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Diagnosis of Autism Spectrum Disorders 

Diagnosis of Autism Spectrum Disorders
Diagnosis of Autism Spectrum Disorders

Katherine Gotham

, Somer L. Bishop

, and Catherine Lord

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Points of Interest

  • History of autism and ASD classification.

  • Current criteria for and presentation of pervasive developmental disorders.

  • Potential revisions to ASD criteria and classification framework.

  • Participant characteristics that affect diagnosis.

  • Instruments and methods for assessing ASD.

  • Diagnostic issues often overlooked in research.


Since its original description by Leo Kanner in 1943, autism has come to be recognized as a neurodevelopmental disorder that manifests in infancy or early childhood and encompasses both delays and deviance in a “triad” of behavioral domains (Wing & Gould, 1979): reciprocal social interaction, communication, and restricted and repetitive behaviors and interests. Autism is thought to be the cornerstone of a spectrum of disorders, commonly referred to as autism spectrum disorders (ASD) or pervasive developmental disorders (PDD). This spectrum includes Asperger’s syndrome (AS), and Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS, or atypical autism), as well as two very rare disorders, Rett’s disorder and Childhood Disintegrative Disorder (CDD).

Studies of monozygotic twin concordance for autism, and of families in which parents have multiple affected children, have established that risk for ASD is influenced by genetic factors (Morrow et al., 2008; Constantino & Todd, 2008). A “broader phenotype” of social impairments in family members of individuals with ASD continues to generate interest as a potential window into the genetic transmission of these disorders (Dawson et al., 2007). Though associations have been shown between increased rates of ASD and genetic, chromosomal, and/or brain abnormalities, no biological marker adequately accounts for a significant minority of cases with reasonable specificity. Therefore diagnosis is currently based on behavioral phenotype alone.

In this chapter, we provide an overview of the history of autism and ASD classification, including criteria for and presentation of each of the PDDs, participant characteristics that affect diagnosis, instruments and methods for assessing ASD, innovative uses for the diagnostic measures, and diagnostic issues often overlooked in research.

Epidemiology and Diagnosis

Whereas autism was previously thought to occur in approximately 4 children out of 10,000 based on epidemiological studies published in the 1960s, the autism spectrum currently is thought to have a combined prevalence rate of 50–60 out of 10,000 school-age children (Chakrabarti & Fombonne, 2005; CDC, 2007). Refinements to diagnostic criteria, addressed later in this chapter, surely have impacted these prevalence rates (D. Bishop, Whitehouse, Watt, & Line, 2008). Growing ASD prevalence and awareness of the disorders in turn demand greater research attention to the boundaries of and within this spectrum. Indeed, one of the primary issues in ASD diagnosis today is a debate about the clinical and biological validity of distinct categorical disorders within the spectrum (see below).

ASD is more prevalent among males, with an approximate gender ratio of 4:1. There seems to be a higher proportion of severe cognitive impairment in females with ASD than in males (Fombonne, 2005a). It is speculated that gender may be differently associated with various etiological subtypes in ASD (Miles et al., 2005). Though we may come to see subgroups with different ASD severity levels and cognitive ranges in which sex ratios differ from that in the overall population, at this point there is no specific profile of ASD impairments that distinguishes girls from boys (except for greater female prevalence in Rett’s disorder).

Factors such as race, ethnicity, and socioeconomic class are not thought to influence presentation of ASD. We mention them here, however, because they have been associated with age of first diagnosis, and with over- or underdiagnosis of ASD, depending on the specific group. Kanner noted that the parents of his sample were well educated and high achieving, leading to a notion that autism was more prevalent among the higher socioeconomic classes. Later, more rigorous studies of SES and ASD found that autism crosses social class (Schopler, Andrews, & Strupp, 1980; Wing, 1980). However, early diagnosis of children with lower SES is often impeded by less sensitive referral sources, limited access to specialized clinics, and the cost of a diagnostic evaluation. Accurate diagnosis for a complicated case of ASD may span a couple of years and require thousands of dollars (Shattuck & Grosse, 2007). One study found that children from poor or near-poor families receive an initial diagnosis up to 11 months later than children from wealthier families (Mandell, Novak, & Zubritsky, 2005). Age of identification was significantly higher for African American and Latino children than for white children in another study in which the entire sample had low SES (Mandell, Listerud, & Levy, 2002), although this was not replicated in two more recent studies (Mandell et al., 2005; Wiggins, Baio, & Rice, 2006). In 2009 Mandell and his research team examined age of diagnosis by race and other factors in over 76,000 Medicaid-enrolled children with new diagnoses of an ASD. They found that African American children were diagnosed with an ASD at a mean age of 70.8 months, compared to the overall sample mean of 68.4, whereas Latino and Asian children tended to receive diagnoses at younger ages than did children in other ethnic groups, including Caucasian children (Mandell, Morales, et al., 2009). The author postulates that the findings might be due to the amelioration of ethnicity-related disparities in impoverished samples, or perhaps a phenomenon in which the most severely impaired children within some ethnic groups are the only ones to be identified in early childhood, decreasing the observed age of diagnosis for a particular group. Indeed, another study by the same team found that black and Hispanic children were less likely to have a documented ASD than were white children (Mandell, Wiggins, et al., 2009). Research is currently being done to determine the influence of cultural factors in observing and reporting autism behaviors, as well as differences in ASD prevalence across racial/ethnic groups (Mandell, Wiggins, et al., 2009; Bhasin & Schendel, 2007; Overton, Fielding, & Garcia de Alba, 2007; Schieve, Rice, & Boyle, 2006).

Diagnostic Classification

In 1943, Kanner used the term “infantile autism” to describe 11 children who exhibited limited interest in and impaired social response to others from infancy onward (Kanner, 1943). These children were either nonverbal or had impaired communication, as well as behavioral rigidity. Virtually simultaneously, Hans Asperger described a similar group of male children (Asperger, 1944), but the fact that Kanner published in English and Asperger in German barred the comparison of these findings. For decades, most mental health professionals continued to think of children with this behavioral profile as having “childhood schizophrenia” (Tidmarsh & Volkmar, 2003), until the work of Rutter and Kolvin in the 1970s distinguished the two conditions in terms of clinical characteristics and outcome (Rutter, 1970, 1972; Kolvin, 1971). Whereas childhood schizophrenia was characterized by disordered personality, thought, and mood and blunted affect, usually with normal intelligence and an onset after 11 years of age, “infantile autism” was noted from infancy or shortly after in children with a range of intellectual functioning, and was marked by speech delay, ritualistic behaviors, and deficits in social relationships and imaginative play.

In 1980, the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition (DSM-III; APA, 1980), first included “infantile autism” under a new diagnostic category of Pervasive Developmental Disorder, partly in recognition of Wing’s “triad of impairments” often associated with intellectual disabilities (Wing & Gould, 1979). With the 1987 revisions, DSM-III-R changed the diagnostic label to “autistic disorder.” Also, “Not Otherwise Specified” categories were added to this version of the DSM, thereby creating PDD-NOS. The World Health Organization’s International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10; WHO, 1990), which included Rett’s disorder and CDD in the Pervasive Developmental Disorder category, came into widespread use in 1994. The DSM-IV was published in the same year (APA, 1994), and had PDD criteria revised to correspond to ICD-10 criteria for these disorders.

The DSM-IV PDD classifications and a brief overview of their criteria are presented below (see also Tidmarsh & Volkmar, 2003). Because ICD-10 categories and criteria are so similar to DSM-IV classification, the former system will not be reviewed in depth here. ICD-10 includes more subtypes of PDD than does DSM-IV. Nonetheless, the similarity between these systems has already had a profound impact by enabling international merging of datasets and comparison of research findings (e.g. International Molecular Genetic Study of Autism, Gong et al., 2008; Autism Genome Project et al., 2007).

Autistic Disorder

In the DSM-IV, autistic disorder is diagnosed when six symptoms are present across the three domains of qualitative impairment in social interaction, communication, and restricted repetitive and stereotyped patterns of behavior, interests, and activities. At least two of the symptoms must be from the social domain, with at least one symptom present from each of the other two domains. Social, language, or play abnormalities or delays must be present before the age of 3, and Rett’s disorder and CDD must first be ruled out before assigning a diagnosis of autistic disorder.

Impairment in social reciprocity is believed to be the central defining characteristic of autism (Williams White, Koenig, & Scahill, 2007; Carter, Davis, Klin, & Volkmar, 2005). Difficulties in social interaction present in various ways within and across individuals, such as a toddler who does not direct eye contact or a changed facial expression to her parent when something startles her, but looks up briefly in the direction of the noise and continues playing, an adolescent who interjects abruptly during a group conversation to bring up his own interest in videogames, or an adult who makes no response to another’s comment about having a terrible day.

Delay, impairment in, or absence of communication strategies is also characteristic of autism. These difficulties are evident in both verbal (e.g., late onset of phrase speech, pronoun reversal, stereotyped speech) and nonverbal (e.g., minimal use of gestures) aspects of communication. Recent factor analyses of standardized diagnostic measures, the Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2000) and the Autism Diagnostic Interview–Revised (ADI-R; Lord, Rutter, & LeCouteur, 1994), have shown that social and communication domain items from these measures load onto a single factor (Gotham et al., 2008; Georgiades et al., 2007; Lecavalier et al., 2006), and therefore it is possible that these two symptoms domains will be merged in DSM-V criteria for autistic disorder.

