2013. Vol.4, No.10A, 1-6
Published Online October 2013 in SciRes (
Copyright © 2013 SciRes. 1
Attentional and Executive Deficits in Brazilian Children with
Developmental Dyslexia*
Ricardo Franco de Lima, Cíntia Alves Salgado Azoni, Sylvia Maria Ciasca
Laboratory of Learning Disabilities and Attention Deficit (DISAPRE), State University of Campinas
(UNICAMP), Campinas (SP), Brazil
Received July 14th, 2013; revised August 17th, 2013; accepted September 19th, 2013
Copyright © 2013 Ricardo Franco de Lima et al. This is an open access article distributed under the Creative
Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.
The present study aims to compare the performance between Brazilian children with Developmental
Dyslexia (DD) and children without learning difficulties on tests of attention and Executive Functions.
The study sample consists of study group (20 subjects) attending the Learning Disability clinic of Univer-
sity Hospital and control group (20 subjects) from public school in Campinas-SP. The instruments utilized
were: WISC-III factor indexes and subtests, cancellation test, Trail Making Test, Stroop Color Word Test,
Tower of London, Wisconsin Card Sorting Test and verbal fluency test. The results revealed differences
between groups in scores of different instruments. The findings suggest that children with dyslexia have
difficulties in performing visuospatial and auditive attention tasks, as well as tasks involving different
components of executive functions, such as flexibility, inhibitory control, strategy use, working memory
and verbal fluency. Such changes may be part of dyslexia and accompany the core deficit in the phono-
logical component of language.
Keywords: Neuropsychology; Dyslexia; Attention; Executive Function
Developmental Dyslexia (DD) is a neurobiological disorder
characterized by difficulties in acquiring reading and/or written
skills as a result of deficit in the phonological component of
language. These characteristics are unexpected when consider-
ing the level of intelligence and effective instruction in the
classroom (Lyon, Shaywitz, & Shaywitz, 2003). According to
the International Statistical Classification of Diseases and Re-
lated Health Problems (ICD-10) (WHO, 2008), the main diag-
nostic criteria of DD are level of intelligence within the average,
absence of uncorrected sensory changes, absence of others,
neurological and/or psychiatric disorders, as well as below
average performance in reading/writing.
Developmental Dyslexia is accompanied by impairments in
different cognitive functions such as visuospatial attention and
Executive Functions (EF) (Ruffino et al., 2010; Franceschini et
al., 2012; Lima, Salgado-Azoni, & Ciasca, 2012). Researches
have shown that children with DD exhibit inefficient visuospa-
tial distribution of attention engagement (Ruffino et al., 2010).
The difficulty is also evident for the recruitment of cognitive
resources necessary for performance of complex tasks involv-
ing reaction time and reading fluency (Heiervang & Hugdahl,
2003). In visual attention tasks using reaction time measures,
children with DD show higher resolution time (Facoetti et al.,
Previous studies proposed that the processing of a rapid se-
quence of stimuli in all sensory modalities was hampered by the
slow attentional capture and increased reaction time (Hari &
Renvall, 2001; Facoetti et al., 2010). Another work has shown
impairment in the ability to rapidly change attentional skills
from a target stimulus to another one. The impairment in this
ability may affect the allocation of attentional resources and
processing time and sequence of graphemes for reading (Visser,
Boden, & Giaschi, 2004). These characteristics may accompany
deficits in phonological processing (Hari & Renvall, 2001;
Facoetti et al., 2010).
Some authors suggest that the deficit of visual attention in
DD may be specific to the characteristics of the presented stim-
uli, showing significant only in the processing of verbal mate-
rial (letters and digits), but not with non-verbal (symbols)
(Marzocchi, Ornaghi, & Barboglio, 2009; Savill & Thierry,
2012). Recently, Savill and Thierry (2012) found gaps in atten-
tional engagement with tasks related to phonological demands
(spelling and reading).
Although most authors agree that phonological deficit is cen-
tral in dyslexia (Lyon et al., 2003; WHO, 2008; Lima et al.,
2012), some others have proposed the opposite. According to
this view, attentional mechanisms can control the dorsal visual
stream and are fundamental to the sequential tracking of letters.
Thus, the deficit in this process leads to a cascade of effects,
including impairments in visual processing of graphemes, gra-
pheme-phoneme conversion, and finally, in phonological aware-
ness (Vidyasagar & Pammer, 2009). In contrast, other authors
do not point to evidence that the deficit in phonological proc-
essing is caused by attentional dysfunction (Heim et al., 2010).
Concerning the EF, due to its multifunctional nature, it has
been suggested that there is impairment of only some aspects
*Funding: National Council for Scientific and Technological Development
(Reiter et al., 2005). Previous studies show that when compared
with proficient readers, children with DD show impairments in
performance of instruments that assess inhibitory control (Ev-
eratt et al., 1997; Van Der Sluis, De Jong, & Van Der Lij, 2004;
Reiter et al., 2005), use of cognitive strategies (Helland &
Asbjornsen, 2000), verbal working memory (Brosnan et al.,
2002; Reiter et al., 2005) and other subcomponents of working
memory (Schuchardt, Maehler, & Hasselhorn, 2008). In plan-
ning tasks, there are no differences between DD and control
subjects in total scores; however, such differences are observed
in time to perform the task (Reiter et al., 2005).
Therefore, this study aimed to compare the performance be-
tween children with DD and children without learning difficul-
ties on tests of attention and EF. We tested the hypothesis that
children with DD would exhibit worse performance than chil-
dren without learning disabilities in the instruments used.
The study was approved by the Research Ethics Committee,
University of Campinas (FCM-Unicamp) (protocol n. 648/2007).
The study included a total of 40 children of both genders (53%
boys, 48% girls), aged between 7 - 11 years, average age of
9.38 (SD = 1.08) years, attending the 1st-5th grades of elemen-
tary school.
Two groups were formed from the total sample. The group
with Developmental Dyslexia (DG) was selected from referrals
to the Learning Disability clinic of University Hospital. The
children underwent interdisciplinary assessment (neuropsy-
chology, speech pathology, education, neurology and psychia-
try) and 20 were included in the study diagnosed with devel-
opmental dyslexia. The diagnosis was followed the criteria of
the Diagnostic and Statistical Manual of Mental Disorders
(DSM-IV-TR) (APA, 2002), International Classification of
Diseases (ICD-10) (WHO, 2008) and clinical characteristics:
IQ 80 assessed by Wechsler Intelligence Scale for Children-
WISC-III (Wechsler, 2002); performance 2SDs below age on
measures of reading/writing and phonological processing:
speed reading, reading accuracy, written under dictation, writ-
ten spontaneously, rapid automatized naming test (RAN), pho-
nological awareness test and phonological working memory test.
The DG was formed by 20 children, 55% of boys and 45% of
girls, averaging 9.70 years old (SD = 0.98), 1st - 5th grade. The
inclusion and exclusion criteria were as follows: parent au-
thorization by consent term; submit intelligence quotient (IQ)
within the normal range, i.e., 80, according to WISC-III
(Wechsler, 2002); not making use of psychotropic medicine and
not presenting other neurological symptoms; does not provide
criteria for Attention Deficit Hyperactivity Disorder (ADHD).
The control group (CG) was selected from public school in
Campinas-SP, comprising 20 children without complaints of
learning difficulties and/or attention, proficient readers, 50% of
boys, average age of 9.05 years (SD=1.10), 1st - 4th grade. The
inclusion and exclusion criteria were as follows: parent au-
thorization by consent term; present IQ 80, as WISC-III
(Wechsler, 2002); have been nominated by teachers for not
presenting complaints of difficulties in learning and have read-
ing level expected for their age; not make use of psychotropic
medication, not show any type of sensory impairment and neu-
rological development delay.
All participants were evaluated by the same neuropsycholo-
gist, using the instruments described below.
Wechsler Intelligence Scale for Children (WISC-III) (We-
chsler, 2002). Clinical instrument that assessed intellectual
ability and different cognitive abilities. For the study we used
the full intelligence quotient (IQ), verbal IQ and performance
WISC-III subtests (Wechsler, 2002): Coding (Cod), Symbol-
Search (SS), Arithmetic (Arit) and Digits (Dig). This subtests
assessed attention in visual (Cod and SS) and auditory (Arit and
Dig) modalities. For analysis, we used the weighted scores
from these subtests.
WISC-III indexes (Wechsler, 2002) Distraction Resistance
(DRI) and Speed of Processing (PSI). Indexes related to visu-
ospatial and auditory sustained attention, obtained from WISC-
III subtests. IQs were considered measures of this index factor.
TC (Lezak, 1995; Lima et al., 2012). This test evaluated
visuospatial attention to visual material, visual scanning veloc-
ity and processing. We used two versions: Geometric Figures
(CT-GF) and Row of Letters (CT-LR). Scores were used: time
and errors of omission.
Trail Making Test (TMT-A/B) (Lezak, 1995; Lima et al.,
2012). Part A assesses visual sustained attention and visual scan-
ning ability. Part B assessed mental flexibility and attention-
switching capacity. The scores were obtained: time, switching
errors and sequencing errors.
Stroop Color-Word Test (SCWT) (Lezak, 1995; Lima et al.,
2012). This test evaluated the inhibitory control (ability to in-
hibit automatic response to the issue of controlled response)
and visual selective attention (selection between relevant and ir-
relevant information). Three cards were used: Color (neutral con-
dition), Word (congruent condition) and Color-Word (incon-
gruent condition). The scores were obtained: time and errors.
Tower of London (ToL) (Lezak, 1995; Lima et al., 2012).
This test evaluated the mental ability to plan and logical rea-
soning. It was considered the total score of correct answers.
Wisconsin Card Sorting Test (WCST) (Heaton et al., 2005).
WCST evaluated ability to use and modify strategies using
feedback environment. We considered the following scores:
trials to complete the first category (WCST-TC); number of
completed categories (WCST-CC); number of tests adminis-
tered (WCST-TA); Total number of successes (WCST-NS);
Total number of errors (WCST-NE) and error percentage
Digits-Backward (Wechsler, 2002). Part of digits of the
WISC-III subtest that assessed working memory for verbal
Verbal fluency test (FAS) (Lezak, 1995). FAS evaluated the
capacity of words verbally. We used the phonological semantic
versions and found the average scores for each version.
All participants were assessed individually by a single ex-
aminer, according to specific instructions for each instrument in
the rooms of the Outpatient Neuro-Learning Difficulties or
school, according to the group and after parents signing the
consent inform. Statistical analysis was performed using the
program SPSS Statistics 20.0 for Windows. To compare means
between groups we used the Mann-Whitney nonparametric test.
Copyright © 2013 SciRes.
Copyright © 2013 SciRes. 3
Additionally was calculated measure of effect size (Cohen’s d).
The groups had IQ with scores within the normal range.
Verbal, performance and full IQ scores were higher than aver-
age in the CG and within average in the DG. Mean WISC-III
index is presented in Table 1. Table 2 presents the results of
comparisons between groups with regard to the instruments to
assess attention. Comparisons between the groups for the as-
sessment of executive functions are shown in Table 3.
This study aimed to compare the performance between chil-
dren with DD and children without learning difficulties on tests
of attention and EF. The diagnosis of DD requires the estimate
of the general intellectual ability, excluding the possibility of
explaining the reading difficulty as a lowering of intelligence
(APA, 2002). The DG have the intellectual level at or above the
mean for age, as noted in our results. Although both groups
were classified in normal level, DG showed verbal, perform-
ance and full IQs less than the CG. This result was also ob-
tained in the comparison of mean IQs, in which dyslexics
scored lower in all IQs. Regarding the DG results, our findings
are similar to those obtained in the study by De Clercq-Quae-
gebeur et al. (2010).
In the attentional evaluation, DG had lower scores in WISC-
III subtests. This results suggests that children with DD have
difficulties in tasks involving visuospatial attention skills,
quantitative reasoning, immediate memory and processing
speed. Other studies also found lower performance of children
with DD in digit subtest (WISC) or other versions of the digit
span test (Helland & Asbjornsen, 2000; Clercq-Quaegebeur et
al. 2010). Although the digits subtest requiring sustained atten-
tion for its performance, the response elaboration requires
short-term memory. Furthermore, the weighted score is ob-
tained by summing the order forward and backwards, and the
latter is more closely with verbal working memory. With this in
mind, the impairment of individuals with DD on this task may
suggest difficulties in the mentioned aspects.
The Distraction Resistance Index (RDI) is commonly con-
sidered an objective measure of attention due to its name.
However, your subtests (arithmetic and digits) also require
other skills such as reasoning, numerical knowledge and mem-
ory (Lima et al., 2012). In other hand, the subtests of Process-
ing Speed Index (PSI) are measure more objective of visual
sustained attention, despite the engagement with the visuomo-
tor ability, visual screening graph motor rapid and repetitive
response. However, this aspect does not differentiate them from
other attentional assessment tools. Thus, our results suggest that
children with DD have difficulties in visuospatial and auditory
sustained attention, as well as in processing speed.
Other authors have been indicated that individuals with DD
show changes in processing speed as children with ADHD
(Shanaham et al., 2006). However, other studies contradict this
Table 1.
Comparison of groups in the WISC-III.
Controls Dyslexia
M (SD)
p d ES
Verbal IQ 118.30 (11.41) 104.05 (17.97) <0.01* 0.95* 0.43
Performance IQ 113.50 (14.86) 105.55 (12.76) <0.05* 0.57* 0.28
Full IQ 117.45 (12.64) 105.05 (15.73) <0.05* 0.87* 0.40
IQ: intelligence quotient; M(SD): mean (standard deviation); p: significance level; d: Cohen’s d; ES: effect-size.
Table 2.
Comparison of groups using instruments of attention.
Controls Dyslexia
M (SD)
p d ES
Cod 11.80 (2.40) 10.70 (2.11) >0.05 0.49* 0.24
SS 13.10 (1.48) 10.65 (1.69) <0.01* 1.54* 0.61
Arith 13.00 (1.81) 10.65 (2.70) <0.01* 1.02* 0.46
Dig 12.70 (3.26) 8.95 (1.85) <0.01* 1.41* 0.58
DRI 113.85 (13.48) 97.55 (11.72) <0.01* 1.30* 0.54
PSI 110.45 (13.02) 102.45 (8.76) <0.05* 0.72* 0.34
CT-GF/time 92.35 (24.46) 96.55 (18.48) >0.05 0.19 0.07
CT-GF/omission errors 0.60 (0.94) 1.80 (2.40) >0.05 0.66* 0.31
CT-LR/time 152.05 (64.25) 151.60 (50.12) >0.05 0.00 0.00
CT-LR/omission errors 1.60 (2.56) 5.75 (4.92) <0.01* 1.06* 0.47
Cod: coding; SS: symbol search; Arith: arithmetic; Dig: digits; DRI: distraction resistence index; PSI: processing speed index; CT-GF: cancellation test—geometric figures;
CT-LR: cancellation test—letters in row; TMT: trail making test; M(SD): mean (standard deviation); p: significance level; d: Cohen’s d; ES: effect-size.
Table 3.
Comparison of groups using instruments of executive functions.
