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A stitch in time…: Comparing late‐identified, late‐emerging and early‐identified dyslexia



When dyslexia is diagnosed late, the question is whether this is due to late‐emerging (LE) or late‐identified (LI) problems. In a random selection of dyslexia‐diagnosis case files we distinguished early‐diagnosed (Grade 1–3, n = 116) and late‐diagnosed (Grade 4–6) dyslexia. The late‐diagnosed files were divided into LE (n = 54) and LI dyslexia (n = 45). The LE group consisted of children whose national‐curriculum literacy outcomes did not warrant referral for dyslexia diagnosis in Grades 1–2; the LI group of children whose literacy outcomes did, but who were referred for diagnostic assessment after Grade 3. At the time of diagnosis, the percentage of poor performers on word‐level literacy measures generally did not differ between the groups. Only the LE group contained fewer poor performers than the early‐diagnosed and LI group on some word‐reading measures. All groups showed similar distributions of phonological difficulties. There were no indications of compensation through vocabulary, memory or IQ in either late‐diagnosed group. Our diagnosis‐based study confirms and extends previous research‐based studies on LE dyslexia. Moreover, it shows that LI dyslexia exists, which can be regarded as the existence of instructional casualties. The findings speak to issues of identification, diagnosis and compensation and call for further efforts to improve the early identification of dyslexia.
A stitch in time: Comparing late-identified,
late-emerging and early-identified dyslexia
Elise H. de Bree
| Madelon van den Boer
Boukje M. Toering
| Peter F. de Jong
Research Institute of Child Development and Education, University of Amsterdam, Amsterdam, Netherlands
Department of Education and Pedagogy, Utrecht University, Utrecht, Netherlands
Marnix Academy for the Training of Primary School Teachers, Utrecht, Netherlands
Elise H. de Bree, Department of Education
and Pedagogy, Utrecht University, P.O. Box
80140, Utrecht 3580 TC, Netherlands.
When dyslexia is diagnosed late, the question is whether this
is due to late-emerging (LE) or late-identified (LI) problems. In
a random selection of dyslexia-diagnosis case files we distin-
guished early-diagnosed (Grade 13, n=116) and late-
diagnosed (Grade 46) dyslexia. The late-diagnosed files
were divided into LE (n=54) and LI dyslexia (n=45). The
LE group consisted of children whose national-curriculum lit-
eracy outcomes did not warrant referral for dyslexia diagno-
sis in Grades 12; the LI group of children whose literacy
outcomes did, but who were referred for diagnostic assess-
ment after Grade 3. At the time of diagnosis, the percentage
of poor performers on word-level literacy measures generally
did not differ between the groups. Only the LE group con-
tained fewer poor performers than the early-diagnosed and
LI group on some word-reading measures. All groups showed
similar distributions of phonological difficulties. There were
no indications of compensation through vocabulary, memory
or IQ in either late-diagnosed group. Our diagnosis-based
study confirms and extends previous research-based studies
on LE dyslexia. Moreover, it shows that LI dyslexia exists,
which can be regarded as the existence of instructional
Received: 20 August 2021 Revised: 21 March 2022 Accepted: 4 May 2022
DOI: 10.1002/dys.1712
This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which
permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no
modifications or adaptations are made.
© 2022 The Authors. Dyslexia published by John Wiley & Sons Ltd.
276 Dyslexia. 2022;28:276292.
casualties. The findings speak to issues of identification,
diagnosis and compensation and call for further efforts to
improve the early identification of dyslexia.
diagnosis, dyslexia, late-emerging, late-identified, literacy
Key messages
Ideally, severe and persistent word-level reading difficulties
(dyslexia) are detected as early as possible.
Our findings confirm findings that late-emerging dyslexia exists,
meaning that the severe and persistent poor performance sur-
face later.
We also found that late-identified dyslexia exists, meaning that chil-
dren were referred later than their reading outcomes warranted.
The late-emerging and late-identified groups do not show evi-
dence of compensation of literacy abilities.
Efforts should be made to avoid such instructional casualties (late-
identified dyslexia) and to support the school literacy curriculum.
Dyslexia is a disorder characterized by consistently poor word reading and spelling performances that cannot be
accounted for by general learning difficulties, sensory deficits, or inadequate teaching These word-level literacy deficits
are caused by multiple risk factors (Peterson & Pennington, 2015). As these severe and persistent word reading and
spelling difficulties generally surface in the first years of literacy instruction, children with dyslexia are usually identified
and diagnosed during the first years of primary school. There is, however, also a group of children whose literacy difficul-
ties are identified and diagnosed later, typically after Grade 3. This group forms approximately one-third of samples of
children with literacy difficulties (Catts, Compton, Tomblin, & Bridges, 2012; Leach, Scarborough, & Rescorla, 2003;
Lipka, Lesaux, & Siegel, 2006;Torppa,Eklund,vanBergen,&Lyytinen,2015). An important question is why some chil-
dren's difficulties are identified in the early stages of literacy instruction and those of others only later.
The issue of early and late-diagnosed literacy problems has been targeted in a few studies. The main question is
whether the literacy problems of the late group truly developed at a later stage than those of the early group. Previ-
ous studies reported that this is the case (Catts et al., 2012; Leach et al., 2003; Lipka et al., 2006; Torppa
et al., 2015). Once identified, the outcomes of the early and late groups are generally similar or show a step-wise pat-
tern of performance with a no-literacy problem group outperforming the late group, and the late group out-
performing the early group on some measures (Bazen, van den Boer, de Jong, & de Bree, 2020; Catts et al., 2012;
Compton, Fuchs, Fuchs, Elleman, & Gilbert, 2008; Leach et al., 2003; Lipka et al., 2006; Torppa et al., 2015).
The previous studies into early and late-emerging (LE) dyslexia share some characteristics concerning their liter-
acy assessment. First, some studies (initially) categorized the sample of late poor readers on poor word reading and
reading comprehension difficulties (Catts et al., 2012; Compton et al., 2008; Etmanskie, Partanen, & Siegel, 2016).