Restricted, repetitive behaviors and interests (RRBs) comprise the third domain of autism symptomatology. These include repetitive motor mannerisms (e.g., hand flapping), unusual sensory interests (e.g., squinting one’s eyes to peer at a wind-up toy), and restricted or unusual topics of interest (e.g., collecting ticket stubs, learning and reciting everything there is to know about the Roman emperor Nero). Based on recent analyses of the factor structure and developmental course of behaviors in the RRB domain, some researchers have suggested that this third domain of behavior be split into two separate categories: “repetitive sensory motor behaviors,” which include motor mannerisms, sensory interests, and repetitive use of objects, and “insistence on sameness behaviors,” such as compulsions and rituals and overreliance on routines (Cuccaro et al., 2003; Bishop, Richler, & Lord, 2006; Richler, Bishop, Kleinke, & Lord, 2007).

Asperger’s Syndrome (AS)

Like autism, AS is also marked by social impairment and restricted interests and behaviors. Development of speech is not delayed in AS, but communication abnormalities are often present, including flat intonation, pedantic speech (e.g., “Could I trouble you to answer some questions with regard to this new development?”), and diminished conversational reciprocity, often associated with restricted topics of interest. According to DSM-IV, autistic disorder must be ruled out before a diagnosis of AS can be made. When this rule is observed, the prevalence of AS is very low, making it difficult to gather samples large enough to study potential differences between this disorder and high functioning autism (HFA; or autism without intellectual disability) (see Szatmari, 2000). The DSM-IV rule-out criterion is therefore often ignored, with many clinical and research facilities each tending to use their own AS criteria.

Earlier studies suggested that children with AS differed from those with HFA with regard to impoverished motor skills (Gillberg, 1989) and profiles of discrepantly high verbal IQ (Volkmar et al., 1994). However, the lack of standardization of diagnosis has made these findings difficult to corroborate (Klin, Paul, Schultz, & Volkmar, 2005), and a number of more recent reviews have found little evidence of distinction between AS and HFA (Macintosh & Dissanayake, 2004; Frith, 2004; see also Howlin, 2003). For example, Bennett, Szatmari, and colleagues (2008) found that grouping 6- to 8-year-olds by the presence or absence of structural language impairment (deficits in grammar or syntax) explained more variance in outcome through ages 15–17 on an array of dimensions, including adaptive behavior and scores on the Autism Behavior Checklist (Krug, Arick, & Almond, 1980), than did grouping the sample by clinical diagnoses of AS and HFA. Similarly, Cuccaro and colleagues (2007) found no differences in repetitive behaviors between individuals with diagnoses of AS versus HFA. Based on widespread disagreement in the field about how to diagnose AS, as well as lack of evidence of differences between AS and HFA, there are likely to be significant changes in how AS is conceptualized in future DSM and ICD editions.

Pervasive Developmental Disorder, Not-Otherwise-Specified (PDD-NOS)

PDD-NOS diagnoses are assigned to children who do not meet onset criteria for autistic disorder or whose pattern of impairments falls short of the required number of symptoms in each domain. An individual with PDD-NOS may have symptoms meeting criteria in the social and one other domain, but exhibit no symptoms in the remaining domain, or alternatively, he/she may have a subthreshold number of symptoms in all three domains. Because this category does not have specific criteria of its own, it is often used as a “catch-all” diagnosis for individuals with a spectrum disorder difficult to specify, or for young children to whom professionals do not yet feel comfortable giving an autism diagnosis (Walker et al., 2004; Lord et al., 2006). In a study of interrater diagnostic reliability using three expert raters, the agreement for PDD-NOS (versus autism or AS) was not better than chance (Mahoney et al., 1998). Walker and colleagues (2004) suggested that the reliability and utility of the category may be improved by creating a separate designation for individuals with significant social and communication impairment without restricted, repetitive behaviors (RRBs). However, other studies have indicated that most individuals with PDD-NOS do have RRBs (Matson, Dempsey, LoVullo, & Wilkins, 2008; Bishop et al., 2006), so this revised definition would only account for a very small proportion of PDD-NOS cases.

PDD-NOS and AS may have dimensional differences from autism in some cases, but their utility as distinct, reliable categorical disorders will depend on evidence of their specific value in determining etiology and treatment (Volkmar & Lord, 2007). For future DSM and ICD versions, it will be important to examine whether PDD-NOS should remain a “catch-all” diagnosis or whether the population currently identified with this label could be divided into more definable subtypes, with the “NOS” label used less frequently for cases that fall short of meeting criteria for any PDD subtype.

Rett’s Disorder

This rare disorder appears primarily in girls. Development in infancy is not obviously abnormal initially, but soon head growth slows and fine and gross motor skills may be lost. The loss may include language skills and social interest as well. Social interaction usually improves by late childhood or adolescence, though severe mental retardation and motor impairment are persistent. Rett’s Disorder is characterized by stereotypical motor behaviors, most prominently hand-wringing, and breathing abnormalities, such as breathholding or hyperventilation; seizure activity is common. Mutations to X-linked gene MECP2 account for most cases (Amir et al., 1999).

Because Rett syndrome is associated with a identifiable genetic mutation, it has been argued that it should not be considered within the autism spectrum. However, more recently, as various genetic associations become apparent within this spectrum, the proposal has been made to give an ASD diagnosis on the basis of behavioral characteristics regardless of genetic findings, with genetic or chromosomal abnormalities coded on a separate axis. Thus, children with other identified disorders (e.g., genetic syndromes, fetal alcohol spectrum disorders) could receive an additional diagnosis of ASD if they meet behavioral criteria for social and communication impairments.

Childhood Disintegrative Disorder

Also rare, with prevalence estimated at 2 cases per 100,000 children (Fombonne, 2005b), CDD is differentiated from autism by a marked regression between 2 and 10 years of age following normal development in at least the first two years of life. In CDD, skills are lost in two or more of the following areas: language, social interaction, motor skills, play, or adaptive behavior. Though regression occurs in other ASDs as well (approximately 20–33% of children on the autism spectrum develop some single words in infancy and then lose them, usually between the ages of 18 and 24 months; even more children “lose” other social or communication skills; Luyster et al., 2005), in non-CDD regression, the developed speech is often very limited (i.e., 3–10 single words) and only present for a few weeks or months. Additionally, while loss of eye contact or other signs of social interest and engagement or play skills are often reported in children with autism, regressions in autism, unlike CDD regressions, are less frequently accompanied by losses in adaptive or motor skills.

It once seemed likely that CDD was etiologically distinct from autism. However researchers have recently questioned whether this disorder represents an arbitrary distinction from autism on the basis of the timing of the regression, the level of the child’s skills before the regression, and the type of skills lost. Studies about the validity of CDD as a distinct disorder have suggested that CDD may be accompanied by higher rates of epilepsy, increased fearfulness, and lower intellectual functioning (or less discrepancy between verbal and nonverbal IQ) than is seen in autism (Kurita, Osada, & Miyake, 2004; Malhotra & Gupta, 2002; Volkmar & Rutter, 1995). At this time, it remains unclear whether CDD represents extremes on all three dimensions of autism-like regression (e.g., lateness of regression, strength of prior skills, and amount of skills affected by the regression) or a unique disorder.

Factors That Affect the Presentation of ASD

ASDs are heterogeneous disorders, and individuals with these diagnoses can look quite different from each other. A nonverbal 16-year-old who avoids eye contact and spins in circles might share a diagnosis of autism with a hyperactive, verbally fluent 4-year-old who seeks out others to talk at length about his interest in maps and state capitals. Because ASDs are developmental disorders, they both influence and are influenced by developmental levels of the individual (such as language level, “mental age,” and chronological age). Thus, diagnosticians must be familiar with the range of factors that can affect the presentation of ASD across individuals. Furthermore, although autism spectrum disorders are considered some of the most reliably diagnosable psychiatric disorders of childhood (Volkmar & Lord, 2007), current classification systems may be most useful in the diagnosis of somewhat verbal, school-age children with mild-to-moderate intellectual disability. Special considerations must be taken, therefore, when assessing individuals on the “extremes” of the spectrum: very young children and adults; individuals with severe intellectual disability and those with average to above-average intelligence; and individuals with very limited or very strong verbal skills.

Chronological Age

As with any developmental disorder, chronological age has a significant impact on the way in which ASD symptoms manifest. Individuals behave differently at different phases in development, and these changes affect the presentation of their symptoms, as well as the contexts in which they should be evaluated. Most individuals with ASD continue to exhibit social and communication difficulties and restricted or repetitive behaviors across the lifespan, but the particular nature of these symptoms is likely to change dramatically with age.

In recent years, a great deal of attention has been given to identifying symptoms of ASD in very young children. Early identification of autism has been emphasized in clinical research and practice due to the reported benefits of early intervention. Current research suggests that autism can be diagnosed reliably by age 2 and nonautism ASD by age 3 (Turner, Stone, Pozdol, & Coonrod, 2006; Chawarska, Klin, Paul, & Volkmar, 2006). Some first signs in infants that are associated with later ASD diagnoses include failure to respond to one’s name, poor eye contact, and an array of unusual reactions to sensory properties of objects (Dawson et al., 2004; Baranek, 1999). Although the field continues to make gains in the area of early assessment and diagnosis (see Chapter 5 in this volume), many professionals are still not well versed in the range of social and communication abilities exhibited by typically developing infants and toddlers. Knowledge of chronological age expectations in normal development is therefore essential for all professionals working with this population (see Bishop, Luyster, Richler, & Lord, 2008).

