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Cognitive functioning in children with autism: Circumventing common assessment problems

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Jason C. Vladescu
A dissertation submitted in partial fulfillment of
the requirements for the degree of
Doctor of Philosophy
Department of Psychology
Central Michigan University
Mount Pleasant, Michigan
June, 2010
UMI Number: 3436501
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UMI 3436501
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Accepted by the Faculty of the College of Graduate Studies,
Central Michigan University, in partial fulfillment of
the requirements for the doctoral degree
Dissertation Committee:
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Committee Chair
Faculty Member
Faculty Member
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College of Graduate Studies
Sharon Bradley-Johnson, Ed.D., Chair
Carl M. Johnson, Ph.D.
Justin D. Oh-Lee, Ph.D.
Although my name is listed on the cover, many individuals played an important
role in the completion of this work. Foremost, I extend a sincere thank you to my mentor
and advisor, Dr. Sharon Bradley-Johnson. Sharon, I will be forever thankful for how
much you taught me, the unconditional support you provided, and the guidance you
offered throughout my graduate training. A very special thank you to Dr. Carl M.
Johnson and Dr. Justin D. Oh-Lee for their ideas, suggestions, and flexibility that helped
me to improve and complete this project. To the other faculty who played an important
part in my training - Dr. Timothy Hartshorne, Dr. Michael Hixson, Dr. Sandra Morgan,
Dr. Susan Jacob, and Dr. Katrina Rhymer - thank you for being wonderful teachers. I
would not be where I am without the love and support of my family. Heartfelt thanks to
my parents (Florin & Katherine); Derek; Karina; my grandparents (Jack & Eda); and
Mike, Joyce, Phil, Alex, and Ryan Darcey. I love you all! To Meghan Caswell and
Rachel Knight, a big thank you and a hug for your unwavering friendship and for
volunteering your time to accompanying me to collect data. I wish to acknowledge the
support of Central Michigan University in producing this work. Last, but far from least,
thanks to all my friends from the 'Cuse, Michigan, and Nebraska for the support, laughs,
and adventures.
This work is dedicated to my mother, Katherine (Trina) Vladescu. Everything I am and
everything I will become I owe to her. Mom, you taught be many things, but above all
you showed me how to unselfishly love and still enjoy life. IfI become half the person,
parent, friend, and professional my mother is, I will consider myself fortunate.
by Jason C. Vladescu
Several characteristics common to children with autism may make it difficult to
obtain accurate standardized test results. Because of problems encountered when testing
the cognitive development of children with autism, questions remain regarding the
percentage of these children who are functioning in the cognitively impaired range. The
purposes of this study were to evaluate the accuracy of the commonly reported
percentage of 75-85% of children with autism who are cognitively impaired and to test
the effects of procedures for addressing several problems encountered when assessing
young children with autism. Fewer than 75% of participants obtained standard scores at
or below the cutoff of 70 for cognitive impairment. Furthermore, results suggested that a
test and procedures implemented to circumvent difficulties encountered when testing
children with autism did not lead to significantly better performance than when testing
with these procedures withheld. Findings are discussed in terms of clinical implications
and directions for future research.
Early Identification
Cognitive Development
Difficulties in Assessing Children with Autism
Purpose ofthis Study
Specific Hypotheses
1. Summary of Participant Characteristics
2. Summary of Participant Scores
3. Summary of GARS-2 Ratings
4. Correlations between scores obtained on the CAS-2, WPPSI-III, and
Increasing interest in autism has been evident over the past five years. This
interest is not restricted to physicians, researchers, and families of children directly
affected by the disorder, rather the public as a whole seems interested in understanding
this intriguing, yet potentially devastating disorder. From the pages of the New York
Times to MSNBC daytime shows, autism is receiving considerable coverage. However,
issues surrounding the assessment of cognitive functioning in children with autism still
remain, and are the focus of this study.
Currently, autism is thought to represent only one part of a spectrum of disorders
known as pervasive developmental disorders (New York State Department of Health,
1999). The Diagnostic and Statistical Manual of Mental Disorders-Forth Edition-Test
Revision (DSM-IV-TR) (American Psychiatric Association, 2000) and the International
Classification of Diseases-Tenth Edition (ICD-10) (World Health Organization, 2003)
classify autism along such a spectrum that is distinct from four other pervasive
developmental disorders: Rett's syndrome, childhood disintegrative disorder (CDD),
Asperger's syndrome, and pervasive developmental disorder-not otherwise specified
Kanner (1943) first described the condition using the term autistic. Meaning "an
absorption in the self or subjective mental activity" (Wicks-Nelson & Israel, 2000,
p.321). The term autistic was based on Kanner's observation that beginning at birth these
children were unable to relate to people and situations as others do.
Autism includes impairment of development in several areas. However, because
symptoms and severity vary so much from child to child, general descriptions do not
describe all children with autism perfectly. The characteristics ofthe associated
impairments fall along a gamut ranging from mild to more severe (New York State
Department of Health, 1999). Currently, no criteria separate variations within the
disorder (e.g., highfunctioning autism), therefore, autism should be considered a
spectrum upon which children with the disorder generally fall (Freeman & Cronin, 2002).
The essential features of autism, known as the "triad problems," include impaired
communication, social functioning, and behavioral variability (e.g., restricted, repetitive
behaviors, interests, and activities) that appear in the first three years of life (American
Psychiatric Association, 2000). Sensory and perceptual deficits, behaviors problems, and
impaired cognitive performance also are concerns with autism (American Psychiatric
Association, 2000).
