pragmatis, phonologial proessing, and reading ......autism speaks) indicates a recurrence rate in...

PRAGMATICS, PHONOLOGICAL PROCESSING, AND READING: LANGUAGE ABILITIES IN ‘UNAFFECTED’

SCHOOL-AGED SIBLINGS OF CHILDREN WITH AUTISM SPECTRUM DISORDER

by

Ellen Elizabeth Drumm

A thesis submitted in conformity with the requirements for the degree of Master of Arts

Graduate Department of Applied Psychology and Human Development

Ontario Institute for Studies in Education (OISE)

University of Toronto

© Copyright by Ellen Elizabeth Drumm 2014

ii

PRAGMATICS, PHONOLOGICAL PROCESSING, AND READING: LANGUAGE ABILITIES IN ‘UNAFFECTED’ SCHOOL-AGED SIBLINGS OF CHILDREN WITH AUTISM SPECTRUM DISORDER

Ellen Elizabeth Drumm

Master of Arts Applied Psychology and Human Development

University of Toronto 2014

Abstract

Siblings of children with Autism Spectrum Disorder (ASD) who do not have ASD outcomes are more

likely than their peers to experience delays in language acquisition as preschoolers. However, less

is known about how these siblings are faring when they are school-aged. We examined language-

related abilities of 17 non-ASD siblings, aged 8-11. On average, the non-ASD siblings performed

more poorly than the normative sample on measures of phonological memory and phonological

awareness. In contrast, word-level reading was intact. No impairments relative to norms were

found on a direct child assessment and parent-report measure of pragmatic language; however,

recommendations for further research in this area are made. The two pragmatic measures

demonstrated weak convergent validity; questions were raised regarding the influence of having

an older child with ASD and the effects on parents’ frame of reference. Comparing two direct

language assessments, this sample performed more poorly in pragmatics than structural language.

iii

Acknowledgments

This research would not have been possible without the support of a number of people. First

and foremost, I am indebted to my supervisor and mentor, Dr. Jessica Brian. Her patience and guidance

were invaluable throughout this process. I would like to thank Dr. Judy Wiener for feedback on the study

proposal and manuscript as well as the Canadian Sibling Study investigators for backing this project.

Thank you to Adriana Munoz for her methodical assistance with transcription and scoring.

Unquestionably, this research would not have been possible without the children and families

who graciously volunteered two days of their time to participate in this study. Finally, I would like to

acknowledge the various funding sources that supported my work: the Frederick Banting and Charles

Best Canada Graduate Scholarship, Ontario Graduate Scholarship, Kimel Family Award for Research in

Pediatric Disability, and OISE Academic Excellence Award.

iv

Table of Contents

1. Introduction…………………………………………………………………………………………………………………………………………1

1.1 Siblings of Individuals with ASD: Increased Susceptibility .................................................................. 2

1.2 Structural Language Development ..................................................................................................... 5

1.3 Pragmatic Language ......................................................................................................................... 12

1.4 Phonological Processing and Rapid Naming ..................................................................................... 17

1.5 Word-Level Reading ......................................................................................................................... 19

1.6 Current study .................................................................................................................................... 21

2. Method ................................................................................................................................................... 23

2.1 Participants ....................................................................................................................................... 23

2.2 Measures .......................................................................................................................................... 24

2.3 Procedure ......................................................................................................................................... 27

2.4 Data Analysis .................................................................................................................................... 28

3. Results ..................................................................................................................................................... 29

3.1 Sample Characteristics ..................................................................................................................... 29


3.3 Phonological Processing and Reading .............................................................................................. 31

4. Discussion ............................................................................................................................................... 33

4.1 Structural Language, Cognition, and Autism Traits .......................................................................... 33


4.3 Phonological Processing and Reading .............................................................................................. 41

4.4 Conclusions ....................................................................................................................................... 43

5. References .............................................................................................................................................. 46

v

List of Tables

Table 1. Summary of Measures………………………………………………………………………………………………………..……24

Table 2. Sample Characteristics…………………………………………………………………………………………………….……….29

Table 3. Pragmatic Language Performance in Non-ASD Siblings………………………………………………….………...30

Table 4. Phonological Processing and Reading Performance of Non-ASD Siblings……………………….………...32

LANGUAGE ABILITIES IN SCHOOL-AGED NON-ASD SIBLINGS

1

PRAGMATICS, PHONOLOGICAL PROCESSING, AND READING: LANGUAGE ABILITIES IN ‘UNAFFECTED’ SIBLINGS OF CHILDREN WITH AUTISM SPECTRUM DISORDER

ASD is a neurodevelopmental disorder characterized by social-communication deficits and

the presence of repetitive behaviours, activities, or interests (APA, 2013). Despite increasing

attention to the developmental challenges in family members of individuals with ASD1, the

developmental risks and outcomes of non-ASD siblings are only beginning to be understood.

Evidence has advanced primarily in the past four years, through longitudinal studies that have

examined younger siblings from infancy through to preschool. However, there is limited research on

the broader developmental challenges that these siblings may face later in childhood. Few published

studies have followed siblings past age 3, and significant methodological limitations have been

identified with their case definitions and measurement (Drumm & Brian, 2013). One of the major

drawbacks of limiting studies to the preschool years is the missed opportunity to observe comorbid

and pervasive neurodevelopmental conditions, such as learning disabilities and pragmatic language

impairment, which do not typically manifest until grade school.

Emerging research suggests that ‘unaffected’ siblings (i.e., those with non-ASD outcomes) of

children with ASD are at greater risk of delayed acquisition of language and communication

impairments during the preschool years (Hudry et al., 2014; Landa et al., 2012; Messinger et al.,

2013). Understanding the nature of risks in language development as these siblings grow is critical, as

language proficiency has a significant impact on overall development and quality of life (van Agt,

Verhoeven, van den Brink, & de Koning, 2011). Language is necessary for communicating needs and

desires; the key to academic achievement and occupational performance; and integral to building

1 The term ASD includes the previous DSM-IV (APA, 2000) categories of Autistic Disorder, Asperger

Syndrome, and Pervasive Developmental Disorder-Not Otherwise Specified. For the purposes of this paper, when siblings is used as a stand-alone term it will always refer to children who do not have ASD themselves, but do have an older brother or sister (proband) with ASD.

LANGUAGE ABILITIES IN SCHOOL-AGED NON-ASD SIBLINGS 2

social relationships and understanding the world around us. Discovering whether ostensibly

unaffected siblings of children with ASD are at risk for challenges in language development or

language-related school abilities would have practical implications in terms of early screening and

timely access to language and learning interventions.

This paper will begin with a brief review of research on siblings of individuals with ASD and

their increased susceptibility to ASD, ASD traits, and other neurodevelopmental and psychiatric

disorders. It will then turn to the literature on our main topic of interest: language abilities of siblings

of children with ASD, including structural language development, pragmatics, phonological

processing, and reading. This study will extend the research in these latter three domains. Broadly,

we are interested in whether siblings are at an increased risk for impairment in pragmatics,

phonological processing, and/or reading.

1.1 Siblings of Individuals with ASD: Increased Susceptibility

Part of the broader rationale for investigating the language and learning abilities of siblings of

children with ASD is the considerable evidence that these siblings are at an increased risk for

developmental differences, particularly in domains that are affected by ASD. First degree relatives of

individuals with ASD are at greater risk for ASD, ASD traits, and other neurodevelopmental and

psychiatric disorders. Decades of research into the genetic architecture of ASD reveals that there is a

substantial genetic contribution to ASD, with hundreds of ASD-risk genes implicated (see Devlin &

Scherer, 2012 for a review), though pre- and post-natal environmental factors are also seen as

playing a noteworthy role (Hallmayer et al., 2011). Accordingly, ASD has a high recurrence rate within

families and a high concordance rate in monozygotic twins, with the latter falling between 50-90%

(Bailey et al., 1995; Hallmayer et al.; Ronald & Hoekstra, 2011). The most recent estimate from a

large-scale consortium of phenotyping studies (the ‘Baby Sibs Research Consortium’, funded by


Autism Speaks) indicates a recurrence rate in younger siblings of children with ASD of 18.7%, which

represents almost a 1 in 5 chance of being diagnosed with ASD (Ozonoff et al., 2011). This compares

to a prevalence of 1 in 88 in the general population (Centre for Disease Control and Prevention,

2012), indicating that siblings are over 16 times more likely to develop ASD.

The familial aggregation of ASD has led many researchers to investigate the presence of

“autistic-like” characteristics in family members. Evidence has been found for subclinical

manifestations of the core features of ASD (social-communication impairment and repetitive

behaviours/interests) in relatives and the general population (Dawson et al., 2007; Sucksmith, Roth,

& Hoekstra, 2011; Szatmari et al., 2008). These milder presentations of ASD symptomatology,

referred to as the “broader autism phenotype”, or BAP (Piven, Palmer, Jacobi, Childress, & Arndt,

1997), are more common in biological relatives of children with ASD than in nonbiological relatives or

the general population, and rates of BAP increase as the incidence of ASD in a family increases

(Gerdts, 2012; Losh, Childress, Lam, & Piven, 2008; Piven et al.; Szatmari et al., 2000). The majority of

research into autistic traits has focused on the parents of children with ASD (Baron-Cohen &

Hammer, 1997; Piven et al., 1994; Yirmiya & Shaked, 2005); however, a growing body of literature is

beginning to explore BAP in siblings.

To date, research has focused on genetic explanations of BAP symptoms (e.g., Gerdts, 2012;

Piven, 1999), but it is possible that modelling may also play a role for younger siblings of children

with ASD. In typical populations, older siblings and twins, serving as an example to emulate, have

been seen to affect early behaviour and language development of their brothers and sisters, such as

in the development of an autonomous language between two young twins (Bakker, 1987; Luria &

Yudovitch, 1959). Very little research has systematically investigated the role modelling may play in

the presentation of BAP in younger siblings of children with ASD; however, several studies discuss


modelling theoretically as one possible element that could help explain this phenomenon (see Toth

et al., 2007; Shivers, Deisenroth, & Taylor, 2013). We may expect that any effects of behavioural

modelling that do exist would be strongest early in development; as the younger siblings grow older,

begin school, and experience a wider array of playmates and social interactions, the modelling effect

from the older sibling with ASD would diminish. More research would be needed on this topic before

conclusions could be drawn as to whether behavioural modelling plays a role in early BAP symptoms.