Unlike infants and toddlers, adolescents and adults with ASD have received relatively little attention in the recent literature, particularly with regard to assessment and diagnosis. Adolescents and adults with ASD often exhibit greater social interest than younger children, but have exaggerated, stilted, or otherwise abnormal means of interacting, including poor social reciprocity and difficulty sustaining interactions. Across many studies, the use of communicative speech increases from childhood to adulthood, but aspects of communication remain impaired in ASD into adulthood, particularly those related to social functioning, such as gestures, perseveration, or overly literal interpretation of language (Seltzer, Shattuck, & Abbeduto, 2004). Based on a more limited body of research, the presence of RRBs seems to be relatively stable into adulthood, though the particular manifestation of these behaviors may change, for example, shifting from a toddler who seeks out only toys that have buttons, to an adolescent conversing about her restricted interest in constellations (Seltzer et al., 2004).

As a result of rising prevalence estimates and increased public awareness of ASD, more and more adults are presenting for initial evaluations with concerns about ASD. However, because ASD is normally diagnosed during childhood, most empirically derived assessment tools were designed for and validated on samples of children with ASD. Future research will need to dedicate more attention to developing best practice guidelines for assessment and diagnosis of adults with suspected ASD.

Mental Retardation

Intellectual disability was once thought to be present in most autism cases, but findings from more recently recruited samples estimate that 29–60% of children with autism fall in the normal range of nonverbal IQ (Fombonne, 2005a; Tidmarsh & Volkmar, 2003). Although there is a great deal of variability in developmental trajectories and outcomes for children with ASD, nonverbal IQ has been found to be one of the best prognostic indicators (Thurm, Lord, & Lee, 2007; Venter, Lord, & Schopler, 1992). Consequently, information about a child’s cognitive abilities is important in programming and planning for the future.

Because skill expectations are different for children at different developmental levels, knowledge about a child’s cognitive abilities is necessary in order to accurately assess his/her social and communication skills. We would not expect, for example, the same level of social sophistication from a 14-year-old with mild intellectual disability as we would if his cognitive abilities were in the average range. Thus, as mentioned previously, it is essential that clinicians familiarize themselves with typical social behaviors for individuals at different developmental stages, taking into account both chronological and mental age. This is necessary in order to “separate” the behaviors related to ASD from those related to intellectual disability. Studies comparing children with ASD to children with nonspectrum developmental delays (e.g., Down syndrome, intellectual disability of unknown etiology), have provided essential information about behaviors that are more or less specific to ASD, and have shown that even children with significant delays (without ASD) exhibit social competencies, such as joint attention skills, that many children with ASD do not (Dawson et al., 2004; Bishop, Gahagan, & Lord, 2007).

It is more difficult to make diagnostic differentiations in children with profound levels of intellectual disability. These individuals are very likely to meet criteria for ASD because their general level of functioning falls below a preschool level. In these cases, it may not be possible to differentiate individuals with profound mental retardation in whom the ASD is “primary” from those in whom the intellectual disability is the central cause of their difficulties. Furthermore, as discussed below, diagnostic instruments for ASD do not have the same psychometric properties when applied to populations of individuals with very severe cognitive disabilities.


As is the case with nonverbal skills, language abilities vary widely among children and adults with ASD. Whereas many or most children with autism were once expected to be nonverbal or minimally verbal, these rates have changed dramatically with the recognition of milder cases, as well as greater access to early language intervention. In one study of children with relatively severe ASD, about 40% of school-age children had complex fluent speech by age 9, and the proportion of completely nonverbal children was less than 15% (Lord et al., 2006), indicating that previous estimates of 50% of children with ASD being nonverbal are no longer valid.

Assessing social difficulties and communication impairments across a range of language levels from nonverbal to fluent requires expertise in various instruments (as discussed later) but also an understanding of the range of behaviors associated with the autism spectrum. It is important to recognize that individuals with more limited language abilities who do not have ASD still employ nonverbal forms of communication, such as gestures and eye contact, to initiate social interactions. Therefore, understanding the numerous ways in which humans communicate and what is expected for individuals at different developmental stages is required in order to be able to distinguish ASD from other disorders.

Comorbid Disorders

Comorbidity of ASD with other psychiatric disorders occurs frequently and may have great impact on the already heterogeneous presentation of these disorders. Some of the most common comorbid disorders include anxiety, depression, hyperactivity, attention problems, obsessive-compulsive features, oppositional-defiant disorder, tics, and epilepsy. Tuberous sclerosis and Fragile X account for a relatively small proportion of ASD cases (though conversely, a significant proportion of children with these disorders have autism or ASD) (Lord & Spence, 2006; see also Chapter 46, this volume). Schizophrenia has also been reported to co-occur with ASD, though infrequently. Adults with ASD may sometimes receive a schizophrenia diagnosis because of social isolation, flat affect, speaking their thoughts aloud, and/or endorsing the idea of “hearing voices” based on a literal interpretation, e.g., someone was speaking in the next room and could be heard despite not being immediately present (Fitzgerald, 1999).

Physical disabilities, such as blindness, deafness, or conditions that impair or prohibit motor coordination, also impact ASD presentation and diagnosis. These disabilities can affect social development; they also can render irrelevant certain behaviors that influence diagnosis, e.g., eye contact in blind children, or response to name in deaf children. These conditions may also prevent a referred individual’s participation in standard forms of assessment (e.g., a child with cerebral palsy who cannot construct block designs for cognitive testing).

Many of these disorders have social implications, and some of them are associated with specific kinds of repetitive behaviors, especially motor mannerisms, which can make diagnosis of ASD and comorbid disorders challenging. Comorbidity is more the rule than the exception in assessment today, due to high rates of co-occurring conditions within individuals on the autism spectrum (Sterling, Dawson, & Estes, 2008; Matson & Nebel-Schwalm, 2007).

While ASDs are commonly thought to be life-long disorders, there has been a great deal of recent interest and research on “optimal outcome” children—those who come to function in the normal range of cognitive, adaptive, and social skills, and thus no longer qualify for an ASD diagnosis. Though the accuracy and standardization of assessment and diagnosis may play a role in the observation of this phenomenon, a subtype of children on the spectrum who “recover” would likely be associated with and influenced by many of the factors described in this section—such as strong initial language and cognitive abilities and younger chronological age at identification (Helt et al., 2008).

Assessment of ASD

Diagnostic assessment of ASD is carried out by a number of professionals, e.g., physicians, psychologists, and educators. The type of professional or service system making the diagnosis will often affect how that diagnosis will be used to obtain services: distinct labels from different professionals are usually needed for eligibility of insurance or governmental funding, educational placement, or treatment planning (Shattuck & Grosse, 2007). Regardless of the assessment venue or the qualifications of the evaluator, it is vital that all professionals undertaking ASD assessment have clinical experience, skill, and familiarity with individuals with ASD and related disorders. Diagnosticians should be aware of best practices in the field and utilize standardized instruments. At the same time, clinical judgment has been found to contribute to the stability of ASD diagnosis beyond the classification from common standardized measures (Lord et al., 2006). Thus, even when required training has been completed for use of a particular diagnostic measure, a background of clinical experience with individuals with ASD is integral to competent diagnostic practice. Frequent, active contact with individuals with ASD led to excellent interrater reliability for clinical diagnosis in DSM-IV field trials, compared to fair reliability in less experienced professionals (Volkmar et al., 1994). Beginning professionals must have access to adequate supervision, and “experts” must maintain a high rate of ongoing clinical involvement with the ASD population.

Components of a Diagnostic Assessment

Before proceeding with a behavioral assessment for ASD, appropriate steps should be taken to ensure that the referred individual is physically healthy. These may include a physical exam to take growth measurements and rule out medical disorders that might obscure the presentation of ASD, as well as hearing, speech, and language assessments. In some cases, additional neurological or genetic testing may be indicated (see the American Academy of Pediatrics Council on Children with Disabilities guidelines for autism evaluation, Johnson et al., 2007).

A multidisciplinary assessment for ASD should include a caregiver-based developmental history that addresses milestones and noted abnormalities in the individual’s earliest years. A pregnancy and birth history should be taken, as well as an overview of the referred individual’s general health, including sleeping and eating behaviors, and a family history documenting relatives with ASD, genetic conditions, and mental health issues. Teachers or daycare providers can also assist in providing additional information about the individual’s behavior.

In addition to obtaining information from parents and teachers about an individual’s behavior, a diagnostic assessment should always include a direct observation of the referred individual. The child or adult with ASD should be seen personally by the diagnostician, and ideally, the observation should include the administration of a semistructured observational measure to assess the presence of symptoms associated with ASD (see below). The direct assessment should also include cognitive and language testing, as verbal and nonverbal abilities directly affect how symptoms of ASD manifest. Furthermore, a home or school visit may be useful for directly observing behavior problems or peer relationships that occur outside of the clinic setting.