Although considered a low-incidence disability, autism is a disability that most
school psychologists and other health-care providers encounter. Autism is the fastest
growing developmental disability (Autism Society of America, 2003). The DSM-IV-TR
(American Psychiatric Association, 2000) suggests an Autistic Disorder rate of 2-5 per
10,000 individuals, other sources suggest higher rates. Shriver, Allen and Mathews
(1999) reported a rate of 10 +/- 5 in 10,000, and Bristol et al. (1996) indicated that
diagnoses on the autism spectrum impact 22 persons per 10,000. Fombonne (2003)
referenced three studies that showed rates in the area of 60 per 10,000. The Autism
Society of America (2003) indicated that 1 to 1.5 million Americans have some form of
autism. The number of 6- to 21 -year-old students with autism receiving services under
the Individuals with Disabilities Education Act (IDEA) is reported to have increased 500
percent from 1993 (under 20,000 individuals) to 2002 (almost 120,000 individuals)
(United States Government Accountability Office, 2005). A significant difference in
autism rates exists between genders; specifically the disorder is four to five times higher
in males than females (DSM-IV-TR, 2000).
Although the DSM-IV-TR and ICD- 10 are useful tools in clinical practice,
research, and education, when diagnosing autism, school psychologists must focus on
federal guidelines (IDEA, 2004) for practice within the schools. These guidelines for
autism state:
Autism means a developmental disability significantly affecting verbal and
nonverbal communication and social interaction, generally evident before age three,
which adversely affects a child's educational performance. Other characteristics often
associated with autism are engagement in repetitive activities and stereotyped
movements, resistance to environmental change or change in daily routines, and unusual
responses to sensory experiences.
(i) Autism does not apply if a child's educational performance is adversely
affected primarily because the child has an emotional disturbance, as defined in
paragraph (c)(4) of this section.
(ii) A child who manifests the characteristics of autism after age three could be
identified as having autism if the criteria in paragraph (c)(l)(i) of this section are satisfied
(p. 309).
The criteria presented in the federal guidelines (see Appendix A for the specific
criteria) must be met if a student is to be diagnosed as autistic and eligible for services
within the school setting. Diagnosis outside of the school is guided by DSM-IV-TR
criteria (see Appendix B for this description) in the United States and by ICD-IO criteria
(see Appendix C for this description) internationally.
Considerations in the assessment of at-risk children who present with difficulties
consistent with autism generally follow the best practice path of assessment - collect the
best possible data from various areas using many different sources and techniques.
Freeman and Cronin (2002) suggested that information should be obtained from a
developmental history, rating scales (e.g., Autism Behavior Checklist [ABC]), a medical
assessment (including auditory and visual examinations), a psychological assessment
(including cognitive and adaptive assessment), a communication assessment,
occupational and physical therapy assessments, a family assessment (mandatory
determination of family and parental support), and a mental status assessment (i.e.,
observations of the student's social interactions, communication and range of interests).
Early Identification
As with any disorder, the importance of early identification and intervention is
critical for effective intervention. As research on autism accumulates, evidence continues
to show the impact early identification and intervention can have on the prognosis for
children with autism. Early identification of autism and other related developmental
disorders is recognized as "best practice," and the federal regulations (IDEA, 2004)
mandate early identification of, and intervention for, developmental disabilities. Freeman
and Cronin (2002) noted that "It is now recognized that autism/PDD is a biological
disorder and that early intervention is effective. Thus, because children with autism/PDD
benefit from early intervention the need for early identification and diagnosis has become
increasingly important (p. I)." Early identification and intervention not only enhances
later functioning, it also improves language, intelligence quotients (IQs) and behavior
(Eaves & Ho, 2004; Makrygianni & Reed, 2010), and helps families begin the
information gathering and treatment process.
Lovaas (1993) examined the long-term effects of a one-to-one behavioral
treatment program for children with autism, who at the time of intake, were all less than
46 months of age. Follow-up studies indicated that by age 7 the children in the
experimental group attained higher IQs and had less restrictive school placements than
the children in the control group. Both groups were again examined at a mean age of
1 1.5, and results revealed that the experimental group's gains over the control group were
maintained (Lovaas, 1993).
Several recent studies suggest that stable diagnosis is possible as early as 1 8-24
months of age (Eaves & Ho, 2004) and some suggest diagnosis is even possible as early
as 15 months (Klin et al., 2004). Thus, atypical behaviors associated with autism are
identifiable within the first few years of life.
Cognitive Development
One characteristic of autism, the impairment of cognitive development, is the
focus of the current study. Information in the DSM-IV-TR (American Psychiatric
Association, 2000) indicates that, "In most cases, there is an associated diagnosis of
Mental Retardation, which can range from mild to profound" (p. 71). Sigman (1998)
suggested that 75 to 80% of individuals with autism score more than two standard
deviations below the mean on general intelligence instruments. However, Sigman did not
specifically address the degree of impairment. Although the majority of articles report
that about 75% of children with autism are functioning in the cognitively impaired range
(e.g., Carpentieri & Morgan, 1996; Joseph, Tager-Flushbery & Lord, 2002; Scheuffgen,
Happe, Anderson & Frith, 2000, Shriver et al., 1999), Newson and Hovanitz (1997)
reported a slightly higher figure of about 85%. Also, in the Freeman et al. (1991) study
77% of the sample had verbal scores in the cognitively impaired range. Thus, most
studies report that about 75% of these children are cognitively impaired, but several
studies report slightly higher percentages up to about 85%.