Controls Dyslexia
p d ES
TMT-A/time 60.05 (25.05) 58.40 (17.41) >0.05 0.08 0.04
TMT-A/errors 0.00 (0.00) 0.25 (0.79) >0.05 0.45* 0.22
TMT-B/time 143.80 (76.47) 193.85 (97.30) >0.05 0.57* 0.27
TMT-B/switching errors 0.00 (0.00) 1.10 (1.74) <0.01* 0.89* 0.41
TMT-B/sequencing errors 0.10 (0.45) 1.05 (1.23) <0.01* 1.03* 0.46
SCWT-color/time 16.10 (2.47) 22.95 (4.01) <0.01* 2.06* 0.72
SCWT-color/errors 0.25 (0.55) 0.80 (0.77) <0.05* 0.82* 0.38
SCWT-word/time 11.25 (1.71) 20.65 (5.36) <0.01* 2.36* 0.76
SCWT-word/errors 0.00 (0.00) 0.85 (0.93) <0.01* 1.29* 0.54
SCWT-color word/time 37.00 (8.31) 46.55 (20.20) >0.05 0.62* 0.30
SCWT-color word/errors 2.50 (2.21) 4.60 (3.27) <0.05* 0.75* 0.35
ToL 20.97 (2.58) 19.55 (3.12) >0.05 0.50* 0.24
WCST-TC 14.60 (10.29) 25.50 (35.68) <0.05* 0.42* 0.20
WCST-CC 5.50 (1.41) 3.70 (2.11) <0.05* 1.00* 0.45
WCST-TA 108.30 (20.49) 119.50 (15.52) >0.05 0.62* 0.29
WCST-NS 71.50 (9.06) 62.85 (16.47) >0.05 0.65* 0.31
WCST-NE 118.60 (12.93) 101.75 (19.34) <0.05* 1.02* 0.46
WCST-EP 117.55 (12.01) 101.75 (18.90) <0.05* 1.00* 0.47
Digits 4.97 (1.90) 3.03 (.84) <0.01* 1.32* 0.55
FAS-fonology 8.71 (2.14) 6.23 (2.12) <0.01* 1.16* 0.50
FAS-semantic 11.14 (2.01) 10.75 (2.83) >0.05 0.15 0.08
TMT: trail making test; SCWT: stroop color word test; ToL: tower of London; WCST-TC: Wisconsin card sorting test—trials to complete the first category; WCST-CC:
completed category; WCST-TA: tests administered; WCST-NS: number of successes; WCST-NE: number of errors; WCST-EP: error percentage; M(SD): mean (standard
deviation); p: significance level; d: Cohen’s d; ES: effect-size.
position. Bonifacci and Snowling (2008) found that the per-
formance of children with DD was similar to children with
borderline intelligence level on tasks of processing speed. De
Clercq-Quaegebeur et al. (2010) found deficits in the PSI of
WISC-IV, but the result was explained only by the performance
in the “coding” and not the “symbol search”, which to the au-
thors does not indicate lowering overall processing speed.
However, the cited studies used different methods: PSI of the
WISC-IV (De Clercq-Quaegebeur et al., 2010) and computer-
ized measures with reaction time using tracking of numbers and
letters (Bonifacci & Snowling, 2008).
We suggest that the specificity and diversity of stimulus ma-
terials (visual and auditory modalities, letters, numbers, shapes)
and types of involved responses (verbal-motor output) can lead
to different results.
There were differences between groups in omission errors of
cancelattion tests. We think that, despite of the DG having
demonstrated adequate time resolution, the quality of atten-
tional performance and recruitment resources to control this
performance was lower, expressed by the large number of er-
rors. In general, the literature indicates that children with DD
have difficulty in serial visual tracking tests (as cancellation
tests), by reducing the number of items simultaneously proc-
essed (Hari & Renvall, 2001). Another aspect to be cited is that
this performance occurred mainly in the TC - letters in row,
which has verbal stimuli. These data corroborate with the atten-
tional characteristics presented in previous studies, which de-
scribe that attentional deficits may be specific to verbal stimu-
lus (Marzocchi et al., 2009; Savill & Thierry, 2012).
Considering different executive functioning capabilities,
children with DD have impaired performance on different
components. Previous studies with DD showed damaged per-
formance on the TMT. Our results show significative differ-
ences between groups in scores of time (only Part B) and errors
(Parts A and B). In TMT - Part A, there were differences in
error score, using only magnitude measure (Cohen’s d). Others
studies using traditional statistics this difference was not ob-
tained (Reiter et al., 2005; Närhi et al., 2008; Lima et al., 2012).
Copyright © 2013 SciRes.
In TMT-Part E, which involves alternating numerical and al-
phabetical sequence, our result was similar to that obtained by
others studies (Reiter et al., 2005; Närhi et al., 2008; Lima et
al., 2012), so that the children of DG showed higher scores and
time errors.
In the assessment of inhibitory control by SCWT, DG had
more time to solve the three cards (Color, Word and Color-
Word) and, consequently, a greater number of errors. The re-
sults suggest impaired performance in inhibitory control, as
indicated by other studies (Everatt et al., 1997; Brosnan et al.,
2002; Reiter et al., 2005). Everatt et al. (1997) suggest that, to
resolve Stroop test, some level of word processing should be
possible, causing problems in automatization and control re-
sponses, i.e., color naming. Thus, alterations in lexical access
and in their attentional demands may serve as a basis for under-
standing the performance of individuals with DD in that test.
The groups also differ when considering the ToL, using
Cohen’s d. Other study found no score differences between
children with DD and good readers (Lima et al., 2012) regard-
ing the correct answers, but at the time of planning (Reiter et al.,
2005). Besides planning, the ToL also involves logical mathe-
matical reasoning, which is not compromised in children with
DD (Lima et al., 2012). Thus, we can suggest that, despite the
need for a longer time for the organization and planning of
response, which involves others executive functions and proc-
essing speed, children with DD can show satisfactory perform-
Regarding WCST, individuals with DD had more trials to
solve the first category of WCST (average of 25 trials); they
also completed fewer categories (average of three categories),
i.e., they finished 128 completed trials without completed the
six categories. Consequently, their scores were higher in the
total number of errors/percentage of errors and lower scores of
correct trials. Contradictory results are found in the literature.
Some studies indicate that individuals with DD have higher
percentage of perseverative errors (Marzocchi et al., 2009), and
while others studies point out that they complete fewer catego-
ries, but do not show more perseverative errors (Menghini et al.,
2010) Using the reduced and adapted version of the WCST
(modified card sorting test), it was found that children with DD
had fewer errors and perseverations. The authors explained that
this result may be due to the familiarity of dyslexics with test-
ing procedures in diagnostic situations (Reiter et al., 2005).
This explanation does not seem more plausible than the possi-
bility of amendments to cognitive ability assessed by the in-
strument. Moreover, other study (Marzocchi et al., 2009) using
the original version of the WCST indicate otherwise, coinciding
with our findings.
We used the Digits Backward (WISC-III) scores as a meas-
ure of verbal working memory, and DG scored lowered when
compared with CG. There is evidence of deficits in the resolu-
tion of the forward and backward digit span in children with
DD (Jeffries & Everatt, 2004). Other studies indicate that in-
struments that assess phonological working memory can be
used to distinguish children with dyslexia and control problems
because they reflect the level of phonological representation
(Jeffries & Everatt, 2004; Reiter et al., 2005; Schuchardt et al.,
2008; De Clercq-Quaegebeur et al., 2010).
The FAS was used in our study to measure verbal fluency.
Initially, according to our results, both groups showed semantic
category scores greater than the phonological category. This
can be considered normal due to the greater ease of semantic
test. However, the groups only differed in phonological cate-
gory. Previous studies described impairments in children with
DD when performing verbal fluency tests, with the recovery of
fewer words, especially in phonological category (Reiter et al.,
2005; Marzocchi et al., 2009).
We suggest that the results described above may not be part
of the core deficit in DD (Lima et al., 2012), but accompany the
deficit in the phonological component of language. According
to the literature, the attentional posterior system of superior
parietal cortex, mediated by the magnocellular processing, can
support impairments in visuospatial attention in DD (Facoetti et
al., 2010; Franceschini et al., 2012). In addition, top-down
executive control mechanisms, mediated by different regions of
the frontal lobe, may help explain deficits in executive func-
tioning skills. Thus, addition of language, DD can be consid-
ered a disorder of multiple deficits and at different levels, af-
fecting directly affect reading and writing.
The results suggest that children with Developmental Dys-
lexia have difficulties in visuospatial attention tasks and differ-
ent components of Executive Functions (flexibility, inhibitory
control, strategy use, working memory and verbal fluency),
confirming the hypothesis of the study. More studies on such
cognitive skills can assist in planning the evaluation, as well as
the development of neuropsychological intervention programs,
as described by Lorusso, Facoetti and Bakker (2010).
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