Chapter 4 Readers of this chapter will be able to: 1. Describe the similarities and differences between the speech, language, and communication profiles of children with disorders of known genetic origin and more primary developmental language disorders. 2. Discuss language disorders and differences associated with sensory impairments. 3. Describe the ways in which acquired language disorders in children differ from congenital developmental language disorders. 4. Highlight the language and communication impairments associated with psychiatric disorders of complex genetic origin. 5. Explain the role of extreme environmental disadvantage in language and communication impairment. 6. Evaluate the overlap between developmental language disorders and literacy disorders. 7. Consider the particular challenges that arise when assessing language and communication in the nonverbal child. 8. Discuss the relationship between social, cognitive, and emotional factors in language development and disorder. Our perspective in this book is that it is more important in clinical practice to describe the nature of a child’s language disorder than to get to the root cause of the problem. We discussed earlier how the diagnostic category in which a child is placed may not always either explain or predict language and communication behavior. We know there is considerable variability within a single diagnostic category; sometimes the differences between children with the same “diagnosis” are as striking as the similarities. We’ve also talked about the fact that many children don’t fit very neatly into one diagnostic classification. The causal model we outlined in Chapter 1 (see Figure 1-1) gives us a clue as to why this is so: several genetic, environmental, and cognitive risk factors are common across disorders, increasing the chances that children may have symptoms of different disorders at the same time. For example, many children with intellectual disability (ID) have characteristics of autism spectrum disorder (ASD) and many children with ASD have additional intellectual disabilities. Finally, we’ve said that knowing a child’s diagnostic label often doesn’t precisely indicate a specific child’s assessment or intervention needs. Knowing that a nonverbal child has ASD, for example, does not automatically prescribe the program. Should he or she be given intervention in the speech modality, or should an alternative modality such as sign language be introduced? This decision is not very different from the decision that must be made in the case of a non-speaking child who has a hearing impairment or a severe motor speech disorder. The American Association on Intellectual and Developmental Disabilities (AAIDD, www.aaidd.org) provides the following definition of intellectual disability (Schalock et al., 2010): In addition, the AAIDD (2010) diagnosis requires that: 1. Limitations in present functioning must be considered within the context of community environments typical of the individual’s age, peer group, and culture. 2. Valid assessments consider linguistic and cultural differences in the way people communicate, move, and behave. 3. Within an individual, limitations often coexist with strengths. 4. The major purpose of describing limitations is to develop a profile of needed supports. The AAIDD provide definitions of intellectual and adaptive function. Intellectual functioning, or intelligence, refers to general mental capacity, such as learning, reasoning, and problem solving. This may be operationalized on the basis of IQ test scores; generally, an IQ test score of around 70 to 75 indicates a limitation in intellectual functioning. This range of scores translates to a criterion of at least 2 standard deviations below the mean (a standard score of 100). You’ll remember from Chapter 2 that fewer than 3% of a normally distributed population will score farther from the mean than -2 SD (see Figure 2-11). You’ll note that this is not an absolute score; the inclusion of adaptive skills in the definition leaves open the option of diagnosing an intellectual disability in an individual who has borderline IQ scores and significant limitations in adaptive behavior. Although adaptive behavior is often evaluated subjectively, standardized measures exist for various aspects of adaptive performance. Some examples include: the Adaptive Behavior Assessment System—2nd edition (ABAS:2; Harrison & Oakland, 2003), the Scales of Independent Behavior-Revised (SIB-R; Bruininks, Woodcock, Weatherman & Hill, 1997), the Adaptive Behavior Scales-School—2nd edition (ABS-S:2; Lambert, Nihira & Leland, 1993), and the Vineland Adaptive Behavior Scales—II (Sparrow, Cichetti, & Balla, 2005). Ecological inventories and environmental assessments (see Chapter 8) also can be used to assess various aspects of adaptive performance. Early reports of the cognitive profile of individuals with nonspecific ID reported a similar pattern of cognitive development to typically developing children, but a slower developmental trajectory (Owens, 2009). Other researchers have reported a more uneven profile of cognitive development with more pronounced deficits in executive functioning (EF; Willner et al., 2010) and working memory (Henry & Winfield, 2010; Caretti, Belachi, & Cornoldi, 2010) than would be expected