When addressing the severity of impairment, consistent with the DSM-IV-TR
description, Carpentieri and Morgan (1996) suggested that the majority of these
individuals are functioning within the moderate to severe range of mental retardation.
However, Morgan, Campbell and Jackson (2003) reported that half of the individuals
with autism have IQs between 50 and 70, and 27% have IQs lower than 50. Thus,
whether most of these individuals are functioning in the mild or moderate range of
cognitive impairment is unclear.
Some studies suggest that individuals with autism may display a particular pattern
or profile on intelligence tests; however, this issue also is subject to debate. A number of
studies reported that individuals with autism often have lower scores on verbal measures
than on measures of performance (e.g., Filipek et al., 2000; Joseph, Tager-Flushbery &
Lord, 2002; Sigman, 1998). However, Filipek et al. (2000) found the verbal IQ performance IQ (VIQ-PIQ) split varies as a function ofthe degree of impairment. They
found that when both the Full Scale and Verbal IQ are above 70, 80% of these
individuals with autism will not have a significant VIQ-PIQ disparity.
Joseph et al. (2002) examined numerous cognitive profiles and found the "V
(verbal) < NV (nonverbal)" profile to be the most distinct cognitive profile. Some have
even suggested the use of IQ profiles as a possible diagnostic aid (Lincoln, Courshesne,
Kilman, Elmasian, & Allen, 1988). However, past research indicates that differences
between performance and verbal abilities decrease with age, as language functioning
improves (Lincoln, Courchesne, Allen, Hanson, & Ene, 1998). Joseph et al. (2002)
recently observed this decrease, but noted that a V < NV IQ profile has not been found
consistently in research. In their study, 47.9% of the preschool participants demonstrated
a significant V < NV discrepancy of at least 14 points on the Differential Abilities Scale
(DAS). For the school-age group, 34 percent exhibited a V < NV profile.
In addition, specific subtest patterns have been reported for children with autism.
On the Wechsler Scales, Filipek et al. (2000) and Joseph et al. (2002) reported that Block
Design is usually the highest subtest, whereas Newson and Hovanitz (1997) reported
Object Assembly as the highest. The Comprehension Subtest is typically the lowest for
these children (Filipek et al., 2000).
On the DAS Joseph et al. (2002) found that preschoolers' performance on Pattern
Construction was higher than other subtest scores and their Verbal Comprehension
performance was the lowest. For the school-age group, Pattern Construction was
significantly higher than other scores, and Word Definitions was the lowest score.
Some children with autism have cognitive "splinter" skills that are areas of
strength when compared to functioning in other areas. Among these isolated abilities are
rote memory and hyperlexia (Morgan, Campbell & Jackson, 2003). Geiger, Smith and
Creaghead (2002) reported that children with autism frequently display a profile that
reflects higher motor and visual-motor skills. However these strengths have been
reported to be underrepresented on measures of cognitive abilities (Geiger et al., 2002).
Children with autism show inspection times (a measure of speed ofprocessing) that are
as fast as age-matched normally developing children and significantly faster than children
who are cognitively impaired (Scheuffgen et al., 2000). In rare cases (i.e., about 10
percent), children with autism also display savant skills. Such savant skills include
"supernatural" numerical or calendar skills, or superb talents in art or music (Morgan et
al., 2003). The majority of savant individuals have impairments in their general cognitive
and adaptive functioning (Morgan et al., 2003).
When parents' and teachers' estimates of the cognitive levels of children with
autism have been compared with research findings and results from assessment
specialists, a lack of conformity between the two sides has been found (Geiger et al.,
2002). Parents' and teachers' estimates of a child's cognitive ability are higher than
results from professional assessment. One explanation Geiger, Smith and Creaghead
(2002) offered was that an assessment within a clinical setting may not be as accurate as
reports from parents because parents have "access to more extensive and different
samples of behavior" (p. 31 1) across several environments.
Authors of the Adaptive Behavior Assessment System - Second Edition (ABASII; Harrison & Oakland, 2003) conducted numerous clinical validity studies as evidence
of the convergent and discriminate validity of the ABAS-II. Included in the data
collected were data describing how individuals with autism performed when compared
with members from the standardization sample. One sample group consisted of 35
children with autism, ages 3-2 to 5-1 1 who were rated using the Teacher/Day Care
Provider Form; another sample included 34 children with autism, ages 3-1 to 5-1 1 rated
on the Parent/Primary Caregiver Form; and a third sample consisted of 32 individuals
with autism, ages 5 to 1 8 rated using the Teacher Form. All groups had mean General
Adaptive Composites (GAC) that were significantly lower than the mean GAC for the
children in the norm sample. Furthermore, for the three groups significant differences
were found for all skill areas and adaptive domains except the Functional Pre-Academics
Skill Area on the Parent Form, suggesting that young children with autism do well in this
area according to their parents' ratings. Children with autism have significant difficulties
with most adaptive skills according to these studies.
