming time results in seconds for AQT color, form, and color–form in three age groups: 45–55, 56–70, and 71–90 years old,
of 121 cognitively healthy Italian primary care patients presented as box-plots with median and outliers. ∗Extreme outliers: data points
that are above Q3 +3×IQR. Mild outliers: data points that are above Q3 +1.5 ×IQR, but are not extreme outliers. Q3: the upper
interquartile range; IQR: interquartile range.
scores (in seconds) for typical, slower-than-typical,
and atypical/pathological processing speed.
Ethics and consent
In compliance with the Helsinki guidelines for
human subject research, all patients were legally
competent to provide informed consent, and were
informed of the following:
1. The study’s purpose, aims, potential risks, and
benefits.
2. The confidential manner in which the data would
be collected and handled to protect privacy.
A quick test of cognitive speed in Italians 5
Table 2. AQT criterion-referenced cut-off times in seconds for the
typical (less than +1.0 SD), slower-than-typical (between +1.0 and
+2.0 SD), and atypical/pathological (greater than +2SD)
performance ranges for 121 cognitively healthy Italian primary care
patients divided into three age groups
TYPICAL SLOWER-THAN-ATYPICAL/
RANGE TYPICAL PATHOLOGICAL
....................................................................................................................................................................................................
AQT MEASURE 45–55 YEARS OLD
Color <25sec 25to27sec >27 sec
Form <30sec 30to34sec >34 sec
Color–form <47sec 47to51sec >51 sec
AQT MEASURE 56–70 YEARS OLD
Color <29sec 29to32sec >32 sec
Form <32sec 32to36sec >36 sec
Color–form <58sec 58to66sec >66 sec
AQT MEASURE 71–90 YEARS OLD
Color <35sec 35to40sec >40 sec
Form <37sec 37to42sec >42 sec
Color–form <69sec 69to80sec >80 sec
3. They could abstain or withdraw at any time from
the study without affecting their physician–patient
relationship.
4. They would not be identified by any published
results.
According to Italian legislation, an ethical
approval was not necessary for this type of study.
Participants received no compensation.
Results
A Quick Test of Cognitive Speed naming times
stratified for age-level groups and gender are
reported in Table 1. The number of naming errors
was low in agreement with findings in healthy
American and Swedish adults (Wiig et al.,2002;
2003).
Normality tests for all AQT naming times
distributions rejected normality. The non-normal
distribution pattern was also confirmed by
distribution curves and by quantile–quantile
plots. There were significant AQT naming time
differences between younger (45–55 years old),
older (56–70 years old), and the oldest (71–90
years old) participants for all AQT measures.
One-way ANOVA comparisons of mean lognormal
naming time differences for color, form, and color–
form combination naming between the three age
groups showed for AQT color: F(2, 118) =45.64,
p<0.0001; AQT form: F(2, 118) =23.76, p <
0.0001; AQT color–form: F(2, 118) =42.90, p <
0.0001. Differences in AQT reading times between
the young–old group (56–70 years old) and the
old–old group (71–90 years old) also proved to be
substantial and significant (p <0.001; Table 1).
The distribution of naming time results of the three
age groups is also shown in corresponding box
plots in Figure 2. Age as a continuous variable
correlated positively and moderately with AQT
naming times: r =0.65 for AQT color (p <0.001),
r=0.53 for AQT form (p <0.001), r =0.63
for AQT color–form (p <0.001), and correlated
negatively and moderately with the MMSE score:
r=–0.44, p <0.001. Separate criterion cut-off
times were thus developed for different age groups.
Standard deviations from the naming–time mean
scores determined the typical (less than +1 SD),
slower-than-typical (between +1and+2 SD), and
atypical/pathological (greater than +2 SD) ranges
adopting the same theoretical approach used in
other languages (Wiig et al., 2002;2003). Cut-off
times were rounded to the nearest second for ease
of reference (Table 2).
Years of education correlated positively but
weakly with the MMSE score (r =0.27, p =0.003),
and negatively but weakly with AQT naming times
for AQT color (r =–0.16, p =ns), AQT form (r =
–0.24, p =0.007), and AQT color–form (r =–0.19,
p=0.041). T-tests showed no significant
differences between genders for either MMSE
scores or AQT reading times.
A Quick Test of Cognitive Speed naming times
in a US population-based sample of 90 cognitively
healthy 55–70-year-old patients (Nielsen and Wiig,
2011) and 46 Italian primary care patients aged 56–
70 years in this study are shown in Table 3.