given overall level of intellectual ability. Willner et al. noted that, in a cohort of individuals with ID attending day center services, EF skills were not strongly correlated with IQ scores, but that impairments in EF may be more closely associated with impairments in adaptive behavior. Henry and Winfield (2010) considered the relationship between different components of working memory and scholastic attainment in 11- to 12-year-old children with ID. They found that measures of phonological working memory (word and digit repetition) accounted for a large degree of variance in literacy skill, whereas measures of the “central executive” (a listening span task, in which children make true/false judgements about statements while simultaneously remembering the final word of each statement) were more predictive of numeracy skill. Caretti et al. (2010) indicated that working memory performance in ID was particularly influenced in attentional control and in “updating” information held in temporary store. Cognitive abilities do generally improve throughout childhood and into adulthood, though IQ scores (which take age into account) remain stable throughout development for many individuals (Yang et al., 2010). Delayed language acquisition is often one of the first signs of ID. One question that the clinician is likely to face is whether language skills are in line with nonverbal mental age expectations, or whether language is impaired relative to other cognitive achievements. Both patterns of language acquisition have been observed; Miller and Chapman (1984) estimated that approximately 50% of children with nonspecific ID had language skills commensurate with nonverbal abilities. The remainder have more uneven profiles; 25% had expressive language deficits relative to comprehension skill (which was on par with nonverbal mental age) while the remainder had deficits in both comprehension and expression. This variation may be related to differences in cognitive abilities, for instance the differences in working memory and attention control we discussed earlier (Abbeduto & Boudreau, 2004). In general, the acquisition of specific grammatical devices follows a typical developmental sequence, albeit at a slower developmental pace. However, once the mean length of utterance (MLU) is above 3, children with ID tend to use shorter, less complex sentences with fewer elaborations and relative clauses than do typical peers at the same MLU level (Abbeduto & Boudreau, 2004). It has generally been thought that vocabulary is easier for children to learn than syntax; however, recent research suggests this may be artifact of test selection (Chapman, 2006). Specifically, the Peabody Picture Vocabulary Test (PPVT IV) (Dunn & Dunn, 2007) exaggerated differences between IV vocabulary and syntax in adolescents with nonspecific ID relative to the vocabulary subtest of the Test of Auditory Comprehension of Language—3 (Carrow-Woolfolk, 1999). On this measure, age-equivalent scores did not differ significantly from syntactic measures. Chapman (2006) concluded that, while vocabulary size may be an advantage in ID, conceptual knowledge is more in keeping with developmental expectations (see also Norbury, Griffiths, & Nation, 2010, for a similar pattern of results in autism spectrum disorder). The ability to use language meaningfully in social contexts is an important component of adaptive behavior, yet the pragmatic skills of children with nonspecific ID have attracted relatively little research attention. Pragmatic competence in everyday situations requires the integration of cognitive, linguistic, and social-emotional cues, making it particularly vulnerable in ID. Not surprisingly then, the evidence that exists suggests that pragmatic development often lags behind cognitive development, though it may not be qualitatively different (Abedutto & Boudreau, 2004; Abedutto & Hesketh, 1997). Specifically, individuals with ID may be slow to develop intentional communication in the pre-verbal stages of development. Once some language is acquired, children with ID are able to engage in socially meaningful conversations, with adequate turn-taking and topic maintenance skills. However, they may be less able to clarify meaning and request clarification when they have not understood utterances. In addition, using language forms for different social purposes may also be challenging. Recent research suggests that individuals with ID have considerable difficulties constructing coherent narratives (Murfett, Powell, & Snow, 2008), but are able to make use of gestural supports to enhance understanding, particularly in the context of understanding verbal humour (Degabriele & Walsh, 2010). Like other aspects of language development, literacy is slower to progress for children with ID. However, just as we see in typical development, phonological processing skills predict word and non-word reading in this population (Wise et al., 2010), while word reading and oral language skills predict reading comprehension abilities (Verhoeven & Vermeer, 2006). Differences in literacy achievement are not caused by lack of reading opportunity in the home literacy environment; van der Schuit et al. (2009) demonstrated that parents of children with ID provided similar literacy opportunities as other families, although the children with ID initiated these activities less often. Home literacy experiences were associated with the child’s verbal and nonverbal abilities, indicating that parents adapt their level of engagement to the child’s linguistic abilities. Down syndrome (DS) is the most common genetic cause of intellectual disability, occurring in approximately 1 in 700 live births (Canfield et al., 2006). DS is named for John Langdon Down, the nineteenth-century English physician who first published a description of a group of clients with the syndrome. In the majority of cases, DS results from an extra (third) copy of chromosome 21 (which is why it is sometimes referred to as trisomy 21); increasing maternal age significantly increases risk of Down syndrome (see Fidler & Daunhauer, 2011 for a comprehensive review of etiological factors). Down syndrome is characterised by mild to moderate ID, hypotonia (low muscle tone), distinctive facial features such as microgenia (an abnormally small chin), round face, macroglossia (protruding or oversized tongue), epicanthal fold (fold of skin on the eyelid), short stature and shorter limbs, and hyperflexibility of joints (Figure 4-1). DS is also associated with a number of health concerns including a higher risk for congenital heart defects, gastroesophageal reflux disease, recurrent ear infections, obstructive sleep apnea, and thyroid disfunction. Co-morbid autism is diagnosed in 10% of children with DS, though there is debate concerning the degree to which severe cognitive impairments increase the likelihood of a dual diagnosis. As individuals with DS are now living longer, it has become apparent that adults with DS are at greatly increased risk of experiencing early onset Alzheimer’s disease. In DS, the earliest symptoms of Alzheimer’s disease are marked changes in behavior, rather than cognitive decline (Nelson et al., 2001). Children with DS experience global developmental delays in fine and gross motor skills. These motor delays are accompanied by mild to moderate intellectual disability, with the majority of IQ scores between 40 and 70 (Hodapp, Evans, & Gray, 1999). Individuals with DS generally have an uneven profile of cognitive development that may impact on language development and language processing. For instance, they have marked deficits on measures of working memory, but these are more pronounced with verbal material relative to visuospatial working memory (Lanfranchi, Jerman, & Vianello, 2010), a pattern that appears to be unique to DS and not other syndromes of ID (Edgin, Pennington, & Mervis, 2010). Executive functions, the cognitive processes integral to adaptive, goal-directed actions, are vulnerable in DS (Kittler, Krinsky-McHale, & Devenny, 2008). These include problems with response inhibition (impulse control), cognitive flexibility, and planning. Limitations in response inhibition have been linked to reduced generation of strategies for delaying gratification, difficulties persisting with learning tasks, and engaging in more off-task behavior (Kopp et al., 1983, Vlachou & Ferrell, 2000). Individuals with DS have greater difficulty than mental-age–matched comparison groups learning new rules and applying them (Lanfranchi et al., 2010). They also take longer to solve problems and are more likely to abandon efforts at problem solving, reflecting difficulties with planning and persistence (Fidler et al., 2005; Lanfranchi et al, 2010). Clearly, deficits in executive skills can impact academic performance as children with DS struggle to stay on task and monitor and adapt their own behavior to achieve learning goals. Speech intelligibility in DS is poor relative to cognitive ability and is particularly pronounced in connected speech (Barnes et al., 2009). Most speech sound errors are developmental in nature (e.g., cluster reduction and final consonant deletion) though some atypical errors are also evident, such as vowel distortions and inconsistent pronunciations (Cleland et al., 2010). Reduced intelligibility may be attributed in part to anomalies of the articulatory structures or complications arising from frequent bouts of middle ear infection (Martin et al., 2009). Apraxia of speech has also been reported in DS (Rupela & Manjula, 2007), suggesting assessment of oral-motor structure and function is warranted. Like children with primary DLD, children with DS appear to have disproportionate difficulties acquiring and using syntax (Chapman, 2006; Laws & Bishop, 2003). Syntactic comprehension is characterised by slowed growth and even decline in late adolescence (Laws & Gunn, 2004) and is more impaired than overall cognitive ability and vocabulary size (Caselli et al., 2008; Price, Roberts, Vandergrift, & Martin, 2007). Expressive syntax presents even greater challenges and can be an earlier indicator of language difficulties. Children with DS produce shorter and less complex sentences and fewer question/negation forms than typically developing peers matched for nonverbal mental age (Caselli et al., 2008; Price et al., 2008). Similarities and differences have also been noted between the grammatical profiles of individuals with DS and individuals with other DLDs (Ypsilanti & Grouios, 2008). For instance, numerous similarities between DS and more specific language impairments have been noted (Laws & Bishop, 2004) with particular limitations in tense marking (past tense –ed; third person singular –s) (Caselli et al., 2008; Laws & Bishop, 2003). On the other hand, individuals with DS appear to have more pronounced grammatical deficits relative to other groups with ID of known genetic origin. For instance, Price et al. (2008) reported that grammar was more severely impaired in DS than in Fragile X syndrome and that differences persist into adolescence and early adulthood (Finestack & Abedduto, 2010). Acquisition of first words in DS is significantly delayed and subsequent growth of expressive vocabulary is slower than expected (Berglund, Eriksson, & Johansson, 2001). Once words are acquired, there is some debate as to whether vocabulary keeps pace with nonverbal cognitive abilities, and whether there are asymmetries in receptive/expressive vocabulary as there are in grammatical development. Some investigators have reported receptive vocabulary scores in line with cognitive expectations (Laws & Bishop, 2003), whereas other have reported that expressive vocabulary is impaired relative to peers matched on nonverbal IQ (Caselli et al., 2008; Price et al., 2007). Differences between studies may be due, in part, to differences in the vocabulary measures used (cf. Chapman, 2006), though differences in participants (hearing status or parental education levels) cannot be ruled out. There is some evidence that gesture is preferentially used by young children with DS and supports vocabulary comprehension, and may be predictive of later vocabulary development (Zampini & D’Odorico, 2009). Individuals with DS are proficient in using referential cues to learn new words (McDuffie, Sindberg, Hesketh, & Chapman, 2007) but word learning and vocabulary growth may be hampered by limitations in phonological short-term memory (Jarrold, Thorn, & Stephens, 2009). Pragmatics is generally considered to be an area of strength for individuals with DS, although early joint communicative behaviors such as mutual eye contact, vocalizations, and dyadic interactions with caregivers may be delayed or less coordinated than those observed in typically developing (TD) infants (Berger & Cunningham, 1983; Jasnow et al., 1988). By the age of two, infants with DS catch up, with many children with DS showing more social-interactive behaviors than TD peers (Mundy et al., 1988). Children with DS use the same variety communicative functions (comment, answer, protest) as language- or nonverbal ability-matched younger children, though they demonstrate fewer requesting behaviors (Beeghly et al., 1990). Conversational development is also an area of strength, as children with DS demonstrate high levels of contingent responding and topic maintenance (Beeghly et al., 1991; Tager-Flusberg & Andersen, 1991). Narrative skills of children with DS also reflect a good conceptual understanding of the story. When narrating a wordless picture book, children with DS produce more plot lines and thematic elements relative to MLU-matched peers (Miles & Chapman, 2002). This narrative strength may depend in part on the level of support provided. For instance, when asked to narrate stories without picture support, individuals with DS may recall fewer important story elements (Kay-Raining Bird, Chapman, & Schwartz, 2004; Murfett, Powell, & Snow, 2008). Other aspects of language use may be vulnerable. Roberts et al. (2007) reported that children with DS provided fewer elaborative utterances in conversational turns relative to peers matched for nonverbal ability, instead providing minimally adequate replies. In addition, individuals with DS are less likely to signal non-comprehension of language or request clarifications in referential communication tasks (Abbeduto et al., 2008). Abbeduto et al. reported that the ability to request clarification was associated with vocabulary and syntactic skills, highlighting the strong links between core language skills and use of those skills in social contexts. These pragmatic behaviors may also be associated with executive skill, and particularly the ability to monitor comprehension, though further research is needed in this area. Reading skills of children with DS are extremely variable and little is known about the proportion of children with DS who achieve reading proficiency (Martin et al., 2009). It is clear that, like other aspects of language development, literacy development in DS follows a protracted, though qualitatively similar, developmental course (Cardoso-Martin, Peterson, Olson, & Pennington, 2009). For example, as in the case of typical development, word and non-word reading in DS is intimately related to phonological processing skills (Lemons & Fuchs, 2010; Roch & Jarrold, 2008). Comparison of word reading and comprehension skills suggests that individuals with DS are more likely to have a profile similar to that of “poor comprehenders” in which word reading abilities outstrip reading comprehension skills (Roch & Levorato, 2009). Poor reading comprehension was associated with levels of oral language comprehension, suggesting that oral language comprehension should form the foundations of educational interventions aimed at improving literacy skill for this population (cf. Clarke et al., 2010). With regard to intervention, the ultimate goal should be to improve functioning in communication, academic, social, and vocational areas (American Speech-Language and Hearing Association [ASHA], 2005a). Decisions about what to prioritize in invention should be made in collaboration with families and clients themselves, and should focus not just on developing skills, but on the functional use of those skills in academic, vocational, and social contexts. With this in mind, Martin et al. (2009) suggest that general priorities for working with DS populations will be to target early communication using milieu communication techniques (see Chapter 3) with families to support development of early vocalizations, gesture, and eye gaze to initiate and respond to “conversational” exchanges (cf. Fey et al., 2006). Martin et al. also advocate targeting speech skills, complex language structures, and early literacy skills. While reading development may be seen as an outcome of early intervention strategies, there is also evidence that using written language in intervention programs may, because of its visual modality, support oral language, speech, and memory development in DS (Roberts et al., 2008; Laws, 2010). Williams syndrome (WS) is a complex neurodevelopmental disorder that results from the deletion of approximately 25 genes on one copy of chromosome 7q11.23 (Osborne, 2006). It is a relatively rare disorder with a prevalence rate of 1 in 7,500 live births (Stromme et al., 2002). WS is associated with multiple physical, cognitive, and behavioral features. Physical features include characteristic facial dysmorphology (Figure 4-2), cardiovascular heart disease, growth deficiency, and connective tissue abnormalities. The striking behavioral phenotype is one of overfriendliness, social gregariousness, and marked anxiety (see Mervis & John, 2010, for review). Infants and toddlers with WS experience global developmental delays, and older children and adults with WS generally have mild to moderate ID. Some individuals will have IQs within the low average range, while others will experience more severe impairment (Mervis & John, 2010). Apart from general ID, WS is associated with a unique profile of cognitive strengths and weaknesses. Most notably, children with WS have profound difficulties with visual-spatial construction, with scores on the Spatial Cluster of the Differential Ability Scales (Elliot, 2007) some 20 points lower than scores on other intelligence scales (Mervis & John, 2010). These cognitive deficits occur in the context of difficulties with adaptive behavior, particularly in the areas of motor development and independent living (Mervis & Morris, 2007). Canonical babbling is significantly delayed in infants with WS relative to age-matched infants (Mervis & Becerra, 2007). Onset of babbling is predictive of onset of word production. There are no reports of significant speech sound disorders or reduced intelligibility in older, verbal children with WS. Initial reports of grammatical development suggested that grammar was “intact” and much better than expected for overall level of nonverbal cognitive ability. Indeed, when compared with ability-matched peers with Down syndrome, the grammatical skills of children with WS are superior (Joffe & Varlokosta, 2007). However, Mervis and John (2010) point out that these findings may reflect the more pronounced grammatical limitations that characterize children with DS rather than demonstrating superior grammatical skills in WS. When compared to younger typically developing children with equivalent cognitive levels or to other participants with ID, grammatical skills are more in line with, or sometimes below, developmental expectations (Mervis & Becerra, 2007). Deficits in grammatical understanding are evident, but these are strongly related to verbal working memory abilities and general levels of cognitive ability (Mervis & John, 2010). Understanding and production of concrete vocabulary are relative strengths for individuals with WS, resulting in consistently higher scores on measures of vocabulary such as the PPVT (Dunn & Dunn, 2007) and the Expressive Vocabulary Test (Williams, 2006), relative to other language measures (cf. Brock, 2007). However, as we’ve seen in our earlier discussions, this profile is not unique to WS and characterizes many DLDs. What is less common across disorders is the profound difficulty with relational or conceptional vocabulary experienced by individuals with WS. This vocabulary is important for marking spatial, temporal, and dimensional concepts as well as for devices such as conjunction and disjunction. Deficits with these terms mimic deficits in spatial abilities (Mervis & John, 2008). In contrast to children with DS, children with WS have pronounced pragmatic difficulties, despite the superficial air of social skill. The emergence of joint attention is delayed and there is an atypical temporal relationship between gesture and word production. In typical development (as well as in DS), referential gestures such as pointing precede referential word production (Mervis & Becerra, 2007). Although WS is often conceptualized as the “opposite” of ASD because of the increased interest in social interaction in WS, systematic investigation has highlighted overlaps between the two disorders. For example, although children with WS