The assessment of cognitive functioning is not required for decisions regarding
evaluation of academic success and educational programming (Shriver et al., 1999), nor
is it required for the diagnosis of autism. However, Newson and Hovanitz (1997)
suggested that intelligence test results are useful in several ways. Information regarding
cognitive levels helps determine if social and language impairments are below what
should be expected considering cognitive functioning. IQ results also may serve as a
rough estimate of academic achievement. Additionally, researchers find measures of
cognition useful in matching or distinguishing groups of children with autism from
children in other diagnostic categories, and valuable for studies examining treatment
outcome and follow-up. Ozonoff, Goodlin-Jones, and Solomon (2005) noted that level of
cognitive functioning is related to a child's ability to acquire skills and is a good predictor
of outcome. Results can also be useful in eligibility for IQ-related services. However,
the information intelligence tests provide must be considered carefully, because
measuring cognitive functioning of individuals with autism is not a straightforward task.
The behaviors and impairments these individuals have often "presents an assessment
challenge" (Ozonoff et al., 2005, p.529) and contribute to making testing situations that
are "fraught with difficulty" (Sigman, 1998, p. 820). And as Eaves and Ho (2004) noted,
test results for children with autism may be quite unreliable. Thus, drawing conclusions
regarding the percentage of children who are autistic and cognitively impaired, the degree
of impairment, and possible cognitive profiles is difficult because of the numerous
problems associated with the assessment of these children.
Difficulties in Assessing Children with Autism
Vacca (2007) indicated that several characteristics common to children with
autism "necessitate a sophisticated approach to assessment" (p. 51). Other researchers
have suggested that symptoms characteristic of autism make it difficult to obtain accurate
standardized testing results. For example, Butter, Mulick, and Metz (2006) indicated
"symptoms of autism likely interfere with testing conditions and artificially suppress
scores" (p. 240). A major concern for assessment of cognitive functioning of children
with autism is their language impairment. The United States Government Accountability
Office (2005) recognized that "a child with autistic disorder may have great difficulty
with communicating" (p. 23). Their inability to express or comprehend language is the
most common complaint of parents (Lovaas, 2003). Communication impairments are
more complex than simple speech delays and fall within a range of deficits (Filipek et al.,
2000). Receptive language is commonly delayed for the majority of children with
autism. Lovaas (2003) stated that while many of these individuals are able to respond to
simple instructions (e.g., "Sit down"), they fail to understand "complex and abstract
language" (p. 3).
Expressive language skills range from total mutism to fluent verbal ability.
Almost all individuals with autism vocalize (Lovaas, 2003), but as Sigman (1998)
reported only about half develop communicative speech. Mutism is further complicated
because these children often do not develop nonverbal means of communicating complex
thoughts as children with hearing impairments or language problems do (Newson &
Hovanitz, 1997). Furthermore, even the majority of individuals with autism who do have
good verbal ability display errors in language. Common errors are in semantics, social
pragmatics (Filipek et al., 2000), and prosody (e.g., atypical rhythm and loudness)
(Klinger & Dawson, 1996; Sigman, 1998). Children with autism also have difficulty
with prepositions (e.g., above), pronouns (e.g., his, hers), and time concepts (e.g., last)
(Lovaas, 2003). They also have been reported to have greater impairment in verbal
reasoning skills than children who are cognitvely impaired and of the same intellectual
level (Carpentieri & Morgan, 1996). Eighty-five percent of children with autism develop
immediate or delayed echolalia (i.e., word-for-word duplication of previously heard
words or sentences) (Klinger & Dawson, 1996). Echolalic responses have a
communicative function such as "requesting, self-regulation, protesting, and affirmation"
(Klinger & Dawson, 1996, p. 315). Thus, for about half of these children, tests that
require vocal expression would be inappropriate and for many of these children receptive
language is a problem also. Ozonoff et al., (2005) stress the importance of using an
instrument that provides separate measures of verbal and nonverbal skills when testing
children with autism.
Impairments in the pragmatic aspect of language are considered the most
pronounced language impairment in individuals with autism (Klinger & Dawson, 1996).
The literature indicates that numerous pragmatic functions of language are lacking. Even
for the children with autism who have strong linguistic abilities, issues regarding the use
of unrelated details in conversations, continuation on specific topics of conversation,
inappropriate changes in conversation topics (Klinger & Dawson, 1996), limited sharing
of information, idiosyncratic language use, problems with speaker-listener
interactions/rules, and problems in initiating and maintaining topics and conversational
turn-taking are commonly present (Newson, 1998). When asked for clarification,
children with autism are less likely to add useful information to help the listener (Newson
& Hovanitz, 1997). All of these difficulties would be a concern when tests that require
vocal responses are used. Problems with speaker-listener interactions/rules could
negatively affect performance even on tests that do not require a vocal response.
Impairment in the social abilities of children with autism also is viewed as a
primary deficit (Klinger & Dawson, 1996). Important in understanding social and
environmental information is the ability to focus attention on another individual using
nonverbal behavior (e.g., eye contact). Children with autism have difficulty displaying
joint attention (Klinger & Dawson, 1996). A related difficulty these children display is a
failure to visually orient to social stimuli (e.g., looking when their name is called) and
nonsocial stimuli (e.g., responding to the noise of a rattle). Difficulties in joint attention
make it difficult for examiners to know when a child is attending to directions during
testing, and lack of visual orienting to social and nonsocial stimuli may invalidate many
test items.