When evaluating adolescents and adults who have the cognitive and language abilities to report on their own symptoms, it may also be appropriate to incorporate self-report measures into the diagnostic assessment. Standardized self-report questionnaires such as the Autism Spectrum Quotient (AQ: Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001—see below) have been developed to obtain symptom reports directly from the referred individual. These instruments hold promise as a means of gaining a better understanding about the perspectives and internal experiences of individuals with ASD. However, given that lack of insight is one of the features of ASD, further work is required to understand the extent to which adolescents and adults with ASD are capable of providing valid reports about their own strengths and difficulties (see Bishop & Seltzer, submitted).

Following the assessment, diagnostic feedback should be provided to the parents or referred adult both in person and in a written report. The family should be provided with information about ASD, and the clinician may wish to discuss coping skills and support resources with the family (Lord & McGee, 2001). If the primary clinician is not a psychiatrist, parents should have the option of requesting a psychiatric consult to discuss the patient’s medication needs, if any.

Because of the time, expertise, number of professionals, waiting lists, and costs, multidisciplinary assessments may not be a reality for all families with children with ASD, nor is it necessary in all contexts (e.g., confirming a previous diagnosis for research inclusion). However, clinicians should attempt to review information from as many of the above-mentioned sources as possible when making a clinical diagnosis of ASD. Communication between professionals from various disciplines promotes accurate and efficient diagnosis.

Differential Diagnosis

Many psychiatric disorders impact social communication, thus differential diagnosis of ASD can be complicated. Some of the most common non-ASD diagnoses given to children referred for ASD evaluations are language disorders, such as receptive-expressive language disorder or pragmatic language impairment, attention-deficit/hyperactivity disorder (ADHD), and intellectual disability. In each case, social and communication impairments should be assessed relative to the individual’s developmental level (Volkmar & Lord, 2007). Other diagnoses that referred children may have received in error include right hemisphere learning problems, hearing disabilities, obsessive compulsive disorder (OCD), schizoid personality disorder, attachment disorder, selective mutism, and Landau-Kleffner syndrome (characterized by language loss and seizure onset; Landau & Kleffner, 1998). While some differential diagnoses are more likely to be ruled out before an ASD diagnosis is made (e.g., schizoid personality disorder or selective mutism), others may warrant consideration as comorbid disorders (e.g., language disorders or intellectual disability).

Diagnostic Measures

Diagnosis of ASD has benefited from the development of standardized measures. This review will touch on the clinical utility and psychometric properties of a few questionnaires, interviews, and observational measures that have historical importance or current relevance in ASD diagnosis. See Lord and Corsello (2005) for a more detailed review of ASD diagnostic instruments.

Though measures vary in their purpose and convenience (thus clinical diagnosticians and research projects employ a range of the measures described below, as well as others), a number of instruments have come to be included in an internationally recognized “best practice” diagnostic assessment for ASD. These include the parent/caregiver interview, the Autism Diagnostic Interview-Revised (ADI-R; Lord et al., 1994), and the standardized clinical observation, the Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2000), as well as the Social Communication Questionnaire (SCQ; Rutter, Bailey, & Lord, 2003) and the Social Responsiveness Scale (SRS; Constantino, 2002). The ADI-R and ADOS exist in 20 authorized translations worldwide, the SCQ in 17, and the SRS in 18. Due in part to the widespread use of these instruments, research findings can be more easily compared and samples collapsed across data collection sites.

Despite the strong predictive validity of some of the assessment tools described below, an individual’s diagnosis of ASD should never depend on the diagnostic classification of a single measure or combination of measures. Be it for access to early intervention, educational services, or inclusion in a research sample, the ability of an experienced clinician is required to integrate information from standardized diagnostic instruments and other sources into a clinical diagnosis.


Questionnaires offer the advantage of being able to collect a large amount of information in a relatively short amount of time. As part of a diagnostic assessment, questionnaires can also be useful for gathering information from multiple informants, such as teachers, daycare workers, or, in the case of adult clients, supervisors, siblings, or spouses. A number of questionnaires have been designed to assess behaviors characteristic of ASD. Whereas earlier questionnaires relied on general and vague descriptions of behavior, such as “social interest” or “emotional connection,” more recently developed instruments inquire about specific, empirically identified symptoms of ASD that are intended to differentiate children with ASD from those who are typically developing or who have nonspectrum disorders. Nevertheless, even recently developed questionnaires have limitations, including reliance on the report of “lay observers” (e.g., parents), as well as interreporter differences in the way that questions are interpreted. Thus, whereas these tools can be useful for quickly gauging the types of behaviors that a child exhibits in different settings, questionnaires used as part of a diagnostic assessment should be combined with information from a parent interview and child observation.

Questionnaires developed to assist in the diagnosis of ASD include the Autism Behavior Checklist (ABC; Krug, Almond, & Arick, 1993), the Gilliam Autism Rating Scale (GARS; Gilliam, 1995), the Social Communication Questionnaire (SCQ; Rutter, Bailey, & Lord, 2003), and the Autism Spectrum Screening Questionnaire (ASSQ: Ehlers, Gillberg, & Wing, 1999). The ABC may be filled out by parents or teachers and inquires about behaviors related to sensory interests, body and object use, language and social interaction, and self-help. Based on findings that the instrument does not always adequately distinguish between individuals with autism and those with nonspectrum disorders (Volkmar et al., 1988, Eaves, Campbell, & Chambers, 2000), the ABC may be more appropriate for documenting change in response to treatment or education, rather than as a diagnostic measure (Lord & Corsello, 2005). Similarly, the GARS, which is also a parent-rated questionnaire intended to indicate autism likelihood, has been shown to underidentify children as having autism (sensitivity = .48) (South et al., 2002), suggesting that it should not be used as a primary diagnostic tool. The SCQ is a parent checklist based on questions from the Autism Diagnostic Interview (see below). Though the SCQ works relatively well for identifying children with ASD in certain populations (especially when used together with the Autism Diagnostic Observation Schedule—see below), cut-offs may need to be adjusted for younger children (see Corsello et al., 2007). The ASSQ is another brief symptom checklist for use in a clinical setting. It is specifically intended to identify characteristics of Asperger’s syndrome and high functioning autism, and thus is not appropriate for use with the full range of individuals referred for ASD diagnostic assessment.

Questionnaires that have been designed as continuous measures of ASD symptoms or traits include the Social Responsiveness Scale (SRS; Constantino, 2002) and the Autism Spectrum Quotient (AQ: Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, 2001). The SRS is a parent- or teacher-rated questionnaire that consists of 65 items assessing communication, social interaction, and repetitive and stereotyped behaviors and interests. When parent and teacher ratings are combined, the measure has excellent specificity for indicating the presence of ASD (.96) versus other disorders, but sensitivity is relatively low (.75) (Constantino et al., 2007). When only a parent rating is used, specificity is still good (.84), though sensitivity is less clear (Constantino et al., 2007). In its current format, the SRS is only validated for children between the ages of 4 and 18 years, though an adult research version of the instrument is currently being developed (see Constantino & Todd, 2005). For adults with suspected ASD, the Autism Spectrum Quotient (AQ) is available as a continuous measure of ASD traits. The AQ is a self-report measure for adults with average or above average intelligence. Adapted versions of the instrument have been validated for use with adolescents (Baron-Cohen, Hoekstra, Knickmeyer, & Wheelwright, 2006) and children aged 4–11 (Auyeung, Baron-Cohen, Wheelwright, & Allison, 2008) with suspected ASD. Parent-report versions of the AQ are also available to supplement the self-report forms (see Baron-Cohen et al., 2001; Baron-Cohen et al., 2006).


Like questionnaires, diagnostic interviews collect information from informants about an individual’s behaviors. An advantage of the interview format is that the interviewer has some control over the way in which questions are interpreted, because clarification can be provided when necessary. Semistructured interviews that are scored by the interviewer are also advantageous, because, as opposed to more subjective interpretations of behavior (e.g., a parent rating a behavior as normal/abnormal, mild/severe), scores are derived from a trained interviewer’s objective assessment of a behavioral description. On the other hand, interviews are often lengthy and thus time-consuming. Furthermore, unlike questionnaires, which can be mailed and completed anywhere, interviews require face-to-face contact between an informant and a trained examiner.

The Autism Diagnostic Interview-Revised (ADI-R; Lord et al., 1994) is a standardized, semistructured parent interview that is administered by a trained clinician in approximately 2–3 hours. Diagnostic algorithms, which yield a classification of “autism” or “nonspectrum,” are overinclusive for individuals with nonverbal mental ages below 18 months and those with severe to profound intellectual disability (Lord, Storoschuk, Rutter, & Pickles, 1993; Nordin & Gillberg, 1998). However, the measure has good to excellent predictive validity for most other developmental groups, especially when used in combination with the Autism Diagnostic Observation Schedule (see Risi et al., 2006). Although some researchers have used ADI-R scores to measure severity of autism symptoms and improvement over time, the ADI-R was developed with the goal of distinguishing individuals with ASD from those without ASD. Thus, more research is required to determine the extent to which higher scores on the ADI-R correspond to “more severe” autism, as well as whether current scores can be used to track changes over time.

The Diagnostic Interview for Social and Communication Disorders (DISCO; Wing, Leekam, Libby, Gould, & Larcombe, 2002) is another semistructured, standardized interview used in ASD assessment. It is primarily intended to assist in clinical assessment of an individual rather than to yield a categorical diagnosis, although diagnostic algorithms for research use have been created (Leekam, Libby, Wing, Gould, & Taylor, 2002). Unlike the ADI-R, the DISCO assesses a number of non-ASD-specific behaviors, including maladaptive behaviors and those related to daily living skills.

