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ADULTS WITH DYSLEXIA 1
Annals of Dyslexia
(Published online September 2020)
Alexandra Reis1, 2, Susana Araújo3, Inês Salomé Morais1,2, & Luís Faísca1,2
Reading and reading related skills in adults with Dyslexia from different orthographic
systems: A review and meta-analysis
1 Departamento de Psicologia e Ciências da Educação, Universidade do Algarve, Faro, Portugal
2 Center for Biomedical Research - CBMR, Universidade do Algarve, Faro, Portugal
3 Faculdade de Psicologia, Universidade de Lisboa, Lisboa, Portugal
Corresponding author: aireis@ualg.pt
https://doi.org/10.1007/s11881-020-00205-x
ADULTS WITH DYSLEXIA 2
Abstract
An individual diagnosed with dyslexia in childhood typically remains dyslexic throughout
his/her life. However, the cognitive profile of adults with dyslexia has been less explored than
that of children. This meta-analytic study is intended to clarify three questions: (1) To what
extent, and in what manner, do adults with reading difficulties (dyslexia) differ from typical
adult readers in measures of reading and writing competence and related cognitive skills? (2)
To what extent do speed measures pose a greater challenge than accuracy measures in an
adult population that has already had years of print exposure? and (3) To what extent does
orthographic transparency modulate the reading profile of adults with dyslexia? A total of 178
studies comparing adults with dyslexia and matched controls were reviewed. The results
showed that adults with dyslexia exhibited poor performance on almost all reading and writing
tasks expressed by very large effect sizes (range: 1.735 ≤ d ≤ 2.034), except for reading
comprehension (d = 0.729). Deficits in the reading and writing related variables are also
present but with a lower expression (range: 0.591 ≤ d ≤ 1.295). These difficulties are
exacerbated for speed measures, especially for word and pseudoword reading, phonological
awareness, and orthographic knowledge. Orthographic transparency proved to be a significant
moderator of dyslexic deficits in word and pseudoword reading, reading comprehension,
spelling, and phonological awareness, with the expression of the deficits being weaker on
transparent—as opposed to intermediate and opaque—orthographies. Overall, the meta-
analysis shows that reading and writing difficulties persist in adulthood and are more
pronounced in speed measures. Moreover, symptoms are more severe for reading and writing
than they are for measures tapping into the cognitive processes underlying reading skills.
Orthographic transparency has a significant effect on the manifestation of dyslexia, with
dyslexia symptoms being less marked on transparent orthographies. In addition, phonological
awareness seems to be a minor problem in adulthood, especially for transparent
orthographies.
ADULTS WITH DYSLEXIA 3
Keywords: meta-analysis, dyslexic adults, reading, spelling, phonological awareness,
orthographic transparency
ADULTS WITH DYSLEXIA 4
Introduction
An individual diagnosed with dyslexia in childhood typically remains dyslexic
throughout his/her life (Hatcher, Snowling, & Griffiths, 2002; Pammer, 2014). Affected
individuals face difficulties acquiring reading and related cognitive skills—difficulties that
persist into adulthood. Therefore, such individuals are at risk of developing secondary
emotional and behavioural problems associated with educational failure, and later may
encounter unemployment and consequent psychological, economic, and social problems
(Gerber, 2012; Watson & Boman, 2005).
Despite this life-long persistence, the manifestations of dyslexia in adults, as opposed
to children, are far from understood, and the study of adults with dyslexia might bring new
insights into the field of developmental dyslexia. While studies with children are critical to
understanding the development of early reading skills and the cognitive capacities that predict
reading, they do not provide information about the long-term stability of reading deficits and
the actual profile of adults with dyslexia. For example, Miller-Shaul's (2005) results suggested
that, in an opaque orthography, some deficits present in children with dyslexia are attenuated
in adults but this is not an overall phenomenon. The gap between dyslexic and typical readers
decreases in adults compared to children in decoding errors, word reading in context and
orthographic ability measures; however, it increases in most of the phonological processing
tasks (e.g. phonological rhyming). Therefore, studies with children do not clarify which specific
deficits persist from childhood even after years of formal schooling and print exposure and the
reading domains that are somewhat compensated for in adulthood. In this way, adults with
dyslexia might represent a valuable model for studying whether the behavioural
manifestations of dyslexia change in the long run.
Furthermore, an important question that can be addressed through the study of
adults is why do some individuals attain age-appropriate reading skills despite a history of
ADULTS WITH DYSLEXIA 5
reading and spelling difficulties (compensated or high-functioning dyslexics) while others do
not (non-compensated) (Lefly, & Pennington, 1991; for a recent discussion on this topic, see
Cavalli, Duncan, Elbro, El Ahmadi, & Colé, 2017a; Eloranta, Närhi, Eklund, Ahonen, & Aro,
2019). One approach to exploring this question is the cognitive profiling of this population. For
instance, Cavalli and collaborators (2017a) tried to understand which language abilities
dyslexics may rely on to compensate for their deficits. The results revealed the existence of
deficits in phonological but not morphological abilities, suggesting that university students
with dyslexia may compensate for their reading weaknesses by drawing on morphological
knowledge.
Understanding the pattern of strengths and weakness of this adult population is critical
given the growing number of dyslexic students in higher education institutions (Pino &
Mortari, 2014). To that end, the need to construct adequate assessment and diagnostic
protocols has previously been recognised by Callens, Tops, Stevens, and Brysbaert (2014). The
better and more sensitive the instruments that are used to characterise this specific group, the
better the quality of the support that is provided, which means this group will experience
fewer difficulties in terms of academic skills and success.
Thus, we performed a systematic review of the residual difficulties of adults with
dyslexia. The only meta-analytic evidence available so far about adults with reading disorders
was obtained by Swanson and Hsieh (2009). Adults with reading disorders differ significantly
from typical adult readers in measures such as word recognition, pseudoword reading, reading
comprehension, spelling, writing, naming speed, phonological processing verbal memory,
vocabulary, and verbal intelligence (moderate to high effect sizes). In addition, differences are
seen in general cognitive variables, such as problem-solving/reasoning, visual memory,
monitoring or executive processing, perceptual skills, general intelligence and personality (low
to moderate effect sizes). Furthermore, effect sizes varied as a function of reading and
intellectual level; larger effect sizes emerged for studies with relatively high IQs and low overall
ADULTS WITH DYSLEXIA 6
reading scores. Taken in their totality, these results support the idea that the deficits found in
children persist until adulthood.
However, with few exceptions, most of the findings concerning adults with dyslexia
come from studies conducted in English, which is assumed to have the most opaque
alphabetic orthography. In Swanson and Hsieh’s meta-analysis, 50 out of 52 studies contained
samples that were recruited from English-speaking populations. Hence, the results cannot be
generalised to orthographies with different characteristics. The importance of considering the
role of orthographic transparency in reading acquisition and dyslexia is empirically justified,
given the number of large-scale studies from the last decade showing that the degree of
symbol-sound consistency of a language may affect the rate of reading acquisition (Seymour,
Aro, & Erskine, 2003) and the cognitive skills that predict reading performance (Landerl et al.,
2019; Vaessen et al., 2010; Ziegler et al., 2010). Moreover, it is well known that reading
difficulties are sensitive to orthographic transparency; thus, studies have been conducted to
analyse the characteristics of dyslexia in different orthographies (Landerl et al., 2013; Ziegler,
Perry, Ma-Wyatt, Ladner, & Schulte-Körne, 2003). For instance, in orthographies that are more
transparent than English, the difficulties in terms of reading skills are usually determined by
reading fluency rather than by accuracy (see, for example, for Italian, Re, Tressoldi, Cornoldi,
and Lucangeli, 2011, and for Spanish, Suárez-Coalla and Cuetos, 2015).
As most of the research seeking to characterise dyslexia in adulthood has concentrated
on English-based samples, the results cannot be fully generalised to other samples from less
opaque orthographies. For instance, Pennington, van Orden, Smith, Green, and Haith (1990)
indicated that poor phonological awareness is one of the primary deficits that persist in
anglophone adults with dyslexia, while Nergard-Nillssen and Hulme (2014) suggested that
spelling problems were the most prominent markers of dyslexia in adults in a Norwegian
sample (a more transparent orthography). Interestingly, in a Dutch sample (intermediate
orthography), Tops, Callens, Lammertyn, van Hees, and Brysbaert (2012) identified word
ADULTS WITH DYSLEXIA 7
reading, word spelling, and phoneme reversal time as the tests with the most predictive power
to identify dyslexia in adulthood.
In light of this heterogeneity, and to fill a gap in Swanson and Hsieh’s meta-analysis
(2009), we reviewed 178 studies whose distribution in terms of orthographic transparency
was: 12.9% samples from transparent orthographies, 19.7% from intermediate orthographies
and 67.4% from opaque orthographies. In addition, we extended the previous meta-analytic
review by including separate analyses by accuracy and speed measures, as both measures are
critical to the diagnosis of dyslexia and potentially interact with orthographic depth (Share,
2008). This decision was also made based on previous studies showing that speed measures
(such as reading fluency) are more suited than accuracy measures to identify reading problems
in adults, particularly those coming from more transparent orthographies (Re, Tressoldi,
Cornoldi, & Lucangeli, 2011; Suárez-Coalla & Cuetos, 2015).
Considering the topics currently under discussion regarding dyslexia in adults and the
importance of orthographic consistency in the expression of symptoms of dyslexia, we
intended in this meta-analytic study to clarify the following critical questions: (1) To what
extent, and in what manner, do adults with reading difficulties (dyslexia) differ from typical
adult readers (control group) on measures of overall reading and writing competence and
related cognitive skills? (2) To what extent do speed measures pose a greater challenge than
accuracy measures in an adult population that has already had years of print exposure? and (3)
To what extent does orthographic transparency modulate the reading profile of adults with
dyslexia? The broad age range in the adult sample creates the possibility of analysing the
effects of differences in reading practice on the symptoms of dyslexia. Thus, we also analyse
whether age moderates the differences between the groups.