6F. Petrazzuoli et al.
Table 3. AQT test results comparing cognitively healthy samples of the US patients and the
Italian primary care patients
USA,n=90 ITALY,n=46
(Nielsen and Wiig, 2011) (Italian adults)
.....................................................................................................................................................................................................................................................................
Age in years, mean ±SD 60.8 ±4.9 62.7 ±4.4
Range 55–70 56–70
Women, n (%) 52 (42) 19 (41)
Men, n (%) 48 (58) 27 (59)
AQT color (seconds) 22.4 ±3.8 24.9 ±3.7
Range 16–32 18–33
AQT form (seconds) 25.5 ±4.3 28.1 ±4.0
Range 20–40 19–40
AQT color–form (seconds) 49.7 ±8.1 49.9 ±8.2
Range 38–70 35–77
MMSE (points) NA 28.9 ±0.8
Range NA 27–30
Education in years, mean ±SD 12.2 +2.3 12.9 ±3.8
Range 9–19 8–19
Discussion
In this study, we obtained normative naming-
times for AQT processing-speed tests used to
assess cognitive function from a culturally and
linguistically representative sample of cognitively
healthy Italian primary care patients. Age proved
to have a significant effect on processing speed and
this concurs with previous findings (Jacobson et al.,
2004; Nielsen and Wiig, 2006; Wiig et al.,2007).
Years of education also correlated significantly
but weakly with AQT naming times, a finding
previously unreported.
The differences between AQT naming times
in 46 Italian primary care patients aged 56–70
years in this study and 90 American subjects
(Nielsen and Wiig, 2011) of the same age range
seen in Table 3 were considerably smaller than
the differences between 90 American subjects and
90 healthy Arabic speaking Jordanian adults of
the same age range (Wiig and Al-Halees, 2013).
This may reflect cultural, educational, and linguistic
differences. It should also be noted that the order of
naming of colors and forms in the dual dimension
the AQT color–form test is reversed between Italian
and English, which could impact naming times.
Cardiovascular diseases, diabetes, and hyperten-
sion are common in middle-aged and elderly people
visiting primary care and are indeed associated
with impaired cognition (Halling and Berglund,
2006; Elias et al.,2012). A few outliers in our
study showing long AQT reading times in the
two older groups of patients could be explained
by the high sensitivity of the AQT test, which
might have detected initial cognitive impairment
not yet clinically evaluable and not detected
by MMSE, although the present study was not
designed to test this assumption. This study was
carried out in primary care, and the assessment
of cognitive normality was based on the MMSE
score, the clinical judgment of patient’s primary care
physician, and information obtained from patient’s
close relatives and patients themselves. No extensive
neuropsychological battery was used. However, we
trust that our broad definition of cognitive normality
provides a more accurate representation of the real
population and therefore better normative data for
clinical usage.
Primary care physicians are usually the first
health professionals that patients or their families
contact for memory loss concerns (Waldorff et al,
2005; Brodaty et al.,2006; Pirani et al.,2010). Yet,
these physicians often complain about the lack of
suitable instruments and time to assess cognition.
The ideal cognitive screening test for primary care
would be brief, easily administrable, and scored
with high sensitivity and specificity for identifying
impairment (Milne et al.,2008; Holsinger et al.,
2012). In Italy, as in many other countries, the CDT
and MMSE are commonly used in combination as
“first line tests” for dementia evaluation by both
neurologists and primary care physicians. Alas, the
CDT has proved to be difficult to assess in the
primary care setting (Ehreke et al.,2009). So it has
been suggested that AQT could replace CDT in
combination with MMSE for dementia evaluation
(Kvitting et al.,2013). The AQT is currently in
clinical use in Sweden for dementia assessments in
both primary and secondary care. The high negative
predictive value of an AQT result is one of its main
advantages making it suitable as a clinical screening
tool. Whether the cut-off time developed in our
A quick test of cognitive speed in Italians 7
study would be suitable in validating AQT as a
cognitive screening tool remains to be investigated
in future studies. The AQT brain speed test however
seems to fill a gap in cognitive testing since few
tests measure speed, which is correlated to brain
processing.
This study has acknowledged limitations: First,
the sample of 121 patients was small; however,
the patients were consecutively recruited from
different parts of Italy: North and South, rural, and
urban settings. This indicates that our dataset is
representative of the Italian population. We did not
follow the patients over time to rule out incipient
dementia, however, there is a paucity of published
results as to how normal groups of people respond
to clinical measures of different types of morbidity.