Children with autism may display "stimulus overselectivity" or "overly narrow
attention" (Lovaas, 2003). In other words, when presented with a compound stimulus,
the child only responds to one portion, or a restricted range ofthe components of the
stimulus. Lovaas (2003) provided the following example: "When presented with a
teacher's verbal request, a child may either read the teacher's lips or attend to the
teacher's gaze instead of responding to the teacher's voice" (p. 45). Thus, ensuring that
children with autism understand test directions can be challenging for examiners.
Lovaas (2003) found that during the course of intense behavioral therapy, without
addressing attention difficulties, overselective attending diminishes or completely
disappears. However, for children with autism who have not received such intense
treatment, stimulus overselectivity may be present during assessment. During testing, the
child may attend and respond to cues the examiner unintentionally provides (e.g., gaze
towards an item), and disregard cues (e.g., vocal instruction) the examiner wants the child
to focus on (Lovaas, 2003). Lovaas (2003) noted that the children may be reinforced for
this type of attending ifthey correctly solve an item, and thus, they will continue to focus
on that cue throughout an assessment session, even when it is ineffective in the long run.
Wavering levels of motivation also presents a challenge in assessing children with
autism, and can have a significant impact on assessment outcomes (Ozonoff et al., 2005).
In an attempt to evoke a necessary level of motivation, the use of reinforcement, and
other techniques (e.g., frequent breaks) "can result in very different test scores" (Ozonoff,
et al., 2005, p.529). At the same time, it is important to adhere to standardized
administration procedures, and consider all procedures used during testing when
interpreting results.
Different forms of tantrums and aggression have been observed in individuals
with autism (Lovaas, 2003) as well. More likely to occur in those children with cognitive
impairments, self-injurious behavior has been observed to include head-banging, hairpulling, head-slapping and self-biting (Klinger & Dawson, 1996). Such physical
aggression (e.g., scratching, biting, and/or hitting) also may be directed towards others
(Lovaas, 2003). A lack of emotional control is sometimes observed in terms of lengthy
bouts of crying and screaming (Newson & Hovanitz, 1997). If such behaviors are
present, they usually become significant problems by 2 or 3 years of age, and parents
often report that children with autism " are very hard to manage, have a low frustration
tolerance, and respond to even minor frustrations with a great deal of anger" (Lovaas,
2003, p. 4). As a result, instances of self-injurious and aggressive behaviors have been
observed to occur primarily during times of frustration, and in anticipation of, and during
times of, unexpected changes. Thus, such behavior seems to represent a means of
communication for individuals who have limited or no verbal means of communicating
(Klinger & Dawson, 1996). However, Newsom and Hovanitz (1997) listed other
motivational variables that may play a part in self-injurious behaviors. These include,
neurochemical abnormalities, medical problems, positive reinforcement (e.g., adult
attention), negative reinforcement (e.g., escape from task), and sensory stimulation.
Aggressive behavior, towards oneself and/or another person, certainly can
interfere with the cognitive assessment of a child with autism. During the administration
of a measure of cognitive development there are going to be tasks that are challenging
and frustrating for any child. Going into a clinic or having an examiner come into their
home or school for an assessment is a change in the child's routine. There also will be
many points of change during testing with the presentation of new tasks. And, as
reported, children with autism not only have a low tolerance for frustration and change,
but also tend to respond to these situations with a great deal of anger (Klinger & Dawson,
1996; Lovaas, 2003). Thus, situations of self-injurious behavior or aggression towards
the examiner may occur when assessing children with autism. As a result, testing may
need to be stopped and may or may not be able to continue. Consequently, test results
may be incomplete or invalid. Maintaining the child's attention and motivation to
participate may be very difficult for some ofthese children.
Children with autism often engage in excessive amounts of self-stimulatory
behavior. Although all humans self-stimulate, for individuals with autism, these
behaviors are more intense and often of a more unusual form. Examples of these self-
stimulating behaviors include body-rocking, hand-flapping, light gazing, spinning
objects, lining up objects, and jumping (Lovaas, 2003). In addition, there may be an
obsession with numbers, letters, internal power mechanisms of toys and items with
particular textures (Lovaas, 2003). Typically recognized during the second year of life
(Lovaas, 2003), children with autism, during unstructured play, often engage in less
symbolic and functional use of objects then other children do (Sigman, 1998). They
often play with toys "in a peculiar and idiosyncratic fashion by, for example, turning a
toy truck upside down and spinning its wheels" (2003, p. 4). The automatic
reinforcement (i.e., specifically sensory or perceptual feedback) that such behaviors
generate and the operant escape/avoidance contingencies provided by these behaviors
provide the basis for their continuance. The specific sensory or perceptual reinforcers
may be enteroceptive, exteroceptive, or a combination of the two (Newsom, 1998). SeIf15
stimulating behaviors are problematic during assessments because during such behavior,
the examinee's focus will be on self-stimulation, not the task at hand. Therefore,
examiners should not present items during instances of self-stimulation. However, this
may be easier said than done, as some self-stimulating behaviors are subtle (e.g., light
Klinger and Dawson (1996) made clinical observations of individuals with autism
exhibiting fearful responses to common objects such as "the vacuum cleaner, particular
television commercials, elevators, blacktop and clothing" (pp. 319-320). Such fears are
reported to be related to abnormal sensory responses, and can cause problems not only in
daily living situations (Klinger & Dawson, 1996), but during cognitive assessments as
well. Children with autism who display fears of common objects may have difficulty
with an assessment if they respond fearfully to some of the objects used during the test.