Observational Measures

Observation by a trained clinician is a critical component of any ASD diagnostic evaluation, and a diagnosis should never be made without first directly observing and interacting with a referred individual. Use of a standardized observation instrument is also recommended, because the observational period can be structured to specifically elicit behaviors associated with an ASD diagnosis. For example, in the absence of any particular demands, an individual who is allowed to talk at length about a particular topic may appear socially skilled, but as soon as he is encouraged to talk about something outside of his interests, his difficulties with conversation and social reciprocity will become more apparent. Thus, employing some type of semistructured observation measure is preferable to simply watching an individual referred for ASD.

The Childhood Autism Rating Scale (CARS; Schopler, Reichler, & Renner, 1986) is one of the most widely used autism diagnostic scales. Originally designed to be scored based on an examiner’s observations, the CARS is often used now as a general rating of all information available (e.g., scores may be derived from parent report, as well as from direct observation). Created before the current diagnostic classification systems, it is likely that the CARS overidentifies certain children (e.g., young nonspectrum children with intellectual disability) as having autism, while underestimating the difficulties of high-functioning children with ASD (see Lord & Corsello, 2005; Van Bourgondien, Marcus, & Schopler, 1992). Consequently, whereas it may be useful in some cases as a screening measure or a summary coding of all clinical information, care should be taken in using the CARS as the only observation measure in a diagnostic assessment.

The Autism Diagnostic Observation Schedule (ADOS; Lord et al., 2000) is a semistructured, standardized observation of children and adults referred for ASD. Like the ADI-R, its companion measure, the ADOS was created by operationalizing DSM-IV criteria for autism. Both original and revised diagnostic algorithms (see Gotham, Risi, Pickles, & Lord, 2007) show strong predictive validity, with the revised set of algorithms showing better specificity in lower-functioning populations. Because of its strong discriminant validity, the ADOS is widely used in international clinical and research efforts. It is useful in standardizing clinical observation, but must be considered in conjunction with a developmental history and clinical judgment of an experienced clinician.

With the recent interest in early diagnosis of ASD, several observational measures have been developed for use in very young children at risk for ASD and other communication disorders. The Communication and Symbolic Behavior Scales (CSBS; Wetherby & Prizant, 2002) evaluates communication and symbolic abilities in babies and toddlers and can be useful in identifying children who may require further evaluation. The Screening Tool for Autism in Toddlers (STAT: Stone, Coonrod, & Ousley, 2000) is an interactive screening measure for children between 24 and 35 months. The STAT has been shown to distinguish 2-year-old children with autism from those with nonspectrum developmental delays, but it is less good at picking up children with milder ASD symptoms (e.g., children with PDD-NOS). More recently, the Autism Observation Scale for Infants (AOSI: Bryson, Zwaigenbaum, McDermott, Rombough, & Brian, 2004) was developed to identify very young children (6 to 18 months) who may be at risk for ASD. Finally, the ADOS has been adapted for use with children aged 12 to 30 months; see Luyster et al., 2009, for description and psychometric analysis of this new toddler module.

Though direct observation is a crucial component of ASD diagnostic assessment, children and adults do not always behave as they normally would when they are “under the microscope,” being observed by professionals in an unfamiliar setting. Furthermore, it is not always possible to observe an individual’s full range of strengths and difficulties within a relatively short clinical observation period. Questionnaires and interviews provide information about behaviors that occur across various settings outside of a clinical context. As such, all three sources of information (questionnaires, interviews, and observations) are valuable components of a thorough ASD assessment.

Complementary Assessment Measures

In addition to ASD-specific diagnostic instruments, measures of cognitive, adaptive, and language abilities should be included in an ASD diagnostic evaluation. Individuals with ASD often have significantly discrepant verbal and performance IQ scores, so cognitive tests that yield separate verbal and nonverbal IQ scores should be selected. When working with individuals with less sophisticated language abilities, tests with lower language demands, such as the Mullen Scales of Early Learning (Mullen, 1995) and the Differential Ability Scales (DAS; Elliot, 1990), are sometimes preferable to tests that rely more on verbal instructions (e.g., the Wechsler Intelligence Scale for Children; Wechsler, 2003). Adaptive functioning is most commonly assessed with a parent interview, such as the Vineland Adaptive Behavior Scales, 2nd edition (Vineland-II; Sparrow, Cicchetti, & Balla, 2005), which yields separate normalized scores and age equivalents in the domains of communication, daily living skills, socialization, and motor skills. Language testing is also an important component of an ASD assessment. Tests should be selected such that receptive and expressive language skills are evaluated separately (see Paul, 2007).

Supplementary assessment tools may be indicated depending on the particular behavioral profile, or on the intervention, educational, or vocational needs of an individual referred for diagnostic assessment. Measures might be drawn from other areas of psychopathology to assess for comorbidities or to evaluate particular aspects of learning or achievement. For example, the Child Behavior Checklist (CBCL) is a parent/caregiver questionnaire that results in a total score, an Internalizing and Externalizing Scale score, and Syndrome and DSM Oriented Scales, one of which is a Pervasive Developmental Disorder Problems scale (Achenbach & Rescorla, 2000). The CBCL is not intended to be diagnostic, but can be used to identify a range of behavioral issues (ASD-specific and otherwise) to target for intervention. The Repetitive Behavior Scale–Revised (RBS-R; Bodfish, Symons, Parker, & Lewis, 2000) evaluates a range of repetitive behaviors seen in individuals with ASD and other developmental disorders and may be useful both for diagnostic purposes and for tracking changes in these behaviors over time. Other questionnaires that can be used to assess problematic behaviors in ASD include the Aberrant Behavior Checklist (Aman & Singh, 1994) and the Nisonger Child Behavior Rating Form (Tasse, Aman, Hammer, & Rojahn, 1996). The PDD Behavior Inventory (PDD-BI: Cohen, Schmidt-Lackner, Romanczyk, & Sudhalter, 2003) includes questions about adaptive and maladaptive behaviors, and is designed to evaluate responsiveness to intervention in children with ASD. For educational or vocational planning for individuals with ASD, the Psychoeducational Profile, 3rd edition (PEP-3; Schopler, Lansing, Reichler, & Marcus, 2004) and the Adolescent and Adult Psychoeducational Profile (AAPEP; Mesibov, Schopler, & Carson, 1989) may be used.

Though this list is far from exhaustive, we have attempted to review some of the more widely used instruments in ASD assessment. Evaluators should always keep in mind that certain accommodations may be necessary in order to obtain valid assessments of individuals with ASD, such as supplementing verbal directions with visual supports (e.g., schedules or reward systems), or using tests outside of the standard age range (e.g., administering a preschool language test to an older child with limited verbal abilities).

Looking Ahead

The field has made great strides in designing and validating instruments for use in ASD assessment and diagnosis, as well as in revising diagnostic criteria to be more inclusive of individuals across the full autism spectrum. However, there are many challenges that lie ahead in terms of further refining classification criteria and diagnostic instruments to meet current needs. As mentioned previously, more research is needed in the area of assessment methods for very young and/or very cognitively impaired individuals, and for adults across the range of abilities. It will be necessary to examine how well current diagnostic standards, which are largely based on observations of school-age children with ASD, apply to very young or older individuals. Do the same symptoms continue to be diagnostically relevant as individuals grow older, or should core symptoms of the disorder be defined relative to a person’s developmental stage?

Some researchers have proposed shifting from a categorical approach in ASD diagnosis toward a more dimensional framework. Continuous measures of social and communication difficulties could be used to describe a child’s level of social impairment/competence across different domains. Since many childhood disorders are characterized by social difficulties, this would aid in identifying areas of strength and difficulty in children with various disorders (including ASD), which could then be used to guide intervention efforts for these children.

Another advantage of thinking dimensionally about ASD symptoms rather than relying primarily on categorical distinctions is that we may be able to develop more meaningful measures of severity. There is currently no well-defined benchmark for “average autism,” so it is difficult to classify children as mild or severe, especially since a child may have very severe symptoms in one domain of behavior and relatively mild symptoms in another. Quantitative approaches to measuring symptoms across domains could improve our ability to describe different developmental trajectories and responses to treatment, which would in turn further efforts to identify subgroups of children with ASD and to isolate endophenotypes that may map onto specific genetic or neurobiological findings.


Standardized diagnostic criteria and “best practice” assessment measures have been associated with more comparable research findings and the ability to reliably describe younger and milder cases of autism spectrum disorders. Current research is underway to explore the relationship between participant characteristics such as gender, ethnicity, cognitive and language abilities, and comorbid disorders with specific ASD symptoms and severity. Further advancements in ASD diagnostic practices are needed to identify subtypes for neurobiological, genetic, and treatment research, as well as to define boundaries or dimensional gradations within the spectrum for clinical and research use.

Challenges and Future Directions

  • Achieving consistent early identification practices across geographic regions and within socioeconomic and ethnic groups

  • Revising international classification criteria to reflect data on symptom specificity and presentation

  • Identifying symptom profiles in historically overlooked populations, such as individuals with severe intellectual disability and adults with ASD

  • Measuring autism severity as a means to subtype groups within the spectrum

Suggested Readings

Fombonne, E. (2005). The changing epidemiology of autism. Journal of Applied Research in Intellectual Disabilities, 18, 281–294.