And for the AQT brain processing speed test there
are few published studies on the performance of
cognitively healthy people. To our knowledge, only
two previous normative AQT studies have used a
larger population than the present study (Bruna
et al.,2007; Wiig and Al-Halees, 2013). We have
designed a future validation study to establish AQT
sensitivity and specificity measures in the Italian
population to differentiate between neurotypical
adults and adults with mild cognitive impairment
or mild-to-moderate dementia.
Conclusions
We have established preliminary normal cut-off
times for the AQT test in Italian primary care
patients based on +1and+2 SDs, adopting the
theoretical approach used in other languages and
settings. We have also planned a future study to
eventually refine the AQT naming cut-off times for
normality aiming at an optimal balance between
sensitivity and specificity in cognitive diagnostics.
Conflict of interest
None.
Description of the authors’ roles
Ferdinando Petrazzuoli and Elisabeth Wiig
conceived the study. Ferdinando Petrazzuoli was
responsible for the manuscript and the analysis of
the data. Sebastian Palmqvist and Hans Thulesius
helped in study plans and critically revised the ma-
nuscript. Ferdinando Petrazzuoli, Marco Cambielli,
Nicola Buono, Carmine Farinaro, Valerio Marsala,
Alfredo Cuffari, Enzo Pirrotta, Maurizio D’Urso,
and Francesco Chiumeo provided data for the study
and reviewed the manuscript.
Acknowledgments
We express our gratitude to the Italian primary care
patients who participated in the study. The study
did not receive external funding.
References
Andersson,M.,Wiig,E.H.,Londos,E.andMinthon,L.
(2007). Quick Test of Cognitive Speed: a measure of
cognitive speed in dementia with Lewy bodies. American
Journal of Alzheimer’s Disease and Other Dementias, 22,
313–318.
Brodaty, H., Low, L. F., Gibson, L. and Burns, K.
(2006). What is the best dementia screening instrument for
general practitioners to use? American Journal of Geriatric
Psychiatry, 14, 391–400.
Bruna, O. et al. (2007) . Early detection of cognitive
impairment. Adaptation of the Alzheimer’s Quick Test to
the Spanish population. Paper presented at the Spanish
Psychiatric Society Joint Mid-Year Meeting, 4–7 July 2007,
Conference Bilbao, Spain.
Burns, A., Lawlor, B. and Craig, S. (2002). Rating scales
in old age psychiatry. British Journal of Psychiatry, 180,
161–167.
Christensen, H. (2001). What cognitive changes can be
expected with normal ageing? Australian and New Zealand
Journal of Psychiatry, 35, 768–775.
Duncan,B.A.andSiegal,A.P.(1998). Early diagnosis
and management of Alzheimer’s disease. Journal of Clinical
Psychiatry, 59, S15–S21.
Ehreke, L. et al. (2009). Is the clock drawing test appropriate
for screening for mild cognitive impairment? Results of the
German study on Ageing, Cognition and Dementia in
Primary Care Patients (AgeCoDe). Dementia and Geriatric
Cognitive Disorders, 28, 365–372.
Elias, M. F., Goodell, A. L. and Dore, G. A. (2012).
Hypertension and cognitive functioning: a perspective in
historical context. Hypertension, 60, 260–268.
Folstein, M. F., Folstein, S. E. and McHugh, P. R.
(1975). “Mini-mental state”: a practical method for
grading the cognitive state of patients for the clinician.
Journal of Psychiatric Research, 12, 189–198.
Geerlings, M. I., Jonker, C., Bouter, L. M., Adler, H. J.
and Schmand, B. (1999). Association between memory
complaints and incident Alzheimer’s disease in elderly
people with normal baseline cognition. American Journal of
Psychiatry, 56, 531–527.
Halling, A. and Berglund, J. (2006).Association of diagnosis
of ischemic heart disease, diabetes mellitus and heart failure
with cognitive function in the elderly population. The
European Journal of General Practice, 12, 114–119.
Holsinger, T., Plassman, B. L., Stechuchak, K. M.,
Burke, J. R., Coffman, C. J. and Williams, J. W. Jr.
(2012). Screening for cognitive impairment: comparing the
performance of four instruments in primary care. Journal of
American Geriatric Society, 60, 1027–1036.
Ijuin, M. et al. (2013). Walking exercise and cognitive
functions in community-dwelling older adults: preliminary
8F. Petrazzuoli et al.
results of a randomized controlled trial. International
Journal of Geriatric Psychiatry, 28, 109–110.
Jacobson, J. M., Nielsen, N. P., Minthon, L., Warkentin,
S.andWiig,E.H.(2004). Multiple rapid automatic
naming measures of cognition: normal performance and
effects of aging. Percepual & Motor Skills, 98, 739–753.
Kvitting, A. S., Wimo, A., Johansson, M. M. and
Marcusson, J. (2013). A Quick Test of Cognitive Speed
(AQT): usefulness in dementia evaluations in primary care.
Scandinavian Journal of Primary Health Care, 31, 13–19.
Milne, A., Culverwell, A., Guss, R., Tuppen, J. and
Whelton, R. (2008). Screening for dementia in primary
care: a review of the use, efficacy and quality of measures.
International Psychogeriatrics, 20, 911–926.
Molloy, D., Alemayehu, E. and Roberts, R. (1991).
Reliability of a standardized Mini-Mental State
Examination compared with the traditional Mini-Mental
State Examination. American Journal of Psychiatry, 148,
102–105.
Nielsen, N. P. and Wiig, E. H. (2006) Alzheimer’s quick
test screening criteria for West African speakers of Krio.
Age and Ageing, 35, 503–507.
Nielsen, N. P. and Wiig, E. H. (2011). An additive model
for relations between AQT single- and dual-dimension
naming speed. Percepual & Motor Skills, 112, 499–508.
Nielsen, N. P., Wiig, E. H., Warkentin, S. and Minthon,
L. (2004). Clinical utility of color–form naming in
Alzheimer’s disease: preliminary evidence. Percepual &
Motor Skills, 99, 1201–1204.
Palmqvist, S. (2011). Validation of brief cognitive tests in mild
cognitive impairment, Alzheimer’s disease and dementia with
Lewy bodies. Dissertation, Clinical Memory Research Unit,
Lund University, Sweden.
Palmqvist, S., Minthon, L, Wattmo, C., Londos, E. and
Hansson, O. (2010). A quick test of cognitive speed is
sensitive in detecting early treatment response in
Alzheimer’s disease. Alzheimer’s Research & Therapy,2,29.
Pirani, A., Broda, H., Martini, E., Zaccherini, D.,
Neviani, F. and Neri, M. (2010). The validation of the
Italian version of the GPCOG (GPCOG-It): a contribution
to cross-national implementation of a screening test for
dementia in general practice. International Psychogeriatrics,
22, 82–90.
Rosen,W.G.,Mohs,R.C.andDavis,K.L.(1984). A
new rating scale for Alzheimer’s disease. American Journal
of Psychiatry, 141, 1356–1364.
Salthouse, T. A. (1996). The processing-speed theory of
adult age differences in cognition. Psychological Review,
103, 403–428.
Waldorff, F. B., Rishøj, S. and Waldemar, G. (2005).
Identification and diagnostic evaluation of possible
dementia in general practice. Scandinavian Journal of
Primary Health Care, 23, 221–226.
Warkentin, S. et al. (2005). The AQT as a useful short
screening test for dementia. Evidence from two European
cultures. International Psychogeriatrics, 17 (Suppl. 2),
160.
Warkentin, S., Erikson, C. and Janciauskiene, S. (2008).
rCBF pathology in Alzheimer’s disease is associated with
slow processing speed. Neuropsychologia, 46, 1193–1200.
Wiig,E.H.andAl-Halees,Y.(2013). A quick test of
cognitive speed: preliminary screening criteria for
Arabic-speaking adults, ages 40 to 80 years. Perceptual &
Motor Skills, 117, 615–626.
Wiig, E. H. and Nielsen, N. P. (2012) . A quick test of
cognitive speed for comparing processing speed to
differentiate adult psychiatric referrals with and without
attention-deficit/hyperactivity disorders. The Primary Care
Companion for CNS Disorders, 14.
doi:10.4088/PCC.11m01273.
Wiig, E. H., Nielsen, N. P., Minthon, L. and Warkentin,
S. (2002). A Quick Test of Cognitive Speed (AQT).San
Antonio, TX: Pearson/PsychCorp.
Wiig, E. H., Nielsen, N. P., Minthon, L. and Warkentin,
S. (2003). AQT: Assessment of Parietal Function. Svensk
Version & Norsk Versjon. Stockholm, Sweden:
Pearson/PsychCorp.
Wiig, E. H., Nielsen, N. P. and Jacobson, J. (2007). A
Quick Test of cognitive speed: patterns of age groups 15 to
95 years. Percepual & Motor Skills, 104, 1067–1075.