Parents and siblings of individuals with ASD also appear to be at greater risk for a range of

neurodevelopmental and psychiatric difficulties and disorders, including but not limited to language

impairments, dyslexia, attention deficits, obsessive-compulsive traits, social phobia, and depression

(Baron-Cohen & Hammer, 1997; Bolton, Pickles, Murphy, & Rutter, 1998; Hollander, King, Delaney,

Smith, & Silverman, 2003; Piven & Palmer, 1999). In early childhood, siblings of children with ASD are

at greater risk for suboptimal cognitive development as well temperament and behaviour difficulties,

including poor emotion regulation and sleep disturbance (Brian et al., 2008; Brian et al., in press;

Clifford et al., 2013; Constantino, Zhang, Frazier, Abbacchi, & Law, 2010; Garon et al., 2009;

Schwichtenberg et al., 2013; Stone, McMahon, Yoder, & Walden, 2007).

Georgiades et al. (2013) studied 170 non-ASD siblings and 90 low-risk controls at 12 and 36

months of age. Cluster analysis was used on the combined sample, revealing a distinct cluster of

children with reduced cognitive performance and elevated ASD symptomatology as measured by the

Autism Observation Scale for Infants (AOSI; Bryson, Zwaigenbaum, McDermott, Rombough, & Brian,

2008) as early as 12 months of age. The vast majority of children in this cluster (almost 90%)

consisted of non-ASD siblings, representing 19% of the total non-ASD sibling sample. On average, at

3 years of age this subgroup of children displayed more social and communication challenges, lower

levels of cognitive functioning, and more internalizing problems, as measured by the Autism


Diagnostic Interview-Revised (ADI-R: Rutter, LeCouteur, & Lord, 2003), Mullen Scales of Early

Learning (MSEL; Mullen, 1995), and Infant-Toddler Social-Emotional Assessment (Carter & Briggs-

Gowan, 2000), respectively.

The research outlined above underscores that siblings of children with ASD are an at-risk

group: not only for ASD and ASD-related symptoms, but also for broader developmental difficulties.

We now turn to look specifically at the research on language abilities. Each of the following sections

will provide context by briefly summarizing the abilities of children with ASD before focusing on their

non-ASD siblings.

1.2 Structural Language Development

Although structural language development (i.e., lexical and syntactic abilities in receptive and

expressive language) is not a target of the current study, we will begin here as it is the basic building

block of other linguistic skills. Across the spectrum of individuals diagnosed with ASD there exists an

extremely wide range of structural language abilities. Some children have very limited expressive and

receptive language and are essentially non-verbal; others have well-developed structural language

and score in the average or above average range on standardized tests of language fundamentals

(Ellis Weismer et al., 2007; Tager-Flusberg, Paul, & Lord, 2005). Across the gamut of lexical and

syntactic abilities, many children with ASD display atypical or idiosyncratic language, such as

stereotyped and repetitive speech, echolalia, and neologisms (Tager-Flusberg & Calkins, 1990;

Volden & Lord, 1991).

Along with atypical language, another common characteristic of ASD is delayed language

acquisition. On average, toddlers with ASD produce their first words at around 38 months of age,

instead of by the typical 8-14 month mark (Howlin, 2003). Howlin collected retrospective reports of

early language from parents of older children. Almost all research into early language development in


children with ASD is limited by this method of data collection; however, a study by Ellis Weismer,

Lord, and Esler (2010) recently confirmed the severity of early language delays with direct

assessment measures and with a very large sample of toddlers (ages 24-36 months, mean age = 30.6

months) with ASD (n = 257) and a control group with non-ASD developmental delay (DD; n = 69). In

this study, toddlers with ASD displayed significantly greater language delays than the DD group.

Toddlers with ASD also showed an atypical pattern of lower receptive to expressive language scores

on the MSEL – a language profile that is opposite to the profile in typically developing (TD) children as

well as in the DD control group in this study. Likewise, in a sample of 294 preschool children with

ASD, Volden et al. (2011) found a pattern of more impaired receptive language relative to expressive

language on the Preschool Language Scale-4 (Zimmerman, Steiner, & Pond, 2002), another direct

assessment measure of structural language.

Turning to the 4 out of 5 younger siblings who do not receive a diagnosis on the autism

spectrum, research has shown that delays in early language acquisition reliably differentiates this

group from toddlers with no family history of ASD. The strongest research design we have to study

early language development of siblings is prospective, longitudinal investigation of younger siblings

of probands with confirmed ASD, often compared to children with no family history of ASD (herein

referred to as low-risk controls: e.g., Mitchell et al., 2006; Zwaigenbaum et al., 2005). This study

design allows for babies to be recruited before or shortly after birth, and infants’ development to be

followed from very early in life. In the last decade, large-scale longitudinal studies of this nature have

been running in Canada, the United States, the United Kingdom, and Israel (Ozonoff et al., 2011;

Zwaigenbaum et al., 2007). Research from these studies provides a long-awaited opportunity to

examine the risks and outcomes for siblings – in language and many other domains – paired with


very solid methodology and growing sample sizes. To date, most prospective studies of this kind have

focused on development from 0-36 months of age.

Zwaigenbaum, Bryson and colleagues have been following one of the largest (and growing)

longitudinal cohorts of siblings for over a decade. One of the earliest studies from this cohort

(Zwaigenbaum et al., 2005) compared 23 low-risk controls with 65 high-risk siblings (19 with ASD and

46 non-ASD, as determined by ADOS diagnostic cut-off scores at age two). At 12 months, non-ASD

siblings displayed lower receptive language scores on the MSEL, as well as fewer phrases and

gestures as reported by parents on the MacArthur Communicative Development Inventory (M-CDI;

Fenson et al., 1993), in comparison to low risk controls. Non-ASD siblings from this cohort were also

found to display fewer play-related gestures compared to controls at 18 months, as reported by

parents on the M-CDI (Mitchell et al., 2006).

As this cohort of infant siblings has grown older, the diagnostic status of all participants is

determined by an independent best estimate diagnostic assessment at 3 years of age (a diagnosis at

age 3 has strong diagnostic stability: Charman et al., 2005; Guthrie, Swineford, Nottke, & Wetherby,

2013). A clinician with autism expertise determines each participant’s clinical best estimate diagnosis,

informed by the two gold-standard autism diagnostic measures – the Autism Diagnostic Observation

Schedule (ADOS; Lord et al., 2000), and the ADI-R – and blinded to family status and previous

assessment information. This diagnostic model results in a rigorous methodology that follows best

clinical and research practice. In the investigation of “unaffected” siblings, this level of systematic

categorization of participants into ASD and non-ASD groups is vitally important. Otherwise, children

who actually have ASD could artificially inflate the scores of the so-called non-ASD group.

In an American cohort of siblings, Toth and her colleagues (2007) studied 42 non-ASD siblings

and 20 low-risk controls, ages 18-25 months old. The non-ASD siblings displayed lower receptive


language scores on the MSEL, analogous to the findings of Zwaigenbaum et al. (2005), and matching

the pattern of lower receptive than expressive language seen with children with ASD, as described by

Ellis Weismer et al. (2010) and Volden et al. (2011). Non-ASD siblings used fewer words and distal

gestures, lower overall rates of social communication on the Communication and Symbolic Behavior

Scales Developmental Profile (Wetherby & Prizant, 2001), and a significant number of siblings

displayed below average expressive language abilities on the MSEL. However, it is noteworthy that

the non-ASD status of participants as young as 18 months old was determined at this same time

point. Diagnostic status is may not be stable at this age, and thus the sibling group means could have

been lowered by participants who later met criteria for ASD.

The work of Yirmiya and colleagues (2006; 2007) in Israel reveals a similar profile of results

amongst a group of 30 siblings and 30 low-risk controls, 4-36 months old. These two studies continue

to highlight the prevalence of early language delays in the sibling group: they were characterized by

lower scores on the language domains of the Bayley Scales of Infant Development (Bayley, 1993) and

the Reynell Developmental Language Scale (Reynell & Grubber, 1990). However, both of these

studies lacked a systematic method for assessing ASD symptomatology beyond a short parental

questionnaire: the Checklist for Autism in Toddlers (CHAT; Baron-Cohen, Allen, & Gillberg, 1992) or

the Social Communication Questionnaire, (SCQ; Rutter, Bailey, & Lord, 2003). Moreover, one

participant received a diagnosis of ASD, but this child’s data were not removed from those of the

remaining, non-ASD siblings. Nonetheless, it is unlikely that the observed group differences could be

entirely explained by one participant’s scores, and thus the sub-optimal performance of the sibling

group likely provides evidence of developmental concerns in at least some members of this group.

Hudry et al. (2014) and the British BASIS team provide further support for early language

delays in siblings of children with ASD and the lack of “receptive advantage” as seen in children with


ASD, but not in TD children. This study included 53 high-risk siblings (17 with ASD and 36 non-ASD, as

determined at age 3 by a clinical researcher), who were assessed at 7, 14, 24, and 38 months. One

third of the non-ASD siblings in this sample were determined to have atypical outcomes at age 3,

operationalized as displaying ASD traits or poor cognitive/language outcomes (i.e., high scores of the

ADOS or the ADI-R; low scores on the MSEL). As a group, these atypical non-ASD siblings showed

persistent language delay and no “receptive advantage”. The typical outcome non-ASD siblings,

however, displayed language delays at 14 months, but by 24 months these had resolved and they

were on par in receptive and expressive language with the low-risk control group.

Landa and colleagues (2012) were the first to use latent class analysis to examine

developmental trajectories of siblings of children with ASD. Their sample of 204 siblings, whose

cognitive, language, and motor development was followed every 6 months from 6-36 months using

the MSEL, yielded four class trajectories: (1) accelerated development, (2) normal development, (3)

early motor/receptive language delay, and (4) developmental slowing. Siblings were also divided into

unaffected, BAP, and ASD groups based on performance at their 3-year assessment. Here again we

see a different definition of BAP; in this study, participants were classified as BAP if they had social or

language delay (i.e., siblings could be defined as BAP if they displayed early language delay, even if

they showed no atypical social-communication features representing ASD traits). Membership in

each class was generally as expected, with the majority of unaffected siblings falling into classes 1

and 2, the majority of BAP siblings falling into 2 or 3, and the majority of ASD siblings falling into 2, 3,

or 4. Overall, 18.4% of non-ASD siblings fell into class 3, revealing early receptive language and motor

delay in a substantial proportion of this group. In the same longitudinal cohort, Landa et al. (2013)

reported a one-time raw score decline on the MSEL in 2% of non-ASD siblings, but no further detail

or analysis was provided to elucidate the specific nature of this finding.