Lord, C., Risi, S., DiLavore, P., Shulman, C., Thurm, A., & Pickles, A. (2006). Autism from 2 to 9 years of age. Archives of General Psychiatry, 63(6), 694–701.

Risi, S., Lord, C., Gotham, K., Corsello, C., Szatmari, P., Cook, E., et al. (2006). Combining information from multiple sources in the diagnosis of autism spectrum disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 1094–1103.


Achenbach, T. M., & Rescorla, L. A. (2000). Manual for ASEBA preschool forms and profiles. Burlington: University of Vermont, Research Center for Children, Youth, & Families.Find this resource:

    Aman, M. G., & Singh, N. N. (1994). Aberrant Behavior Checklist—Community. Supplementary Manual. East Aurora, NY: Slosson Educational Publications.Find this resource:

      American Psychiatric Association (1980). Diagnostic and statistical manual (3rd ed.). Washington, DC: APA Press.Find this resource:

        American Psychiatric Association (1994). Diagnostic and Statistical Manual of Mental Disorders (4th ed.). Washington, DC: APA Press.Find this resource:

          Amir, R. E., Van den Veyver, I. B., Wan, M., Tran, C. Q., Francke, U., & Zoghbi, H. Y. (1999). Rett syndrome is caused by mutations in X-linked MeCP2, encoding methyl-CpG-binding protein 2. Nature Genetics, 23, 185–188.Find this resource:

          Asperger, H. (1944/1991). Die “autistischen psychopathen” in kind esalter. Archive fur Psychiatrie und Nervenkrankheiten, 117, 76–136. Translated by U. Frith (Ed.), Autism and Asperger syndrome (1991, pp. 37–92). Cambridge: Cambridge University.Find this resource:

            Autism Genome Project Consortium et al. (2007). Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nature Genetics, 39(3), 319–328.Find this resource:

            Auyeung, B., Baron-Cohen, S., Wheelwright, S., & Allison, C. (2008). The Autism Spectrum Quotient: Children’s version (AQ-Child). Journal of Autism and Developmental Disorders, 38(7), 1230–1240.Find this resource:

            Baranek, G. (1999). Autism during infancy: A retrospective video analysis of sensory-motor and social behaviors at 9–12 months of age. Journal of Autism and Developmental Disorders, 29(3), 218–224.Find this resource:

            Baron-Cohen, S., Hoekstra, R. A., Knickmeyer, R., & Wheelwright, S. (2006). The Autism-Spectrum Quotient (AQ)—Adolescent version. Journal of Autism and Developmental Disorders, 36, 343–350.Find this resource:

            Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 5–17.Find this resource:

            Bennett, T., Szatmari, P., Bryson, S., Volden, J., Zwaigenbaum, L., Vaccarella, L., et al. (2008). Differentiating autism and Asperger syndrome on the basis of language delay or impairment. Journal of Autism and Developmental Disorders, 38, 616–625.Find this resource:

            Bhasin, T. K., & Schendel, D. (2007). Sociodemographic risk factors for autism in a US metropolitan area. Journal of Autism and Developmental Disorders, 37, 667–677.Find this resource:

            Bishop, D. V. M., Whitehouse, A. J. O., Watt, H. T., & Line, E. A. (2008). Autism and diagnostic substitution: Evidence from a study of adults with a history of developmental language disorder. Developmental Medicine and Child Neurology, 50(5), 341–345.Find this resource:

            Bishop, S. L., & Seltzer, M. M. (submitted). Self-reported symptoms in adults with autism spectrum disorders.Find this resource:

            Bishop, S. L., Gahagan, S., & Lord, C. (2007). Re-examining the core features of autism: A comparison of autism spectrum disorder and fetal alcohol spectrum disorder. Journal of Child Psychology and Psychiatry, 48(11), 1111–1121.Find this resource:

            Bishop, S. L., Luyster, R., Richler, J., & Lord, C. (2008). Diagnostic assessment. In K. Chawarska, A. Klin, & F. R. Volkmar (Eds.), Autism spectrum disorders in infants and toddlers: Diagnosis, assessment, and treatment (pp. 23–49). New York: Guilford.Find this resource:

              Bishop, S. L., Richler, J., & Lord, C. (2006). Association between restrictive and repetitive behaviors and nonverbal IQ in children with autism spectrum disorders. Child Neuropsychology, 12, 247–267.Find this resource:

              Bodfish, J. W., Symons, F. J., Parker, D. E., & Lewis, M. H. (2000). Varieties of repetitive behavior in autism: Comparisons to mental retardation. Journal of Autism and Developmental Disorders, 30(3), 237–243.Find this resource:

              Bryson, S. E., Zwaigenbaum, L., McDermott, C., Rombough, V., & Brian, J. (2004). The Autism Observation Scale for Infants: Scale development and reliability data. Journal of Autism and Developmental Disorder, 38, 731–738.Find this resource:

              Carter, A. S., Davis, N. O., Klin, A., & Volkmar, F. R. (2005). Social development in autism. In F. R. Volkmar, R. Paul, A. Klin, & D. Cohen (Eds.), Handbook of autism and pervasive developmental disorders: Vol. 1. Diagnosis, development, neurobiology, and behavior (pp. 312–334). Hoboken, NJ: Wiley.Find this resource:

                Centers for Disease Control (2007). Prevalence of autism spectrum disorders—Autism and developmental disabilities monitoring network, six sites, United States, 2000. CDC Morbidity and Mortality Weekly Report, 56, 1–11.Find this resource:

                  Chakrabarti, S., & Fombonne, E. (2005). Pervasive developmental disorders in preschool children: confirmation of high prevalence. American Journal of Psychiatry, 162, 1133–1141.Find this resource:

                  Chawarska, K., Klin, A., Paul, R., & Volkmar, F. (2006). Autism spectrum disorder in the second year: Stability and change in syndrome expression. Journal of Child Psychology and Psychiatry, 48(2), 128–138.Find this resource:

                  Cohen, I. L., Schmidt-Lackner, S., Romanczyk, R., & Sudhalter, V. (2003). The PDD Behavior Inventory: A rating scale for assessing response to intervention in children with pervasive developmental disorder. Journal of Autism and Developmental Disorders, 33, 31–45.Find this resource:

                  Constantino, J. N. (2002). The Social Responsiveness Scale. Los Angeles: Western Psychological Services.Find this resource:

                    Constantino, J. N., LaVesser, P. D., Zhang, Y., Abbacchi, A. M., Gray, T., & Todd, R. D. (2007). Rapid quantitative assessment of autistic social impairment by classroom teachers. Journal of the American Academy of Child and Adolescent Psychiatry, 46, 1668–1676.Find this resource:

                    Constantino, J. N., & Todd, R. D. (2005). Intergenerational transmission of subthreshold autistic traits in the general population. Biological Psychiatry, 57, 655–660.Find this resource:

                    Constantino, J. N., & Todd, R. D. (2008). Genetic epidemiology of pervasive developmental disorders. In J. Hudziak (Ed.), Developmental psychopathology and wellness: Genetic and environmental influences (pp. 209–224). Arlington, VA: American Psychiatric Publishing.Find this resource:

                      Corsello, C., Hus, V., Pickles, A., Risi, S., Cook, E. H., Leventhal, B. N., et al. (2007). Between a ROC and a hard place: Decision making and making decisions about using the SCQ. Journal of Child Psychology and Psychiatry, 48, 932–940.Find this resource:

                      Cuccaro, M., Nations, L., Brinkley, J., Abramson, R., Wright, H., Hall, A., et al. (2007). A comparison of repetitive behaviors in Asperger’s disorder and high functioning autism. Child Psychiatry and Human Development, 37, 347–360.Find this resource:

                      Cuccaro, M. L., Shao, Y., Grubber, J., Slifer, M., Wolpert, C. M., Donnelly, S. L., et al. (2003). Factor analysis of restricted and repetitive behaviors in autism using the Autism Diagnostic Interview-R. Child Psychiatry and Human Development, 34(1), 3–17.Find this resource:

                      Dawson, G., Estes, A., Munson, J., Schellenberg, G., Bernier, R., & Abbott, R. (2007). Quantitative assessment of autism symptom-related traits in probands and parents: Broader Phenotype Autism Symptom Scale. Journal of Autism and Developmental Disorders, 37, 523–536.Find this resource:

                      Dawson, G., Toth, K., Abbott, R., Osterling, J., Munson, J., Estes, A., et al. (2004). Early social attention impairments in autism: Social orienting, joint attention, and attention to distress. Developmental Psychology, 40(2), 271–283.Find this resource:

                      Eaves, R. C., Campbell, H. A., & Chambers, D. (2000). Criterion-related and construct validity of the Pervasive Developmental Disorders Rating Scale and the Autism Behavior Checklist. Psychology in the Schools, 37, 311–321.Find this resource:

                      Ehlers, S., Gillberg, C., & Wing, L. (1999). A screening questionnaire for Asperger syndrome and other high-functioning autism spectrum disorders in school age children. Journal of Autism and Developmental Disorders, 29, 129–141.Find this resource:

                      Elliot, C. D. (1990). Differential abilities scale (DAS). San Antonio, TX: Psychological Corporation.Find this resource:

                        Fitzgerald, M. (1999). Differential diagnosis of adolescent and adult Pervasive Developmental Disorders/Autism Spectrum Disorders (PDD/ASD): A not uncommon diagnostic dilemma. International Journal of Psychiatry in Medicine, 16, 145–148.Find this resource:

                          Fombonne, E. (2005a). The changing epidemiology of autism. Journal of Applied Research in Intellectual Disabilities, 18, 281–294.Find this resource:

                          Fombonne, E. (2005b). Epidemiological studies of Pervasive Developmental Disorders. In: F. R. Volkmar, A. Klin, R. Paul, & D. J. Cohen (Eds.), Handbook of autism and pervasive developmental disorders (3rd ed., Vol. 1, pp. 42–69). New York: Wiley.Find this resource:

                            Frith, U. (2004). Emmanuel Miller lecture: Confusions and controversies about Asperger syndrome. Journal of Child Psychology and Psychiatry, 45, 672–686.Find this resource:

                            Georgiades, S., Szatmari, P., Zwaigenbaum, L., Duku, E., Bryson, S., Roberts, W., et al. (2007). Structure of the autism symptom phenotype: A proposed multidimensional model. Journal of the American Academy of Child and Adolescent Psychiatry, 46(2), 188–196.Find this resource:

                            Gillberg, C. (1989). Asperger syndrome in 23 Swedish children. Developmental Medicine and Child Neurology, 31, 520–531.Find this resource:

                            Gilliam, J. E. (1995). Gilliam Autism Rating Scale. Austin, TX: ProED.Find this resource:

                              Gong, X., Bacchelli, E., Blasi, F., Toma, C., Betancur, C., Chaste, P., et al. IMGSAC (2008). Analysis of X chromosome inactivation in autism spectrum disorders. American Journal of Medical Genetics. Part B, Neurosychiatric Genetics, 147B(6), 830–835.Find this resource:

                              Gotham, K., Risi, S., Dawson, G., Tager-Flusberg, H., Joseph, R., Carter, A., et al. (2008). A replication of the Autism Diagnostic Observation Schedule (ADOS) revised algorithms. Journal of the American Academy of Child and Adolescent Psychiatry, 47(6), 643–651.Find this resource:

                              Gotham, K., Risi, S., Pickles, A., & Lord, C. (2007). The Autism Diagnostic Observation Schedule (ADOS): Revised algorithms for improved diagnostic validity. Journal of Autism and Developmental Disorders, 37, 400–408.Find this resource:

                              Helt, M., Kelley, E., Kinsbourne, M., Pandey, J., Boorstein, H., Herbert, M., et al. (2008). Can children with autism recover? If so, how? Neuropsychology Review, 18, 339–366.Find this resource:

                              Howlin, P. (2003). Outcome in high-functioning adults with autism with and without early language delays: Implications for the differentiation between autism and Asperger syndrome. Journal of Autism and Developmental Disorders, 33, 3–13.Find this resource:

                              Johnson, C. P., Myers, S. M., & American Academy of Pediatrics Council on Children with Disabilities (2007). Identification and evaluation of children with autism spectrum disorders. Pediatrics, 120(5), 1183–1215.Find this resource:

                              Kanner, L. (1943). Autistic disturbances of affective contact. Nervous Child, 2, 217–250.Find this resource:

                                Klin, A., Pauls, R., Schultz, R., & Volkmar, F. (2005). Three diagnostic approaches to Asperger Syndrome: Implications for research. Journal of Autism and Developmental Disorders, 35, 221–234.Find this resource:

                                Kolvin, I. (1971). Studies in childhood psychoses. I. Diagnostic criteria and classification. British Journal of Psychiatry, 118, 381–384.Find this resource:

                                Krug, D. A., Arick, J. R., & Almond, P. J. (1980). Autism screening instrument for educational planning. Portland, OR: ASIEP Educational.Find this resource:

                                  Krug, D. A., Arick, J. R., & Almond, P. J. (1993). Autism screening instrument for educational planning (2nd ed.). Austin, TX: ProEd.Find this resource:

                                    Kurita, H., Osada, H., & Miyake, Y. (2004). External validity of Childhood Disintegrative Disorder in comparison with Autistic Disorder. Journal of Autism and Developmental Disorders, 34(3), 355–362.Find this resource:

                                    Landau, W. M., & Kleffner, F. R. (1998). Syndrome of acquired aphasia with convulsive disorder in children. 1957. Neurology, 51(5), 1241.Find this resource:

                                    Lecavalier, L., Aman, M., Scahill, L., McDougle, C., McCracken, J., Vitiello, B., et al. (2006). Validity of the Autism Diagnostic Interview-Revised. American Journal of Mental Retardation, 111(3), 199–215.Find this resource:

                                    Leekam, S. R., Libby, S. J., Wing, L., Gould, J., & Taylor, C. (2002). The Diagnostic Interview for Social and Communication Disorders: Algorithms for ICD-10 childhood autism and Wing and Gould autistic spectrum disorder. Journal of Child Psychology and Psychiatry and Allied Disciplines, 43(3), 327–342.Find this resource:

                                    Lord, C., & Corsello, C. (2005). Diagnostic Instruments in Autistic Spectrum Disorders. In F. R. Volkmar, R. Paul, A. Klin, & D. J. Cohen (Eds.), Handbook of autism and pervasive developmental disorders (pp. 730–770). New York: Wiley.Find this resource:

                                      Lord, C., & McGee, J. (2001). Educating children with autism spectrum disorders: Report of the Committee on Early Intervention in Autism. Washington, DC: National Academy of Sciences.Find this resource:

                                        Lord, C., Risi, S., DiLavore, P., Shulman, C., Thurm, A., & Pickles, A. (2006). Autism from 2 to 9 years of age. Archives of General Psychiatry, 63(6), 694–701.Find this resource:

                                        Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Jr., Leventhal, B. L., DiLavore, P. C., et al. (2000). The Autism Diagnostic Observation Schedule-Generic: A standard measure of social and communication deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223.Find this resource:

                                        Lord, C., Rutter, M. L., & LeCouteur, A. (1994). The Autism Diagnostic Interview-Revised: A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders, 24, 659–685.Find this resource:

                                        Lord, C., & Spence, S. (2006). Autism spectrum disorders: phenotype and diagnosis. In S. Moldin & J. Rubenstein (Eds). Under-standing autism: From basic neuroscience to treatment (pp. 1–23). New York, NY: Taylor & Francis.Find this resource:

                                          Lord, C., Storoschuk, S., Rutter, M., & Pickles, A. (1993). Using the ADI-R to diagnose autism in preschool children. Infant Mental Health Journal, 14, 1234–1252.Find this resource:

                                          Luyster, R., Gotham, K., Guthrie, W., Coffing, M., Petrak, R., Pierce, K., et al. (2009). The Autism Diagnostic Observation Schedule—Toddler Module: A new module of a standardized diagnostic measure for ASD. Journal of Autism and Developmental Disorders, 39(9), 1305–1320.Find this resource:

                                          Luyster, R., Richler, J., Risi, S., Hsu, W., Dawson, G., Bernier, R., et al. (2005). Early regression in social communication in autism spectrum disorders: A CPEA study. Developmental Neuropsychology, 27(3), 311–336.Find this resource:

                                          Macintosh, K. E., & Dissanayake, C. (2004). Annotation: The similarities and differences between autistic disorder and Asperger’s disorder: A review of the empirical evidence. Journal of Child Psychology and Psychiatry, 45, 421–434.Find this resource:

                                          Mahoney, W. J., Szatmari, P., MacLean, J. E., Bryson, S., Bartolucci, G., Walter, S., et al. (1998). Reliability and accuracy of differentiating pervasive developmental disorder subtypes. Journal of the American Academy of Child and Adolescent Psychiatry, 37, 278–285.Find this resource:

                                          Malhotra, S., & Gupta, N. (2002). Childhood Disintegrative Disorder: Re-examination of the current concept. European Child and Adolescent Psychiatry, 11, 108–114.Find this resource:

                                          Mandell, D. S, Listerud, J., & Levy, S. E. (2002). Race differences in the age at diagnosis among Medicaid-eligible children with autism. Journal of American Academy of Child and Adolescent Psychiatry, 41, 1447–1453.Find this resource:

                                          Mandell, D., Morales, K., Xie, M., Polsky, D., Stahmer, A., & Marcus, S. (2009). Factors associated with age of diagnosis among Medicaid-enrolled children with autism spectrum disorders in the United States. International Meeting for Autism Research, Chicago, Illinois, May 7, 2009.Find this resource:

                                            Mandell, D., Novak, M., & Zubritsky, C. (2005). Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics, 116(6), 1480–1487.Find this resource:

                                            Mandell, D., Wiggins, L., Arnstein Carpenter, L., Daniels, J., DiGiuseppi, C., Durkin, M., et al. (2009). Racial/ethnic disparities in the identification of children with autism spectrum disorders. American Journal of Public Health, 99(3), 493–498.Find this resource:

                                            Matson, J., Dempsey, T., LoVullo, S., & Wilkins, J. (2008). The effects of intellectual functioning on the range of core symptoms of autism spectrum disorders. Research in Developmental Disabilities, 29, 341–350.Find this resource:

                                            Matson, J., & Nebel-Schwalm, M. (2007). Comorbid psychopathology with autism spectrum disorder in children: An overview. Research in Developmental Disabilities, 28(4), 341–352.Find this resource:

                                            Mesibov, G., Schopler, E., & Caison, W. (1989). The Adolescent and Adult Psychoeducational Profile: Assessment of adolescents and adults with severe developmental handicaps. Journal of Autism and Developmental Disorders, 19, 33–40.Find this resource:

                                            Miles, J., Takahashi, T. N., Bagby, S., Pahota, S. K, Vaslow, D. F., Wang, C. H., et al. (2005). Essential versus complex autism: Definition of fundamental prognostic subtypes. American Journal of Medical Genetics, 135, 171–180.Find this resource:

                                            Morrow, E., Yoo, S., Flavell, S., Kim, T, Lin, Y. Hill, R., et al. (2008). Identifying autism loci and genes by tracing recent shared ancestry. Science, 321(5886), 218–223.Find this resource:

                                            Mullen, E. (1995). Mullen Scales of Early Learning (AGS ed.). Circle Pines, MN: American Guidance Service.Find this resource:

                                              Nordin, V., & Gillberg, C. (1998). The long-term course of autistic disorders: Update on follow-up studies. Acta Psychiatrica Scandinavica, 97, 99–108.Find this resource:

                                              Overton, T., Fielding, C., & Garcia de Alba, R. (2007). Differential diagnosis of Hispanic children referred for Autism Spectrum Disorders: Complex issues. Journal of Autism and Developmental Disorders, 37, 1996–2007.Find this resource:

                                              Paul, R. (2007). Language disorders from infancy through adolescence: Assessment and intervention (3rd ed.). St. Louis: Mosby-Year Book.Find this resource:

                                                Richler, J., Bishop, S. L., Kleinke, J. R., & Lord, C. (2007). Restrictive and repetitive behaviors in young children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37, 73–85.Find this resource:

                                                Risi, S., Lord, C., Gotham, K., Corsello, C., Szatmari, P., Cook, E., et al. (2006). Combining information from multiple sources in the diagnosis of autism spectrum disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 1094–1103.Find this resource:

                                                Rutter, M. (1970). Autistic children: Infancy to adulthood. Seminars in Psychiatry, 2, 435–450.Find this resource:

                                                Rutter, M. (1972). Childhood schizophrenia reconsidered. Journal of Autism and Childhood Schizophrenia, 2(4), 315–337.Find this resource:

                                                Rutter, M., Bailey, A., & Lord, C. (2003). Social Communication Questionnaire (SCQ). Los Angeles: Western Psychological Services.Find this resource:

                                                  Schieve, L. A., Rice, C., & Boyle, C. (2006). Parental report of diagnosed autism in children aged 4–17 years—United States—2003–2004. CDC Morbidity and Mortality Weekly Report, 55, 481–486.Find this resource:

                                                    Schopler, E., Andrews, C. E., & Strupp, K. (1980). Do autistic children come from upper middle-class parents? Journal of Autism and Developmental Disorders, 10, 91–103.Find this resource:

                                                    Schopler, E., Lansing, M., Reichler, R., & Marcus, L. (2004). Psychoeducational Profile, Third Edition (PEP-3). Austin, TX: Pro-Ed, USA.Find this resource:

                                                      Schopler, E., Reichler, R., & Renner, B. (1986). The childhood autism rating scale (CARS) for diagnostic screening and classification of autism. Part of the series Diagnosis and teaching curricula for autism and developmental disabilities. New York: Irvington.Find this resource:

                                                        Seltzer, M., Shattuck, P., & Abbeduto, L. (2004). Trajectory of development in adolescents and adults with autism. Mental Retardation and Developmental Disabilities Research Reviews, 10(4), 2004, 234–247.Find this resource:

                                                        Shattuck, P. T., & Grosse, S. D. (2007). Issues related to the diagnosis and treatment of autism spectrum disorders. Mental Retardation and Developmental Disabilities Research Reviews, 13, 129–135.Find this resource:

                                                        South, M., Williams, B. J., McMahon, W. M., Owley, T., Filipek, P. A., Shernoff, E., et al. (2002). Utility of Gilliam Autism Rating Scale in research and clinical populations. Journal of Autism and Developmental Disorders, 32, 593–599.Find this resource:

                                                        Sparrow, S. S., Cicchetti, D. V., & Balla, D. A. (2005). Vineland Adaptive Behavior Scales (2nd ed.). Circle Pines, MN: American Guidance Service.Find this resource:

                                                          Sterling, L., Dawson, G., & Estes, A. (2008). Characteristics associated with presence of depressive symptoms in adults with autism spectrum disorder. Journal of Autism and Developmental Disorders, 38(6), 1011–1018.Find this resource:

                                                          Stone, W. L., Coonrod, E. E., & Ousley, O. Y. (2000). Screening tool for autism in two-year-olds (STAT): Development and preliminary data. Journal of Autism and Developmental Disorders, 30(6), 607–612.Find this resource:

                                                          Szatmari, P. (2000). The classification of autism, Asperger’s syndrome, and pervasive developmental disorder. Canadian Journal of Psychiatry, 45(8), 731–738.Find this resource:

                                                          Tassé, M. J., Aman, M. G., Hammer, D., & Rojahn, J. (1996). The Nisonger Child Behavior Rating Form: Age and gender effects and norms. Research in Developmental Disabilities, 17, 59–75.Find this resource:

                                                          Thurm, A., Lord, C., & Lee, L. (2007). Predictors of language acquisition in preschool children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(9), 1721–1734.Find this resource:

                                                          Tidmarsh, L., & Volkmar, F. R. (2003). Diagnosis and epidemiology of autism spectrum disorders. Canadian Journal of Psychiatry, 48(8), 517–525.Find this resource:

                                                          Turner, L., Stone, W., Pozdol, S., & Coonrod, E. (2006). Follow-up of children with autism spectrum disorders from age 2 to age 9. Autism, 10(3), 243–265.Find this resource:

                                                          Van Bourgondien, M., Marcus, L., & Schopler, E. (1992). Comparison of DSM-III-R and childhood autism rating scale diagnoses of autism. Journal of Autism and Developmental Disorders, 22(4), 493–506.Find this resource:

                                                          Venter, A., Lord, C., & Schopler, E. (1992). A follow-up study on high functioning autistic children. Journal of Child Psychology and Psychiatry, 33(3), 489–507.Find this resource:

                                                          Volkmar, F. R., Cicchetti, D. V., Dykens, E., Sparrow, S. S., Leckman, J. F., & Cohen, D.F. (1988). An evaluation of the Autism Behavior Checklist. Journal of Autism and Developmental Disorders, 18, 81–97.Find this resource:

                                                          Volkmar, F. R., Klin, A., Siegel, B., Szatmari, P., Lord, C., Campbell, M., et al. (1994). Field trial for autistic disorder in DSM-IV. American Journal of Psychiatry, 151, 1361–1367.Find this resource:

                                                          Volkmar, F. R., & Lord, C. (2007). Diagnosis and definition of autism and other pervasive developmental disorders. In F. R. Volkmar (Ed.), Autism and pervasive developmental disorders (2nd ed., pp. 1–31). Cambridge: Cambridge University Press.Find this resource:

                                                            Volkmar, F. R., & Rutter, M. (1995). Childhood Disintegrative Disorder: Results of the DSM-IV autism field trial. Journal of the American Academy of Child and Adolescent Psychiatry, 34, 1092–1095.Find this resource:

                                                            Walker, D., Thompson, A., Zwaigenbaum, L., Goldberg, J., Bryson, S., Mahoney, W., et al. (2004). Specifying PDD-NOS: A comparison of PDD-NOS, Asperger syndrome, and autism. Journal of the American Academy of Child and Adolescent Psychiatry, 43, 172–180.Find this resource:

                                                            Wechsler, D. (2003). Wechsler Intelligence Scales for Children (4th ed.). San Antonio, TX: Psychological Corporation.Find this resource:

                                                              Wetherby, A., & Prizant, B. (2002). Communication and Symbolic Behavior Scales Developmental Profile—First Normed Edition. Baltimore, MD: Paul H. Brookes.Find this resource:

                                                                Wiggins, L. D., Baio, J., & Rice, C. (2006). Examination of the time between first evaluation and first autism spectrum diagnosis in a population-based sample. Journal of Developmental and Behavioral Pediatrics, 27, 79–87.Find this resource:

                                                                Williams White, S., Koenig, K., & Scahill, L. (2007). Social skills development in children with autism spectrum disorders: A review of the intervention research. Journal of Autism and Developmental Disorders, 37, 1858–1868.Find this resource:

                                                                Wing, L. (1980). Childhood autism and social class: A question of selection? British Journal of Psychiatry, 137, 410–417.Find this resource:

                                                                Wing, L., & Gould, J. (1979). Severe impairments of social interaction and associated abnormalities in children: Epidemiology and classification. Journal of Autism and Developmental Disorders, 9(1), 11–29.Find this resource:

                                                                Wing, L., Leekam, S. R., Libby, S. J., Gould, J., & Larcombe, M. (2002). The Diagnostic Interview for Social and Communication Disorders: Background, inter-rater reliability and clinical use. Journal of Child Psychology and Psychiatry and Allied Disciplines, 43, 307–325.Find this resource:

                                                                World Health Organization (1990). International Classification of Diseases (10th ed.). Diagnostic Criteria for Research. Geneva: WHO.Find this resource: