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Development from Preschool Through School Age 

Development from Preschool Through School Age
Chapter:
Development from Preschool Through School Age
Author(s):

Tony Charman

DOI:
10.1093/med/9780195371826.003.0015
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Points of Interest

  • Do we know if diagnosis from age 2 is reliable and stable?

  • What features are associated with better social and communication outcomes?

  • When do associated features such as mental health problems begin to emerge?

Over the past decade there has been remarkable progress in our understanding of the early development of children with autism spectrum disorders. Until the 1990s it was rare for children to receive a diagnosis of autism until the age of 3 or 4 years. Therefore, much of the historical literature in both the clinical and research fields starts with descriptions of children with autism at age 4 to 5 years or older. Several factors have driven this change, including efforts to improve earlier identification with the recognition that earlier-delivered intervention may improve outcomes and prevent “secondary” neurodevelopmental disturbances (Dawson, 2008; Mundy, 2003), the development of prospective screening instruments to indentify possible cases of autism from the first few years of life (Charman & Baron-Cohen, 2006; Zwaigenbaum & Stone, 2006), and the use of the genetic high-risk research design of prospectively studying younger siblings of children with a diagnosis of autism from the first year of life (Yirmiya & Ozonoff, 2007). This decade of work has uncovered important evidence regarding the developmental trajectory of autism spectrum disorder from toddlerhood, through the preschool years into school age and beyond. An even more recent development has been the application of modern neuroimaging and neuroscientific experimental approaches to infants, toddlers, and young preschool children with autism spectrum disorders (Courchesne et al., 2007). While many of the insights gained from these clinical and experimental studies have proved clinically useful—in particular with respect to questions about when autism can be diagnosed reliably and how stable the diagnosis is over the course of the preschool years as well as the ability to predict (at least at a group level) outcomes many years later—they have also raised considerable challenges. Among the most notable challenges are the substantial variability in early development trajectory in children with autism and our difficulty in disentangling the extent to which these variable trajectories for individual children are due to intrinsic versus extrinsic factors. This chapter will summarize the state of our current knowledge of these issues and identify challenges for future research and clinical studies.

Diagnosis and Developmental Trajectory Through the Preschool Years

There is a degree of irony that while both psychiatric classification systems are clear that, at least to meet criteria for the core disorder of childhood autism (ICD-10; World Health Organization, 1993) or autistic disorder (DSM-IV-TR; American Psychiatric Association, 2000), symptoms of autism are usually present in the first 3 years of life as evidenced by abnormalities in social interaction, language as used in social communication, and early play skills, until the 1990s few studies had been conducted with samples under the age of 3 years. This is not to challenge the notion that in many if not most cases of autism spectrum disorder, excepting perhaps those with very high IQ or those who meet criteria for Asperger’s syndrome, there is some developmental anomaly within the first 3 years. Some recent evidence suggests that, at least in the case of childhood autism, early developmental perturbation that in some but not all cases meets recognized criteria for regression might occur for the majority as opposed to the minority of cases (Landa et al., 2007; Pickles et al., 2009). It may well be that parents do not always notice or pick up on more subtle changes in their children’s social and communicative development from infancy to toddlerhood unless there is frank regression, most typically evidenced in a loss of expressive language skills. Rather, it is to point out that apart from rare exceptions (Gillberg et al., 1990) until the mid-1990s the majority of information about development from toddlerhood through the preschool years came from retrospectively reported information from parents. The growth in our knowledge base regarding the presentation of autism in the preschool years over the past decade is demonstrated by a simple experiment. In August 2008 entering the search terms “autism” and “toddlers” into PudMed identified 88 articles. Seventy-seven of these were published after 2000, 57 of which were dated from 2005.

One of the most significant challenges and concerns of this new era of prospectively studying children with autism spectrum disorders from the age of 2 and 3 years concerned diagnosis. Given the relative lack of experience of applying the diagnostic criteria to children of this age, even among the relatively expert clinical teams conducting such studies, one critical question quickly arose: Was the diagnosis accurate and stable when applied at this age? Fortunately, many research teams were studying cohorts of toddlers by the mid-1990s, and evidence regarding the issues of diagnostic accuracy and stability began to emerge as the cohorts were followed into preschool and in the mid-2000s into the school-age years. What emerged from these programs of work were some clear messages (autism can be accurately diagnosed in 2-year-olds) but also some areas of uncertainty that will take continued study to resolve (in some cases diagnosis appears less stable). This research will be reviewed next.

Table 13-1 summarizes the diagnostic outcome studies that have followed cohorts of children from initial diagnostic assessments around the age of 2 years into the preschool years and, in several of the more recent studies (Charman et al., 2005; Lord et al., 2006; Turner et al., 2006), into the school-age years. The first series of studies (Cox et al., 1999; Lord, 1995; Moore & Goodson, 2003; Stone et al., 1999) all showed high stability of diagnosis in particular for “core” autism, with somewhat lower stability for broader autism spectrum disorder (ASD) and Pervasive Developmental Disorder Not-Otherwise-Specified (PDD-NOS). The movement across the ASD/PDD-NOS diagnostic category boundary was somewhat different in the different studies, with Stone et al. (1999) finding that 4 out of 12 children who met broader ASD criteria at the initial assessment did not meet criteria for an autism spectrum disorder at follow-up, whereas Cox et al. (1999) found that 7 from 31 children who did not receive an autism spectrum diagnosis at the initial assessment met criteria for broader ASD at follow-up. Several of the studies (Cox et al., 1999; Lord, 1995; Stone et al., 1999) concluded that, for 2-year-olds, expert clinical judgment is more reliable than the standard diagnostic instruments—the Autism Diagnostic Interview-Revised (ADI-R; Lord et al., 1994) and the Autism Diagnostic Observation Schedule-Generic (ADOS-G; Lord et al., 2000). Several studies also found that behaviors from the third symptom cluster that defines autism—restricted and repetitive behaviors and activities—were less evident at 2 years of age than at 3 to 5 years of age (Cox et al., 1999; Moore & Goodson, 2003; Stone et al., 1999). The samples in these early studies differ in a number of characteristics, including how and for what purposes they were ascertained (for example, prospectively using the CHAT screening instrument in the Cox et al. study vs. following clinical referral for possible autism in the Lord, Moore and Goodson, and Stone et al. studies), IQ, language ability, and the different use and implementation both of standard diagnostic instruments but also of DSM-IV and ICD-10 diagnostic criteria, and these differences might account for the differences found.

Table 13–1. Studies of diagnostic stability from preschool into the school-age years

Reference

Age Time 1

Age Time 2

Diagnoses at Time 1

Findings

Lord (1995)

31 months

50 months

16 CA, 14 NS

Diagnosis largely stable; Clinical judgment more reliable than ADI-R

Stone et al. (1999)

31 months

45 months

25 CA, 12 ASD, 8 NS

CA diagnosis largely stable; ASD less so (4 out of 12 moved to NS at Time 2); Fewer repetitive symptoms at Time 1

Cox et al. (1999)

21 months

45 months

9 CA, 3 ASD, 31 NS

CA diagnosis largely stable; NS less so (7 out of 31 moved to ASD at Time 2); Fewer repetitive symptoms at Time 1; Clinical judgment more reliable than ADI-R

Moore & Goodwin (2003)

34 months

53 months

16 CA, 3 ASD, 1 NS

Diagnosis stable (slight movement between CA and ASD only)

Charman et al. (2005)

25 months

85 months

26 CA

Diagnosis largely stable (3 moved to ASD and 1 to NS at Time 2)

Turner et al. (2006)

31 months

109 months

18 CA, 7 ASD

Diagnosis largely stable (2 CA moved to NS and 1 ASD moved to NS at Time 2)

Lord et al. (2006)

29 months

112 months

84 CA, 46 ASD, 42 NS

Diagnosis of CA largely stable (12 from 84 moved to ASD and 1 to NS at Time 2); ASD less so (27 of 46 moved to CA and 5 to NS at Time 2); NS less so (2 from 42 moved to CA and 9 to ASD at Time 2)

Chawarska et al. (2007)

22 months

36 months

19 CA, 9 ASD

Diagnosis of ASD stable (2 of 19 CA cases moved to ASD at Time 2); Clinical judgment more reliable than ADI-R and ADOS-G

Turner & Stone (2007)

29 months

53 months

38 CA, 10 ASD

Diagnosis stability moderate only (6 of 38 CA cases moved to ASD and 13 moved to NS at Time 2; 6 of 10 cases of ASD moved to NS at Time 2)

Kleinman et al. (2008)

27 months

53 months

46 CA, 15 ASD, 16 NS

Diagnosis stability moderate only (15 of 61 ASD cases moved to NS at Time 2)

CA = ICD-10 childhood autism/DSM-IV autistic disorder; ASD = PDD-NOS, atypical autism; NS = nonspectrum.

The more recent studies differ from the earlier ones in a number of features, most notably considerably larger sample sizes (N = 172, Lord et al., 2006; N = 77, Kleinman et al., 2008) and follow-up periods that extend to age 7 years in the Charman et al. (2005) study and age 9 years in the Lord et al. (2006) and Turner et al. (2006) studies. Broadly, the lessons learned are the same—that the diagnosis of autism is highly stable in these samples but that of broader ASD is less so. Lord et al. (2006) found that age 2 scores on measures of repetitive and restricted behaviors and activities predicted an autism diagnosis at age 9 years. In some of these more recent studies there was greater movement from having an ASD diagnosis at age 2 years to a nonspectrum diagnosis at age 4 (Kleinman et al., 2008; Turner & Stone, 2007). While the authors report the factors associated with these “good outcomes”—mainly higher IQ and better language competency—it is important to remain cautious regarding predictors of poorer or better outcomes. However, the general pattern is of high stability of diagnosis for autism, replicating the earlier pioneering longitudinal work of Sigman and colleagues, who found high stability of diagnosis of children from 4 years of age through to mid-childhood (13 years) and young adulthood (19 years) (McGovern & Sigman, 2005; Sigman & Ruskin, 1999).

For clinicians the lesson is to accept that autism is a developmental disorder and at a very young age there may be less certainty regarding the pattern of behavior that a child is showing and the likelihood of their continuing to meet diagnostic criteria into the future. Charman and Baird (2002) discuss the importance of understanding the diagnostic process as an iterative process to be worked out between clinician teams and parents over time and that concepts such as a “working diagnosis” can be helpful. However, at the same time, clinical teams need to be aware of the need to provide sufficient certainty regarding the child’s condition that they are not refused appropriate services following assessment. One other important clinical reminder is that while the trajectory of early emerging impairments in social and communication development accompanied by rigid and repetitive behaviors and interests characterizes many children on the autism spectrum, there is a subgroup of particularly verbal and able children who go onto to receive a diagnosis of autism (sometimes called “high functioning autism”) or Asperger’s syndrome who may not receive a diagnosis in the preschool years. There is also another group who might meet diagnostic criteria for an autism spectrum disorder who do not receive an explicit diagnosis—those individuals with moderate to severe intellectual disability or those with an already identified preexisting associated medical condition, such as Fragile X or Down syndrome. In a recent epidemiological study Baird et al. (2006) found that, for cases meeting research diagnostic criteria for an autism spectrum disorder following in-depth assessment, low IQ predicted those who had not received a clinical diagnosis by local clinical services by age 10 years. One final caveat is that the studies summarized in Table 13-1 largely come from expert research clinical centers specifically studying young cohorts of children. In community settings in many countries there is evidence including from recent studies that for many children and their families a diagnosis is not confirmed until children are well into the school-age years (Howlin & Asgharian, 1999; Wiggins et al., 2006).

One final feature that emerges from these longitudinal studies is that, aside from the issue of diagnostic or categorical stability, the developmental trajectory of symptoms measured using a continuous or dimensional (as opposed to a categorical) metric changes over time (see also Honey et al., 2008). For example, Charman et al. (2005) described how the trajectories of the social, communication, and repetitive domain scores on the ADI-R had different developmental trajectories over time, consistent with the notion that the various aspects that make up the autism phenotype might not be tied together as closely as suggested by the current classification systems. This notion has also received support from a twin study demonstrating that, while each component of the autism phenotype is highly heritable, there is only very modest commonality in the heritability of the three components (Ronald et al., 2006). The recognition that autism is a complex neurodevelopmental condition and that the presentation changes (in different ways in different individuals) over time presents considerable challenges to genetic and neuroscientific investigations (Happé et al., 2006). Longitudinal studies tracing the behavioral autism phenotype will therefore be important not only for informing clinicians regarding diagnostic practice but also for answering basic science questions regarding influences on the etiology and course of the disorder.

Language and Communication Development from Toddlerhood to the School-Age Years

Delayed language milestones are common in many preschool children with autism spectrum disorders, and the diagnostic criteria include both a delay in the emergence of language and the atypical use of nonverbal social-communication abilities including joint attention behaviors, social imitation, and pretend play abilities. However, while it is not uncommon for 2- and 3-year-olds with core autism (as opposed to those with Asperger’s syndrome) to be nonverbal, language and nonverbal communication abilities typically do begin to develop throughout the preschool period as children enter kindergarten and school (Charman, Drew, et al., 2003; Luyster et al., 2007). Previously, the prognosis in terms of the proportion of children with autism who go on to develop functional language was considered poor, with papers from the 1970s and 1980s suggesting that perhaps only 50% of children develop functional speech (DeMyer et al., 1973; Freeman et al., 1985)—a reflection of the severely autistic and intellectually delayed cohorts who were first studied longitudinally. However, more recently it has become clear that language onset and outcomes are very variable, but generally more positive, for children with the spectrum of autism disorders. For example, in the large clinical cohort recently described by Hus and colleagues (N = 983; mean age 8 years, SD 5 years, range 4 to 52 years; Hus et al., 2007) only 9.8% had no single words (using the ADI-R criteria of 5 or more words used on a daily basis excluding “mama,” “papa,” etc.), 41.0% had delay in single word onset (> 24 months) but had single words when assessed, and half were not delayed in single word onset (49.2%; data from Hus et al., 2007, Table 5, p. 443). For phrase speech, the comparable figures were 24.0% of individuals with no phrase speech when assessed, 51.3% with delayed phrase speech onset (>33 months) but with phrased speech when assessed, and one quarter were not delayed in phrase speech (24.7%; data from Hus et al., 2007, Table 5, p. 443). A longitudinal study with a subgroup (N = 206) of the same cohort measured language ability at age 2, 3, 5, and 9 years (Anderson et al., 2007). This allowed sophisticated statistical modeling using growth curves to plot the trajectory of language development through the preschool years into school age. At a group level, the trajectory of growth in language abilities was slower for the children with a diagnosis of autism than for the children with PDD-NOS or a nonspectrum developmental disorder. However, within each diagnostic group language growth and outcomes were very variable—and this variability increased over time—with some children in each group making such good progress that their language abilities were at the expected level at age 9 years, whereas other children in each group, in particular a subset of the children with “core” autism, made very little progress at all (see Figure 13-1). Age 2 symptom severity, nonverbal cognitive abilities, and joint attention skills were significant predictors of language outcomes at age 9 years. Anderson et al. (2007) conclude that their study “offers messages of both hope and realism” (p. 602) regarding the language outcomes of children receiving an early diagnosis of autism spectrum disorder.

Figure 13–1. Language growth curves from 2 to 9 years. Copyright © 2007 by the American Psychological Association. Reproduced with permission from Anderson, D. K., Lord, C., Risi, S., Shulman, C., Welch, K., DiLavore, P. S., et al. (2007). Patterns of growth in verbal abilities among children with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 75, 594–604.

Figure 13–1.
Language growth curves from 2 to 9 years. Copyright © 2007 by the American Psychological Association. Reproduced with permission from Anderson, D. K., Lord, C., Risi, S., Shulman, C., Welch, K., DiLavore, P. S., et al. (2007). Patterns of growth in verbal abilities among children with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 75, 594–604.

There is also increasing recognition that while expressive language competencies might be the most evident delay for some preschool children with autism spectrum disorders, receptive abilities can be relatively more delayed (Charman, Drew, et al., 2003; Hudry et al., 2008; Luyster et al., 2007). This is clinically important but requires sensitive handling to explain that what parents sometimes take as “understanding” is often understanding of familiar routines and contextual cues rather than language comprehension per se. However, this finding is important as it is related to the appropriate focus of development, psycholinguistic approaches to communication intervention for preschool children with autism (see below).

Over the past 20 years there has been increasing interest in delineating the emergence of language competencies in children with autism spectrum disorder from toddlerhood through the preschool years. In part, this is to aid the clinical ability to determine likely prognosis—clinicians will recognize how parents understandably desire to be told if their child will talk and when. However, it has also helped develop our theoretical understanding of how (albeit sometimes delayed) language develops in autism. This is important both to understand if the mechanisms underpinning (delayed) language development are the same as or different from those in typically developing infants—about which a great deal is known (Bloom, 2000)—and to inform communication-based approaches to early intervention (see below).

Many studies over the past 20 years have demonstrated the perhaps unsurprising fact that over time individual variability is relatively stable in cohorts of preschoolers with autism— that is, early language competence predicts later language competence—including in some studies that followed children into the school-age period (e.g. Charman et al., 2005; Lord & Schopler, 1989; Mundy et al., 1990; Sigman & Ruskin, 1999; Venter et al., 1992). However, theoretically more interesting has been the question of whether earlier-emerging social communication abilities predict later language development. A strong psycholinguistic tradition from the study of normative language development has shown that this is the case for typically developing infants and toddlers (Bates et al., 1989; Carpenter et al., 1998; Morales et al., 2000; Mundy & Gomes, 1998). Given that many preschoolers with autism spectrum disorders are impaired in their development of language ability and of early social communication abilities, the question of whether such associations also hold for toddlers and preschoolers with autism is both of clinical but also of theoretical interest. Demonstrating that the same association holds between early social communication abilities and later language development might suggest that similar developmental mechanisms are operating—albeit at a slower rate than in the typical case. Mundy et al. (1990) were the first to provide evidence to support this position, finding that joint attention behaviors (alternating gaze, pointing, showing, and gaze following) measured at 45 months were associated with language outcomes 13 months later. Sigman and Ruskin (1999) extended this finding by demonstrating associations from the preschool years to later language ability at 12 years of age. Stone and colleagues have also demonstrated longitudinal associations between various aspects of imitation and play as well as joint attention abilities at 2 years of age and language abilities measured at 4 years of age. This pattern has now been replicated in several other studies (e.g. Toth et al., 2006), including one that followed children with autism spectrum disorders from toddlerhood (20 months) into the preschool years (42 months; Charman, Baron-Cohen, et al., 2003).

These findings are both of theoretical and practical importance. Theoretically they suggest that since some of the associations seen in preschoolers with autism spectrum disorders are similar to that seen in typical development it might be the case that the mechanisms that operate are similar too. This is relevant to informing approaches to communication-based approaches to intervention. Although individual stability of skills (language to language) or of one “precursor” skill to another later emerging skill (joint attention to language; Charman et al., 2000) may tell us something about intrinsic characteristics of the child, they may also suggest routes to intervention. Evidence consistent with this proposition was provided by Siller and Sigman (2002), who demonstrated that individual differences in maternal synchronicity (sometimes called “sensitivity”) measured in joint play interactions was associated with later language outcomes even over many years. The circle is squared, so to speak, by several recent randomized controlled intervention trials. These have used a variety of social-communication strategies, including the promotion of joint attention, imitation, and joint social engagement skills both directly delivered by therapists (Kasari et al., 2006, 2008; Yoder & Stone, 2006) and delivered by training parents in these methods (Aldred et al., 2004; Drew et al., 2002), and found that language outcomes (and in the case of the Aldred et al. study social outcomes) can be improved. For developmentalists, this convergence of evidence that for preschool children with autism spectrum disorders there are both naturalistic associations over time between early social communication skills and later language outcomes and that these can be altered by targeted intervention in controlled studies is as close to evidence for a development mechanism as it is possible to get (Bradley & Bryant, 1983).

Social Development and Adaptive Behavior Development into the School-Age Years

While the development of language and communication abilities has understandably been the focus of much research interest in delineating the developmental trajectory of children with autism spectrum disorders from preschool to the school-age years, it is also of considerable importance to measure and understand the influences on social development. This reflects not only the central place that social development—both the characteristic social impairments that are the primary feature of the diagnostic criteria but also the continuing emergence of positive social interests and competencies—has in our understanding of autism but also the changing social environment that children encounter as they emerge from the preschool period. When children enter kindergarten or preschool and then school their social milieu and the challenges they face in terms of forming friendships and social relationships changes considerably. Several studies have looked at the trajectory of social development in autism—both in terms of symptom measures but also in terms of everyday socially adaptive behavior, as measured by instrument such as the Vineland Adaptive Behavior Scales (VABS; Sparrow et al., 1984, 2006).

Initial studies used retrospective designs to document the changes in autism symptoms, including social behaviors, comparing current to past symptoms by parent report on the ADI-R. Piven et al. (1996) studied 38 adolescents and adults and found reductions on all 3 symptom domains compared to retrospective report at age 4 to 5 years. Fecteau et al. (2003) compared parent current report of symptoms at a mean age of 13 years with retrospective report at age 4 to 5 years in a sample of 28 children and adolescents and found significant reduction in symptoms on each of the 3 ADI-R domain scores, with most improvement shown in social symptoms. Interestingly, both studies reported fewest improvements in the repetitive behaviors and restricted interests domains. Piven et al. (1996) caution against the reliability of retrospective parental report that can be subject to biases in both directions (remembering things as “much worse” than they were in the light more recent improved behaviors and skills; and underreporting current symptoms as they are an improvement on the past) and also that the particular items included in the ADI-R algorithm that was developed to capture a lifetime diagnosis with age 4 to 5 years being considered the prototypical age at which autism symptoms are fully emerged and the presence at any point in a child’s past (ADI-R “ever” ratings) might underestimate current social and communication difficulties in school-age children, adolescents, and adults.

A prospective longitudinal study by Szatmari and colleagues (Starr et al., 2003; Szatmari et al., 2003) has followed a group of high-IQ children and adolescents with autism (N = 41) and Asperger’s syndrome (N = 17) from their initial diagnostic assessment at age 4 to 6 years over two years to age 6 to 8 years (Starr et al., 2003) and then to young adolescence (10 to 13 years; Szatmari et al., 2003). They found somewhat different patterns for the diagnostic groups with slight increases in social and communication symptoms on the ADI-R for the Asperger’s group but reductions in social symptoms, but not communication symptoms, for the “high functioning” autism group (Starr et al., 2003). For neither group did scores on the repetitive and rigid behaviors change over time. The Szatmari et al. (2003) report focused on predictors of later outcomes and found that early language and nonverbal abilities were the strongest predictors but also reported lower adaptive behavior on the VABS in adolescence compared to childhood. As summarized above, in their diagnostic outcome study Charman et al. (2005) also reported ADI-R symptom domain scores and found that from 2 to 7 years of age social and communication symptoms diminished (while those in the repetitive behavior domain initially increased and then decreased. One striking finding from this study was the increasing variability of the level of social symptoms over time and also among the general trends to diminished social impairment different children made progress across different timepoints as measured at age 2, 3, 4, to 5 (this timepoint only was retrospective) and 7 years. What this study does not answer is the underlying explanation for why some children, for example, make considerable progress between age 3 and age 4–5 years, while for others the most gains are made between 5 and 7 years. This pattern of individual variability is illustrated in Figure 13-2. While longitudinal studies are valuable, only randomized trials have the power to indicate likely causative effects of extrinsic factors, and only larger cohort studies (such as the Anderson et al. (2007) language study described above) the power to model different subgroup trajectories. Moss et al. (2008) reported ADI-R scores in a cohort of 35 children assessed at age 4 years and again at age 11 years and found that social and nonverbal communication domain scores were significantly reduced over time but repetitive behavior domain scores did not change. Lord et al. (2006) also presented ADI-R and ADOS scores at age 2 and age 9 years but found a somewhat different pattern. On the ADI-R, scores increased in each of the 3 domains (Lord et al., 2006, Table 2). On the ADOS-G the pattern was somewhat different, with a reduction in social domain scores and repetitive behavior domain scores for both children with an age-2 diagnosis of autism and PDD-NOS but little change in communication domain scores. Comparing findings across these different studies is not possible due to differences in the child characteristics, measures used and timepoints of the assessments, as well as extrinsic factors (such as interventions; likely differing etiologies) that were not controlled and often not measured. However, in line with our current conception of autism spectrum disorders as developmental disorders there is change in social symptoms as children enter the school-age years, and at a group level the most consistent finding is that social symptoms diminish. However, what is notable in line with the data presented on language above is that variability increases over time. At a clinical level this can be frustrating for clinicians and for parents alike—what parents want to know is what the future holds for their own child. From the clinician’s perspective extrapolating from group data to an individual child is not possible. This high-lights the need for continuing longitudinal and controlled intervention trials in order to better inform prognosis and also to identify those individuals most in need of the most intensive interventions.

Figure 13–2. ADI-R Reciprocal Social Interaction Domain scores from Charman, T., Taylor, E., Drew, A., Cockerill, H., Brown, J. A., & Baird, G. (2005). Outcome at 7 years of children diagnosed with autism at age 2: Predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. Journal of Child Psychology and Psychiatry, 46, 500–513.

Figure 13–2.
ADI-R Reciprocal Social Interaction Domain scores from Charman, T., Taylor, E., Drew, A., Cockerill, H., Brown, J. A., & Baird, G. (2005). Outcome at 7 years of children diagnosed with autism at age 2: Predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. Journal of Child Psychology and Psychiatry, 46, 500–513.

The above studies examined the trajectories of social impairments as measured by the diagnostic instruments the ADI-R and ADOS, but there are other facets of social development that are not always well captured by such instruments, in particular everyday social, communication, and daily living adaptive skills. Several studies have shown that early social communication behaviors such as joint attention, imitation, and play are predictive of later language and social outcomes (Charman et al., 2003; Toth et al., 2006). Recent, more experimental studies have indicated that individual differences in key brain regions such as the amygdala are also associated with behavioral outcomes, reflecting the fact that autism is a neurobiobehavioral disorder (Munson et al., 2006; Mosconi et al., 2009).

Several cross-sectional studies have used the VABS (Sparrow et al., 1984) with samples of school-age children with an autism spectrum disorder. At least 2 findings have a high degree of consistency across samples. The first is that overall adaptive outcome is significantly lower than IQ, and the second is that, perhaps unsurprisingly, socialization skills are most delayed in comparison to communication and especially daily living skills (Carpentieri & Morgan, 1996; Freeman et al., 1999; Klin et al., 2007; Liss et al., 2001; Saulnier & Klin, 2007; although see Klin et al, 2007, Figure 1, for a example in the Michigan sample where daily livings skills are as depressed compared to IQ as socialization skills).

These findings are clinically important for several reasons. First, even for individuals who perform at or above age expectations within the adult-directed and relatively contained and predictable psychometric test situation their everyday “street smarts” (Klin et al., 2007) coping behavior can be significantly impaired. Indeed, the discrepancy between IQ scores and adaptive functioning is often most notable in individuals with high IQs, and Klin and colleagues found that socialization and daily living skills standard scores were 2 to 3 standard deviations below Full Scale IQ scores in 2 independent samples. This study also found that adaptive skills (in terms of standard scores) decreased with age, suggesting that the “lag” between measured intelligence and everyday coping widened between the early school years and late adolescence (see Szatmari et al, 2003; summarized above). Note however, that other studies have found no association between age and adaptive ability (e.g. Schatz & Hamden-Allen, 1995), and one study even found a positive association (Freeman et al., 1999). Further longitudinal studies are required to understand which developmental pattern is most representative. Both Klin et al. and Szatmari et al. found only marginal associations between autistic social and communication impairments and adaptive skills, suggesting that everyday adaptive behavior needs to be the target of intervention studies, alongside social understanding and skills and language and communication skills.

Alongside the discrepancy between a child’s intellectual ability and his/her adaptive functioning, many children with autism spectrum disorders, including those with average or above average IQ, have significant difficulties with self-help and self-organization. This is related to their problems with the components of executive function, including set-shifting, generating ideas, and planning (Russo et al., 2007). Instruments such as the Behavioural Assessment of Dysexecutive Syndrome for Children (BADS-C; Emslie et al., 2003) can be helpful when used in conjunction with a structured parents and teacher rating scale, (e.g. the Adaptive Behaviour Assessment System-Second Edition [ABAS-II; Harrison & Oakland, 2003] or the Vineland Adaptive Behaviour Scale-II [Sparrow et al., 2006]) for determining whether executive functioning difficulties are affecting daily functioning (Bolte & Poustka, 2002). Gilotty et al. (2002) found negative associations between executive dysfunctions, including the ability to initiate behaviors and working memory, as measured by the Behavior Rating Inventory of Executive Function (BRIEF; Gioia et al., 2000) and adaptive skills as measured by the VABS. One clinical lesson from these findings is that in particular as the social and organizational challenges of the school environment increase as children enter high school and teaching moves from a one-teacher, one-classroom environment to a many-teachers, many-classrooms environment, children with autism may need support to manage this more challenging environment (see Ozonoff, 1998; for examples of everyday strategies to overcome executive difficulties). Executive difficulties also impact on a child’s ability to learn in the classroom environment, and a detailed psychometric assessment can identify specific executive difficulties that can inform approaches to remediation (see Box 13-1).

A number of recently developed standardized instruments exist that test a range of cognitive abilities that make up the executive system (Delis-Kaplan Executive Function System [D–KEFS]; Delis et al., 2001; NEPSY; Korkman et al., 1997). Alongside routine psychometric assessment of IQ and language and communication skills, psychometric assessment of executive abilities, as well as attention and memory abilities (e.g. Working Memory Test Battery for Children (WMTB-C; Pickering & Gathercole, 2001); Test of Everyday Attention in Children (TEA-Ch; Manly et al., 1998)) can be helpful in identifying why a seemingly bright child is struggling either with learning or with managing the complex school environment. Based on a detailed psychometric assessment of executive, memory and attention difficulties bespoke approaches to intervention to bootstrap executive or memory difficulties can then be implemented to help a child fulfill their learning potential within the school environment and at home.

The Emergence of Comorbid Psychiatric Disorders in the School Age-Years

It is common for preschool children with an autism spectrum disorder to manifest behavior problems, and advice on management should form part of the postdiagnostic support provided by clinical services (Herring et al., 2006). However, several recent studies using questionnaire measures have reported high rates of psychiatric problems in school-age children and adolescents with autism spectrum disorders (Steinhausen & Metzke, 2004; Sukhodolsky et al., 2008). Two recent studies have used structured parental interviews that assess psychiatric disorder “caseness” and also found high rates. Leyfer et al. (2006) described rates of lifetime psychiatric disorder in 5- to 17-year-old children with autism, using a new interview, the Autism Comorbidity Interview-Parent and Lifetime Version (ACI-PL), modified from the KSADS (Chambers et al., 1985). Just less than three quarters met criteria for one or more DSM-IV disorders, with the most commonly reported disorders being specific phobia (44%), obsessive compulsive disorder (36%), and ADHD (30%). Studying a population-derived sample of 10- to 14-year-olds with autism or a broader autism spectrum disorder, Simonoff et al. (2008) found that 70% of participants had at least one comorbid disorder and 41% had 2 or more. The most common diagnoses were social anxiety disorder (29%), attention-deficit/hyperactivity disorder (28%) and oppositional-defiant disorder (28%). Simonoff and colleagues systematically examined whether the presence of psychiatric disorders was systematically associated with child (e.g., low IQ), parental (e.g., parent mental health difficulties), or contextual (e.g., deprivation) factors, but found few associations. Simonoff et al. (2008) suggest that the presence of an autism spectrum disorder “trumps” other risk factors that are commonly associated with childhood psychiatric disorders. They conclude that “Psychiatric disorders are common and frequently multiple in children with autism spectrum disorders. They may provide targets for intervention and should be routinely evaluated in the clinical assessment of this group” (Simonoff et al., 2008, p. 921). There are issues regarding the extent to which these disorders should be considered truly “comorbid”—an independently occurring disorder unrelated to the primary symptoms of autism itself—or whether psychiatric symptom scales are endorsed by parents on the basis of autistic symptoms (see also Pine et al., 2008). While further research including direct assessments of mental state in school-age children is warranted to help determine the answer to this conundrum, the challenges of interviewing children with low IQ and the veracity and representativeness of self-report in children (and indeed adults) with autism spectrum disorders are considerable. It might be that in the future advances in genetics or neuroimaging experimental methods will help disentangle these issues, although for now clinicians, educators, and parents need to be aware that cognitive and behavioral manifestations that resemble those seen in children and adolescents without autism but with psychiatric disorders are common in autism spectrum disorders.

Conclusions

It is now widely recognized that there is very large heterogeneity in the children for whom a clinical diagnosis of “autism spectrum disorder” is clinically appropriate and that etiology will differ from case to case, moving some researchers from the biological fields of science to coin the term “the autisms” (Geschwind & Levitt, 2007). However, autism remains quintessentially a developmental disorder and heterogeneity in many, if not most, domains of functioning increases with age. Thus, predicting outcomes into the school years for children seen as toddlers and preschoolers can be very difficult. Determining the influence of intrinsic and extrinsic factors—and the interplay between the two (see Dawson, 2008)—remains a significant challenge but one in which the pace of research is at last beginning to catch up with the questions that parents understandably ask of clinicians (“How will my child do in school?”; “Will they go to college and be able to live independently?”) (see Howlin et al., 2009; Rogers & Visnara, 2008; for reviews). The evidence base for interventions for preschool and school-age children has, until recent years, been woefully inadequate (see chapters by Green; Kasari; Rogers; Schreibman and Smith; for reviews). However, there are an increasing number of published studies including randomized controlled trials that provide evidence for the benefit of interventions, including those that focus on areas of core deficit such as communication (Aldred et al., 2004; Howlin et al., 2007; Kasari et al., 2008; Yoder & Stone, 2006).

The findings of the longitudinal studies summarized earlier and those of intervention trials offer both hope but also caution. Hope because some children with autism make significant progress as they enter the school-age years. Caution because in all cohort and intervention studies some children make little progress and because development can bring with it new challenges and problems such as mental health difficulties. Over the past decade there has understandably been a great focus on toddlers and preschoolers with autism spectrum disorders, with great advances in knowledge and clinical practice about early risk signs and early detection and diagnosis. The challenges faced by school-age children with autism spectrum disorders differ from those of the toddler, whose parents or caregivers structure much of their everyday world. An increasing emphasis on social group activities, self-organized behavior, and formal learning as children enter school can be a very challenging change for many children with autism spectrum disorders and much work remains to be done for us to understand how to help children with autism, their families, and educators to meet these challenges.

Challenges and Future Directions

  • We need to integrate information on behavioral developmental trajectories with emerging developmental neurobiological accounts.

  • The developmental trajectory of individual children differs significantly, and we do not know how much individual trajectories are influenced by intrinsic versus extrinsic factors.

  • Better-controlled studies on the effects of intervention and schooling are needed.

Suggested Readings

Anderson, D. K., Lord, C., Risi, S., Shulman, C., Welch, K., DiLavore, P. S., et al. (2007). Patterns of growth in verbal abilities among children with autism spectrum disorder. Journal of Consulting and Clinical Psychology, 75, 594–604.

Charman, T., Taylor, E., Drew, A., Cockerill, H., Brown, J. A., & Baird, G. (2005). Outcome at 7 years of children diagnosed with autism at age 2: Predictive validity of assessments conducted at 2 and 3 years of age and pattern of symptom change over time. Journal of Child Psychology and Psychiatry, 46, 500–513.

Charman, T., & Baird, G. (2002). Practitioner review: Diagnosis of autism spectrum disorder in 2-and 3-year-old children. Journal of Child Psychology and Psychiatry and Allied Disciplines, 43, 289–305.

Lord, C., Risi, S., DiLavore, P. S., Shulman, C., Thurm, A., & Pickles, A. (2006). Autism from 2 to 9 years of age. Archives of General Psychiatry, 63, 694–701.

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