Methods
Study Selection and Inclusion Criteria
ADULTS WITH DYSLEXIA 8
The studies included in the meta-analysis were identified in searches of the PsycINFO
and PubMed databases, using a combination of search terms related to reading disorders in
adulthood [(Adult OR Students OR College Students) AND (Dyslexia OR Reading Disorders OR
Reading Disabilities)] and using, as filters, Adults (18 years and older) and Peer-Reviewed
Journals. The meta-analysis included only studies published in English. Our search covered the
title, abstract, and keywords of all published articles that were available in the databases from
2006 until November 2019. We choose this time window to prevent an overlap with Swanson
and Hsieh’s (2009) previous meta-analysis. After the removal of duplicates, we found 3196
references. For inclusion, a study had to meet the following criteria: i) report original empirical
data for reading and reading-related variables, ii) compare the performance of individuals with
dyslexia to that of typical control readers (matched by relevant variables), iii) maintain a
sample age over 18 years old, and iv) contain enough information to compute effect sizes. The
samples with dyslexia were required to have an explicit classification as “dyslexics” or with
“specific reading disability/disorder”, typically based on a previous diagnosis. To avoid
violation of the independence of observations, studies from the same authors were examined
for duplicate samples. Whenever this occurred, we included only the articles that had more
complete data sets and/or larger samples (See Figure 1).
[Insert Figure 1 about here]
In the original search, only 178 articles met all of our inclusion criteria. Two of the
authors independently coded a random sample of 30% of the studies. Intercoder agreement
was estimated using the Pearson correlation for continuous information (such as effect sizes)
and Cohen’s kappa for categorical information (such as type of measure). Intercoder
correlation coefficients ranged from .96 to 1.0, while the kappa coefficients ranged from .85 to
1.0. Disagreements were resolved by consulting the original article or by discussion.
Coding Procedure and Moderator Variables
ADULTS WITH DYSLEXIA 9
For each study, the following information was coded for dyslexic and control (typical
readers) groups: sample size, mean age, number of females, mean years of schooling when the
information was available and orthography in which the participants were assessed. Means
and standard deviations for the dyslexic and control groups were also extracted for reading
and reading-related measures, for accuracy and speed (whenever available). These included
the most widely studied measures of core cognitive skills in reading disorders in children and
adults, and were categorized into three main groups: reading and writing variables (word,
pseudoword and text reading, reading comprehension, spelling); reading- and writing-related
variables (phonological awareness, orthographic knowledge, phonological memory, rapid
automatized naming, verbal working memory and vocabulary); and general cognitive ability
(full IQ, verbal- and nonverbal IQ, abstraction, and speed of processing). Data for all reading
and writing measures and reading-related measures were based on tests that were either
specifically designed for the study or taken from well-known reading batteries. Examples of
tests in these categories are provided.
Reading and writing variables. The following categories were considered:
(1) Word Reading: This category included word reading measures aimed at assessing
the visual recognition of real words from different categories (e.g. regular and irregular words)
by means of single-word identification tasks [e.g. Woodcock Reading Mastery Test (WRMT),
Wide Range Achievement Test (WRAT), Test of Word Reading Efficiency (TOWRE), One Minute
Test for timed reading of words (OMT) and the Alouette reading Test];
(2) Pseudoword Reading: This category included measures of single-pseudoword
reading to assess decoding skills [e.g. Wechsler Individual Achievement Test (WIAT), De Klepel
Test, Word Attack from Woodcock-Johnson III (WJ3)];
(3) Text Reading: This category included measures in which the participant solely has
to read a passage from a scholastic book, a text or unconnected sentences, with no need to
ADULTS WITH DYSLEXIA 10
answer any questions about it [e.g. Gray Oral Reading (GORT), Nelson-Denny Reading Test,
Memory-Transfer battery (MT)];
(4) Reading Comprehension: This category included measures in which the participant
reads a passage or sentence and then has to answer questions about it to assess her/his
comprehension [e.g. York Adult Assessment Battery Revised (YAA-R)] or in which the
participant is asked to perform a multiple-choice sentence completion task within a time limit
(e.g. Reading Age Test; 1-min TIL);
(5) Spelling: This category included measures aimed at assessing the ability to spell
using conventions of letter-sound relationships, such as writing words or pseudowords from
dictation [e.g. Outil de DÉpistage des DYSlexies (ODEDYS), Wechsler Individual Achievement
Test (WIAT), Dyslexia Adult Screening Test (DAST)].
Reading- and writing-related variables. The following categories were considered:
(1) Phonological Awareness: This category included several tasks requiring participants
to reflect upon and manipulate the speech sounds of words (e.g. phoneme deletion,
spoonerism, syllable reversal, and rhyme recognition) [e.g. Comprehensive Test of
Phonological Processing (CTOPP), Batería para la Evaluación de la Competencia Lectora
(EVALEC), YAA-R, DAST, ODEDYS]. Since the assessment of phonological awareness involved
tasks with different complexity levels, this category was subdivided into four levels adapted
from Parrila, Dudley, Song, and Georgiou (2020). Level 1 tasks focus on phonological units
larger than phonemes that require simple processing (judgement, matching or segmentation
of syllables or rhymes); Level 2 tasks focus on phonological units larger than phonemes and
require more complex processing (reversal or deletion of syllables and rhymes); Level 3 tasks
focus on phonemes and require simple phonemic awareness processing (matching, blending,
and segmentation of phonemes); and Level 4 tasks focus on phonemes and require complex
manipulations (deletion and substitution of phonemes and spoonerisms).
ADULTS WITH DYSLEXIA 11
(2) Phonological Memory: This category included tasks in which phonological
processing is automatically engaged, such as word and pseudoword repetition (e.g. CTOPP,
ODEDYS) and digit span forward tasks (e.g. WAIS);
(3) Orthographic Knowledge: This category included tasks in which the participant
must access specific information stored in long-term memory about how to represent spoken
language in written form, such as word chains, orthographic choice, proofreading, and lexical
decision tasks [e.g. Dyslexia Screening Battery (DUVAN)];
(4) Verbal Working Memory: This category included the classic digit span backward
measure from batteries such as the Wechsler Adult Intelligence Scale (WAIS);
(5) Vocabulary: This category included measures of semantic knowledge about words
and objects [e.g. vocabulary test from WAIS, Peabody Picture Vocabulary Test (PPVT-4),
Shipley vocabulary and Échelle de Vocabulaire en Images Peabody (EVIP)]. Given that
vocabulary measures are occasionally used as matching criteria for selecting participants, only
effect sizes (ESs) from studies in which vocabulary was exclusively used to characterised
groups were included to avoid underestimating the true vocabulary deficits;
(6) Rapid Automatized Naming (RAN): This category included measures of phonological
retrieval and processing, assessed through tasks featuring a continuous matrix presentation of
alphabetic (letters and digits) and non-alphabetic (objects and colours) stimuli, as in the
standard serial Rapid Automatized Naming Test (Denckla & Rudel, 1976).
General cognitive variables. The following categories were considered:
(1) Intelligence (IQ): The intelligence measures were coded to distinguish between full
IQ (e.g. WAIS full scale), verbal IQ (e.g. Woodcock-Johnson III – WJ-III-COG and the verbal scale
from WAIS) and nonverbal IQ (e.g. Raven Progressive Matrices and the performance scale from
WAIS). In order to not underestimate the true differences between groups, only ESs from
ADULTS WITH DYSLEXIA 12
studies in which IQ measures were not used as criteria for matching groups were included in
the analysis;
(2) Abstraction: This category included the similarities subtest from WAIS;
(3) Speed of Processing: This category included tasks with a speed factor (e.g. Digit-
Symbol Coding from WAIS and reaction time tasks).
We note that other cognitive variables (e.g. nonverbal working memory, attention,
oral comprehension, writing, and calculation) were also considered but were not included in
the analyses because there were only a few studies (< 7) for each.
Task measures. Task scores were classified as accuracy or speed measures. A score
was considered as an accuracy measure when it corresponded to the number, percentage,
and/or proportion of correct responses/errors in a time-unlimited task. A score was classified
as a speed measure when the performance was based on the number of correct responses by
time-limited tasks (correct responses per second) and when the score corresponded to the
time spent completing a time-unlimited task.
Orthography. Orthographic consistency was coded into three categories of complexity
expressing the feedforward and feedback consistency of grapheme-phoneme and phoneme-
grapheme correspondences (like a recent large-scale cross-linguistic study by Landerl and
collaborators, 2013) and based on Seymour, Aro, and Erskine’s (2003) classification: “opaque”
(Danish, English, French and Hebrew) and “transparent” (Spanish, Icelandic, Norwegian, Italian,
Finnish, Polish), with high and low levels of inconsistencies in both directions, respectively, and
“intermediate” complexity level (Dutch, German, European-Portuguese and Swedish) with high
feedforward consistency but low feedback consistency or the reverse. Our classification was
similar to the one used in a recent meta-analysis (Araújo & Faísca, 2019). Also, based on
Verhoeven and Perfetti (2017), consonantal root-based writing systems such as Hebrew were
included in the opaque category.
ADULTS WITH DYSLEXIA 13
Meta-analytic procedures
Effect size estimates. Data were analysed using the Comprehensive Meta-Analysis
software (Borenstein, Hedges, Higgins, & Rothstein, 2005). Effect sizes involving group
comparisons between readers with dyslexia and typical control-matched readers were
computed with Cohen’s d with corrections for small sample sizes (Hedges, 1981). Effect size
estimates were, in some cases (e.g. a study reporting two measures of real word reading),
aggregated using the arithmetic mean to avoid over-representation of multi-experiment
studies in the overall analyses (Rosenthal, 1991). When means and standard deviations were
not provided, d values were estimated from the reported t or F statistics. A positive d value
indicated that the control subjects had the highest group mean. A commonly used
interpretation is to refer to effect sizes as small (d = 0.2), medium (d = 0.5) and large (d = 0.8)
based on Cohen’s (1988) recommended guidelines.
When individual studies reported more than one effect size of interest for the same
sample, we used the shifting unit of analysis approach (Cooper, 2010), as this procedure
provides a good compromise between preserving the independence of the effect sizes and
retaining the maximum amount of information from each study. In this approach, each effect
size associated with a sample is first coded as if it were an independent estimate of the
relationship. The unit of analysis is then shifted according to the hypothesis being tested. For
the overall mean effect analysis, and whenever the moderator corresponded to a between-
studies factor defining separate groups of participants (e.g. orthography), we used the sample
as a unit of analysis. The multiple effects from each sample were aggregated so that each
sample contributed only one effect and all sample averaged effects were (almost)
independent. When testing the moderator effect of an outcome domain (e.g. type of reading
measure), and when multiple effect sizes were available within the same sample, we shifted
ADULTS WITH DYSLEXIA 14
the unit of analysis from the sample to the effect sizes, thereby allowing each sample to
contribute one effect size to each category of the moderator.