In the largest sibling sample to date (also based on combined data collected from the Baby

Siblings Research Consortium), Messinger et al. (2013) analyzed the 3-year outcomes of 507 non-ASD

siblings and 324 low-risk controls. As a group, non-ASD siblings displayed lower verbal functioning, as

measured by a combined receptive and expressive language score on the MSEL, as well as lower

cognitive scores on the MSEL and higher ASD traits on an ADOS severity metric. As hypothesized, not

all siblings demonstrated developmental difficulties; group differences were driven by the

performance of a subset of siblings. A latent class analysis revealed that the majority (65%) of non-

ASD siblings occupied classes typified by low ASD severity and average developmental functioning. A

further 14% of non-ASD siblings occupied a class typified by elevated ASD severity and high

developmental functioning – although a similar proportion of controls fell into this class. The

remaining 21% of non-ASD siblings – disproportionate to controls – fell into classes of high ASD

severity with low-average developmental functioning and low ASD severity with low developmental

functioning, revealing that a substantial minority (i.e., one-third) of non-ASD siblings display BAP

characteristics, at three years of age, with or without developmental delays.

Very few longitudinal studies have been published examining the language abilities of

siblings beyond 3 years of age. In a study of 37 non-ASD siblings and 22 low-risk controls between

ages 4 to 7, Warren et al. (2012) surprisingly found no group differences on a direct measure of

structural language, the Clinical Evaluation of Language Fundamentals, Preschool edition (CELF-

Preschool; Wiig, Secord, & Semel, 2004). They also found no group differences on measures of

cognition and behavioural regulation. One significant finding was lower executive functioning

abilities in the non-ASD siblings on the Developmental Neuropsychological Assessment (NEPSY-II;

Korkman, Kirk, & Kemp, 2007).


In another longitudinal study, Gamliel and colleagues (2009) published a follow-up

evaluation of non-ASD siblings at 7 years of age. They compared three groups, determined at age 7,

using multilevel growth curve analysis: siblings displaying BAP, siblings without BAP, and low-risk

controls. BAP was defined as one or more scores 1.5 standard deviations below average on the CELF-

3 (Semel, Wiig, & Secord, 1995), Wechsler Intelligence Scale for Children (WISC-III; Wechsler, 1991),

and/or Wide Range Achievement Test (WRAT-III; Jastak & Wilkinson, 1993), and/or parental reports

of difficulties. Note, however, that ASD symptomatology was not considered in this definition of BAP.

The results of this study reaffirm language as a core area of concern for non-ASD siblings: the sib-BAP

group had significantly lower structural language scores than controls at 7 years, and showed a

pattern of lower language (but not cognitive) scores in early childhood. Interestingly, the majority of

these BAP siblings demonstrated functional difficulties for the first time at 7 years, having not

exceeded the threshold for concern at 4 years. This delayed onset of impairment may be due to the

increasing psychosocial and academic demands that children face as they grow older. However, no

assessment of autism symptomatology was employed at the 7-year mark and the authors define BAP

without assessing autistic traits, revealing a lack of consensus in the literature over case definitions. It

also raises the possibility that some of the BAP (non-ASD) siblings in this study unknowingly met

criteria for ASD. As the study relies on delineating a relatively small group of high-risk children into

those with ASD, those with BAP, and those without either of the above, if any children were

misclassified, their performance could artificially affect the group means and affect the

interpretation of findings.

In contrast to Gamliel et al.’s (2009) findings at 7 years, Ben-Yizhak et al. (2011) did not find

evidence of impaired structural language in non-ASD siblings at 9-12 years. Moreover, there was not

even a trend in this direction; on average, siblings classified as BAP received the highest receptive


and expressive language scores, followed by non-BAP siblings, and lastly the low-risk control group.

Of note, these two conflicting studies used the same language measure (CELF-3) and the same cohort

of siblings. Two notable differences between these two studies are: the age of the siblings and the

definition of BAP used to dichotomize the sibling group (Ben-Yizhak et al. operationalized BAP as an

ADOS algorithm score ≥ 4, whereas Gamliel et al. defined BAP as poor performance on measures of

structural language, cognitive ability, and/or school achievement). It is important to bear in mind the

impact different case definitions may have on results. As well, the specific nature of language

difficulties may evolve over the course of development, so there is a need to be mindful of the

effects of both increasing demands and opportunities for improvement.

In sum, prospective studies of non-ASD siblings clearly highlight language as a core area of

concern. In early childhood, non-ASD siblings are at an increased risk for delays in language

acquisition. Currently there is relatively sparse research on structural language past age three – and

results regarding these non-ASD siblings are mixed. As these children enter middle childhood, a host

of developing language abilities, beyond lexical and syntactic skill, become of increasing importance.

1.3 Pragmatic Language

Although structural aspects of language may be intact in some children diagnosed with ASD,

pragmatic abilities are universally impaired (Ben-Yizhak et al., 2011; Bishop, 1989; Volden, Coolican,

Garon, White, & Bryson, 2009). Pragmatics refers to the appropriate social use of language as a

communicative tool, and a diagnosis of ASD requires a deficit in social-communicative behavior (APA,

2013). Hymes (1971) described pragmatics as “a speaker having knowledge of when to say what to

whom, and how much to say” – for example, deciding when to use a pronoun (e.g., “he jumped”)

versus a pronominal expression (e.g., “the dog jumped”) based on a listener’s need for reference.

The speaker must give enough information, but not too much information, in order to transmit their


message appropriately in relation to the communicative context. In turn, the listener must rely on

this communicative context in order to successfully interpret the message. In the pragmatics domain,

“information” includes two types of cues: linguistic (e.g., word choice, amount of background story)

and paralinguistic (e.g., tone of voice, volume modulation, emphasis, prosody, gestures). Individuals

with ASD have well-documented difficulties with conversational back-and-forth, conversational

repair, adjusting the register of speech to a given social situation, as well as non-verbal components,

such as appropriately integrating eye contact, facial expressions, and gestures (Eigsti, de Marchena,

Schuh, & Kelley, 2011; Nadig & Shaw, 2012; Tager-Flusberg et al., 2005).

Measurement limitations are one of the major barriers to research on pragmatic language.

Pragmatics is defined as context-appropriate behaviour; as such it makes most sense to study it in

context, but this can be challenging. It is a difficult balance between measurement reliability (i.e.,

collecting standardized, quantifiable data) and external validity (i.e., capturing the wide variety of

impairments that occur spontaneously in the complex social world). One approach has been to

examine speech produced during discourse or narrative tasks. Participants are presented with a

standard task, such as telling a story from a wordless picture book, and their responses are analyzed

for a variety of pragmatic markers. Individuals with ASD have impairments in narrative and discourse

tasks (Colle, Baron-Cohen, Wheelwright, & van der Lely, 2008; Diehl, Bennetto, & Young, 2006; Losh

& Capps, 2003; Norbury, Gemmell, & Paul, 2014), although there has been mixed agreement for the

type and extent of impairment (Tager-Flusberg & Sullivan, 1995). Some of the discrepancy may be

explained by how strictly the interpretation focuses on pragmatics or confounds general story-telling,

syntax, and semantics. Compared to matched controls, individuals with ASD show less effective and

less efficient use of cohesive ties of reference, such as the over-use of pronominal expressions when

maintaining reference – a type of non-elliptical speech (e.g., “The boy went to the lake. The boy took


his dog.”), and the use of unresolved anaphors leading to ambiguous pronouns (e.g., “Mike and

Henry went to the mall. He really liked it.”; Baltaxe & D'Angiola, 1996; Colle et al.). Of note, children

who have an earlier history of ASD but who no longer meet the criteria for a diagnosis show

persistent pragmatic impairments in narrative tasks (Kelley, Paul, Fein, & Naigles, 2006).

One norm-referenced measure of pragmatics is the Test of Pragmatic Language (TOPL). The

TOPL is able to capture a wide range of expressive pragmatic abilities through direct assessment,

although the standardized nature of the assessment means that children answer hypothetical

questions in a structured setting with examiner support. Several studies have demonstrated that

children with ASD score poorly on the original version of the TOPL (Phelps-Terasaki & Phelps-Gunn,

1992), and their low scores are not accounted for by difficulties with structural language or non-

verbal intellectual reasoning (Volden et al., 2009). In a study by Young and her colleagues (2005),

performance on the TOPL discriminated between children with ASD and those who were typically

developing. Similarly, in a study by Kelley, Fein, and Naigles (2010), children with high-functioning

autism scored significantly more poorly on the TOPL than a matched control group. In a third study,

Volden and Phillips (2010) found that 9 out of 16 participants with high-functioning autism received a

standard score of less than 80 (i.e., >1 standard deviation below the mean) on the TOPL; however, a

few participants received scores in the average range, highlighting the variability in abilities of this

group, and also the limitations of this structured question-and-answer measure. In 2007, a new

version of the TOPL was released (TOPL-2; Phelps-Terasaki & Phelps-Gunn, 2007). Whether the

revised TOPL-2 will be a more sensitive measure of pragmatic language for children with ASD remains

an open question.

Given the widespread nature of pragmatic impairments in individuals with ASD, they are a

natural candidate for investigation in siblings of children with ASD. Currently, there is a dearth of


systematic research regarding the pragmatic language abilities of siblings. We know that many

children with autism display structurally intact language, and yet, the investigation of language in

siblings usually only extends to the assessment of language fundamentals. One of the reasons

pragmatic research has likely been limited is due to measurement difficulties. Research on parents of

children with ASD reveals pragmatic language impairments compared to controls, but is limited to

mostly self-report questionnaires and semi-structured interviews (Hurley, Losh, Parlier, Reznick, &

Piven, 2007; Landa et al., 1992; Wheelwright et al., 2010; Whitehouse & Bishop, 2009).

There has been some limited investigation of the pragmatic abilities of siblings in middle

childhood, though only two recent noteworthy studies were uncovered in our review. A third study

compared siblings of probands with ASD, DD, and language impairment, but did not remove the

identified subgroup of siblings diagnosed with ASD during the analysis of pragmatic language

measures (Pilowsky et al., 2003). In 2006, a study by Bishop, Mayberry, Wong, Maley, and Hallmayer

examined the pragmatic abilities of 42 non-ASD siblings and 46 low-risk controls using the Children’s

Communication Checklist (CCC-2: Bishop, 2003), a parent-report questionnaire. Four of the subscales

of the CCC-2 examine pragmatics and four examine structural aspects of language. An advantage of

the CCC-2 is that it was designed to capture the variety of pragmatic difficulties that are common

along the autism spectrum (along with identifying children with pragmatic language impairment and

specific language impairment). There is strong evidence that the CCC-2 is a sensitive measure of

pragmatic deficits in children with ASD (Bishop & Baird, 2001; Botting, 2004; Embrechts & Geurts,

2008; Geurts et al., 2004; Volden & Phillips, 2010), but Bishop et al.’s (2006) study is the first

investigation of the CCC-2 in non-ASD siblings. No significant group differences were found for the

pragmatics scales; however, when looking at the total score of the CCC-2, 24% of the non-ASD

siblings of children with ASD scored more than two standard deviations below the controls’ mean.


These siblings were more likely to have fathers who scored high on the social and communication

scales of the Autism Quotient (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001), a self-

report questionnaire. The authors suggest that the CCC-2 could have utility as a brief screening

device for BAP, but further investigation of pragmatic abilities in non-ASD siblings is needed. Given

that differences in pragmatic abilities may not be obvious to parents and may be exacerbated by

differences in frames of reference (e.g., sibling families have a child with ASD to compare to, while

control families do not), direct-observation measures might yield more informative data.

In 2011, Ben-Yizhak and colleagues published the first study of non-ASD siblings of children

with ASD that directly examined both structural language and pragmatics. Siblings from a

longitudinal cohort were followed-up in middle-childhood (32 siblings, 38 low-risk controls; 9-12

years old). Structural language and cognitive abilities were evaluated by the CELF-4 (Semel, Wiig, &

Secord, 2003) and WISC-IV (Wechsler, 2003), respectively. By comparing the scores from a subset of

items from the ADOS, the authors found evidence that siblings classified as BAP had significantly

more pragmatic impairments than siblings classified as typically developing. Although this is a

starting point, the use of the ADOS as the measure of pragmatic language has substantial limitations.

The authors used items from the ADOS both to create their BAP/non-BAP sub-groups, and to create

their variable of pragmatic impairment. Extrapolating items from the same measure for both

variables reduces the independence of the data, especially given evidence of high intra-domain

correlations (Gotham, Risi, Pickles, & Lord, 2007). There is very sound rationale for proposing that

siblings may be at an increased risk of pragmatic language impairment; however, more systematic

research is needed to explore this area.


1.4 Phonological Processing and Rapid Naming

Phonological processing is the ability to hear, remember, and manipulate the sounds in

words. Rapid naming is the ability to quickly and efficiently name sequences of familiar items (e.g.,

letters or numbers) presented in a visual array. Both of these psychological phenomena are critical

during the elementary school years, as they predict achievement in both reading and spelling (Leong,

1999; Wolf, Bowers, & Biddle, 2000). These are the underlying processes needed for decoding words,

and are most often impaired in children with word-level reading disabilities including dyslexia.

Phonological processing is commonly conceptualized as including two distinct but related parts:

phonological awareness and phonological memory. Phonological awareness is the ability to rhyme,

blend, segment, and in other ways manipulate the sounds in words. Phonological memory is the

ability to briefly store and recall phonological or sound information, often measured by tasks of

nonword repetition.

Children with ASD are more likely than typically developing children to have deficits in

phonological awareness, phonological memory, and rapid naming (Lindgren, Folstein, Tomblin, &

Tager-Flusberg, 2009; Losh, Esserman, & Piven, 2010; Smith Gabig, 2010). Relatively few studies,

however, have examined these domains in non-ASD siblings of children with ASD, and results have

been mixed in the wider investigation of these abilities in first-degree relatives. In the investigation of

rapid naming abilities, parents of children with ASD have been found to show poorer performance

than control parents – particularly on tasks that involve colour and object naming, which is less

influenced by experience and exposure to print than are letter and number naming (Losh et al., 2010;

Piven & Palmer, 1997). Research into rapid naming in siblings has been limited, and to date the

authors know of no studies that have examined colour and object naming in siblings.


In an investigation of phonological memory using the nonword repetition task of the

Comprehensive Test of Phonological Processing (CTOPP; Wagner, Torgesen, & Rashotte, 1999),

Gerdts (2012) found that both siblings and parents had mean scores in the Below Average range,

revealing deficits relative to the normative sample. Additionally, siblings from families with multiple

children with ASD (multiplex) had significantly poorer nonword repetition scores than siblings from

families with only one child with ASD (simplex). In another study of phonological memory, Schmidt et

al. (2008) found that parents of low-functioning children with ASD did more poorly on a task of

nonword repetition than control parents. Conversely, other studies have found no significant

differences in this domain between first-degree relatives of children with ASD and first-degree

relatives of children with specific language impairment (Lindgren et al., 2009) as well as low-risk

control families (Bishop et al., 2004; Wilson et al., 2013). Of note, although Wilson et al. found no

behavioural performance differences between ASD parents and control parents on a nonword

repetition task, their fMRI analysis did reveal additional, likely compensatory, brain activity in the

ASD parents while they were completing the task.

The literature on phonological processing is split between robust findings of deficits in first-

degree relatives of children with ASD and findings of no significant differences between this group

and control participants. Of note, the vast majority of studies have chosen to include only one short

task of phonological processing, and most have chosen nonword repetition. However, there are

many different aspects of phonological processing, and deficits in any one area can still result in

functional impairment. Most studies have overlooked the phonological awareness component of

phonological processing. For example, “elision” is a common phonological awareness activity where

a sound needs to be subtracted from a word, such as saying ‘cup’ without the /k/. Poor performance

on elision activities is highly predictive of reading disability, and in Smith Gabig’s (2010) study of


children diagnosed with ASD, he found elision to be their most impaired ability. In order to confirm

whether or not siblings are at risk for difficulties in this domain, a selection of phonological

awareness skills should be examined, along with the first investigation of colour/object rapid naming

and replications of performance on nonword repetition tasks.

1.5 Word-Level Reading

Reading is a school-related language ability that is typically divided into three skill

components: word reading, reading fluency, and reading comprehension. Word-level reading is the

basic building block of reading abilities and the component most directly related to phonological

processing and rapid naming abilities. Word-level reading is usually assessed by reading lists of words

and nonwords of increasing length and difficulty. Nonwords, also called pseudowords, are nonsense

“words” (e.g., dreep, shrup) that conform to the typical pronunciation patterns of a language.

Difficulties with reading are not a hallmark of ASD. A substantial portion of verbal children

with ASD have average or above average reading abilities, while others have readings skills at the

level of younger children (Asberg & Dahlgren Sandberg, 2012). A recent meta-analysis by Brown,

Oram Cardy, and Johnson (2013) highlights the individual variability in reading skills in children with

ASD. Across the studies captured in this meta-analysis, at the group level TD controls outperformed

the ASD participants on reading comprehension tasks. Word-level decoding difficulties explained 55%

of the variance in reading comprehension in the ASD samples.

Studies on word-level reading abilities in children with ASD have revealed mixed results;

some studies have found word reading deficits relative to TD controls (Huemer & Mann, 2010; Jones

et al., 2009), while others have found no deficits (Nation, Clarke, Wright, & Williams, 2006; Smith

Gabig, 2010). Still other studies have noted the phenomenon of hyperlexia in a minority of children

with ASD (Newman et al., 2007; Saldana, Carreiras, & Frith, 2009; Smith & Bryson, 1988). Hyperlexia


refers to cases where word reading abilities are unexpectedly high in relation to reading

comprehension, verbal skills, and general cognitive functioning. Phonological processing appears to

be intact in children with hyperlexia and ASD (Newman et al.), and researchers have hypothesized

that an obsession with print in some children with ASD may lead to greater reading exposure and

hyperlexia (Saldana et al.). However, it is hard to draw firm conclusions from this field of literature, as

research into hyperlexia suffers from inconsistent case definitions as well as very small sample sizes.

Researchers have found a word vs. nonword performance split in children with ASD, where

nonword reading falls significantly lower than word reading (Nation et al., 2006; Smith Gabig, 2010),

a pattern not seen in the TD controls in these studies. When reading real words, memory abilities can

be recruited to aid performance (i.e., a well-developed sight vocabulary, which may be a particular

strength in children with ASD, reduces the need to sound-out words). Conversely, nonword reading

relies entirely on decoding skills that incorporate grapheme-phoneme correspondence (i.e.,

knowledge of which sounds can be made by which letters) and phonological processing. Thus, the

word vs. nonword reading discrepancy further implicates phonological processing difficulties in

children with ASD. Smith Gabig also noted clinically that children with ASD appeared slower and

more hesitant to decode words; however, their scores did not capture speed or reading latency.

Relatively few studies have investigated word-level reading abilities in relatives of children

with ASD. Parents of children with ASD more frequently report having a history of reading problems

than do parents of typically developing children and parents of children with Down syndrome (Bishop

et al., 2004; Folstein et al., 1999). In Folstein et al., parents of children with ASD demonstrated

poorer performance on the Woodcock-Johnson nonword reading task when compared to parents of

children with Down syndrome. However, siblings in both groups performed on par on this same task.

Szatmari et al. (1993) found no differences in siblings’ nonword reading or other reading abilities


measured on the WRAT-III. Recently, Ben-Yizhak et al. (2011) also found no differences in nonword

decoding between siblings of children with ASD (with and without BAP) and controls on the Hebrew

version of the WRAT-III.

Although previous research does not provide a strong indication for reading difficulties in

siblings of children with ASD, we are still interested in this domain primarily due to clinical

observations during implementation of the Canadian Infant Sibling Study. A surprisingly large number

of families report reading and general learning difficulties in their non-ASD children. As well, the

current study will extend this field of literature by capturing word-level reading speed or efficiency,

which was observed, though not measured formally by Smith Gabig (2010). Word-level reading

fluency is often a more sensitive measure of reading difficulties, and this skill has yet to be studied in

either children with ASD or their siblings.

1.6 Current study

The last decade has yielded a fair amount of research into the risks and outcomes of younger

siblings of children with ASD. Within the group of siblings who do not have ASD, many show early

delays in structural language development, “autistic-like” traits, and other developmental concerns.

What we do not know yet is the language and learning outcomes of these siblings beyond early

childhood, as they face increasing psychosocial and academic demands. It is possible that siblings,

just like their brothers and sisters with ASD, may have intact lexical and syntactic oral language, but

still experience functional impairment in other linguistic and language-related learning domains.

Identifying the nature of risks for siblings of children with ASD has relevant clinical implications: if

language-related learning challenges are a risk during middle childhood, surveillance can lead to

earlier access to interventions, which can improve outcomes in language development and school

achievement.


The aim of the current study was to better characterize the language and learning abilities of

ostensibly unaffected younger siblings of children with ASD. Our focus was on school-aged siblings, in

order to extend the research on this age group and in turn allow us to measure language-related

abilities that emerge later in development. We examined three domains: pragmatics, phonological

processing, and reading. In pragmatics, we extended the work of Bishop et al. (2006) and Ben-Yizhak

et al. (2011) by including a standardized direct assessment measure and comparing results with a

parent questionnaire. In phonological processing, this study is contributing to the debate over

deficits in phonological memory as well as addressing a gap in the literature by testing a selection of

phonological awareness tasks and rapid naming. In reading, we conducted the first investigation of

word-level reading efficiency to investigate risk for reading disabilities in this population.

We recruited 17 school-aged non-ASD siblings, age 8-11. The three language domains of

interest cannot be thoroughly studied until children are school-aged, as we do not have direct

assessments to validly measure impairments until this age. Autism symptomatology of all

participants was assessed by a direct observational measure (the ADOS) and a parental report

measure (the SCQ). Structural language and cognitive capabilities were assessed by the CELF-4 and

the WISC-IV, respectively. In order to test for impairments in our three domains of interest, the

following measures were completed: TOPL-2, CCC-2, CTOPP-2 (Wagner, Torgesen, Rashotte, &

Pearson, 2013), and Test of Word Reading Efficiency (TOWRE-2; Torgesen, Wagner, & Rashotte,

2012).

We examined whether siblings have deficits, relative both to normative performance, on

these standardized measures, and calculated the proportion of participants who presented a reading

disability or pragmatic language impairment profile. We hypothesized that younger siblings of

children with ASD will show deficits relative to norms in one or more of the standardized measures,


revealing that they may be at greater risk for functional impairments in one or more of these

domains. If this is the case, early surveillance of siblings of children with ASD would be recommended

as early intervention in these domains will lead to better long-term outcomes. We also compared

performance on the two measures of pragmatic language performance to help evaluate the

strengths of each measure and provide clinical and research recommendations for this population.

We hypothesized that the direct measure and parent report measure of pragmatic language would

perform similarly.

2. Method

2.1 Participants

Seventeen children age 8-11 participated in this study. All participants were recruited as part

of an ongoing longitudinal study following their development from infancy through to middle

childhood (“Infant Sibling Study”: Zwaigenbaum et al., 2005). All participants had an older brother or

sister (proband) with a confirmed diagnosis of ASD, but did not have ASD themselves. The non-ASD

status of these younger siblings was determined by a clinical child psychologist or developmental

pediatrician with expertise in autism. One of these expert clinicians determined a clinical best

estimate for each sibling, based on a review of a research reliable ADOS and the child’s performance

on measures of intelligence, structural language, and adaptive behaviour. At the time of the

determination, clinicians were blinded to the child’s current diagnostic status and past history. All 17

participants received a clinical best estimate of non-ASD.

All siblings met the following additional inclusion criteria: (i) no specific neurological or

genetic conditions predisposing to ASD (e.g., fragile X syndrome, tuberous sclerosis), (ii) absence of

severe motor and sensory impairment that could interfere with the valid interpretation of study

measures, (iii) verbal IQ (i.e., WISC-IV verbal comprehension index) greater than 80, (iv) no severe


psychiatric disorders (e.g. bipolar, schizophrenia) that could confound study results, and (v) be an

English-speaking family to ensure parents can complete questionnaires and that the child’s language

skills can be validly assessed by our team. For the purposes of this study, English-speaking will be

defined as a minimum of 80% English exposure in the home and attendance at an English school

since beginning first grade.

2.2 Measures

Table 1 Summary of Measures

Construct Measure(s)

Pragmatic language Test of Pragmatic Language (TOPL-2) Children’s Communication Checklist (CCC-2)

Phonological processing Comprehensive Test of Phonological Processing (CTOPP-2) Word-level reading Test of Word Reading Efficiency (TOWRE-2) Structural language Clinical Evaluation of Language Fundamentals (CELF-4) Cognitive abilities Wechsler Intelligence Scales for Children (WISC-IV) Autism traits Autism Diagnostic Observation Schedule (ADOS)

Social Communication Questionnaire (SCQ)

2.2.1 Measures of Pragmatic Language

Test of Pragmatic Language, 2nd edition (TOPL-2). The TOPL-2 (Phelps-Terasaki & Phelps-

Gunn, 2007) is a norm-referenced measure of pragmatic language for children 6- 18 years of age. The

TOPL-2 is made up of six core subcomponents including physical setting, audience, topic, purpose

(speech acts), visual-gestural cues, and abstraction. Children are shown a picture, read a short

vignette, and asked to create a verbal response for one of the characters. Items require various

pragmatic skills such as: interpreting indirect and figurative language, tailoring apologies or

persuasion to different audiences and situations, repairing a communicative breakdown, recognizing

the emotional states of the actors, and making inferences about information that is not explicitly

stated.


Children’s Communication Checklist, 2nd edition (CCC-2). The CCC-2 (Bishop, 2003) is a 70-item

norm-referenced questionnaire that identifies communication problems in children 4-16 years old. It

requires 5-15 minutes to complete by a caregiver or adult who has regular contact with the child. The

CCC-2 includes four general language scales (speech, syntax, semantics, and coherence) and four

pragmatic scales (initiation, scripted language, nonverbal communication, and context). Items are

scored on a scale of 0 to 3, where 0 indicates that a behaviour ‘never’ occurs and 3 indicates that a

behaviour ‘always’ occurs. The initiation scale rates inappropriate initiation of communication, such

as starting conversations with strangers or difficulty stopping the child from talking. The scripted

language scale rates repetitive, idiosyncratic, and echolalic language. The nonverbal communication

scale rates difficulties with eye contact, personal space, and facial expressions. The context scale

rates understanding of jokes and puns, nonliteral language, and communication in different social

contexts (e.g., difficulty conversing with a group of other children).

2.2.2 Measure of Phonological Processing

Comprehensive Test of Phonological Processing, 2nd edition (CTOPP-2). The CTOPP-2 (Wagner

et al., 2013) is a norm-referenced measure of phonological processing and rapid naming for

individuals 4-24 years of age. The CTOPP-2 consists of 13 subtests that assess phonological

awareness (e.g. blending and segmenting sounds, isolating phonemes), phonological memory (e.g.

nonword repetition and digit span), and rapid naming (e.g. sequential naming of letters, numbers,

colours, and objects).

Subtests of the original CTOPP were the most popular norm-referenced measures of

phonological processing used in studies of children with ASD and their families (see Gerdts, 2012;

Schmidt et al., 2008; Smith Gabig, 2010), and it is also the preeminent norm-referenced measure

employed in studies of children with reading disabilities including dyslexia (Davis, 2003).


2.2.3 Measure of Word-Level Reading

Test of Word Reading Efficiency, 2nd edition (TOWRE-2). The TOWRE-2 (Torgesen et al., 2012)

is a norm-referenced measure of word-level reading efficiency for individuals 6-24 years of age.

Word-level reading efficiency is determined by accuracy and speed (i.e., fluency) while reading lists

of words and nonwords. The TOWRE-2 provides scores for sight word efficiency, phonemic decoding

efficiency, and total word reading efficiency.

The TOWRE-2 was chosen as it is one of the only validated, norm-referenced measures of

word-level reading that accounts for reading speed, capturing possible difficulties with latency,

hesitation, and self-correction. Poor performance on the TOWRE is indicative of a reading disability;

however, a limitation of using the TOWRE as the sole measure of reading ability is that the current

study will not capture reading comprehension or text reading fluency.

2.2.4 Measure of Structural Language

Clinical Evaluation of Language Fundamentals, 4th edition (CELF-4). The CELF-4 (Semel et al.,

2003) is a comprehensive measure of receptive and expressive syntax and basic semantics at the

word and sentence level which can be administered in 45-60 minutes. The CELF-4 has been normed

for use with individuals ages 5 to 21. Four subtests combine to give a Core Language Index. Subtests

include Concepts & Following Directions, Word Structure, Recalling Sentences, and Formulating

Sentences. The CELF-4 has good reliability, validity, and utility.

2.2.5 Measure of Cognitive Abilities

Wechsler Intelligence Scale for Children, 4th edition (WISC-IV). The WISC-IV (Wechsler, 2003)

is a measure of general intellectual ability for children ages 6:0 through 16:11 years. It requires

between 60 and 90 minutes for administration and yields a full-scale IQ as well as four indices: Verbal


Comprehension, Perceptual Reasoning, Working Memory, and Processing Speed. All indices have a

mean of 100 and standard deviation of 15.

2.2.6 Measures of Autism Traits

Autism Diagnostic Observation Scale (ADOS). The ADOS (Lord et al., 2000) is a structured play

schedule which uses standardized activities and ‘presses’ to elicit communication, social interaction,

imaginative use of play materials, and repetitive behaviors, allowing the examiner to observe the

occurrence or non-occurrence of behaviors important to the diagnosis of ASD. Subscale scores for

communication and social domains are based on a subset of items previously identified to best

discriminate autism/ASD from other developmental disabilities, and summed to generate an overall

diagnostic algorithm score. This study employed the ADOS Module 3 for children and adolescents

with fluent language abilities.

Social Communication Questionnaire (SCQ) Lifetime. The SCQ (Rutter et al., 2003) is a

measure of ASD symptomatology across the domains of reciprocal social interaction, communication,

and stereotyped behavior. This parent-report questionnaire includes 40 items about the child’s

behavior, each requiring a yes/no response. The SCQ provides a total score between 0 and 40. A

score above 15 is considered to be in the autism range.

2.3 Procedure

Eligible unaffected siblings were recruited through their participation in the ongoing

longitudinal Infant Sibling Study (ISS). Families were approached either during their middle childhood

follow-up visit or, for siblings who had completed their middle childhood assessment within the past

two years, they were contacted and invited to take part in the current study. The primary outcome

measures (TOPL-2, CTOPP-2, and TOWRE-2) were completed in one session for each child, lasting


approximately two hours. The remaining measures (WISC-IV, CELF-4, ADOS, CCC-2, and SCQ) were

collected at the time of the regular ISS middle childhood follow-up visit.

2.4 Data Analysis

To determine whether non-ASD siblings display deficits relative to the normative sample on

measures of pragmatics, phonological processing, and word-level reading, a series of one-sample t-

tests was conducted for the subtest scores of the TOPL-2, CCC-2, CTOPP-2, and TOWRE-2. We

calculated the proportion of participants who displayed deficits, operationalized as Below Average

performance (i.e., below the 25th and 16th percentiles).

Next, we examined the number of participants who presented with profiles of clinical

impairment (i.e., reading disability or pragmatic language impairment). A reading disability profile

was defined as TOWRE-2 and CTOPP-2 scores below the 16th percentile, in combination with average

or above average IQ on the WISC-IV (full-scale IQ, verbal IQ, or performance IQ). A pragmatic

language impairment profile was defined as scores below the 16th percentile on tasks of pragmatic

language, in combination with average or above average performance in structural language as

measured by the CELF-4.

To further explore how the two pragmatic language measures performed in this sample, we

calculated correlation coefficients between the TOPL-2 pragmatic language index and the four

pragmatic scales of the CCC-2. A paired samples t-test was conducted to compare TOPL-2 scores with

structural language as measured by the CELF-4. Finally, percent accuracy was calculated for the

whole group for each of the six domains of pragmatics measured by the TOPL-2.


3. Results

3.1 Sample Characteristics

Seventeen children aged 8-11 (M = 10.8, SD = 1.4) participated in this study. All participants

met the study inclusion/exclusion criteria and were retained in the analysis. The final sample

included 8 males and 9 females; 14 participants were of European descent and 3 were of Asian or

mixed Asian-European descent. As a group, the non-ASD siblings demonstrated performance in the

average range on measures of verbal IQ, non-verbal IQ, working memory, processing speed, and

structural language (see Table 2). Standard scores on these measures have a mean of 100 and a

standard deviation of 15.

Table 2 Sample Characteristics

Domain M (SD) Range

CELF-4 Structural Language (core index) 111.9 (11.7) 100-123 WISC-IV Verbal IQ 105.9 (11.8) 81-134 Non-Verbal IQ 109.5 (14.9) 74-138 Working Memory 107.9 (10.5) 86-127 Processing Speed 103.0 (13.2) 85-131 ADOS Autism Symptoms (revised algorithm total) 3.38 (3.34) 0-13 SCQ Autism Symptoms (total) 1.94 (2.08) 0-7

Average scores on measures of autism symptomatology were relatively low and below the

threshold for clinical concern. The ADOS Module 3 revised algorithm cut-off for ASD is a total score of

7, and elevated scores are often considered to be within three points from the cut-off (Ben-Yizhak et

al., 2011; Ozonoff et al., 2014). Two participants scored above the ASD cut-off of 7, and four more

participants received elevated scores ≥ 4. The SCQ cut-off for ASD is a total score of 15, and scores ≥

11 are considered elevated (Corsello et al., 2007). No participants scored above these cut-offs on the

SCQ. Scores on these measures informed the clinical best estimate, but ultimately the non-ASD

status of siblings was determined by the judgment of a clinician with autism expertise.



One-sample t-tests were conducted to evaluate whether the average performance of non-

ASD siblings differed from that of the normative samples of the TOPL-2 and CCC-2 (see Table 3). The

test value was set at the 50th percentile (i.e., a standard score of 100). The non-ASD siblings

performed significantly above the normative sample on two parent-report scales of pragmatic

language; Initiation (t(14) = 2.17, p < .05) and Scripted Language (t(14) = 2.51, p < .05). The Cohen’s d

index (0.56 and 0.65, respectively) indicated a medium effect size. The group of non-ASD siblings

demonstrated strengths on this parent-report measure of pragmatic language. All other t-tests were

non-significant.

Table 3 Pragmatic Language Performance in Non-ASD Siblings

Proportion Below Average

Measure M SD ≤25th Percentile ≤16th Percentile

TOPL-2 Index 96.47 10.34 35% (6) 18% (3) CCC-2 Initiation 11.47 2.615 12% (2) 6% (1) Scripted language 11.40 2.165 12% (2) 6% (1) Context 11.07 2.685 6% (1) 6% (1) Non-verbal comm. 11.33 2.870 12% (2) 12% (2)

To examine the convergent validity between our two measures of pragmatic language,

correlations were run between the TOPL-2 pragmatic language index and the four pragmatic scales

of the CCC-2. The TOPL-2 demonstrated a weak and non-significant relationship with three of the

CCC-2 scales: Initiation (r(15) = .37, p > .05), Scripted Language (r(15) = .33, p > .05), and Context

(r(15) = .34, p > .05). A strong positive correlation was found between the TOPL-2 and the CCC-2

Non-Verbal Communication scale, r(15) = .67, p < .01.

Next, a paired samples t-test was conducted to compare performance on our direct child

assessments of pragmatic and structural language (TOPL-2 and CELF-4, respectively). Standard scores


on both measures have a mean of 100 and a standard deviation of 15, making them easily

comparable. The mean performance of siblings on the TOPL-2 was significantly lower than the mean

performance on the CELF-4, t(15) = 4.63, p < .001 (see Table 1 and 2). The Cohen’s d index (1.20)

indicated a large effect. Although the pragmatic language performance of the non-ASD siblings fell

within the Average range, it was significantly lower than their performance on the measure of

structural language used in the current study.

The performance of three participants indicated the presence of pragmatic language

impairment, operationalized as scores below the 16th percentile on the TOPL-2 together with average

performance on the CELF-4 core language index. All three participants received scores at the 50th

percentile or higher on the CELF-4, with TOPL-2 scores at the 4th, 13th, and 16th percentiles, for each

case, respectively.

The TOPL-2 allows for item analysis by categorizing which subcomponents of pragmatic

language are required to pass each item. As a group, the non-ASD siblings appeared to have similar

rates of accuracy across all pragmatic subcomponents: 37% correct Visual-Gestural (monitoring facial

expressions, body language, and gestures), 41% correct Physical Context (attending to setting and

contextual characteristics), 45% correct Audience (tailoring messages to different audiences), 46%

correct Topic (introducing, changing, and maintaining topics; repairing a communicative breakdown),

46% correct Purpose (achieving a purpose, e.g., explaining, requesting, apologizing, persuading,

promising, objecting), and 49% correct Abstractions (explaining a proverb or metaphor).

3.3 Phonological Processing and Reading

A series of one-sample t-tests were conducted to evaluate whether the average performance

of non-ASD siblings differed from that of the normative samples of the CTOPP-2 and TOWRE-2 (see

Table 4). The test value was the 50th percentile (i.e., 100 for standard scores and 10 for scaled scores).


Table 4 Phonological Processing and Reading Performance of Non-ASD Siblings

Proportion Below Average

M SD ≤25th Percentile ≤16th Percentile

Phonological Processing, CTOPP-2 Elision 10.82 2.186 12% (2) 0% (0) Blending words 8.53 2.577 53% (9) 29% (5) Phoneme isolation 8.18 1.380 65% (11) 29% (5) Memory for digits 11.12 1.764 0% (0) 0% (0) Nonword repetition 7.12 2.176 71% (12) 59% (10) Rapid letter naming 11.41 2.093 0% (0) 0% (0) Rapid number naming 10.24 2.840 35% (6) 24% (4) Reading Efficiency, TOWRE-2 Words 105.12 12.191 12% (2) 12% (2) Nonwords 104.41 14.444 6% (1) 6% (1)

The non-ASD siblings performed significantly below the normative sample on one measure of

phonological memory; Nonword Repetition (t(16) = -5.46, p < .000). The Cohen’s d index (1.32)

indicated a large effect. When compared to a cut-off score of performance at or below the 16th

percentile, 59% of siblings scored in the range of impairment; 71% performed at or below the 25th

percentile. The non-ASD siblings performed significantly below the normative sample on two

measures of phonological awareness; Phoneme Isolation (t(16) = -5.45, p < .000) and Blending Words

(t(16) = -2.35, p < .05). The Cohen’s d index (1.32 and 0.57, respectively) indicated a large effect for

Phoneme Isolation and a medium effect for Blending Words. When compared to a cut-off score of

performance at or below the 16th percentile, 29% of siblings scored in the range of impairment in

each of these subtests; over half the sample had scores at or below the 25th percentile. In sum,

relative to the normative sample of each measure, the non-ASD siblings demonstrated weaknesses in

the areas of phonological memory and phonological awareness.

All other t-tests were non-significant. The average performance of the non-ASD siblings did

not significantly differ from average based on test norms on measures of rapid naming or reading


efficiency. No individual participant’s performance indicated the presence of a reading disability,

operationalized as performance below the 16th percentile on a CTOPP-2 composite and TOWRE-2

composite, together with average performance on the WISC-IV verbal, non-verbal, or full-scale IQ.

4. Discussion

This study allowed us to examine the language abilities of a well-characterized sample of

school-aged siblings of children with ASD. Participants, age 8-11, were followed from infancy as part

of a longitudinal study of siblings and met rigorous criteria to determine their non-ASD status before

being included in the current analyses. A review of published work from prospective longitudinal

studies that have followed siblings up to age 3 reveals that siblings with non-ASD outcomes are at

increased risk for delays in language acquisition, suboptimal cognitive development, elevated ASD

traits, and other behavioural concerns. However, there is a dearth of research on language

development in these children through to middle childhood. One of the major drawbacks of limiting

studies to the preschool years is the missed opportunity to observe language-related abilities and

challenges which do not fully manifest until grade school. The primary aim of the study was to

examine whether new language-related difficulties emerged as school-aged siblings met with

increasing psychosocial and academic demands, specifically in the domains of pragmatics,

phonological processing, and word-level reading.

4.1 Structural Language, Cognition, and Autism Traits

Although it was not a primary area of analysis, structural language, cognition, and autism

traits were measured in all participants. Mean standard scores of the non-ASD siblings revealed that,

as a group, they are performing well across all domains on these two tests. Means of structural

language, verbal and non-verbal intelligence, working memory, and processing speed ranged from

103 to 112, indicating performance solidly in the average range. Similarly strong mean performance


was found in Ben-Yizhak et al.’s (2011) follow-up of non-ASD siblings age 9-12. These authors divided

non-ASD siblings into a BAP and non-BAP group based on elevated ADOS scores. Both groups of non-

ASD siblings performed well on the CELF core language index (M = 113 and 111) and WISC full-scale

IQ (M = 111 and 107).

Taken in combination, these preliminary results are of great interest and highlight a need for

further examination. Recent large-scale investigations of non-ASD siblings have consistently

demonstrated that during preschool this group is at an increased risk of suboptimal structural

language and cognitive performance (Brian et al., in press; Georgiades et al., 2012; Landa et al. 2012,

2013; Messinger et al., 2013; Ozonoff et al., 2014). However, as these studies only report on siblings

up to age 3, we do not yet know whether early patterns of poor performance represent delays that

endure across development. Do those high-risk children with early deficits continue to exhibit poorer

performance throughout development, or do they catch up to their peers as they grow and

experience increased opportunities for improvement?

The current study and Ben-Yizhak et al. (2011) found strong structural language and cognitive

abilities in school-aged siblings, suggesting the possibility that poor performance early in

development could be indicative of a delay that is by and large overcome by elementary school.

Conversely, these preliminary outcomes could be an artifact of small sample sizes. Studies with

smaller sample sizes generally rely on statistical techniques that compare the mean performance of

all children with ASD, and this approach may obscure true effects occurring in a sub-group of siblings.

Due to the nature of ongoing longitudinal studies, which only began in this field in the past decade or

so, the published work on siblings age 0-3 have much larger sample sizes. In turn, this has allowed for

more sophisticated statistical analysis, such as the use of cluster analysis and latent class analysis

with this younger age group. Previous large-scale investigations of pre-school age siblings have


demonstrated that non-ASD siblings are overrepresented in classifications of poor performance;

however, the majority of non-ASD siblings still fall into categories denoting typical development. For

example, in Messinger et al. (2013) 65% of non-ASD siblings fell into categories representing low ASD

traits and typical verbal and non-verbal developmental functioning. Larger sample sizes are required

in order to apply more sophisticated statistics to studies of school-aged siblings of children with ASD

before conclusions can be drawn as to whether suboptimal skills of non-ASD siblings at age 3

indicates merely a delay that is specific to early development or whether it is more enduring.

Autism traits were assessed in this sample through direct assessment (ADOS), parent report

(SCQ), and clinical evaluation (clinical best estimate). Of note, two siblings scored above the ASD cut-

off on the ADOS, and four more received elevated scores (i.e., within three points from the cut-off),

for a total proportion of 35% that could be classified as BAP. As these measures are not normed and

no control group was included in this study, few other conclusions can be drawn from these data.

These measures were included to rigorously ensure that participants did not have ASD. All

participants were categorized as non-ASD through clinical best estimate by a clinical child

psychologist or developmental pediatrician with expertise in ASD, the gold standard for ASD

diagnosis. A score on a test of ASD symptoms informs the clinical diagnosis, but does not provide the

full picture. Ultimately, ASD status in clinical practice as well as the current study is determined by

the judgment of a clinician with expertise in assessment of ASD.


Pragmatic language (the appropriate social use of language as a communicative tool) is

universally impaired in individuals with ASD, making it a natural candidate for examination in siblings.

Although there is very sound rationale for proposing that siblings of children with ASD may be at an

increased risk of pragmatic language impairment, currently there is insufficient evidence to conclude


whether or not this is the case (Drumm & Brian, 2013). In the current study, no impairments in

pragmatic language were found when comparing the current sample to the normative samples of

each pragmatic language measure used herein (TOPL-2 and CCC-2). Further, pragmatic strengths

were reported in the parent questionnaire compared to the normative sample. These findings stand

in contrast to previous research that has compared non-ASD siblings to low-risk controls, in which

equivalent abilities (Bishop et al., 2006) or pragmatic deficits (Ben-Yizhak et al., 2011) have been

demonstrated. Siblings in the current study scored significantly higher (i.e., better) than the 50th

percentile on two of the four CCC-2 pragmatic scales; Initiation and Scripted Language. The Initiation

scale captures difficulties with conversational initiation and management, such as starting

conversations with strangers or talking at length about things others are not interested in. The

Scripted Language scale captures repetitive, idiosyncratic, and echolalic language. The pragmatic

strengths reported on both scales had a medium effect size, with the non-ASD siblings scoring over

0.7 standard deviations above the 50th percentile.

When interpreting the results of the CCC-2, it is essential to consider the unique shared

ecological context of the family units examined in this study. All parents in this study have a child

with ASD who by definition has clinically impaired pragmatic abilities (Ben-Yizhak et al., 2011; Bishop,

1989; Volden et al., 2009), and they are reporting on a younger unaffected child. No research has

established the validity of the CCC-2 in this ecological context. When examining how the CCC-2

performed in this sample, we see that five of the seventeen children were rated as ‘perfect’ (i.e.,

achieved the highest score possible) on this measure. One case in particular illustrates the possible

limitations of this measure with this particular group of children: on three assessments of social-

communication abilities completed by three different experienced examiners, concerns were noted

across the board for this child. His clinical best estimate was BAP; he scored above the ASD cut-off on


the ADOS; and he scored well below average (13th percentile) on the TOPL-2. In contrast, on the CCC-

2 his parent rated him at the 95th percentile with perfect scores across all scales of pragmatics. It

seems likely that this child truly has pragmatic deficits, despite his parent’s endorsement of

pragmatic strengths.

This parent and all parents included in this study have been exposed to the profound

pragmatic difficulties of their older child with ASD, which provides a very different frame of reference

than parents of children with no developmental challenges. Compared to the proband with clinically

impaired pragmatic abilities, there may be tendency to over-estimate these same abilities of the

undiagnosed younger sibling (as, relatively, they may seem very well-developed). Further research is

needed as, if this is a truly occurring phenomenon, it would have implications for both research and

clinical assessment in this population. We hypothesize that when parents of children with ASD report

on ASD-symptom domains in their other children, presentations of mild impairment may be missed.

The opposite effect may also occur: a parent of a child with ASD may be sensitized and better able to

notice and report mild symptoms in other children. Future research should contrast direct child

assessments and parent report measures in this population to identify whether the ecological

context systematically biases parent-reports of ASD symptoms in this population. Until such research

is completed, results should be interpreted with caution. Further, it may be worthwhile for future

research to obtain teacher reports of pragmatics. Teachers see children interacting with peers

throughout the day, and have a very solid developmental normative sample against which to

compare an individual’s abilities, given that they teach many children of the same age.

To examine the convergent validity of the two measures of pragmatic language used in this

study, correlations were conducted between the pragmatic scales of the CCC-2 and TOPL-2. Three of

the CCC-2 scales were weakly correlated in this sample; the exception was the Nonverbal


Communication scale, which demonstrated a strong correlation with the TOPL-2. Overall, the

lacklustre convergence between the CCC-2 and TOPL-2 could be a product of the parent-report bias

hypothesized above. Another consideration is the nature of pragmatic constructs captured by these

two measures. Studies that have compared these two measures in populations of children with

disabilities have made little comment on the content (Hoffman, Martens, Fox, Rabidoux, & Andridge,

2012; Staikova, Gomes, Tartter, McCabe, & Halperin, 2013; Volden & Phillips, 2010). However, there

is surprisingly little overlap between the pragmatic behaviours covered by the CCC-2 and TOPL-2.

The CCC-2 was designed to capture atypical linguistic and paralinguistic acts that occur in

populations with pragmatic impairment. During the validation process, items were chosen based on

which best discriminated typical and atypical populations (Bishop, 2003). The CCC-2 captures atypical

pragmatic behaviours such as a lack of appropriate facial expressions, poor eye contact, echolalia,

overly-precise speech, starting conversations with strangers, and difficulty stopping a child from

talking. None of these behaviours would be captured on the TOPL-2. The TOPL-2 was designed to

capture typical pragmatic abilities that develop over the course of childhood (Phelps-Terasaki &

Phelps-Gunn, 2007). Item choice was conceptually driven and followed the situational-discourse-

semantic model of Norris and Hoffman (1993). To obtain an average or high score on the TOPL-2,

children need to interpret social vignettes and formulate an appropriate response. For instance, to

receive a perfect score on an item that targets communicative repair, a child would need to show

insight into the reason for communicative breakdown (e.g., not enough information was provided

and the audience did not understand the story, or too much information was provided and the story

became boring), and problem-solve how to repair the breakdown. Scores are based exclusively on

the linguistic content of the response rather than aspects of delivery such as those examined by the


CCC-2 (e.g., the child’s use of eye contact, facial expressions, repetitive speech, or off-topic

comments would not be rated).

The CCC-2 and TOPL-2 both measure pragmatics; however, to a large extent they capture

different aspects of this domain, and this serves as a possible explanation of any discrepancies in

performance. One area where these two measures do overlap is interpretation of figurative

language: the CCC-2 asks whether children misunderstand figurative language or jokes, and the

TOPL-2 asks children to explain the meaning of several proverbs and metaphors. However, other

than this subcomponent, these measures are not interchangeable. Future research should be

cognizant of which pragmatic constructs are captured by the CCC-2 and TOPL-2 in order to ensure

the most appropriate measure or measures are included and to ensure that appropriate

interpretations are made.

Pragmatics is a superordinate skill that organizes other aspects of language. Assessment of

pragmatics should always be contextualized within the broader assessment of structural language, in

order to determine whether poor pragmatic performance is commensurate with global language

deficits or representative of specific pragmatic deficits. In the current study, we used two direct child

assessments to compare the pragmatic and structural language performance of non-ASD siblings.

Although mean pragmatic performance on the TOPL-2 fell within age expectations for our sample, it

was significantly lower than their structural language abilities on the CELF-4. As a group, pragmatic

performance was considerably (i.e., more than 1 standard deviation) lower than structural language

performance, with a large effect size. This may actually be an underestimate of the discrepancy, as

the CELF-4 has inadequate ceilings on multiple subtests. The CELF-4 was designed to identify

language impairment (Semel, Wiig, & Secord, 2003) rather than sensitively capture language

‘giftedness’. Several participants in the current sample received perfect or almost perfect scores on


one or more subtests, which translated into a maximum scaled score of 13 or 14 (84th or 91st

percentile).

Overall, pragmatic language was not universally impaired in this sample of non-ASD siblings;

however, it was also not commensurate with their relatively stronger structural language abilities. At

an individual level, three of the seventeen siblings (18%) met criteria for pragmatic language

impairment. These three siblings presented with pragmatic scores on the TOPL-2 below the 16th

percentile and structural language on the CELF-4 at or above the 50th percentile. Taken together,

these results make a compelling argument for further research on this topic. Our analyses are limited

by the small sample size and lack of low-risk control group. Future research with larger sample sizes

could use methods such as latent class analysis to investigate whether siblings with non-ASD

outcomes are overrepresented in classifications of pragmatic impairment.

For a more fine-grained analysis of pragmatic language, the TOPL-2 divided its 43 items into

subcomponent skills (Phelps-Terasaki & Phelps-Gunn, 2007). Unfortunately, norms are not provided

and therefore only the percentage correct could be calculated for each of the six subcomponents

(physical setting, audience, topic, purpose/speech acts, visual-gestural cues, and abstraction). The

group of non-ASD siblings, with 37-49% accuracy, appeared to perform similarly across

subcomponents, providing no specific recommendations to help narrow future research.

Measurement limitations continue to be one of the major barriers to research on pragmatic

language. There are no gold standard tools with adequate reliability and validity that capture the

breadth of clinically-relevant pragmatic abilities (Russell & Grizzle, 2008). The CCC-2 and TOPL-2 were

chosen for this study because they provide normative data, collect information from both children

and parents, and have demonstrated sensitivity to pragmatic language deficits in individuals with

ASD (Bishop & Baird, 2001; Botting, 2004; Embrechts & Geurts, 2008; Geurts et al., 2004; Kelley, Fein,


& Naigles, 2010; Volden et al., 2009; Volden & Philips, 2010; Young et al., 2005; Volden & Phillips,

2010). These measures collect standardized and easily quantifiable data; however, the real social

world is incredibly complex. In the field of pragmatics, measurement reliability is often achieved at

the expense of external validity. Pragmatics is defined as context-appropriate behaviour; as such,

future research with siblings of children with ASD would benefit from including assessments from

real life contexts. Although the resource burden is high and there are no available norms, with a

language-matched control group there is rich information that could be gained from this approach.

Tasks such as the TV Talk Show activity developed by Bryan et al. (1981) or Narrative activity

developed by van der Lely (1997) would be able to quantify children’s conversational turn-taking and

discourse abilities during a spontaneous interaction with another child or adult.

4.3 Phonological Processing and Reading

Mixed or insufficient evidence for impairments in phonological processing and reading in

individuals with ASD and their first-degree relatives make this an area ripe for further investigation

(Sucksmith, Roth & Hoekstra, 2011). In the current study, gold-standard direct assessments of

phonological processing (CTOPP-2) and word-level reading efficiency (TOWRE-2) were completed

with a well-characterized sample of non-ASD siblings who all had average cognitive and structural

language abilities. No impairments in word-level reading were found when comparing the current

sample to the normative sample of the TOWRE-2. These findings are in line with previous research

with non-ASD siblings (Ben-Yizhak et al., 2011; Folstein et al., 1999; Szatmari et al., 1993), and extend

the literature by accounting for reading speed as well as accuracy. Word and nonword reading were

assessed in this study, indicating that both sight vocabulary and decoding abilities were intact.

Siblings in the current sample demonstrated impairments in both phonological memory and

phonological awareness. Impairments in phonological memory had a large effect size; on the


Nonword Repetition task, siblings scored on average 1.4 standard deviations below the 50th

percentile. The majority of siblings demonstrated clinical levels of impairment on this task: 71% fell at

or below the 25th percentile and 59% fell at or below the 16th percentile. These findings are

consistent with two recent studies on phonological memory in first degree relatives of children with

ASD (Gerdts, 2012; Schmidt et al., 2008). The current study is the first known investigation of

phonological awareness in siblings of children with ASD. Impairments were found on a task of

Phoneme Isolation (large effect size; 0.9 standard deviations below the 50th percentile) as well as

Blending Words (medium effect size, 0.7 standard deviations below the 50th percentile). Phoneme

Isolation measures the ability to isolate individual sounds within words; Blending Words measures

the ability to synthesize sounds to form words. On both tasks, close to one-third of siblings

performed at or below the 16th percentile.

These findings suggest that hearing, remembering, and manipulating the sounds in language

may take more effort and resources for these siblings. In this context, it is somewhat surprising that

word-level reading abilities were intact in this sample. Phonological processing deficits are described

as the primary cause of word-level reading disability (Elbro, Nielsen, & Petersen, 1994; Hulme &

Snowling, 2009; McBride-Chang, 1995; Stanovich, 1988) and improvement in phonological processing

leads to improvement in reading abilities (Ehri et al., 2001; Foorman et al., 2012; National Reading

Panel, 2000). However, in a critical literature review, Swanson, Trainin, Necoechea, and Hammill

(2003) demonstrated that the correlations between phonological processing and reading abilities

were only moderate, and suggested that many different psychological processes contribute to an

individual’s reading achievement. In this sample, we saw strong abilities in the domains of working

memory, processing speed, and rapid naming. These processes could be contributing to the strong

word-level reading abilities, in spite of some relative weaknesses in phonological memory and


phonological awareness. No children in this sample presented with a profile of reading disability.

Aside from reading achievement, additional implications of impaired phonological processing

include difficulties pronouncing words correctly and perceiving the speech of others (Wagner,

Torgesen, Rashotte, & Pearson, 2013). These areas were not systematically measured in the current

study but, informally, no concerns were noted by the examiner. Impaired phonological processing

can also hinder oral word learning, particularly early in development (Gathercole, 2006). Delays in

early language acquisition are well-established in non-ASD siblings (Hudry et al., 2014; Landa et al.,

2012; Toth et al., 2007); future longitudinal investigations could examine whether early language

delays relate to impairments in phonological processing in this population. If so, phonological

processing may be a good target for early surveillance and intervention to aid early language and

vocabulary acquisition.

Consistent with previous research, this study found deficits in phonological memory in

‘unaffected’ siblings of children with ASD, and, in the first investigation with this population, also

found deficits in phonological awareness. In contrast, word-level reading efficiency was intact for

both words and nonwords. As this is consistent with previous findings (Ben-Yizhak et al., 2011;

Folstein et al., 1999; Szatmari et al., 1993), word-level reading difficulties may not be at risk in this

population. This study did not examine other aspects of learning disabilities, such as reading

comprehension, writing, mathematics, visual-motor integration, attention, and executive

functioning. Longitudinal follow-up with larger sample sizes may be able to determine whether,

beyond reading alone, broader learning challenges occur more frequently in non-ASD siblings.

4.4 Conclusions

Large-scale longitudinal investigations of the younger siblings of children with ASD have

established that siblings with non-ASD outcomes are at increased risk for developmental difficulties


during preschool, including delays in early language acquisition. However, few published studies have

followed siblings past age 3. One of the major drawbacks of limiting studies to the preschool years is

the missed opportunity to observe language-related abilities and challenges which do not manifest

until children meet with the increasing psychosocial and academic demands of grade school. The

current study examined three such domains in a sample of non-ASD siblings aged 8-11: phonological

processing, reading, and pragmatics. Standardized measures of structural language, cognition, and

autism traits were completed to characterize our sample and confirm non-ASD status. Of note, all

participants demonstrated strong structural language abilities in the average or above average range;

more research is needed before concluding whether language delays in this population are specific to

early development or whether delays are more enduring.

On average, the non-ASD siblings in this sample performed more poorly than published

norms from the standardization sample on measures of phonological memory and phonological

awareness. Hearing, remembering, and manipulating the sounds in language may take more effort

and resources for these siblings. In contrast, rapid naming and word-level reading was intact. This

area of research could be extended by examining the broader learning abilities and challenges in this

population.

Relative to norms, no impairments were found on either a direct child assessment or parent-

report measure of pragmatic language, and, somewhat surprisingly, the parent-report measure

revealed pragmatic strengths. We recommend that this finding be interpreted cautiously, as

differences in pragmatic abilities may not be obvious to parents and may be exacerbated by

differences in frames of reference (e.g., sibling families have a child with ASD to compare to, while

families in the normative sample do not). When comparing two direct language assessments,

pragmatic language of non-ASD siblings was incommensurate with structural language abilities;


although mean pragmatic scores were within the average range, they were significantly lower than

structural language scores. Further, three participants presented with profiles of pragmatic language

impairment. These mixed findings highlight pragmatics as an area for further research. Future

investigations of school-aged siblings of children with ASD would benefit from larger samples and

direct comparisons to low-risk (and typically developing) control groups.

Although the majority of siblings of children with ASD demonstrate a typical developmental

trajectory, it is important for researchers, clinicians, teachers and parents to better understand the

nature of increased risk for siblings, as early detection of emerging developmental concerns can

result in earlier intervention, increased support at home and school, and better outcomes.

Prospective longitudinal studies of younger siblings of children with ASD have been at the vanguard

of research on non-ASD outcomes. As the participants in these ongoing longitudinal studies grow

older, the studies will be well placed to extend our knowledge of the developmental trajectories of

these siblings into middle childhood and, importantly, to link early predictors with later outcomes.

LANGUAGE ABILITIES IN SCHOOL-AGED NON-ASD SIBLINGS

46

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