are more likely to look at faces than children with ASD, their ability to integrate gaze cues for communication purposes is impaired (Lincoln et al., 2007). Even when children do meet criteria for ASD, a significant proportion of children with WS have marked pragmatic difficulties on parent-report measures such as the Children’s Communication Checklist (Bishop, 2003). Laws & Bishop (2004) reported that 79% of children with WS studied were rated as having pragmatic difficulties. These pragmatic difficulties are evident in conversational behavior, in which individuals with WS are less likely to provide contingent and informative responses than peers with more specific DLDs (Stojanovik, 2006). In addition, qualitative differences in narrative skill have been reported; relative to other populations with ID, children with WS made considerably more social evaluative statements and fewer cognitive inferences (Reilly et al., 2004). Like other children with ID, children with WS have more difficulty monitoring their own comprehension and signalling when their conversational partners provide ambiguous or inadequate messages (John et al., 2009). Mervis and John (2010) suggest that intervention approaches developed for other populations with ID and social impairments can also be used for children with WS. In particular, working with families to develop language and communication is a priority for young children with WS. Language intervention is likely to be necessary throughout the school years; the focus of intervention may change and should emphasize use of language targets in academic and socially meaningful contexts. Social skills training for older children is also advocated; these not only aim to promote socially appropriate communication behaviors, but could help children with WS to be more discerning in approaching others and in reading more subtle social-communication cues. To date, only one study has explored literacy intervention in this population. Mervis (2009) suggests that a systematic phonics based approach in the context of direct reading instruction is preferable to a whole word approach for these children. Oral language instruction aimed at improving reading comprehension is also likely to be important (cf. Clarke et al., 2010) and will need to be complemented by explicit strategies for comprehension monitoring and linking text information to general knowledge. Fragile X syndrome (FXS) is a single gene disorder, caused by an expansion of the trinucleotide (CGG), which repeats too often on the fragile X mental retardation gene (FMR1), which is located on the bottom end of the X chromosome (see Hagerman, 2008 for extensive review). Typical individuals have 5 to 44 repetitions on FMR1; premutation carriers of FXS have 55 to 200 repeats, while individuals with the full mutation have in excess of 200 CGG repeats (Schneider, Hagerman, & Hessl, 2009). This expansion leads to eventual silencing of the FMR1 gene, reducing or completely eliminating production of its associated gene protein, FMRP (Oostra & Willemson, 2003). FMRP is critically important for experience-dependent neural development, particularly for the maturation of synapses and synaptic pruning in the developing brain; as such, there is a direct positive correlation between the amount of FMRP expressed and level of cognitive functioning (Schneider, Hagerman, & Hessl, 2009). Unlike Down syndrome, which is not passed down from one generation to another, FXS is an inherited disorder, and is the most common inherited form of ID. FXS occurs in approximately 1 in 4000 males and 1 in 8000 females; it is more common in males because males have only one X chromosome. The prevalence of the premutation is much more common, with approximately 1 in 250 females and 1 in 600 to 800 males having the premutation (Beckett, Yu, & Long, 2005). The full mutation is associated with a characteristic, though variable, physical and behavioral phenotype. Boys with FXS do not have clearly dysmorphic features and are often difficult to identify before the age of 3, unlike children with DS, whose physical features are noticeable from birth. With increasing age, however, characteristic physical features emerge (Figure 4-3). These include elongated face, long and prominent ears, highly arched palate, enlarged head, hypotonia, flat feet, hyperextensible finger joints, and large testicles (macroorchidism). FMRP is also associated with the formation of connective tissue; medical difficulties associated with FXS therefore include occasional joint dislocations, recurrent otitis media, strabismus, mitral valve prolapse, and/or dilation at the base of the aorta and gastrointestinal reflux, which is seen in the majority of male infants with FXS (Hagerman & Hagerman, 2002). Co-morbid conditions are extremely common in FXS and affect language development and disorder. Most striking are the high rates of autism spectrum disorder identified in males with the full FXS mutation; approximately 30% to 50% of boys with FXS meet criteria for a diagnosis of autism spectrum disorder (Harris, 2008). This makes FXS the single largest known genetic cause of ASD, though only 2% to 6% of ASD cases can be attributed to FXS (Reddy, 2005). Although we’ve mentioned that level of FMRP expression is predictive of cognitive ability, it does not appear to be associated with severity of ASD symptoms (Loesch et al., 2007). It is clearly important to distinguish the cognitive and language characteristics of individuals with FXS who also have ASD from those who do not. Other co-morbidities include attention-deficit hyperactivity disorder (ADHD), which is reported to affect 44% to 93% of children with FXS meeting diagnostic criteria for ADHD (Sullivan et al., 2006); seizures, which affect approximately 20% of males; and high rates of anxiety, reported in a national parent survey to affect approximately 70% of males and 56% of females (Bailey et al,. 2008). ID is the predominant cognitive characteristic; nearly all males have a degree of ID that is similar to that seen in DS. Females tend to have less severe ID; approximately 25% have IQ scores less than 70, though about half have borderline IQ scores (Cornish, 2008). The rate of intellectual growth is reported to be about half that of typically developing children, the gap between individuals with FXS and their peer group increases with time, causing an age-dependent gradual decline in IQ (Hall et al., 2008). In addition to cognitive impairment, a core deficit in executive function has also been proposed, with significant deficits in sequential processing, working memory deficits, cognitive flexibility, planning, selective attention, inhibitory control problems, and fine and gross motor delay (Hooper et al., 2008). Of course, there are pockets of relative cognitive strength, which include simultaneous processing and long-term memory (see Finestack, Richmond, & Abbeduto, 2009, for review). Intriguingly, a longitudinal investigation of academic achievement in FXS found that nonverbal IQ and FMR protein expression were not associated with academic level or rate of change in academic performance; however, autistic behavior and level of maternal education were significantly related to academic achievement scores (Roberts et al., 2005). In general, the speech sound production of boys with FXS is commensurate with nonverbal mental age expectations. Barnes et al. (2008) reported that, regardless of ASD status, boys with FXS did not differ from their younger typically developing peers on phoneme accuracy or the number of developmental phonological processes, though they were less intelligible in connected speech. While speech articulation is a relative strength, phonological processing is less well developed in FXS, with many children scoring below the 10th percentile on measures of phonological awareness (Buckley & Johnson-Glenberg, 2008) and demonstrating significant impairments in phonological short-term memory (Baker et al., 2011). Compared to younger typically developing children matched for nonverbal ability, boys with FXS are delayed in both their understanding and production of grammar and morphosyntax (see Finestack et al., 2009 for review). Impairments are noted on both standardized measures and analyses of more spontaneous language samples. For example, boys with FXS have shorter MLUs relative to matched comparison groups even when nonverbal mental age and level of maternal education has been taken into account (Roberts et al., 2007). In addition, less complex noun and verb phrases are evident in conversational language, though production of questions/negation may be more in line with nonverbal skills. Where direct comparisons have been made, the expressive and receptive grammatical skills of boys with FXS are somewhat better than boys with DS, and are comparable in individuals with and without co-morbid ASD (Price et al., 2007, 2008). Investigations of receptive vocabulary knowledge in FXS have yielded mixed results, with some investigators reporting weaker vocabulary scores and others suggesting that vocabulary is commensurate with nonverbal mental age expectations (Finestack et al., 2009). A more consistent finding is that expressive vocabulary, as measured by number of different words used in connected discourse, is impaired and rates of vocabulary growth are slower than those seen for younger typically developing children (Roberts et al., 2002). In general, the presence of co-morbid ASD does not result in more severe vocabulary deficit (Kover & Abbeduto, 2010), though the small number of children with co-morbid diagnoses means we should be cautious in assuming this is always the case. Pragmatic competencies are perhaps most closely aligned with ASD status in boys with FXS. Qualitatively different language characteristics have been reported including increased use of tangential language, perseverative and repetitive speech, delayed echolalia, and use of stereotyped phrases (Cornish et al., 2004). These qualitative differences disrupt conversational exchanges; relative to developmental expectations, boys with FXS have difficulty maintaining coherent, semantically rich conversational exchanges (Roberts, Martin et al., 2007). For example, boys with FXS are more likely to provide conversational turns that are tangential or unrelated, and provide fewer turns in which they add or request new, on-topic information. These anomalies are particularly pronounced in those who also meet criteria for ASD, but are not limited to this subgroup (Roberts, Martin et al., 2007). This raises interesting questions about the source of these conversational errors; in ASD pragmatic errors are largely attributed to deficits in social-cognitive understanding. Children with FXS also show evidence of poor understanding of other people’s minds, as indexed by false belief tasks (Grant, Apperly, & Oliver, 2007). However, these deficits appear to be associated with deficits in working memory and executive control (inhibition) rather than social understanding per se. This suggests that conversational anomalies may also reflect problems with inhibition and working memory. Measures of referential communication also reveal pragmatic weaknesses in FXS. For instance, relative to ability-matched peers, boys with FXS are less able to provide consistent, unambiguous language to describe a target shape to listeners (Abbeduto et al., 2006) and are less likely to indicate that the verbal messages of others are inadequate to meet task demands (Abbeduto et al., 2008). In the latter case, signaling noncomprehension was positively correlated with vocabulary and receptive grammar, and associated with gender; girls with FXS were more likely to signal noncomprehension than male counterparts. Again, these findings appear to indicate a reduced appreciation of listener need and/or deficits in executive skill; within-syndrome comparisons of those with/without co-morbid ASD are needed in order to determine how widespread these pragmatic deficits are. Early differences in language acquisition may be attributable in part to disruptions in early visual experiences, for example triadic joint attention. As a result, toddlers with VI are delayed in their acquisition of first words and phrases (Lahey, 1988). Despite these early delays, previous research has consistently demonstrated that children with VI develop age appropriate vocabularies and MLUs by their third birthday (Andersen, Dunlea, & Kekelis, 1984; Landau & Gleitman, 1985). However, use of language may be disrupted; for example, children with VI and their conversational partners may have difficulty understanding each others’ referents (Landau, 1997). Other pragmatic impairments include the extensive, and sometimes inappropriate, use of questions; a paucity of communicative gestures; and extensive use of imitative speech, repetitions, and verbal routines (Norgate, Collis, & Lewis, 1998; Preisler, 1991). Tadic et al. (2010) compared children with VI to sighted peers on measures of “structural” language (as measured by the Clinical Evaluation of Language Fundamentals [CELF]) and parent report of pragmatic impairments. On the whole, the groups did not differ on structural language measures, with the children with VI outscoring their peers on the Recalling Sentences subtest, demonstrating good verbal memory. However, on the Childhood Communication Checklist—2 (CCC-2), children with VI received consistently poorer scores on the semantics scale, the social interaction scale, and all scales of pragmatic functioning (nonverbal communication, inappropriate initiation, coherence, stereotyped language, and use of context). Scores on the CCC-2 were significantly correlated with a checklist screening for ASD, but were not related to structural language scores. • Provide labels and descriptions of the objects the child handles and what he or she can do with these objects • Ask both open-ended and more directive questions • Provide more qualitative information not only about the child’s actions, but also other things going on in the environment • Model and encourage the child to engage in pretend play
Special consideration for special populations
Intellectual disability
Definition and classification
Cognitive characteristics
Language characteristics
Form
Content
Use
Literacy
DLD associated with disorders of known genetic origin
Down syndrome
Cognitive characteristics
Language characteristics
Form
Content
Use
Literacy
Implications for clinical practice
Williams syndrome
Definition and classification
Cognitive characteristics
Language characteristics
Form
Content
Use
Implications for clinical practice
Fragile X syndrome
Definition and classification
Cognitive characteristics
Language characteristics
Form
Content
Use
DLD associated with sensory impairments
Visual impairment
Related posts:
Stay updated, free articles. Join our Telegram channel
Full access? Get Clinical Tree
Neupsy Key
Fastest Neupsy Insight Engine
Meredith had been a placid baby. She sat up late, not until 9 months of age. She didn’t walk until she was 25 months old, and hardly talked at all before her third birthday. Her parents expressed some concern to their family doctor, who referred Meredith for an evaluation when she was 3½. Meredith’s cognitive skills were found to be even more delayed. Her parents were interviewed about her self-help skills, and they reported that she did not have independent feeding and wasn’t yet toilet trained. Her parents said Meredith acted more “like a 2-year-old” than a preschooler. After some observations of Meredith’s play and further discussion with her family, Meredith’s parents were told that she had global developmental delays and recommended that she be enrolled in a preschool program for children with special educational needs. Her parents were distressed to learn that her problems were serious, but relieved that their concerns were justified and that help was available.