Analysis of effect sizes. Overall effect sizes were estimated by calculating a weighted
average of individual effect sizes (Rosenthal, 1991) based on a random effects model. For each
meta-analysis, we calculated a 95% confidence interval (CI), Z significance test for null effects
and its p-value, within-group heterogeneity (Qwithin), and the percentage of variation across
studies due to heterogeneity rather than sampling error (I2) (Borenstein, Hedges, Higgins, &
Rothstein, 2009).
To test the categorical moderator effects, we proceeded with a subgroup analysis with
the mixed-effects between-groups heterogeneity statistics (Qbetween, which has a chi-square
distribution and is analogous to an analysis of variance F test). For the continuous variables, we
used a meta-regression based on the method of moments for the random effects model to
predict variations in effect size across studies from the moderator variables. We report the
percentage of between-study variance explained (R2) as a measure of the effect size of the
moderator.
Forest plots were used to examine the distributions of effect sizes and to detect
potential outliers, while sensitivity analyses were conducted to determine their impact on the
overall range of means. Sensitivity analyses allow an adjusted overall effect size to be
estimated after the removal of studies one by one. Finally, we examined funnel plots for
random effects models to determine the presence of publication bias. The “trim and fill”
method for random effects models (Duval & Tweedie, 2000) was used to examine the impact
of possible missing studies.
Results
The present meta-analytic study included 178 articles (185 samples) comprising 1,817
effect sizes (ESs) comparing adults with dyslexia to matched typical readers. The total sample
ADULTS WITH DYSLEXIA 15
size was 4,363 (Mean sample size = 23.6; SD = 17.4) for adults with dyslexia and 5,029 (M =
27.2; SD = 23.9) for the control group. Concerning the reading status of the dyslexic
participants, 151 studies (84.8%) explicitly stated that dyslexic individuals had a previous
formal diagnosis of dyslexia; 21 studies (11.8%) included participants who self-reported a
history of reading problems, while in six studies (3.4%), the reading disorder group was
selected from a large pool of participants (in both cases, the authors confirmed the
participants’ reading status with an appropriate battery). In addition, information about
attentional problems was reported for about half of the studies: 103 studies (57.9%) explicitly
claimed that participants with attentional problems were excluded, while three studies (1.7%)
included, in their samples, some participants with or at risk of attentional problems and/or
hyperactivity. Given the low representativeness of these participants in the samples, we
decided to keep these three studies in order to avoid the loss of data. For 72 studies (40.4%),
the authors did not mention whether their samples included or did not include participants
with attention problems.
Overall, the dyslexic and control groups were equivalent in age with a weighted mean
age of 24.7yrs. (k = 148 samples; SEM = 0.80; 95% CI [23.1, 26.4]) and 24.2yrs. (k = 148
samples; SEM = 0.74; 95% CI [22.7, 25.7]), respectively. The sex ratio was also equivalent
between samples (k = 151 samples; female % in dyslexic samples: mean = 55.1%; 95% CI [52.4,
57.7]; female % in control samples: mean = 57.6%; 95% CI [54.9, 60.3]). Thirty studies did not
report information about the participants’ educational level, 100 included samples that were
recruited at universities, 11 included samples with varied educational levels (conjugating basic,
middle, high educational levels and university students), and only 37 reported the average
years of schooling (k = 39 dyslexic samples: mean = 14.0yrs.; SEM = 0.18; 95% CI [13.7, 14.4]; k
= 39 control samples: mean = 13.9yrs.; SEM = 0.17; 95% CI [13.6, 14.3]).
To fulfil our goals, the data was next analysed and reported based on our three main
questions. Additionally, we used a meta-regression analysis to analyse whether the
ADULTS WITH DYSLEXIA 16
participants’ age modulated reading deficits. Whenever the group comparisons included fewer
than six effect sizes for a given category, the results were not reported. Positive ES favoured
adults without reading disorders.
To what extent, and in what manner, do adults with reading difficulties (dyslexia) differ
from typical adult readers (control group) on measures of overall reading and writing
competence and related cognitive skills?
Overall, adult readers with dyslexia show poor performance compared to controls on
all reading and writing tasks, with very large deficits (d > 1.7) in all measures except reading
comprehension (d = 0.729). They also struggle, to a lesser extent (0.5 < d < 1.3) with tasks that
place demands on their phonological awareness and memory, orthographic knowledge and
rapid automatized naming skills. Concerning general cognitive skills, as expected, the observed
ESs vary from small (abstraction: d = 0.143; nonverbal IQ: d = 0.187) to large (speed of
processing: d = 0.840) with some ESs in the small-to-medium range (full IQ: d = 0.296; verbal
IQ: d = 0.424). For a clearer characterisation of adults’ reading difficulties, each skill will be
analysed separately (see Table 1).
[Insert Table 1 about here]
Word Reading
One hundred and sixty-one independent comparisons were made for word reading in
adults with dyslexia and controls. The overall mean effect size was large and significant (d =
1.812, 95% CI [1.690, 1.935], p < .001), confirming that adults with dyslexia perform much
more poorly on isolated word reading than do controls without reading difficulties. A
sensitivity analysis showed that after the removal of potential outliers, the overall effect size
was in the range of 1.786 (95% CI [1.667, 1.904]) to 1.821 (95% CI [1.700, 1.943]). In a trim and
fill analysis, 12 studies were imputed to the right of the mean (the adjusted overall mean was
1.927 (95% CI [1.795, 2.059]). The heterogeneity test was significant, Qwithin (160) = 777.7, p <
ADULTS WITH DYSLEXIA 17
.001, and around 80% of the observed variance was not accounted for by sampling error alone
(I2= 79.43).
Pseudoword Reading
One hundred and thirty-six independent effect sizes compared pseudoword reading
performance in adults with dyslexia and controls. The overall mean effect size was large and
significant (d = 2.034, 95% CI [1.896, 2.172], p < .001), confirming that adults with dyslexia
perform much worse on isolated pseudoword reading than do controls without reading
difficulties. A sensitivity analysis showed that after the removal of potential outliers, the
overall effect size was in the range of 2.012 (95% CI [1.878, 2.145]) to 2.046 (95% CI [1.909,
2.182]). In a trim and fill analysis, nine studies were imputed to the right of the mean (the
adjusted overall mean was 2.136 (95% CI [1.988, 2.285]). The heterogeneity test was
significant, Qwithin (135) = 796.1, p < .001, and around 80% of the observed variance was not
accounted for by sampling error alone (I2= 80.61).
Text Reading
Thirty-nine independent effect sizes were computed for text reading measures. The
overall mean effect size was large and significant (d = 1.761, 95% CI [1.472, 2.050], p < .001),
confirming that adults with dyslexia perform much more poorly than controls when context
assists reading. A sensitivity analysis showed that after the removal of potential outliers, the
overall effect size was in the range of 1.657 (95% CI [1.403, 1.911]) to 1.761 (95% CI [1.472,
2.050]). In a trim and fill analysis, six studies were imputed to the right of the mean (the
adjusted overall mean was 1.980 (95% CI [1.665, 2.295]). The heterogeneity test was
significant, Qwithin (38) = 279.6, p < .001, and over 85% of the observed variance was not
accounted for by sampling error alone (I2= 86.41).
Reading Comprehension
ADULTS WITH DYSLEXIA 18
Thirty-seven independent effect sizes were computed for reading comprehension
measures. The overall mean effect size was close to large and significant (d = 0.729, 95% CI
[0.550, 0.907], p < .001), confirming that adults with dyslexia perform more poorly on reading
comprehension as compared to controls. A sensitivity analysis showed that after the removal
of potential outliers, the overall effect size was in the range of 0.699 (95% CI [0.524, 0.874]) to
0.764 (95% CI [0.550, 0.907]). In a trim and fill analysis, no study was imputed, suggesting the
absence of publication bias. The heterogeneity test was significant, Qwithin (36) = 141.1, p <
.001, and around 75% of the observed variance was not accounted for by sampling error alone
(I2= 74.48).
Spelling
Ninety-nine independent effect sizes compared spelling performance in adults with
dyslexia and in controls. The overall mean effect size was large and significant (d = 1.735, 95%
CI [1.590, 1.880], p < .001), confirming that adults with dyslexia perform much worse on
spelling measures than do controls without reading difficulties. A sensitivity analysis showed
that after the removal of potential outliers, the overall effect size was in the range of 1.717
(95% CI [1.574, 1.860]) to 1.750 (95% CI [1.607, 1.893]). There was evidence of publication bias
favouring studies with larger effect sizes, confirmed by the funnel plot and the trim and fill
analysis (23 studies imputed were on the left side of the mean; the adjusted overall mean was
1.431 and 95% CI [1.369, 1.493]). The heterogeneity test was significant, Qwithin (98) = 446.7, p <
.001, and almost 80% of the observed variance was not accounted for by sampling error alone
(I2= 78.06).
Phonological Awareness
One hundred and one independent effect sizes were computed for the phonological
awareness measures. The overall mean effect size was large and significant (d = 1.177, 95% CI
[1.075, 1.279], p < .001), confirming that adults with dyslexia perform more poorly on
ADULTS WITH DYSLEXIA 19
phonological awareness measures than do controls. A sensitivity analysis showed that after
the removal of potential outliers, the overall effect size was in the range of 1.161 (95% CI
[1.062, 1.260]) to 1.188 (95% CI [1.089, 1.287]). There was evidence of publication bias
favouring studies with larger effect sizes, confirmed by the funnel plot and the trim and fill
analysis (31 studies imputed on the left side of the mean; the adjusted overall mean was 0.934
and 95% CI [0.821, 1.045]). The heterogeneity test was significant, Qwithin (100) = 250.2, p <
.001, and 60% of the observed variance was not accounted for by sampling error alone (I2=
60.02). Beyond the global effect, Table 1 also presents the ESs disaggregated by the level of
processing complexity required by the phonological awareness tasks. There was a significant
effect of levels on the magnitude of the phonological awareness deficit (p < .001; Level 1 was
excluded from the analysis due to the number of ESs). Level 3 presented a large ES, though still
significantly smaller than the other two levels (Level 2 vs. Level 3, p =.040; Level 2 vs. Level 4, p
= .911; Level 3 vs. Level 4, p < .001).
Phonological Memory
Sixty-six independent effect sizes were computed for phonological memory measures.
The overall mean effect size was large and significant (d = 1.034, 95% CI [0. 916, 1.153], p <
.001), confirming that adults with dyslexia perform more poorly on phonological memory
measures as compared to controls. A sensitivity analysis showed that after the removal of
potential outliers, the overall effect size was in the range of 0.995 (95% CI [0.894, 1.097]) to
1.050 (95% CI [0.934, 1.166]). In a trim and fill analysis, no study was imputed, suggesting the
absence of publication bias. The heterogeneity test was significant, Qwithin (65) = 154.7, p <
.001, and around 60% of the observed variance was not accounted for by sampling error alone
(I2= 57.99).
Orthographic Knowledge
ADULTS WITH DYSLEXIA 20
Twenty-six independent effect sizes were computed for orthographic knowledge
measures. The overall mean effect size was large and significant (d = 1.233, 95% CI [1.043,
1.423], p < .001), confirming that adults with dyslexia perform more poorly on tasks involving
orthographic knowledge as compared to controls. A sensitivity analysis showed that after the
removal of potential outliers, the overall effect size was in the range of 1.199 (95% CI [1.012,
1.386]) to 1.273 (95% CI [1.092, 1.453]). There is evidence of publication bias favouring studies
with larger effect sizes, confirmed by the funnel plot and the trim and fill analysis (one study
imputed on the left side of the mean; the adjusted overall mean was 1.210 and 95% CI [1.020,
1.399]). The heterogeneity test was significant, Qwithin (25) = 72.7, p < .001, and over 60% of the
observed variance was not accounted for by sampling error alone (I2= 65.59).
Verbal Working Memory
Twenty-six independent effect sizes were computed for verbal working memory. The
overall mean effect size was large and significant (d = 0.926, 95% CI [0.694, 1.158], p < .001),
confirming that adults with dyslexia perform more poorly on verbal working memory tasks as
compared to controls. A sensitivity analysis showed that after the removal of potential
outliers, the overall effect size was in the range of 0.810 (95% CI [0.684, 0.936]) to 0.950 (95%
CI [0.712, 1.189]). In a trim and fill analysis, nine studies were imputed to the right of the mean
(the adjusted overall mean was 1.181 (95% CI [0.953, 1.409]). The heterogeneity test was
significant, Qwithin (25) = 79.7, p < .001, and almost 70% of the observed variance was not
accounted for by sampling error alone (I2= 68.64).
Vocabulary
Thirty-eight independent effect sizes were computed for vocabulary measures. The
overall mean effect size was medium and significant (d = 0.591, 95% CI [0.440, 0.742], p <
.001), suggesting that adults with dyslexia have weaker vocabulary skills than do controls. A
sensitivity analysis showed that after the removal of potential outliers, the overall effect size
ADULTS WITH DYSLEXIA 21
was in the range of 0.562 (95% CI [0.417, 0.707]) to 0.615 (95% CI [0.467, 0.763]). In a trim and
fill analysis, three studies were imputed to the right of the mean (the adjusted overall mean
was 0.652 (95% CI [0.497, 0.806]). This was confirmed by the funnel plot. The heterogeneity
test was significant, Qwithin (37) = 91.0, p < .001, and almost 60% of the observed variance was
not accounted for by sampling error alone (I2= 59.34).
Rapid Automatized Naming (RAN)
Seventy-seven independent effect sizes were computed for rapid automatized
naming. The overall mean effect size was large and significant (d = 1.191, 95% CI [1.091,
1.290], p < .001), confirming that adults with dyslexia perform more poorly on rapid
automatized naming tasks than do controls. A sensitivity analysis showed that after the
removal of potential outliers, the overall effect size was in the range of 1.175 (95% CI [1.078,
1.273]) to 1.207 (95% CI [1.116, 1.298]). There was evidence of publication bias, confirmed by
the funnel plot and the trim and fill analysis (23 studies imputed on the left of the mean; the
adjusted overall mean was 0.980 and 95% CI [0.870, 1.090]). The heterogeneity test was
significant, Qwithin (76) = 138.4, p < .001, and less than 50% of the observed variance was not
accounted for by sampling error alone (I2= 45.07). Part of this heterogeneity seems to be
explained by the alphabetic nature of the stimulus (see Table 1): the ES associated with RAN
alphabetic (letters and digits, d = 1.295) is significantly larger (p < .001) than the ES of RAN
non-alphabetic (objects and colours, d = 0.972).
Full IQ
Twenty-eight independent effect sizes were computed for full IQ. The overall mean
effect size was significant (d = 0.296, 95% CI [0.158, 0.434], p < .001), confirming that adults
with dyslexia have a somewhat lower performance on full IQ measures as compared to
controls. A sensitivity analysis showed that after the removal of potential outliers, the overall
effect size was in the range of 0.258 (95% CI [0.132, 0.383]) to 0.320 (95% CI [0.184, 0.455]).
ADULTS WITH DYSLEXIA 22
There was no evidence of publication bias, confirmed by the funnel plot and the trim and fill
analysis (0 studies imputed). The heterogeneity test was significant, Qwithin (27) = 48.7, p = .006,
and nearly 45% of the observed variance was not accounted for by sampling error alone (I2=
44.58).
Nonverbal IQ
Seventy-five independent effect sizes were computed for nonverbal IQ. The overall
mean effect size was small but significant (d = 0.187, 95% CI [0.106, 0.269], p < .001). A
sensitivity analysis showed that after the removal of potential outliers, the overall effect size
was in the range of 0.174 (95% CI [0.093, 0.254]) to 0.199 (95% CI [0.119, 0.278]). There was
evidence of publication bias, confirmed by the funnel plot and the trim and fill analysis (11
studies imputed on the left of the mean; the adjusted overall mean was 0.108 and 95% CI
[0.019, 0.198]). The heterogeneity test was not significant, Qwithin (74) = 97.1, p = .037, and
nearly 25% of the observed variance was not accounted for by sampling error alone (I2= 23.82).
Verbal IQ
Ten independent effect sizes were computed for verbal IQ. The overall mean effect
size was small-to-medium and significant (d = 0.424, 95% CI [0.028, 0.821], p = .036),
confirming that adults with dyslexia have a lower verbal IQ as compared to controls. A
sensitivity analysis showed that after the removal of potential outliers, the overall effect size
was in the range of 0.320 (95% CI [-0.056, 0.696]) to 0.556 (95% CI [0.232, 0.881]). There was
no evidence of publication bias, confirmed by the funnel plot and the trim and fill analysis. The
heterogeneity test was significant, Qwithin (9) = 36.4, p < .001, and three-quarters of the
observed variance was not accounted for by sampling error alone (I2= 75.27).
Abstraction
ADULTS WITH DYSLEXIA 23
Thirteen independent effect sizes were computed for abstraction. The overall mean
effect size was small (d = 0.143, 95% CI [-0.121, 0.408], p = .287), suggesting almost equivalent
abstraction skills between adults with dyslexia and controls. A sensitivity analysis showed that
after the removal of potential outliers, the overall effect size was in the range of 0.020 (95% CI
[-0.175, 0.216]) to 0.200 (95% CI [-0.066, 0.467]). There was no evidence of publication bias.
The heterogeneity test was significant, Qwithin (13) = 29.8, p = .003, and almost 60% of the
observed variance was not accounted for by sampling error alone (I2= 59.8).
Speed of Processing
Eleven independent effect sizes were computed for speed of processing. The overall
mean effect size was large and significant (d = 0.840, 95% CI [0.551, 1.129], p < .001),
confirming that adults with dyslexia have a lower speed of processing as compared to controls.
A sensitivity analysis showed that after the removal of potential outliers, the overall effect size
was in the range of 0.778 (95% CI [0.491, 1.026]) to 0.906 (95% CI [0.613, 1.199]). There was
no evidence of publication bias, confirmed by the funnel plot and the trim and fill analysis (0
studies imputed). The heterogeneity test was significant, Qwithin (10) = 36.3, p < .001, and over
70% of the observed variance was not accounted for by sampling error alone (I2= 72.46).
To what extent do speed measures pose a greater challenge than accuracy measures in
an adult population that has already had years of print exposure?
To address this question, we compared the performance of both groups on accuracy-
and speed-based measures of assessment (see Table 2). It is interesting to observe that speed
measures exacerbate the reading symptoms of dyslexia. The ESs for real word (d = 1.914),
pseudoword (d = 2.086), text reading (d = 1.767), reading comprehension (d = 0.900) and
spelling (d = 1.767) were larger when performance was measured with time. However, the
ANOVA analogue analysis indicated significant results only for real word (p < .001) and
ADULTS WITH DYSLEXIA 24
pseudoword reading (p < .001). For reading comprehension, text reading, and spelling, the
differences between speed and accuracy measures were not significant.
Likewise, on reading- and writing-related variables, ESs for both phonological
awareness (accuracy: d = 1.074; speed: d = 1.404) and orthographic knowledge (accuracy: d =
1.027; speed: d = 1.521) were larger when speed measures were used instead of accuracy (p <
.001 and p = .009, respectively).
For the remaining variables, either the number of available studies was insufficient, or
the assessments were based on either speed or accuracy measures.
[Insert Table 2 about here]
To what extent does orthographic transparency modulate the reading profile of adults
with dyslexia?
To determine whether orthographic transparency modulates the way in which
symptoms are expressed in adults with dyslexia, we separated this moderator variable into
three categories of transparency (opaque, intermediate, and transparent). As seen in Table 3,
the three orthographies displayed significant ESs (most of them very large) across all reading
and reading-related skills that we examined. These results confirm that, independent of the
properties of the orthographies, dyslexia symptoms persist into adulthood. However, the
magnitude of some of these deficits does vary.
When the opacity of the orthography was considered (see Table 3), significant
differences were observed for word reading accuracy (p = .016). Transparent had the lowest ES
(d = 1.070), followed by intermediate (d = 1.420) and opaque orthography (d = 1.619). While
the difference between transparent and opaque was significant (p = .004), no differences
ADULTS WITH DYSLEXIA 25
between transparent and intermediate, and between intermediate and opaque were
observed. When word reading was measured with speed, all orthographies revealed larger ESs
(transparent: d = 1.672; intermediate: d = 1.938; opaque: d = 1.952), though no significant
differences between the three levels of orthographic complexity were registered.
For pseudoword reading accuracy, orthographic transparency yielded a marginally
significant effect (p = .073). Again, transparent orthographies showed the smallest ES (d =
1.304), followed by the opaque ES (d = 1.738) and the intermediate orthographies ES (d =
1.976). Pairwise comparisons showed that the difference between transparent vs. opaque (p =
.041) and between transparent vs. intermediate (p = .063) orthographies approached
significance. Larger ESs were observed for pseudoword speed compared to pseudoword
accuracy (transparent: d = 1.711; opaque: d = 2.043; intermediate: d = 2.354) with significant
differences among the three orthographies (p = .048). Pairwise comparisons showed a
difference between transparent vs. intermediate (p = .015) and transparent vs. opaque (p =
.087) orthographies with opaque and intermediate performing at an equivalent level.
Reading comprehension accuracy registered significant differences among
orthographies (p = .047) with larger ESs for intermediate orthographies (d = 1.354) compared
to transparent (d = 0.452) and opaque (d = 0.614). Pairwise comparisons showed that the
deficit in reading comprehension was significantly more marked for intermediate
orthographies (in contrast to transparent orthographies, p = .015, and in contrast to opaque
orthographies, p = .066).
The same holds true for spelling accuracy (p = .007) with larger ESs in studies sampling
participants from intermediate orthographies (intermediate: d = 2.073; opaque: d = 1.708;
transparent: d = 1.250). Pairwise contrasts between transparent vs. intermediate (p < .002),
transparent vs. opaque (p = .024) and intermediate vs. opaque (p = .066) were all reliable.
ADULTS WITH DYSLEXIA 26
Concerning reading- and writing-related skills, orthographic consistency is a significant
moderator variable, in particular for phonological awareness (p = .005) with a medium-to-
large ES observed in transparent orthographies (d = 0.633) and rather large ESs observed in
intermediate and opaque orthographies (d = 1.264 and d = 1.145, respectively). Pairwise
comparisons confirmed that the deficits in this measure were smaller for adults with dyslexia
from transparent orthographies (in contrast to intermediate orthographies, p = .003, and in
contrast to opaque orthographies, p = .002, while no differences were observed for
intermediate vs. opaque orthographies).
In terms of phonological memory, no significant moderator effect of orthography was
observed. The three orthographic groups showed rather equivalent ESs (transparent: d =
0.944; intermediate: d = 1.048; opaque: d = 1.052). The same was true for RAN (transparent: d
= 1.110; intermediate: d = 1.175; opaque: d = 1.211).
For the remaining variables, the impact of orthography on adults with dyslexia could
not be evaluated using the present data set, given the reduced number of effect sizes available
per category.
[Insert Table 3 about here]
Regression Analysis
Lastly, given that age may be associated with a practice factor, a meta-regression
analysis was performed to examine whether this variable predicts the size of the observed
deficits in individuals with dyslexia. This analysis included only studies that mentioned a mean
age value for the dyslexic sample. It is apparent in Table 4, that even in adulthood, age predicts
the size of the reading deficit in dyslexia but only in terms of the accuracy measures of real
word reading (β = -0.04; p = .01). This is also true for spelling (β = -0.03; p = .03), while age has
no significant impact on the ES obtained for the other measures assessed.
ADULTS WITH DYSLEXIA 27
[Insert Table 4 about here]
Sampling Characteristics
Considering the large pool of papers included in this meta-analysis and consequently
the diversity of methods for identifying reading disabilities as well as other comorbidities, it
would make sense to also examine if the different sample selection criteria might affect the
results. As reported previously, 84.8% of the studies explicitly stated that participants included
in the dyslexic group had a previous formal diagnosis, while the remaining did not use that
criterion for including participants in the dyslexic group. Another possible source of variability
is the way that authors dealt with comorbidities, namely the attentional disorders (about 58%
of the studies explicitly stated that participants with attention problems were excluded).
Therefore, the data was analysed in order to test if these different inclusion criteria do affect
the ES of the main reading and writing variables.
First, we examined if the presence of a previous diagnosis of dyslexia (151 studies and
156 samples) vs. no previous diagnosis (self-reported dyslexia or dyslexic participants
identified and selected from a large pool of participants; 27 studies and 29 samples) had an
impact on reading and writing measures. As can be seen in Table 5, only the deficit on
pseudoword reading speed was moderated by the type of diagnosis; this deficit was larger in
studies where dyslexic participants did not have a previous formal diagnosis. To determine the
effect of the control of attentional deficits, we compared studies which explicitly claimed the
exclusion of participants with attentional problems (103 studies and 105 samples) vs. studies
that did not mention whether their samples included participants with attentional problems
(72 studies and 77 samples). The results showed that controlling or not controlling the
ADULTS WITH DYSLEXIA 28
presence of attentional deficits does not moderate the ES in any of the reading and writing
measures.
[Insert Table 5 about here]
Discussion
Dyslexia is a disorder that persists until adulthood, yet studies on adults with dyslexia
are scarce as compared to studies on children with dyslexia. In this meta-analysis, we aimed to
perform a systematic characterisation of the weaknesses that are primarily associated with
dyslexia in adulthood. The knowledge available in the literature suggests that problems in
reading fluency and spelling are the most prominent markers of dyslexia in adulthood
(Nergård-Nilssen & Hulme, 2014). On the other hand, some studies indicate that adults with
dyslexia still differ significantly from those without dyslexia in terms of several cognitive skills,
such as phonological short-term memory, phonological awareness and whole-word processing
(Tamboer et al., 2016; Swanson & Hsieh, 2009). However, with few exceptions, most of these
findings come from studies conducted in English, an opaque orthography. This is critical,
because it is well-established that orthographic transparency has a strong impact on the rate
at which reading skills develop and the way in which symptoms of reading difficulties are
expressed (Landerl et al., 2013; Share, 2008). Furthermore, the assessment of adults with
dyslexia has used either accuracy or speed, or both, as performance indices. However, it is
questionable whether these indices have the same sensitivity in detecting reading disorders in
adulthood and if they potentially interact with orthographic transparency. To address these
issues and to obtain a characterisation of the major cognitive symptoms of dyslexia in adults,
we conducted a meta-analytic review that added performance indices (accuracy and speed)
and orthographic transparency as moderator variables.
How do Adults with Dyslexia Differ from Adult Typical Readers?
ADULTS WITH DYSLEXIA 29
Our first question sought to analyse the extent to which adults with dyslexia differ
from typical readers (control group) on measures of reading and writing (word, pseudoword,
and text reading, reading comprehension, and spelling) and related cognitive skills
(phonological awareness, phonological memory, verbal working memory, orthographic
knowledge, vocabulary, and rapid automatized naming) as well as on general cognitive abilities
(verbal and nonverbal IQs, abstraction, and speed of processing). Empirical studies focusing on
adult groups of readers with dyslexia most often assess the performance of high-functioning,
university students who were diagnosed in childhood, many of whom had probably
participated in intervention programmes. In this review, 80% of the studies tested university
students, so we could expect that some cognitive domains would be compensated for to
varying degrees and, consequently, the differences compared to typical readers attenuated.
Overall, our meta-analytic results showed that adults with dyslexia still score more
poorly than typical readers on reading measures, even when context can assist in decoding as
in text reading, as well as on all reading-related measures considered in this study.
Importantly, this was generally expressed by large effect sizes across domains (most of them
above 1.0) with a few exceptions (vocabulary and reading comprehension). Hence, many
cognitive-linguistic constructs are implicated in dyslexia and impairments in the cognitive
processes that underlie reading skills persist into adulthood. Interestingly, symptoms are
relatively more severe for reading and writing abilities (median d = 1.761; ranging from d =
0.729 to d = 2.034) than for the cognitive processing skills associated with literacy (median d =
1.103; ranging from d = 0.591 to d = 1.295), consistent with Swanson and Hsieh’s (2009) prior
meta-analysis. This dissociation may suggest that years of reading exposure, together with
remediation programmes, could help improve cognitive processing abilities that support
reading and writing (although not sufficiently to perform at a normal level). An alternative
explanation could be that, in adulthood, reading and writing are less dependent on these
abilities than they are in children.
ADULTS WITH DYSLEXIA 30
The only non-significant comparison between typical readers and the dyslexic group
was for abstraction, whereas small and small-to-medium ESs were registered for measures
related to general cognitive skills, such as nonverbal IQ (d = 0.187), full IQ (d = 0.296) and
verbal IQ (d = 0.424). In our results, the relatively larger difference registered for verbal IQ is
probably due to the fact that dyslexic individuals have less with reading and writing, and,
therefore, have a lag in verbal ability. Still, their full IQ score was within the population average
(Dyslexic Mean = 110.9, ranging from 100.5 to 126.0; Controls Mean = 113.5, ranging from
104.9 to 128.8). A practical implication of these results is that nonverbal IQ measures should
be preferable when assessing general cognitive function in individuals with dyslexia, as these
measures depend less on reading abilities and therefore are less detrimental to these readers.
It is important to note, however, that the reported differences between groups in general
cognitive functioning, as measured by nonverbal IQ, did not bias the estimated word reading
deficit (meta-regression for word reading accuracy: k = 72, β = -0.121, p = .642, R2 = .00; for
word reading speed: k = 82, β = -0.128, p = .645, R2 = .00). This finding supports the uncoupling
of reading and IQ (Ferrer, Shaywitz, Holahan, Marchione, & Shaywitz, 2010).
We also investigated the extent to which the age of the dyslexic group (range: 18 to 41
years) was a possible moderator of the effect sizes obtained. Significant negative effects of age
were observed only on word reading accuracy and spelling accuracy, suggesting that the older
the participants, the smaller the deficit. These effects are most likely explained by the reading
practice associated with age. Interestingly, word reading, and spelling correspond to those
variables indicating that they may be more sensitive to lexical knowledge. This might suggest
that the compensation observed in older participants results from the increase in their lexical
knowledge.