Whereas poor word reading is one of the defining characteristics of dyslexia, this is not the case for poor reading
de BREE ET AL.277
comprehension. Poor word readers are not necessarily poor comprehenders (Bazen et al., 2020; Moojen
et al., 2020). This means that it is important to separate word reading from reading comprehension. Moreover, both
in studies designed to establish the prevalence of poor readers (Compton et al., 2008; Etmanskie et al., 2016) and in
studies designed to compare early and late groups (Bazen et al., 2020; Leach et al., 2003; Lipka et al., 2006; Torppa
et al., 2015) the numbers of poor word-readers only have been small. Larger samples of early and late poor word
readers are needed to draw more firm conclusions concerning LE and late-identified (LI )dyslexia.
Furthermore, the previous early- and late studies included word-level reading measures, but only Torppa
et al. (2015) and Leach et al. (2003) included measures of word reading accuracy and fluency in younger readers.
Other studies only included accuracy (Catts et al., 2012; Etmanskie et al., 2016; Lipka et al., 2006) or fluency (Bazen
et al., 2020). Ideally, both are assessed: In the initial stages of reading development, word recognition will be slow and
error-prone, making accuracy an adequately sensitive measure. As reading acquisition progresses, the ease or speed
with which words can be read (correctly) becomes a more sensitive indicator of word reading ability (van Viersen
et al., 2018). Additionally, both word and pseudoword reading outcomes have been found to be informative (Bazen
et al., 2020; Torppa et al., 2015) as both decoding (pseudowords) and sight word reading processes (words) can be
impaired in poor readers (Peterson, Pennington, Olson, & Wadsworth, 2014). In order to further understand the dif-
ference between early and late literacy difficulties, a comprehensive assessment of word-level reading is needed.
Also, the spelling performance of the early and late groups has received little attention so far; only two studies
included a standardized measure of spelling (Etmanskie et al., 2016; Lipka et al., 2006) and two a raw measure
(Bazen et al., 2020; Leach et al., 2003). Given that poor spelling is taken to be a feature of dyslexia and is often part
of a diagnosis of dyslexia (Lyon, Shaywitz, & Shaywitz, 2003; Peterson & Pennington, 2015), it is informative to
include both word reading and spelling outcomes in an evaluation of early and late dyslexia.
On the basis of the previous studies, the consensus seems to be that late-diagnosed literacy difficulties are actually late-
emerging and were not present early on. Nevertheless, there are also indications that instructional casualties(Lyon, 2002;
Snow, 2016) occur (Barbiero et al., 2012), referring to students whose literacy problems were present early on, but were
not identified. Potentially, the group with late-diagnosed literacy problems can be a merger of children with literacy prob-
lems that are late-emerging and children with early problems that were missed and were therefore late identified.
One way to look into the late group is by using formal diagnoses of dyslexia. Such diagnoses include a range of
literacy and cognitive skills, and take into account the development and persistence of literacy problems over time.
Formal diagnoses of late-diagnosed children allow a division between LE dyslexia, with persistent literacy deficits
truly developing at a later age, and LI dyslexia, with persistent literacy deficits being present much earlier than the
actual time of referral for diagnosis. Literacy outcomes at the time of diagnosis of the LI group can then be compared
to the early as well as the LE group. Such a comparison could include text-level literacy outcomes in the early grades,
as the results of this task might be used in the referral process. Indeed, a German study into information that
teachers used in the identification of children that need reading interventions showed that teachers identified more
students with severe reading difficulties on the text level than on the word level (Schmitterer & Brod, 2021).
Next to literacy outcomes, it can be assessed whether LI children differ from early-diagnosed and LE children in
terms of risk factors. The key risk factor associated with dyslexia is a phonological deficit (Peterson &
Pennington, 2015), which usually concerns skills related to grapheme-phoneme associations, phoneme awareness
(PA), and rapid automatized naming (RAN) (de Jong & van der Leij, 2003; Moll et al., 2014; Norton & Wolf, 2012).
Previous research has shown that the late group performs better than the early-identified group on these risk factors
before the literacy difficulties surface (Lipka et al., 2006) and resembles the early group once the literacy difficulties
have become apparent (Bazen et al., 2020; Leach et al., 2003). However, the pattern of findings for the cognitive risk
factors is not entirely consistent: one study reported that the early and late groups showed (equally) low perfor-
mance on RAN prior to the appearance of literacy difficulties (Torppa et al., 2015). Vice versa, PA performance of
278 de BREE ET AL.
the late group at or after the time of diagnosis is not always as poor as that of the early-identified group (Bazen
et al., 2020; Torppa et al., 2015). By dividing the late-diagnosed group into LE and LI children we can shed further
light on the presence and strength of a phonological deficit in the different groups.
Furthermore, a comparison can be made of performance on protective factors, reflecting potential strengths in
more general cognitive abilities such as intelligence, memory, or language skills. These might reduce or mask a pre-
sent literacy and/or phonological deficit (Haft, Myers, & Hoeft, 2016; van Viersen, de Bree, & de Jong, 2019; van
Viersen, Kroesbergen, Slot, & de Bree, 2016). The studies that compared early and late groups on one or more poten-
tial protective factors, that is, non-verbal intelligence (Bazen et al., 2020; Leach et al., 2003), verbal intelligence
(Leach et al., 2003; Torppa et al., 2015), verbal short-term memory (Bazen et al., 2020; Torppa et al., 2015), or work-
ing memory (Lipka et al., 2006) did not find significant differences between the early and late groups. Similarly, Tor-
ppa et al. (2015) and Bazen et al. (2020) found no differences in vocabulary between early and LI groups with
dyslexia and normally reading participants. Although these findings suggest that intelligence, memory, and vocabu-
lary do not function as protective factors that compensate for a literacy deficit of LI children during the early primary
school years, it needs to be assessed whether this is the case for children with LE as well as LI dyslexia.
In the current study, we used case files of formal diagnoses of dyslexia and divided these files into early-diagnosed
(Grades 13) and late-diagnosed children (Grades 46) with dyslexia in the semi-transparent orthography Dutch. The
case files of late-diagnosed children were divided into LE and LI groups. We addressed the following questions:
1. To what extent does the LI group differ from the early-diagnosed and LE group on word reading and spelling out-
comes at the time of diagnosis and on text-level reading measures at the end of Grade 1?
2. To what extent does the LI group differ from the early-diagnosed and LE group on phonological measures at the
time of diagnosis?
3. To what extent does the LI group differ from the early-diagnosed and LE group on potentially compensatory
We had the following expectations:
1. All three groups were expected to show poor literacy outcomes at the time of diagnosis. A very tentative hypoth-
esis, based on the finding by Schmitterer and Brod (2021), is that text-level reading outcomes of the LI group
might be better than their word reading and spelling problems at the end of Grade 1.
2. Based on the hypothesis that LE dyslexia is characterized by a less severe phonological deficit (Bazen et al., 2020;
Lipka et al., 2006; Torppa et al., 2015), children with LE dyslexia might perform better than early-diagnosed and
LI children on tasks assessing a phonological deficit. For children with LI dyslexia, a phonological deficit similar to
the early-identified group was expected.
3. Expectations concerning the protective factors were less clear. For the LE group, dyslexia could be LE due to the
presence of protective factors. This would mean that children with LE dyslexia would display higher intelligence,
memory, and vocabulary scores compared to early-diagnosed children. Empirical findings so far do not suggest this
to be the case (Bazen et al., 2020; Leach et al., 2003; Lipka et al., 2006; Torppa et al., 2015). For the LI group, it
could be the case that their performance on early protective factors (vocabulary) is higher than that of the early-
emerging group. Schmitterer and Brod (2021) found that German teachers' evaluations of a student's need for
reading interventions were partly based on children's vocabulary outcomes. The early-identified group might thus
have lower vocabulary outcomes than the LI group. An alternative option could be that the LI group's performance
on tasks related to protective factors is not high and therefore does not differ strongly from their literacy abilities.
The absence of a clear discrepancy might move teachers' attention away from the literacy problems.
de BREE ET AL.279
5.1 |Dyslexia diagnosis in the Netherlands
In the Netherlands, the diagnosis of dyslexia entails two steps. First, at school, a response-to-intervention approach
is followed Fuchs & Fuchs, 2006; Scheltinga, van der Leij, & Struiksma, 2009). Literacy outcomes at school are moni-
tored using standardized tests twice every year from the start of Grade 1. Low literacy outcomes based on classroom
instruction (Tier 1) should lead to intensified instruction (Tier 2), and further targeted intervention (Tier 3) if out-
comes do not progress. The stepped care entails an increase in time spent on instruction and practice as well as dif-
ferentiation in instruction. If performance remains 10th percentile on three consecutive measurements, despite
increasingly intensive instruction, a child can be referred to specialist care. The 10th percentile is a nation-wide
benchmark (Gijsel, Scheltinga, Druenen, & Verhoeven, 2011; Scheltinga et al., 2009). Importantly, given the time
span of three subsequent measurements, the percentage of children referred to specialized centres is generally lower
than 10% (Vloedgraven et al., 2010). Also, this procedure of three subsequent assessments means that a referral for
dyslexia diagnosis cannot take place before Grade 2.
The second step in the diagnostic process is that children whose word-level literacy remains below the 10th per-
centile despite increasingly intensified instruction and intervention at school are referred by the school to specialized
diagnostic and treatment centres. At the specialized centre, the further procedure for the diagnosis of dyslexia is based
on national health care guidelines and protocols, which, at the time of the diagnostic reports under investigation in the
present study, were those of the National Reference Centre Dyslexia (NRD, 2013) and the Dutch Dyslexia Foundation
(SDN et al., 2016). At the behavioural level, assessment of word-level literacy takes place. Regarding word-level reading
assessment, measures typically include word reading accuracy and fluency, and decoding. These findings provide solid
and coherent insight into word-level reading abilities. Similarly, spelling is typically assessed by a spelling-to-dictation
measure and complemented with a combined accuracy and fluency measure. At the cognitive level, phonological abili-
ties are assessed, given the established relations between phonology and literacy (Hulme, Nash, Gooch, Lervåg, &
Snowling, 2015; van Viersen et al., 2018). Measures are tasks tapping letter-sound knowledge, PA and RAN. Outcomes
can be used to understand and confirm the literacy deficit. Furthermore, an assessment of (other) strengths and weak-
nesses of the child also takes place. This is done to exclude children for whom general learning difficulties or sensory
deficits are the cause of persistent and severe literacy difficulties (e.g., DSM-5; Peterson & Pennington, 2015). A sec-
ond purpose is to assess skills that relate to broader educational needs and could be relevant for dyslexia treatment
and support. It usually entails the assessment of tasks spanning memory and (non-)verbal intelligence. The environment
of the child is also taken into account in the diagnostic process: it is established that unfavourable educational and
environmental issues cannot be the reason for the consistently poor literacy outcomes (in line with response-to-
instruction) and it is ascertained whether there is a family history of dyslexia as a potential risk factor for dyslexia.
5.2 |Case file selection and group assignment
For the current study, we analyzed case files of children who were referred to a specialized centre for specific learn-
ing disabilities in the Netherlands for a diagnostic examination of dyslexia. This is the second step in the dyslexia diag-
nosis procedure described above. As part of the protocol of the institute, the parents of the children agreed to the
use of the scores of this examination for scientific purposes. From all the children who visited the institute between
January 2013 and June 2016 (over 2000 files) we randomly selected 242 files included in the current study. These
files had to concern children who had actually been diagnosed with dyslexia somewhere between Grades 1 and
6. We excluded children with an IQ below 75 (n=5). We then divided the case files into an early-diagnosed group
(n=133), with a diagnosis made in Grades 13 and a late-diagnosed group (n=104), diagnosis between Grades 46.
Next, we excluded cases in the early-diagnosed group: for three cases, school literacy scores had not been
entered in the diagnostic report. For 14 other children, a formal dyslexia diagnosis was made in Grade 2 but their
280 de BREE ET AL.
curriculum literacy outcomes were not in the bottom range and therefore did not warrant referral. All 14 children
had been retained but the norm scores were based on the grade the children were attending. Their higher literacy
scores, therefore, present an inflated picture of their literacy abilities. Nevertheless, to err on the side of caution,
data of these children were excluded from the early-diagnosed sample. The early-diagnosed group consisted of case
files of 116 early-diagnosed children.
The late-diagnosed group was divided into a LE and a LI group. The LI children were those who obtained three
bottom scores (10th percentile) in a row on the standardized national reading and/or spelling tests in Grades 1 and
2 (see materials, below) based on the existing national school protocol (Gijsel et al., 2011). LE children were those
who did not show these persistently low scores in the early school years. School literacy scores had not been
entered in the diagnostic report for 5 children. Therefore, classification was possible for 99 of the 104 late-diagnosed
children. The ensuing groups were 54 children with LE dyslexia and 45 with LI dyslexia.
5.3 |Participants
Participant information per group is presented in Table 1. All participants were fluent speakers of Dutch. None of
the children had another diagnosed disorder (e.g., ADHD, DLD) next to dyslexia. The three groups did not differ on
the distribution of boys/girls χ
(2) =.869, p=.647 and on mono/bilingual children χ
(2) =3.433, p=.180. They
also did not differ on the measure of home socio-economic status (SES), F(2, 212) =.157, p=.855 and school SES F
(2,212) =1.107, p=.333. These SES measures consisted of ratings of the postal code of the children's homes/
schools, reflecting average income and educational attainment, as well as the percentage of unemployment within
the neighbourhood (Netherlands Institute for Social Research, 2017). Mean home and school SES for all three groups
were higher than the national average of 0.28 (SD =1.09).
The groups differed in age F(2, 212) =265.27, p< .001 and in distribution of Grade χ
(10) =221.20, p< .001,
with the early-diagnosed children being younger and in a lower Grade at the time of diagnosis than both the LI and
LE groups (p< .001). The LI and LE groups did not differ from each other in age (p=.96) and distribution of Grade at
which the diagnosis was made χ
(2) =2.86, p=.240.
5.4 |Materials
5.4.1 | Early language and literacy skills
The files of the children included both literacy and vocabulary outcomes from when children were in Grade 1 and
2. These scores were determined at school with the national curriculum-based tests that are administered in all regu-
lar Dutch schools both halfway through and at the end of each school year. The scores consisted of an indication of
the student's level, ranging from 1 through 5 ((1) percentiles 75100; (2) percentiles 5075; (3) percentiles 2550;
TABLE 1 Participant information for the three groups
Early (n=118)
Late (n=99)
Late emerging (n=54)Late identified (n=45)
Mean age of diagnosis 8;5 (8.1 months) 10;9 (10.1 months) 10;9 (10.2 months)
Nr boys 71 (61%) 29 (64%) 30 (55%)
Nr bilingual 3 4 4
SES home 0.94 (0.74) 0.94 (0.68) 1.0 (0.70)
SES school 0.95 (.74) 0.79 (0.71) 1.1 (0.74)
de BREE ET AL.281
(4) percentiles 1025; (5) percentiles 010). All tests have at least sufficient reliability and validity (COTAN, 2010).
For group classification into early, LI and LE (see Procedure), word-reading and spelling scores in middle Grade
1, end Grade 1, middle Grade 2 and end Grade 2 were used. For comparisons of the LI group with early and LE
groups on text-level reading and vocabulary, results of end Grade 1 are reported.
Word reading
The Cito word reading test is a fluency test (DMT; Krom, Jongen, Verhelst, Kamphuis, & Kleintjes, 2010). Children
were presented with three lists of 150 words each; the first list contained monosyllabic words without consonant
clusters (e.g., oom, uncle), the second monosyllabic words with consonant clusters (e.g., bloem, flower), and the third
multisyllabic words (e.g., moeilijk, difficult). Children were asked to read each list of words as quickly and accurately
as possible for 1 minute.
Text reading
The Cito text reading test is a combined accuracy and fluency test (AVI; Krom et al., 2010). The test consists of a
total of 11 texts of increasing difficulty that are adapted to specific Grade levels. Children were presented with the
text that fits their current Grade level and were asked to read the text as quickly and accurately as possible. For each
text, a maximum number of errors and maximum reading speed is provided in the manual. If children met these
criteria, they were presented with a more difficult text. If they did not, they were administered an easier test. This
procedure was continued until the most difficult text they passed in terms of accuracy and speed was determined.
The level of that text is the score (range 111). If children failed to meet the criteria for the easiest text, they
received a score of 0.
The Cito spelling test consisted of two parts of 25 items each (de Wijs, Kamphuis, Kleintjes, & Tomesen, 2010). The
first part was a spelling-to-dictation task that was administered to the entire class. Based on the results of this first
part, children received either the easy or the difficult follow-up test. The easy follow-up test consisted of another
spelling-to-dictation task. The difficult follow-up test consisted of multiple-choice questions. Children were pres-
ented with four sentences that each included a target word and needed to identify which of the target words was
spelled incorrectly.
The Cito vocabulary test consisted of multiple-choice questions (van Berkel et al., 2010). The teacher read aloud a
sentence with a target word. Children saw three pictures and had to choose the picture that best matched the target
word in the sentence (e.g., Inges moeder maakt een maaltijd. Welk plaatje past het best bij een maaltijd?Inge's
mother makes a meal. What picture best matches a meal? There were two parts of 25 items each.
Reading comprehension
The Cito reading comprehension test (Feenstra, Kleintjes, Kamphuis, & Krom, 2010) consisted of short text frag-
ments, mainly fictional texts, and 50 related questions, divided into two parts. All questions were multiple choice and
concerned a question about the actual text, a prediction about the text or a missing word or fragment of text to fill
in. Similar to the spelling test, the first part was the same for all children, and children received either an easy or diffi-
cult follow-up test. The test does not assess global coherence as the fragments are short.
5.5 |Literacy and cognitive skills at diagnostic examination
Diagnostic testing for dyslexia included administering the 3DM (Blomert & Vaessen, 2009), a test battery for children
in Grades 1 through 6, that consists of tasks for literacy, underlying cognitive and memory skills. The 3DM is a
282 de BREE ET AL.
computer-based test that allows registration of both accuracy and response times. Raw scores are automatically
transformed into percentile scores. Additional diagnostic tasks were administered for sight word reading, decoding
skills, spelling to dictation, and intelligence.
Word reading accuracy and speed
The word reading task of the 3DM (Blomert & Vaessen, 2009) consisted of three subtests containing respectively,
high-frequent words, low-frequent words, and pseudowords. Each subtest consisted of five screens of 15 words
each. Across screens, the items increased in difficulty, from monosyllabic words without consonant clusters to three-
syllabic words with consonant clusters. Children were asked to read the words on each screen as quickly and accu-
rately as possible for 30 seconds. Two scores were calculated; a score for (pseudo-)word reading speed, based on
the total number of items read correctly within the time limit, and a score for word reading accuracy, reflecting the
number of words read correctly out of all the words read. Testretest reliability is .73 for accuracy and .95 for speed
(Blomert & Vaessen, 2009).
Spelling recognition
The spelling recognition task of the 3DM consisted of three subtests containing respectively, phonologically consis-
tent words, phonologically inconsistent words with spelling conventions based on phonemes, and phonologically
inconsistent words with spelling conventions based on syllabic structure, each consisting of 18 items. Each item was
presented orally and was presented on the computer screen simultaneously, without the grapheme(s) for one
corresponding phoneme. Children were asked to select the omitted grapheme(s) from four alternatives
(e.g., zwemmen [to swim] was presented as zwe.enwith the alternatives vv, v, mm, m) as quickly and as accurately
as possible with a maximum reaction time of 15 seconds. The task was discontinued after subtest 2 for children in
Grade 1, and for children with less than 6 items correct on subtest 2. Two scores were calculated: spelling recogni-
tion accuracy and spelling recognition speed. Items with reaction times lower than 300 ms were not included. Inter-
nal consistency is .80 for accuracy and .94 for speed (Blomert & Vaessen, 2009).
Word reading fluency
Sight word reading was assessed with the Eén Minuut Test (One Minute Test; Brus & Voeten, 1999;r=.89.92),
which is a standardized test for word reading fluency. Children read aloud as quickly and accurately as possible a list
of 116 words of increasing difficulty. The number of words read correctly in 1 minute was transformed to a stan-
dardized score with a mean of 10 and a standard deviation of 3.
Decoding skills
Decoding skills were assessed with the Klepel (van den Bos, Lutje Spelberg, Scheepstra, & de Vries, 1994;r=.91),
which is a standardized test for pseudoword reading fluency. Children read aloud as quickly and accurately as possi-
ble a list of 116 pseudowords of increasing difficulty. The number of words read correctly in 2 minutes was trans-
formed to a standardized score with a mean of 10 and a standard deviation of 3.
The spelling of words was assessed with PI-dictee (Geelhoed & Reitsma, 1999;r=.87.91), a standardized spelling-
to-dictation task. The task included a total of 9 blocks of 15 items each. Each block consisted of items with the
phoneme-grapheme connections, spelling rules, and exception words taught in a particular Grade. Testing started
with the first block and was discontinued when less than 8 words of a block were spelled correctly. Each word was
read aloud to the child, as well as a sentence including the word. Children were then asked to write down the target
word (e.g., hout. De tafel is van hout gemaakt,wood. The table is made of wood). The score consisted of the total
number of items spelled correctly and was transformed into a percentile score.
de BREE ET AL.283
Phoneme-grapheme connections
Phoneme-grapheme connections were assessed with a letter-sound identification task. The task consisted of
45 items. Children heard a phoneme and were asked to select the matching grapheme(s) from 4 alternatives with a
maximum reaction time of 10 seconds (e.g., /d/ presented with the alternatives g, d, b, p). Accuracy and mean reac-
tion time across items were established. Items with reaction times lower than 300 ms were not included. Internal
consistency for accuracy is .72 and .90 for speed (Blomert & Vaessen, 2009).
Phoneme awareness
PA was assessed with a phoneme deletion task, containing 23 orally presented pseudowords with a CVC or CCVCC
structure. From these pseudowords, children were asked to delete one of the consonants (e.g., /FOT/ without /F/
makes /OT/) with a maximum reaction time of 15 seconds. Both accuracy and speed (mean reaction time from stim-
ulus offset) were scored. Items with reaction times lower than 300 ms were not included. A score for speed was not
calculated if fewer than 5 items were answered correctly. Internal consistency is .76 for accuracy and .90 for speed
(Blomert & Vaessen, 2009).
Naming speed
Naming speed was assessed as the rapid naming of letters (f, k, r, s, t) and digits (1, 4, 5, 6, 8). Each subtest consisted
of two sheets of 15 items each. Children were asked to name all items as quickly and accurately as possible, with a
maximum reaction time of 35 seconds. As errors are very uncommon, only the response time (seconds) was regis-
tered. A separate score was calculated for letters and digits, consisting of the mean reaction time for the two sheets.
Reaction times lower than 1 second were excluded. Testretest reliability is .80 for letters and .83 for digits
(Blomert & Vaessen, 2009).
Memory span
The 3DM contains three tasks to assess memory span, two are verbal and one is nonverbal. To assess verbal memory
span children were presented with strings of phonemes (all consonants) and syllables (CVC or CCV) that they were
asked to repeat in the same order. For the nonverbal memory span task children were asked to reproduce the order
in which four white squares lit up. In each task, 13 strings were presented; two strings of two items, three strings of
three, four and five items, and two strings of six items. Accuracy was scored per item in the string. Internal consis-
tency was .61 for phonemes, .73 for syllables, and .63 for the nonverbal task (Blomert & Vaessen, 2009).
Intelligence was assessed with the Dutch version of the Wechsler Intelligence Scale for Children, third edition (Kort
et al., 2005;r=.85.93), which is an individually administered intelligence test for children aged six to 16 years. The
test included ten subtests that measured different intellectual abilities. Four composite scores, total IQ, verbal IQ,
performance IQ and processing speed (M=100; SD =15), were included.
5.6 |Analyses
Given the categorical outcomes of Grade 1 measures (text-level reading, vocabulary), group comparisons were made
through chi-squared analyses on the distributions of poor performers (10th percentile). Given the assumed skew-
ness of the literacy and phonological measures at the time of diagnosis, group comparisons were made through chi-
squared analyses. We distinguished whether the child did or did not belong to the lowest 10% (or had a standard
score 6). For the IQ measures, we conducted ANOVAs.
Alpha levels were set at .05. For skills that were assessed with several measures, alpha levels were adjusted by
dividing the alpha value of .05 through the number of outcome measures. As multiple measures were only available
284 de BREE ET AL.
for the time of diagnosis, adjusted alpha levels were only applied there. The adjusted values are p< .0125 for the
four-word reading measures; p< .0167 for the three-word spelling measures, p< .008 for the six phonological skills
measures, and p< .0167 for the thee memory measures.
6.1 |Early vocabulary and text-level literacy skills (Grade 1)
6.1.1 | Vocabulary and text-level literacy skills end Grade 1
The percentage of poor performers (10th percentile) on the tasks at the end of Grade 1 is presented in Table 1. The
distribution of performance across the five levels of the text reading, reading comprehension and vocabulary skills
end Grade 1 for the three groups is presented in Figure S1. The percentage of poor performers in Table 2corre-
sponds to those obtaining bottom scores in Figure S1.
In terms of word-level literacy measures, chi-squared analyses show that the LE group differs from the early-
diagnosed and LI groups in the percentage of poor performers (Table 2), confirming both the status of the LE and the
LI groups. Furthermore, the analyses show overall significant differences between the three groups for text reading
and reading comprehension, but not for vocabulary. Follow-up comparisons (Table 2, right-hand columns) show that
the percentages of poor performers in the LI and the early identified group did not differ from text reading (but mar-
ginally so, p=.052) and reading comprehension. The LI group did not differ from the LE group on text reading, but
the LI group did contain more children performing poorly on reading comprehension. The percentages of children at
or below the 10th percentile in the LE and the early-identified group differed for text reading and reading compre-
hension, with fewer children in the LE group obtaining such low outcomes on these tasks.
6.2 |Literacy and cognitive skills at the diagnostic examination
The percentage of children performing poorly within each group (10th percentile or a standard score 6 on the lit-
eracy, literacy-related and memory tasks) at the diagnostic examination is presented in Table 3. Chi-squared statistics
were conducted to examine the differences across groups in the percentages of weak performers (Table 3, right-
TABLE 2 Percentages of children performing at or below the 10th percentile for the early, late-identified (LI) and
late-emerging (LE) groups at the end of first grade
Means Chi-square
Early vs LEEarly LI LE Overall Early versus LI LI versus LE
Word reading 87.1 88.9 21.1 84.91*** ns 44.39*** 70.20***
Word spelling 33.6 48.9 11.3 16.60*** ns 16.83*** 9.26**
Text reading 57.1 40.0 27.5 13.36** ns ns 12.38**
Reading comprehension 30.5 36.9 10.0 9.66** ns 9.17** 7.39**
Vocabulary 10.0 26.3 12.5 3.30 - - -
Note:*p< .05. **p< .01; ***p< .001. For text reading, reading comprehension and vocabulary data was available for a
subset of the children (see Figure S1).
Abbreviation: ns, not significant.
de BREE ET AL.285
hand columns). For completeness' sake, the mean scores of the literacy skills (word reading, spelling) and the risk
(phonology) and protective factors (memory) at the time of diagnosis are presented in Table S1.
The percentage of children performing poorly on word reading and spelling-to-dictation is high in all three
groups. This is expected, as all children had been formally diagnosed with dyslexia and their literacy performance had
to meet the nationally set criteria (see Method). There are no overall differences in this percentage of poor perfor-
mance on one-minute word reading fluency and pseudoword reading. For word reading accuracy and speed, there
are overall differences. Follow-up analyses show that the LE group has a lower percentage of children performing
poorly than the early-diagnosed group on both accuracy and speed. The group also contains fewer children with a
poor accuracy score than the LI group. There are no differences between the early and LI groups. With respect to
spelling, there are no overall differences between the percentages of poor performers on any of the three measures.
In terms of risk and protective factors, there are no overall differences between the groups in the percentages of
poor performers on phonological and memory tasks. ANOVAs on the mean IQ outcomes (Table 4) only showed a signifi-
cant effect on processing speed. Tukey HSD posthoc tests indicated that the LI group obtained significantly lower
processing speed outcomes (p=.016) than the early group, but there were no differences between the LI and LE groups
(p=.323) and between the early-diagnosed and LE groups (p=.448). Although the early-diagnosed group also showed
numerically higher scores on total IQ, verbal IQ and performance IQ, these differences were not significant.
TABLE 3 Percentages of poorly performing children for the early, late-identified (LI) and late-emerging (LE)
groups at the time of diagnosis
Means Ch-square
Early LI LE Overall Early versus LI LI versus LE Early versus LE
Word reading
Word reading accuracy 77.6 75.6 50.0 14.18* ns 6.78* 13.07*
Word reading speed 96.6 93.3 75.9 19.05* ns ns 17.42*
Sight word reading 96.6 93.3 92.5 ns - - -
Decoding 94.4 91.1 83.3 ns - - -
Spelling recognition acc 68.1 66.7 51.9 ns - - -
Spelling recognition speed 55.2 66.7 63.0 ns - - -
Spelling-to-dictation 97.4 88.9 88.9 ns - - -
Letter-sound identific acc 47.4 33.3 46.3 ns - - -
Letter-sound identific speed 47.4 46.7 42.6 ns - - -
PA accuracy 62.1 62.2 63.0 ns - - -
PA speed 48.0 73.8 57.1 ns - - -
Naming speed letters 52.6 46.7 46.3 ns - - -
Naming speed digits 57.8 46.7 37.0 ns - - -
Phonemes 45.7 44.4 57.4 ns - - -
Syllables 41.4 40.0 27.8 ns - - -
Nonverbal 14.7 28.9 31.5 ns - - -
Note: Alpha-values were adjusted to account for multiple testing: word reading measures p< .0125; word spelling measures
p< .0167 phonological skills measures, p< .008 and memory measures p< .0167. Scores are percentile scores, except for
sight word reading and decoding, which refer to standard scores.
Abbreviations: *, significant; , not tested; ns, not significant.
286 de BREE ET AL.
In this study, we evaluated whether LI children with dyslexia differed from early-diagnosed children and children
with LE dyslexia on measures of literacy, correlates of literacy and possible protective factors. Randomly selected
case files of formal diagnoses of dyslexia were categorized as early diagnosed (Grades 13) and late diagnosed
(Grade 46). The late-diagnosed group was divided into LI dyslexia (45% of the late-diagnosed sample), referring to
children whose school literacy performance in Grades 1 and 2 already warranted referral to an institute for special
learning disabilities, and LE dyslexia (55% of the late-diagnosed sample).
7.1 |Similarities and differences between the early-identified, late-identified and late-
emerging groups
At the end of Grade 1, the LI group resembled the early-diagnosed group in word-level literacy, the selection crite-
rion, but also in text reading and reading comprehension. As reading comprehension can be argued to largely reflect
word-reading ability at this early phase of literacy instruction, the reading comprehension findings match those of
the poor word reading skills of the groups. At the time of the diagnosis, word reading and spelling deficits were also
similar in both groups. In contrast, the LE group contained fewer children with word reading accuracy and speed def-
icits at the time of diagnosis. These findings corroborate previous studies reporting more severe reading deficits for
early than LE dyslexia (Bazen et al., 2020; Catts et al., 2012; Compton et al., 2008; Leach et al., 2003; Lipka
et al., 2006; Torppa et al., 2015). This pattern seems robust: Our poor performance criterion was 10th percentile.
Other studies used <25th percentile (Etmanskie et al., 2016; Lipka et al., 2006), <16th percentile (Catts et al., 2012;
Compton et al., 2008; Leach et al., 2003) or < 10th percentile (Bazen et al., 2020; Torppa et al., 2015). The pattern is
the same regardless of the criterion applied.
At the time of diagnosis, all three groups showed relatively low performance on tasks tapping the phonological
deficit and there were no overall group differences These findings match previous studies that did not find differ-
ences between the early and LE groups on risk factors once literacy difficulties had been reported (Bazen
et al., 2020; Leach et al., 2003).
7.2 |Compensation in late-emerging dyslexia?
With respect to the LE group, our findings do not agree easily with the assumption that dyslexia is late-emerging due
to the presence of protective factors in the late-dyslexia group. Although the LE group showed less severe word
reading difficulties at the time of diagnosis on some measures, they did not show outspoken strengths in phonology
TABLE 4 Mean outcomes on intelligence for the early, late-identified (LI) and late-emerging (LE) groups at the
time of diagnosis
Early LI LE F
Total IQ 102.48 (11.9) 98.20 (9.75) 100.78 (11.7) 2.305
Verbal IQ 103.46 (12.1) 99.69 (9.8) 101.43 (11.4) 1.874
Performance IQ 100.83 (12.4) 97.07 (10.8) 99.81 (12.1) 1.598
Processing speed
100.17 (11.9)
93.95 (14.1)
97.65 (11.5) 3.964*
Note:*p< .05; Subscripts refer to posthoc testing for significant main effects: they indicate that group outcomes differ
significantly from each other in these instances.
Data is available for 111 early, 42 late-identified and 51 late-emerging children.
de BREE ET AL.287
or other cognitive abilities. This finding agrees with previous studies on LE dyslexia (Bazen et al., 2020; Leach
et al., 2003; Lipka et al., 2006; Torppa et al., 2015). Similar to findings by Torppa et al. (2015), our LE group does not
have a distinct poor early literacy profile, making the eventual dyslexia of these children difficult to predict. Possibly,
the transition from accuracy to fluency is most difficult for this group of children.
7.3 |Why were children with late-identified dyslexia identified late?
An important finding of the current study is the existence of LI children in the random sample (45%). In terms of
word reading and spelling outcomes at the end of Grade 1, there are no clear reasons why these children were mis-
sed, as they met the criteria for referral in the early grades. The percentages of poor performers in the LI and early-
diagnosed groups also did not differ on text reading, but note that this finding points to marginal significance
(p=.052). We therefore cannot establish whether (all) educators took text reading outcomes into account for decid-
ing on children's referrals, a finding that was reported for German teachers (Schmitterer & Brod, 2021). Reliance on
text reading would run counter to the school-literacy protocols and psychologist dyslexia protocols, which point to
the importance of word-level outcomes (Gijsel et al., 2011; SDN et al., 2016).
The late referral of the LI group could also hypothetically be due to these children being better able to compen-
sate for their literacy difficulties. However, this does not seem to be the case: literacy outcomes were poor, so the
core deficit was not compensated. Furthermore, at the time of diagnosis, the LI group had numerically lower and not
higher mean outcomes than the early-identified group on IQ measures, with significantly lower processing speed.
Additionally, the LI group had a higher percentage of children showing poor performance on non-verbal memory
than the early-identified group. Overall, these findings do not indicate that the late referral of the LI groups is due to
There is also no strong evidence for the reverse option, that lower outcomes on protective factors hampered
the recognition of the literacy abilities in the LI group. The finding that the LI group contained a substantial propor-
tion of children showing both low and high performance on vocabulary indicates that reasons for non-referral in the
early grades are not straightforward. The slightly numerically lower IQ outcomes and the significantly lower
processing speed outcomes attested at the time of diagnosis could also have surfaced in general learning ability in
earlier grades, given the stability of IQ (Beaver et al., 2013). Clearly, this line of reasoning is highly speculative, as
data on vocabulary, IQ and memory is not present for both time points, as we have no information on broader learn-
ing outcomes at school, and we have no information on the teachers' reasons for their late referral of the children.
7.4 |Implications
Whatever the background of LI dyslexia, it seems that attention needs to be devoted to the correct application of
the response-to-intervention framework and the availability of the means to implement this approach to eliminate
the existence of LI children, who can be taken to be instructional casualties. These children have only been provided
with the appropriate dyslexia treatment late. This might have had a detrimental impact on their literacy development
as well as their wellbeing, an area that is vulnerable for people with dyslexia (e.g., Francis, Caruana, Hudson, &
McArthur, 2019; Gibby-Leversuch, Hartwell, & Wright, 2019).
Our findings not only relate to the existence of LI dyslexia (Barbiero et al., 2012; Graham, White, Tancredi,
Snow, & Cologon, 2020), but also to research findings that point to the challenges that educators face in identifying
and shaping literacy interventions: Studies have reported that schools, school psychologists, and teachers were not
always sufficiently familiar with the adequate application of the response-to-intervention framework
(e.g., Kratochwill, Volpiansky, Clements, & Ball, 2007; Vujnovic et al., 2014). It has also been reported that not all chil-
dren requiring more intensive literacy instruction actually receive this help (Graham et al., 2020) and that teachers'
288 de BREE ET AL.
identification of reading difficulties in children does not always take place on the right information (Schmitterer &
Brod, 2021). Consequently, the findings relate to the recent call of devoting more time and effort to translating
research to education (Seidenberg, Cooper Borkenhagen, & Kearns, 2020) and supporting both educators' knowl-
edge of literacy development and disorders and classroom implementation (e.g., Piasta, Connor, Fishman, &
Morrison, 2009).
This attention to the application of the response-to-intervention framework should, on the one hand, limit the
late referral of children for dyslexia diagnosis and specialized treatment and, on the other hand, ensure that children
are not referred too early. Torppa et al. (2015) found that there was an instability in dyslexia between Grades 2 and
8. Specifically, in a larger sample of children (n=182), 55 qualified as poor readers in one of the grades. Of these
55, there were 15 children (15/55 =27%) whose literacy problems had disappeared at Grade 8. This means that a
general sample of children in Grades 1 and 2 will consist of children who show a dip in literacy outcomes, but whose
delay is not persistent (see also Vloedgraven et al., 2010). These children do not require specialized treatment out-
side school. There should thus be a balance between referring too early and too late, by providing the required levels
of support (Tiers 1, 2 or 3) or help at school.
7.5 |Limitations and suggestions for further research
Our study is qualified by the limitation of missing information on the decisions for (late) referral. We do not know
whether the LI children were receiving more specialized help at school prior to their late referral, for instance, or
whether the schools the children attended differed in the speed or ease with which referrals were made. Second, we
have not included all risk factors associated with dyslexia. For instance, we have not looked at visuospatial skills or
visual attention span, which have also been associated with dyslexia (e.g., Bosse, Tainturier, & Valdois, 2007;
Franceschini, Gori, Ruffino, Pedroll, & Facoetti, 2012; Peng & Fuchs, 2014). We cannot rule out that children's abili-
ties on such measures might lead to teachers' interpretations of children's development and might possibly also influ-
ence the identification of literacy difficulties. Third, we cannot draw any conclusions about the prevalence of LI
dyslexia, as we evaluated a random sample of case files of one institute for specific learning difficulties in the
Netherlands. Although this centre has several locations across the Netherlands, we cannot generalize this to a gen-
eral LI percentage. The percentage of LI children in this study was high (45%); there is no a priori reason why this
percentage would be substantially lower in other centres. Nevertheless, a more comprehensive collection of case
files is needed to provide more precise information on this matter. One avenue for further research is to evaluate
the existence of LI dyslexia in other countries, specifically those also applying a response-to-intervention approach.
In sum, our diagnosis-based study confirms and extends the findings of previous research-based studies that
dyslexia can be late-emerging. This calls for more attention to the way dyslexia surfaces across the lifespan and the
required support. Our findings also indicate that instructional casualties occur, as a substantial number of children in
this study were identified late with dyslexia. The literacy outcomes of these children resemble those of early-
diagnosed children and are poorer than those of children with LE dyslexia. The findings thus call for further attention
to shaping and supporting the literacy curriculum at schools. This proverbial stitch in time should prevent late identi-
fication from occurring as well as optimize general literacy instruction.
We are grateful to Roos Roefs for data coding and to EVizier/Opdidakt for allowing us to use the data. We did not
obtain any funding for conducting this study.
The data that support the findings of this study are available from the corresponding author upon reasonable
de BREE ET AL.289
Elise H. de Bree
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