To what extent do speed measures pose a greater challenge than accuracy measures in an
adult population that has already had years of print exposure?
ADULTS WITH DYSLEXIA 31
An innovative aspect of this meta-analytic review was our intention to clarify whether
and to what extent speed measures pose an added challenge, as compared to accuracy
measures, to adults with dyslexia with years of print exposure. Some studies have suggested
that while accuracy improves, adult dyslexics may still experience problems with reading
fluency (Eloranta et al., 2019). Thus, for each domain, we compared the magnitude of the
deficit in accuracy measures with the magnitude of the deficit in speed measures (e.g. word
reading accuracy vs. word reading speed). Our results showed that, relative to control readers,
dyslexic adults, indeed, perform more poorly on speed measures of word and pseudoword
reading, phonological awareness, and orthographic knowledge than on corresponding
accuracy measures. The stronger ESs for speed measures indicate that automaticity is
significantly associated with reading ability, but this is harder to attain in adults with dyslexia
who, compared to children, have more years of reading experience. This result is relevant for
neuropsychological/psychoeducational assessment. Given that their performance is less
impaired when accuracy is measured, tests measuring speed are more sensitive to differences
between adults with dyslexia and control samples. For text reading, reading comprehension,
and spelling the magnitude of the deficit was, in turn, not significantly different between
accuracy and speed measures.
In sum, in adulthood, the main symptoms associated with dyslexia seem somehow
attenuated (word and pseudoword reading, phonological awareness, and orthographic
knowledge) when performance is quantified using accuracy and seem amplified when
performance is measured with time. However, this dissociation between accuracy and speed
may be inflated particularly in transparent orthographies, as we discuss below.
Does orthographic transparency modulate the reading profile of adults with dyslexia?
The third question we intend to examine in this meta-analytic review is the extent to
which the orthography in which we learn to read and write modulates the reading profile of
adults with dyslexia. During the last decade, a number of cross-cultural studies focused on the
ADULTS WITH DYSLEXIA 32
influence of orthographic consistency on reading development (Seymour et al., 2003), on
reading predictors (e.g. Caravolas, Lervåg, Defior, Seidlová Málková, & Hulme, 2013; Moll et
al., 2014; Vaessen et al., 2010; Ziegler et al., 2010) and on the expression of dyslexia (Becker et
al., 2014; Landerl et al., 2013). Given this previous research, we expected that dyslexia's main
deficits would be less prominent in orthographies where access to the written code is more
straightforward. In more transparent orthographies, learning a limited number of grapheme-
phoneme correspondences facilitates the reading of a great number of words, even without
previous contact with the word, while in opaque orthographies, the individuals must learn and
store a larger number of grapheme-phoneme units so that they can read and write effectively.
Our results clearly showed that orthographic transparency is an important factor
affecting the way deficits express themselves. In adulthood, dyslexic participants who learned
how to read and write in transparent orthographies showed less marked deficits overall as
compared to participants who learned to read in more opaque orthographies. This was
particularly visible for accuracy reading measures that seem to discriminate against
participants from different orthographies. Namely, we found significant differences for word
and pseudoword reading, reading comprehension and spelling, which favoured transparent
orthographies. On the other hand, deficits in speed measures were particularly high and
relatively homogeneous, confirming that fluency is a major problem in adulthood dyslexia
across orthographies. In general, these findings corroborate previous cross-language studies
which have indicated that inaccurate decoding and slow reading characterise the
manifestations of dyslexia in opaque orthographies, while slow and effortful reading, rather
than poor accuracy, is characteristic of dyslexia in more transparent ones (e.g. Goulandris,
2003).
For word reading accuracy, participants with dyslexia from transparent orthographies
differ less from normative readers compared to those from opaque orthographies (although
both ESs were large). The comparison between these two orthographic groups was also
ADULTS WITH DYSLEXIA 33
significant. These results are consistent with the literature suggesting that the more opaque
the orthography, the greater the reading deficit (Paulesu et al., 2001; Ziegler et al., 2003).
However, for word reading speed, we found no significant differences in the magnitude of the
deficit between orthographic groups, suggesting that the reading fluency deficit in dyslexia is
equivalent across orthographies. It is interesting to note that dyslexic readers from transparent
orthographies are less impaired in terms of word reading accuracy (d = 1.070) as compared to
word reading speed (d = 1.672). This suggests that speed measures are more suited than
accuracy to identify reading problems in adults, particularly those coming from more
transparent orthographies (Re, Tressoldi, Cornoldi, & Lucangeli, 2011; Suárez-Coalla & Cuetos,
2015).
The results from pseudoword reading followed a similar pattern to word reading for
both accuracy and speed. When pseudoword accuracy was considered, the transparent
orthography showed the lowest ES, followed by the opaque and the intermediate
orthographies, with a slightly significant difference between these two systems. Again,
learning to read in a transparent orthography seems to facilitate decoding. Just like word
reading speed, pseudoword reading speed presented larger ESs as compared to accuracy and
seems particularly difficult for dyslexic adults in intermediate and opaque orthographies (d >
2.0). In transparent orthographies, the pseudoword reading speed deficit was close to the
word reading speed deficit (d ~ 1.7). Overall, it seems that while adults with dyslexia from
more opaque orthographies still struggle with reading accuracy (word and pseudoword), all
adults with dyslexia, independent of the transparency of the orthographic code, have reading
speed problems that are more emphasized in decoding tasks. This outcome confirms previous
studies performed in various languages [e.g. Finish (Lyytinen, Aro, & Holopainnen, 2004),
Italian (Zoccolotti et al., 1999), Dutch (Yap & van der Leij, 1993), and Hebrew (Breznitz, 1997)].
Our study also confirmed that beyond reading difficulties, spelling represents a core
ADULTS WITH DYSLEXIA 34
problem in adults with dyslexia, whose magnitude is moderated by orthography. Participants
with dyslexia from transparent orthographies have significantly less pronounced deficits in
spelling compared to participants from the other orthographies. Data from several studies
conducted in orthographies with different feedforward and feedback consistencies have
previously suggested that spelling problems are the most prominent marker of dyslexia in
adults (Callens et al., 2014; Everatt, 1997; Kemp, Parrila, & Kirby, 2009; Nergård-Nilssen &
Hulme, 2014) and are highly discriminative for dyslexia in higher education (Lindgrén & Laine,
2011). This is at least partly expected because phoneme-to-grapheme mappings needed for
writing are typically less predictable than grapheme-to-phoneme mappings needed for reading
(Bosman & Van Orden, 1997). Consequently, accurate spelling is potentially more demanding
than reading. Our results considering orthography as a moderator seem to support this view:
spelling deficits were significantly smaller in dyslexic readers from transparent orthographies
(i.e. with the highest cross-code consistency both in feedforward and feedback directions; d =
1.250) as compared to intermediate (d = 2.073) and opaque orthographies (d = 1.708).
Indeed, adults with dyslexia (particularly high-functioning dyslexics) seem to be able to
use phonological skills to spell words, but they have difficulty in memorizing orthographic
patterns (Kemp, Parrila, & Kirby, 2009). While the use of these phonological strategies is
particularly advantageous for transparent orthographies, the difficulty in memorising
orthographic patterns prevents the accurate spelling of irregular words that depend on
orthographic knowledge. Interestingly, our dyslexic sample revealed a deficit in the
orthographic knowledge (d = 1.233). The existence of an orthographic deficit in our sample,
together with the possibility of adopting a phonological strategy when spelling consistent
words, can thus explain the smaller deficit observed in transparent compared to more opaque
orthographies, where efficient spelling demands a more lexical strategy.
The observed largest ES for spelling in intermediate orthographies might rely on the
ADULTS WITH DYSLEXIA 35
discrepancy between reading and writing in these orthographies. That is, while in opaque
orthographies the inconsistent grapheme-to-phoneme correspondences somehow prepare
the individuals to deal with the equivalent level of inconsistency involved in writing (namely,
favouring lexical orthographic knowledge), in intermediate ones, the relatively consistent
grapheme-to-phoneme correspondences do not favour compensatory strategies to deal with
less transparent spelling. This may lead, in turn, to a larger spelling deficit, as we found.
Reading comprehension seems to be the core reading skill for which the deficit in
dyslexia is overall less marked (d = 0.729). For reading comprehension accuracy, we found a
significant influence of orthographic transparency with deficit in adults with dyslexia being
higher in intermediate compared to transparent and opaque orthographies. The effect of this
moderator in reading comprehension has received little attention, especially in adults. To our
knowledge, only two studies have analysed this question. Hanley, Masterson, Spencer and
Evans (2004), compared English to Welsh 5th grade children and found that the English children
performed significantly better at answering comprehension questions about stories that they
had read than the Welsh children. This result suggests that being a reader of a transparent
orthography (Welsh) does not confer any advantage as far as reading comprehension is
concerned, while the opaque orthography (English) seems to benefit comprehension. As the
authors argued, the fact that the comprehension score of the English children actually
exceeded the score of the Welsh children might conceivably occur because an opaque
orthography fosters greater emphasis on semantics than on phonologically-based reading
strategies.
More recently, Mcclung and Pearson (2019) analysed the reading comprehension
results from two international assessments (PIRLS and PISA) with children and adolescents
from seven countries. The authors found that competent readers from opaque as compared to
more transparent orthographies may experience smaller but beneficial effects of reading
ADULTS WITH DYSLEXIA 36
comprehension because opaque orthographies encourage a greater reliance on print-to-
meaning connections (Perfetti & Stafura, 2014). On the contrary, reading comprehension of
less competent readers may be slowed down by the demands of opaque orthographies
(irregular phoneme-grapheme correspondences). Hence, according to these studies, we
expected to find larger deficits in reading comprehension for dyslexic readers from more
opaque orthographies, since these orthographies keep less skilled readers mired at the floor of
the distribution but propel more skilled readers toward the ceiling (Mcclung & Pearson, 2019).
However, our results showed an almost equivalent deficit in reading comprehension
for opaque and transparent orthographies (d = 0.614 and d = 0.452, respectively) suggesting
that the orthographic transparency does not affect reading comprehension, at least in adults.
In addition, the surprising results observed in intermediate orthographies do not fit Mcclung
and Pearson’s (2019) proposal. But we note that, due to the imbalance in the number of
studies representing each orthographic group with consequences for the reliability of ESs
estimates and statistical power, results must be looked at carefully. In our opinion, these
different findings about the moderator role of orthographies in reading comprehension
deficits in adults with dyslexia need to be further explored with extended samples.
Regarding the core skills that support reading and writing, our meta-analysis showed
that orthographies have a moderator effect on phonological awareness accuracy. Specifically,
adults with dyslexia performed markedly worse than controls in intermediate and opaque
orthographies (d’s > 1.1) while this phonological awareness deficit was smaller (d = 0.663) in
dyslexic adults from transparent orthographies. Whether this results from a better
compensation or from an a priori lower deficit in individuals with dyslexia in transparent
orthographies is unclear.
The impact of phonological awareness in reading performance across orthographies
was already documented by Ziegler and colleagues in children (Ziegler et al., 2010), showing
ADULTS WITH DYSLEXIA 37
that they were stronger in more opaque orthographies. Furthermore, Furnes and Samuelsson
(2011) investigated the longitudinal predictors of reading and spelling difficulties in children
learning to read either Norwegian (more transparent) or English (opaque), and found that
phonological awareness diminished as a predictor of reading difficulties in transparent
orthographies after the first years in school. These cross-cultural studies with children agree
that phonological awareness in more transparent orthographies becomes less associated with
reading in older children. To confirm that compensation of phonological deficits occurs in more
transparent orthographies, longitudinal cross-cultural studies in adults with dyslexia are
needed.
Since the phonological awareness variable consisted of tests where the participants
had to deal with phonological units of different sizes (syllables, rhymes and phonemes) as well
as tasks with different complexity (from the simplest such as judgement or matching to more
complex ones such as deleting or manipulating phonological units), we reanalysed this variable
by considering the nature of the task and the size of the phonological unit. This analysis
allowed us to investigate if adults with a lifelong history of reading disorders had somehow
compensated for some level of their phonological processing difficulties. The results indicated
a medium-to-large impairment in dyslexia that spans the different phonological awareness
measures and persists into adulthood.
Moreover, in adults with dyslexia, phonological awareness at the syllable level is not
necessarily easier than processing phonemes, and performance seems to depend mainly on
the task demands. Tasks requiring the manipulation of phonological units, either syllables or
phonemes, pose a greater challenge than tasks requiring simpler processing (such as syllables
and phoneme blending). It thus seems that an extended experience with the written code
might help adult dyslexics to solve simple tasks involving phonemes.
ADULTS WITH DYSLEXIA 38
In contrast, the size of the deficit in phonological memory, which is closely tied to
phonological processing (Jong & van der Leij, 1999), was not moderated by the orthography.
Deficits in phonological memory as well as in verbal working memory have been consistently
observed in children and adolescents with dyslexia (Swanson, Zheng, & Jerman, 2009) and our
data confirmed that these deficits persist into adulthood. Such verbal memory deficits
contribute to reading difficulties by preventing an efficient access to the phonological and
executive resources required in reading and writing processes.
Another well-known cognitive correlate of reading and writing is RAN and was thus
also analysed here. As mentioned previously, this meta-analysis showed a large RAN deficit in
adults with dyslexia, extending a recent meta-analysis including mainly dyslexic children
(Araújo & Faísca, 2019). Longitudinal research also demonstrated that rapid naming was, in
fact, a factor that differentiated individuals with persisting reading disorders from those with
improved reading fluency (Eloranta et al., 2019). This meta-analysis added that the magnitude
of this deficit is equivalent across languages, that is, irrespective of the transparency of the
orthography in which participants learned to read. This result adds to the growing evidence
that shows a reliable and strong association between RAN and reading ability in a wide array of
orthographies and across ages (for a review, see Araújo, Reis, Petersson, & Faísca, 2015). The
observed dissociation between alphabetic and non-alphabetic RAN also corroborates with
previous findings: RAN-alphabetic showed a larger ES, supporting the view that RAN-
alphabetic makes a major contribution to reading.
In addition, our meta-analysis addressed the extent to which dyslexia in adulthood
involves weaknesses in other domains beyond reading/writing and phonological processing
skills, such as processing speed and other oral language skills. Results showed that adults with
dyslexia perform significantly weaker than the controls in tasks emphasizing speed, either non-
linguistic or linguistic. Large ESs were observed in processing speed tasks (d = 0.873) and on
ADULTS WITH DYSLEXIA 39
serial rapid naming (d = 1.295 for RAN-alphabetic and d = 0.972 for RAN non-alphabetic).
Research has shown that these kind of tasks become increasingly important as literacy
development progresses, probably because they are more linked to reading fluency than to
single word reading accuracy (Pennington & Lefly, 2001; Puolakanaho et al., 2008; Snowling,
Gallagher, & Frith, 2003; Torppa, Lyytinen, Erskine, Eklund, & Lyytinen, 2010).
One possibility is that these deficits contribute to reading fluency problems that are
particularly hard to remediate in impaired readers (e.g. Thaler, Ebner, Wimmer, & Landerl,
2004). The specific relation between speed of processing, rapid naming and reading has been
discussed in the literature (e.g. Kail & Hall, 1994; Papadopoulos, Spanoudis, & Georgiou, 2016;
Powell, Stainthorp, Stuart, Garwood, & Quinlan, 2007; Vaessen, Gerretsen, & Blomert, 2009).
Some authors (e.g. Kail & Hall, 1994) have argued that naming speed is related to reading
ability because both draw upon a domain-general speed-of-processing factor. Yet, others have
shown that, while RAN does share some part of its predictive variance with speed of
processing, it still accounts for a significant amount of variance in reading ability beyond the
effects of processing speed (e.g. Papadopoulos, Georgiou, & Kendeou, 2009; Powell et al.,
2007). In a recent study with adult dyslexics (Georgiou, Ghazyani, & Parrila, 2018), it was also
demonstrated that entering processing speed as a covariate is not sufficient to eliminate the
differences in RAN components between dyslexics and their reading controls. Thus, evidence
thus far seems to be more compatible with the idea that processing speed is a factor in RAN
performance, but it does not account for the relationship between RAN and reading.
Regarding the existence of a vocabulary deficit in adults with dyslexia, the literature is
not consensual (see, for a review, Cavalli et al., 2017b). Vocabulary was the reading and writing
associated ability that presented the smallest ES compared to the other skills in this meta-
analysis. Yet, the effect was medium (d = 0.591), showing that dyslexic adults do, indeed, have
a deficit in this skill as already shown in Swanson and Hsieh’s (2009) meta-analysis. Hence, this
ADULTS WITH DYSLEXIA 40
result seems to suggest that dyslexics' reading difficulties throughout life represent a
disadvantage for vocabulary acquisition. At least in children, vocabulary knowledge has been
associated with specific reading skills, particularly with decoding and reading comprehension
(Ouellette, 2006). Interestingly, here we found positive significant associations of vocabulary
with word reading speed (k = 24, β = 0.487, p <.001) and reading comprehension (k = 6, β =
0.789, p = .020). Although our data do not allow conclusions about causality, these results are
compatible with the interpretation that reading comprehension difficulties in dyslexia might be
partially explained by vocabulary weaknesses. In addition, the same explanation can justify the
association between vocabulary and word reading speed, suggesting that poor vocabulary
knowledge in adults hinders reading skills.
Finally, given the diversity of inclusion and exclusion criteria used in the 178 studies
analysed, we considered it pertinent to assess the impact on ESs of two aspects related to the
selection procedures of the dyslexic participants, namely requiring or not requiring a previous
formal diagnosis and the exclusion of participants with attentional disorders. The results
indicate that having a formal diagnosis and controlling for attention deficits do not affect the
ESs of the main reading and writing variables.
Conclusion
In conclusion, our meta-analysis is compatible with the view that the cognitive
influences on dyslexia are multifactorial and involve reading and phonological processing
deficits as well as weaknesses in other oral language skills (e.g. vocabulary). Critically, these
deficits in cognitive processes that underlie poor reading skills persist into adulthood.
However, symptoms are more accentuated for reading and writing skills than for reading and
writing associated processes, such as phonological awareness, rapid automatized naming,
phonological memory, verbal working memory and vocabulary. In addition, the primary
symptoms associated with developmental dyslexia seem to be amplified when performance is
ADULTS WITH DYSLEXIA 41
measured with speed. Orthography seems to be an important factor in how symptoms are
expressed. Participants who learned to read and write from transparent orthographies
showed, in adulthood, less marked symptoms as compared to participants from more opaque
orthographies, especially when performance was assessed with accuracy measures. Yet,
deficits are larger and more homogeneous across the three orthographies when speed
measures are used. Phonological awareness (accuracy) seems to be a minor problem in
adulthood mainly for transparent orthographies. We must mention that most of the studies on
adults with dyslexia use samples of university students, including this review, which means
that their findings come from potentially compensated dyslexics.
ADULTS WITH DYSLEXIA 42
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Studies included in meta-
analysis
(n= 178)
Effect Sizes
(n= 1817)
Full-text articles excluded
(n= 1393)
Reasons:
•Did not report suficient data for effect
size calculation
•Samples of selected groups (e.g. no
control group; clinical samples other
than dyslexics; no specific reading
disorder;
•Overlapping sample with other studies
•Acquired dyslexia
•Participants younger than 18 years old
Abstracts excluded
(n= 1471)
Inclusion Criteria
i) report original empirical data for reading and
reading-related variables, ii) compare the
performance of individuals with dyslexia to that of
typical control readers (matched by relevant
variables), iii) maintain a sample age over 18 years
old, and iv) contain enough information to compute
effect sizes.
Literature Search:
•Electronic databases (PsycINFO and PubMed)
•Hand search of journals that specialize in publishing reading research
•Citation search
•Search in prior meta-analysis and narrative reviews
Full-text articles assessed for
eligibility
(n=1573)
Abstracts selected acording to
key words (Dyslexia or specific
Reading disorder)
(n = 1725)
Records after duplicates removed
(n= 3196)
Figure 1. Flow diagram for the search
and inclusion of studies.
ADULTS WITH DYSLEXIA 71
Table 1. Effect Sizes with 95% Confidence Intervals, and Heterogeneity Statistics in studies comparing adults with dyslexia
with typical readers.
Effect Size
Heterogeneity
k
d
95% CI
Z
p-value
I2
QWithin
p-value
Reading and Writing variables
Word Read
161
1.812
1.690 – 1.935
29.0
<.001
79.43
777.7
<.001
Pseudoword Read
136
2.034
1.896 – 2.172
28.8
<.001
80.61
796.1
<.001
Text Read
39
1.761
1.472 – 2.050
11.4
<.001
86.41
279.6
<.001
Reading Comprehension
37
0.729
0.550 – 0.907
8.0
<.001
74.48
141.1
<.001
Spelling
99
1.735
1.590 – 1.880
23.5
<.001
78.06
446.7
<.001
Reading and Writing related variables
Phonological Awareness
101
1.177
1.075 – 1.279
22.7
<.001
60.02
250.2
<.001
Level 1
2
0.757
0.117 – 1.387
2.3
.020
6.41
1.1
.301
Level 2
6
1.290
0.849 – 1.731
5.7
<.001
53.14
10.7
.054
Level 3
21
0.779
0.563 – 0.995
7.1
<.001
53.50
43.0
.002
Level 4
85
1.263
1.156 – 1.371
23.1
<.001
56.88
194.8
<.001
Phonological Memory
66
1.034
0.916 – 1.153
17.1
<.001
57.99
154.7
<.001
Orthographic Knowledge
26
1.233
1.043 – 1.423
12.7
<.001
65.59
72.7
<.001
Verbal Working Memory
26
0.926
0.694 – 1.158
7.8
<.001
68.64
79.7
<.001
Vocabulary
38
0.591
0.440 – 0.742
7.7
<.001
59.34
91.0
<.001
RAN
77
1.191
1.091 – 1.290
23.4
<.001
45.07
138.4
<.001
RAN alphabetic
57
1.295
1.154 – 1.437
18.0
<.001
63.30
152.6
<.001
RAN non-alphabetic
50
0.972
0.816 – 1.128
12.2
<.001
68.62
156.2
<.001
General Cognitive Skills
Full IQ
28
0.296
0.158 – 0.434
4.2
<.001
44.58
48.7
.006
Nonverbal IQ
75
0.187
0.106 – 0.269
4.5
<.001
23.82
97.1
.037
Verbal IQ
10
0.424
0.028 – 0.821
2.1
.036
75.27
36.4
<.001
Abstraction
13
0.143
-0.121 – 0.408
1.1
.287
59.80
29.8
.003
Speed of Processing
11
0.840
0.551 – 1.129
5.7
<.001
72.46
36.3
<.001
Note: number of independent effect sizes (k) that contributed to each meta-analysis; the weighted average effect size of group
differences (d); 95% confidence interval (CI); Z significance test statistic for the effect sizes and corresponding significance
level (p); the proportion of total variance between the effect sizes not explained by chance (I2); within-group heterogeneity of
variance (QWithin) and significance level (p).
ADULTS WITH DYSLEXIA 72
Table 2. Effect Sizes with 95% Confidence Intervals, and Heterogeneity between measures (accuracy vs. speed) in studies
comparing adults with dyslexia with typical readers.
Effect Size
Heterogeneity
k
d
95% CI
Z
p-value
I2
QBetween
p-value
Reading and Writing variables
Word Read
Accuracy
106
1.521
1.377 – 1.665
20.7
<.001
78.31
14.57
<.001
Speed
130
1.914
1.733 – 2.056
26.8
<.001
81.01
Pseudoword Read
Accuracy
84
1.703
1.540 – 1.867
20.4
<.001
77.30
11.24
<.001
Speed
117
2.086
1.933 – 2.239
26.8
<.001
82.07
Text Read
Accuracy
21
1.629
1.253 – 2.004
8.5
<.001
87.35
0.30
.584
Speed
35
1.767
1.445 – 2.088
10.8
<.001
88.07
Reading Comprehension
Accuracy
36
0.703
0.520 – 0.887
7.5
<.001
74.96
0.57
.452
Speed
6
0.900
0.422 – 1.378
3.7
<.001
75.67
Spelling
Accuracy
96
1.720
1.573 – 1.868
22.9
<.001
78.59
0.03
.862
Speed
9
1.767
1.261 – 2.273
6.9
<.001
69.21
Reading and Writing related variables
Phonological Awareness
Accuracy
94
1.074
0.964 – 1.183
19.2
<.001
62.79
11.34
<.001
Speed
46
1.404
1.246 – 1.562
17.4
<.001
64.80
Orthographic Knowledge
Accuracy
21
1.027
0.857 – 1.217
58.6
<.001
58.55
6.82
.009
Speed
14
1.521
1.203 – 1.839
76.2
<.001
76.21
Note: number of independent effect sizes (k) that contributed to each meta-analysis; the weighted average effect size of group
differences (d); 95% confidence interval (CI); Z significance test statistic for the effect sizes and corresponding significance
level (p); the proportion of total variance between the effect sizes not explained by chance (I2); between-groups heterogeneity
of variance (QBetween) and significance level (p).
ADULTS WITH DYSLEXIA 73
Table 3. Effect Sizes with 95% Confidence Intervals, and Heterogeneity between orthographies in studies comparing adults
with dyslexia with typical readers.
Effect Size
Heterogeneity
k
d
95% CI
Z
p-value
I2
QBetween
p-value
Reading and Writing variables
Word Read (acc)
Opaque
81
1.619 b
1.452 – 1.787
18.6
<.001
77.97
8.27
.016
Intermediate
11
1.420 ab
1.010 – 1.830
6.8
<.001
72.67
Transparent
14
1.070 a
0.730 – 1.409
6.2
<.001
76.08
Word Read (speed)
Opaque
85
1.952 a
1.775 – 2.130
21.6
<.001
79.52
1.94
.378
Intermediate
29
1.938 a
1.629 – 2.247
12.3
<.001
85.72
Transparent
16
1.672 a
1.315 – 2.030
9.2
<.001
76.32
Pseudoword Read (acc)
Opaque
62
1.738 b
1.552 – 1.923
18.4
<.001
74.82
5.23
.073
Intermediate
11
1.976 b
1.373 – 2.579
6.4
<.001
85.86
Transparent
11
1.304 a
0.933 – 1.675
6.9
<.001
72.67
Pseudoword Read (speed)
Opaque
77
2.043 b
1.869 – 2.216
23.0
<.001
76.70
6.09
.048
Intermediate
27
2.354 b
1.963 – 2.745
11.8
<.001
89.61
Transparent
13
1.711 a
1.374 – 2.048
10.0
<.001
71.96
Reading Comprehension (acc)
Opaque
20
0.614 a
0.404 – 0.824
5.7
<.001
65.82
6.13
.047
Intermediate
8
1.354 b
0.735 – 1.973
4.3
<.001
84.16
Transparent
8
0.452 a
0.074 – 0.829
2.4
.019
79.40
Spelling (acc)
Opaque
60
1.708 b
1.556 – 1.861
22.0
<.001
61.78
9.97
.007
Intermediate
22
2.073 c
1.716 – 2.430
11.4
<.001
85.46
Transparent
14
1.250 a
0.882 – 1.618
6.7
<.001
84.14
Reading and Writing related variables
Phonological Awareness (acc)
Opaque
71
1.145 b
1.019 – 1.271
17.9
<.001
60.77
10.79
.005
Intermediate
15
1.264 b
0.975 – 1.552
8.6
<.001
69.24
Transparent
10
0.633 a
0.328 – 0.937
4.1
<.001
68.20
Phonological Memory (acc)
Opaque
40
1.052 a
0.891 – 1.212
12.9
<.001
57.22
0.25
.884
Intermediate
18
1.048 a
0.852 – 1.244
10.5
<.001
52.61
Transparent
8
0.944 a
0.545 – 1.344
4.6
<.001
73.06
RAN (speed)
Opaque
54
1.211 a
1.100 – 1.323
21.3
<.001
24.40
0.26
.880
Intermediate
16
1.175 a
0.980 – 1.370
11.8
<.001
54.14
Transparent
7
1.110 a
0.655 – 1.565
4.8
<.001
77.91
Note: number of independent effect sizes (k) that contributed to each meta-analysis; the weighted average effect size of group
differences (d); 95% confidence interval (CI); Z significance test statistic for the effect sizes and corresponding significance
level (p); the proportion of total variance between the effect sizes not explained by chance (I2); between-groups heterogeneity
of variance (QBetween) and significance level (p); a-c Mean effect sizes not sharing the same superscript letters differ at p < .05.
ADULTS WITH DYSLEXIA 74
Table 4. Regression analysis for Age as moderator in studies comparing adults with dyslexia with typical readers.
k
Slope β
p-value
R2
Continuous Moderators
Age (dyslexic group)
Word Read
Accuracy
103
-0.04
.01
.05
Speed
121
-0.02
.31
.00
Pseudoword Read
Accuracy
82
-0.03
.08
.00
Speed
109
-0.00
.82
.00
Text Read
Accuracy
20
-0.06
.11
.00
Speed
35
-0.04
.19
.00
Reading Comprehension
Accuracy
34
-0.02
.16
.02
Spelling
Accuracy
92
-0.03
.03
.07
Phonological Awareness
Accuracy
93
-0.00
.77
.00
Speed
46
0.01
.57
.00
Orthographic Knowledge
Accuracy
20
-0.02
.37
.00
Speed
13
-0.03
.22
.02
RAN alphabetic (speed)
50
-0.03
.13
.00
RAN non-alphabetic (speed)
39
0.01
.78
.00
Note: number of independent effect sizes (k) that contributed to each meta-regression analysis; Slope β and its
significance level (p); explanatory value of the moderator for differences between studies (R2).
ADULTS WITH DYSLEXIA 75
Table 5. Effect Sizes with 95% Confidence Intervals, and Heterogeneity between subgroups (with vs. without previous
diagnosis of dyslexia; with vs. without control of attentional deficits) in studies comparing adults with dyslexia with typical
readers.
Effect Size
Heterogeneity