In conclusion, the deficits and difficulties in the developmental profile of children
with autism include impairments in language and in social abilities. The socioemotional
deficits these children display include problems with joint attention and orienting.
Children with autism also display certain behavioral excesses which include tantrums,
self-injurious behavior and aggression, ritualistic and self-stimulatory behaviors, and
abnormal fears and response to some sensory stimuli. These problems not only occur
throughout daily functioning, but also are encountered when assessing these children.
These problems make obtaining a valid cognitive score for these children difficult.
Akshoomoff (2006) found that a sample of children in an autism spectrum group
completed testing more quickly than an age-matched control group, but "spend
proportionally more time exhibiting off-task behaviors and less time engaged in the
assssment" (p. 269). Therefore, cognitive assessment results for children with autism
may be misleading, and caution should be used when interpreting these results.
Purpose ofthis Study
Because of the problems encountered when assessing the cognitive development
of children with autism, questions remain regarding the percentage of these children who
are functioning in the cognitively impaired range and their severity of cognitive
impairment. Thus, the purpose of this study was to address these concerns for young
children diagnosed with autism and evaluate whether the commonly reported percentage
of cognitive impairment is accurate.
Testing procedures to address a number ofthe problems encountered when
assessing children with autism were used, as well as use the Cognitive Abilities ScaleSecond Edition (CAS-2; Bradley-Johnson & Johnson, 2001) that circumvents some of the
difficulties often present during assessment of these children. The CAS-2 provided a
norm-referenced measure of cognitive ability for the participants who were 3 -year-old
children diagnosed on the autism spectrum. In addition to a General Cognitive Quotient
(GCQ), the CAS-2 provides a nonvocal measure of cognitive ability (the Nonvocal
Cognitive Quotient [NCQ]) for children who are unable to talk, will not communicate
vocally during testing, or whose speech is incomprehensible. If a participant was able to
communicate vocally, a GCQ, as well as a NCQ, was obtained. But, for children unable
to communicate vocally, only a NCQ was obtained. The NCQ makes it possible to
circumvent the difficulty with expressive language that children with autism frequently
display. Another helpful feature of the instrument is that there are no timed items. The
exclusion oftimed items allowed the experimenter to attend entirely to the child, rather
than dividing attention between observing the child and a stopwatch. Also, the lack of
timed items prevented potentially frustrating situations (i.e., not finishing an item before
the time limit) and avoided having to score on item as zero if a child is temporarily
noncompliant. The age-appropriate, interesting toys may have been helpful as well.
The Wechsler Preschool and Primary Scale of Intelligence-Third Edition
(WPPSI-III; Wechsler, 2002) was also administered. The WPPSI-III is a frequently used
childhood test of cognitive abilities that provides both a verbal and performance score.
Administering the WPPSI-III served as a comparison measure that does not have some of
the advantages of the CAS-2. For example, the WPPSI-III includes few interesting toys
and contains timed items.
To address other problems encountered frequently while assessing children with
autism, several procedures were used when the CAS-2 was administered. To limit, as
much as possible, problems involving attention, orienting, and stimulus overselectivity,
attempts were made to ensure the child's attention before presenting an item. Also, items
were presented as quickly as possible to avoid down time and help maintain the child's
attention (i.e., used fast pacing). Ultimately, however, the child dictated the pace at
which items were presented.
To address the concerns of motivation, tantrums and aggressive behavior, if
necessary, edibles or objects the parents indicated the children preferred were used as
needed to enhance participation. Examples of items that have been shown to be
reinforcing for children with autism include: toys that make noise (i.e., clackers, buzzers),
visual toys (i.e., flashlight, pinwheels, Slinkys), and toys that touch the body (i.e., Silly
Putty, vibrating toys) (Lovaas, 1981). These rewards were used following correct
responses and to help a child get through items he or she found difficult. The
experimenter was also familiar with many forms of self-stimulatory behavior these
children frequently display. This information made it possible to avoid presenting items
while a child was engaging in the behavior. These procedures and use ofthe CAS-2 may
enable examiners to obtain more accurate cognitive results for young children with
As numerous sources, including federal regulations, have indicated, the early
identification of developmental disabilities is critical for the most successful intervention
(Makrygianni & Reed, 2010). Therefore, because of the importance and documented
effectiveness of early identification and intervention, the current study's focus was on
preschool children. The age for participation was 3 years, 0 months through 3 years, 1 1
months. This age range was selected because research indicates that early intervention
provided before age 3 1A is more effective than when those same services are provided at
later ages (Wetherby et al., 2004). Other researchers have suggested that being of
younger age when beginning to receive early intervention services is predictive of being
in a regular education classroom when services are discontinued (Harris & Handleman,
Specific Hypotheses
1 . Participants' performance on the CAS-2 would be significantly correlated with
participants' ratings on the ABAS-II.
2. Children participating in the study would receive scores that are consistent with the
data reported in the ABAS-II manual for children with autism. In other words,
participants would do relatively well on the Functional Pre-Academics Skill Area
as rated by their parent and would be below average on other areas ofthe GAC.
3. Using an instrument and procedures that circumvent a number ofthe difficulties
encountered in the assessment of children with autism, fewer than 75 percent of
the participants would have a NCQ on the CAS-2 in the cognitively impaired
4. For those children who are verbal, fewer than 75 percent would have a GCQ on the
CAS-2, in the cognitively impaired range.
5. Because the CAS-2 does not require verbal responses, involves toys children
usually enjoy and has no timed items, participants would score higher on the GCQ
than on the Full Scale of the WPPSI-III, which does not use toys, requires a vocal
response on certain subtests and has timed items.
6. Because the CAS-2 involves toys children usually enjoy and has no timed items,
participants would score higher on the NCQ than on the WPPSI-III Performance
Scale, which does not use toys and has timed items.
7. Consistent with prior studies, for participants who are verbal, the CAS-2 NCQ
would be higher than the GCQ, and the WPPSI-III Performance IQ would be
higher than the Verbal IQ.
8. Because the CAS-2 taps educationally relevant skills, parents would rate summary
reports of children's strengths and difficulties based on the CAS-2 results as
This study consisted of 1 6 participants ages 3 years, 0 months through 3 years, 1 1
months (M= 41.9 months, SD = 3.8). All participants had an independent clinical
diagnosis of autism, or were classified by the school system as autistic. Participants were
recruited from Michigan and New York. The majority of children were from
urban/suburban areas in Michigan and most were boys. Fourteen were Caucasian. The
majority of their mothers had pursued education beyond high school. Table 1 provides a
summary of participant characteristics.
Table 1. Summary of Participant Characteristics.
Ages 3 years, 0 months through 3 years,
1 1 months (M= 41.88 months)
Urban/Suburban (population 2,500 or
Rural (population 0 to 2,499)
Mother's Education Level
Less than High School Diploma
Some College or Technical School (1 to 3
Bachelor 's Degree
Master 's, Professional, or Doctoral Degree
State of Residence
New York
Cognitive Abilities Scale - Second Edition (CAS-2; Bradley-Johnson & Johnson,
2001). The CAS-2 is an individually administered, norm-referenced measure of
intelligence for children from 3 months through 3 years old. The test contains two forms:
the Infant Form (3 through 23 months of age) and the Preschool Form (24 through 47
months of age). Both forms can yield either a General Cognitive Quotient (GCQ) (M=
100, SD = 15) or a Nonvocal Cognitive Quotient (NCQ) to describe cognitive ability.
The NCQ is for children who cannot talk, will not talk or vocalize during testing, or
whose speech cannot be understood.
Because this study involves 3-year-old children, only the Preschool Form is
reviewed. The Preschool Form consists of five areas: Oral Language, Reading,
Mathematics, Handwriting, and Enabling Behavior. The test emphasizes skills relevant
to later academic performance and includes numerous toys that are appropriate for, and of
interest to, young children. The test requires about 25 to 30 minutes to administer.
The CAS-2 norm sample included 1,106 children including children with
disabilities. Demographic characteristics of the sample are similar to US Census data in
terms of geographic distribution, gender, race, ethnicity, residence, and the educational
background of parents.
In regard to reliability, internal consistency data are good. Twenty-five of the 26
coefficients are above .85. When the stability of the CAS-2 is examined, correlations for
ages 12 through 47 months range from .90 to .98. Inter-scorer reliability correlations
range from .95 to .99.
Evidence for content validity is based on research, and the manual addresses
content validity for each item. The content assessed by the CAS-2 is particularly unique
because all items are related to future educational performance. Concurrent validity was
examined by comparing results with the Bayley Scales of Infant Development-Second
Edition (BSID-II; Bayley, 1993), the Pictorial Test of Intelligence-Second Edition (PTI2; French, 2001) and the Wechsler Preschool and Primary Scale of Intelligence-Revised
(WPPSI-R, 1991). Data show that the Preschool Form predicts both intelligence test and
achievement test performance over a 5-year period quite well. Lastly, construct validity
data show that scores increase with age, and means for both genders and racial/ethnic
groups are within the average range. Children with physical impairments score within
the average range and those who are cognitively impaired score in the below average
Wechsler Preschool and Primary Scale ofIntelligence-Third Edition (WPPSI-III,
Wechsler, 2002). The WPPSI-III is a norm-referenced, individually administered
measure of intelligence for children ages 2 years, 6 months through 7 years, 3 months.
The WPPSI-III has two subtest batteries, one for children 2 years, 6 months through 3
years, 1 1 months, and the other for children 4 years through 7 years, 1 1 months. Because
this study only involves 3-year-olds, only the subtest battery for younger children is
reviewed. Results can be described as quotients for the Full Scale IQ (FSIQ), and the
Verbal (VIQ) and Performance (VIQ) IQs (M= 100, SD = 15), and as scaled scores for
the subtests (M= 10, SD = 3).
For children 2 years, 6 months through 3 years, 1 1 months there are 4 core
subtests: Receptive Vocabulary, Information, Block Design and Object Assembly.
Picture Naming is supplemental, and can be used as a replacement for Receptive
Vocabulary or to compute the General Language Composite (GLC). Administration of
the 4 core subtests requires approximately 30 to 35 minutes. Picture Naming adds an
additional 5 to 7 minutes. Block Design and Object Assembly require a stopwatch,
because they are both timed.
The WPPSI-III norm sample included 1,700 children divided into nine age
groups. There were 100 to 200 children in each age group. The norm group was similar
to the 2000 U.S. Census in terms of age, sex, race/ethnicity, parental education level and
geographic distribution. Unfortunately, urban/rural residence data were not addressed.
Special group (e.g., Developmentally Disabled, Gifted/Talented, Mental Retardation)
technical data were reported in the manual.
When reliability data are examined, internal consistency is good for 3-year-olds.
AU subtest and composite correlations are .85 or greater. Stability data are described for
a sample of 157 children (13 to 27 individuals from each of the 9 age groups), of whom
approximately 60 percent were male. The mean test-retest interval was 26 days (range of
14 to 50 days). Data are provided for a 2:6 through 3:11 age group. Three of the four
corrected correlations were above .85, the Performance IQ correlation was .84. Corrected
correlations for the subtests ranged from .74 to .92. All WPPSI-III protocols from the
normative sample were double-scored by independent scorers. An inter-scorer agreement
of .98 to .99 was obtained.
In addressing content validity, detailed discussion including theoretical rationale
and expert reviews are provided. For ages 2:6 to 3:11, exploratory factor analysis studies
supported a 2-factor model (verbal and performance), with Information (.76) and
Receptive Vocabulary (.80) loading on the Verbal factor and Block Design (.58) and
Object Assembly (.56) loading on the Performance factor. Confirmatory factor analysis
further supported the 2-factor model, and additional analysis showed that the
supplemental Picture Naming (.83) subtest loaded on the Verbal factor.
Convergent and discriminant validity were evaluated by examining the
relationship between the WPPSI-III and the following measures: Wechsler Preschool and
Primary Scale of Intelligence-Revised (WPPSI-R, Wechsler, 1989), The Wechsler
Intelligence Scale for Children-Third Edition (WISC-III, Wechsler, 1991), Bayley Scales
of Infant Development-Second Edition (BSID-II, Bayley, 1993), Differential Ability
Scales (DAS, Elliott, 1990), Wechsler Individual Achievement Test-Second Edition
(WIAT-II, The Psychological Corporation, 2001), and the Children's Memory Scale
(CMS, Cohen, 1997). With the exception of the ADHD study, results from special group
studies were consistent with performance expectations.
Gilliam Autism Rating Scale-Second Edition (GARS-2; Gilliam 2006). The
GARS-2 is a rating scale designed to assist in the diagnosis of autism for individuals 3
through 22 years of age. The GARS-2 can be completed by anyone very familiar with
the individual being assessed. The 42 items are divided into the following subtests, each
containing 14 items: Stereotyped Behaviors, Communication, and Social Interaction.
Each item is rated based on frequency of occurrence using a scale ranging from 0 (never)
to 3 (frequently observed). There is also a 25-item Parent Interview used to document an
individual's development prior to 36 months. Items are based on the definitions and
diagnostic criteria for autism provided by the Autism Society of America (ASA, 2003)
and the DSM-IV-TR (2000). Results can be described by an overall Autism Index (AI)
and subtest standard scores. An AI equal to or greater than 85, suggests the presence of
autism is very likely.
The GARS-2 norm sample was similar to U.S. Census data in terms of race,
ethnicity, and geographic area. The author did not provide information on when the data
were collected, nor the socioeconomic or educational levels of the parents, or data on
urban/rural residency of the sample. The age range of the sample included participants
from 3 through 22 years of age, and the number of participants per age level ranged from
3 to 137. In the sample there were approximately 4 times the number of males than
females. Respondents were 807 professionals and 300 parents.
Internal consistency reliability data are good. Correlations for the subtests ranged
from .84 to .88, and for the overall quotient, the correlation was .94. A 1-week test-retest
interval was employed, and the stability data are good. Thirty-seven participants, as rated
by their parents, were involved in the study to evaluate test-retest reliability, and
corrected correlations were less than .85 only for the Communication subtest (r = .70).
Correlations were r = .90, r = .88, and r = .88 for Stereotyped Behaviors, Social
Interaction and AI, respectively. No inter-rater reliability data were presented.
Evidence for the content validity of the scale included the fact that items were
based on definitions given by ASA and DSM-IV-TR. Low to high correlations (.22 to
.78) were found in concurrent validity studies involving comparison of the GARS-2 to
the Autistic Behavior Checklist (ABC) from the Autism Screening Instrument for
Education Planning-Second Edition (ASIEP-2, Krug, Arick & Almond, 1993).
Discriminate validity data indicated that the GARS-2 is effective in discriminating
between those who are classified as autistic and those who are not. And, as expected,
construct validity studies suggested that GARS-2 results did not relate to age.
Adaptive Behavior Assessment Scale-Second Edition (ABAS-II; Harrison &
Oakland, 2003). The ABAS-II has a Parent/Primary Caregiver Form, Teacher/Daycare
Provider form and adult form, and is designed for individuals ages birth to 89 years old.
Because this study requires that the child's parent complete the ABAS-II, only the
Parent/Primary Caregiver Form is reviewed.
The ten subtests are Communication, Community Use, Functional Pre-
Academics, Home Living, Health & Safety, Leisure, Self-Care, Self-Direction, Social
and Motor. These subtests are based on the 10 areas of adaptive behavior suggested by
the American Association of Mental Retardation (AAMR). Scaled scores and age
equivalents are used to describe subtest results. The overall General Adaptive Composite
(GAC) is described as a standard score or percentile.
The norm sample of the ABAS-II included 100 participants per 3-month-interval
from birth through 1-1 1, 100 per 6-month-interval for ages 2-0 through 4-11, and 150 for
ages 5-0 through 5-11. The sample seems similar to the U.S. Census data for race,
ethnicity, sex, and parent's educational level. However, specific data are not provided to
determine how geographically representative the sample is. Furthermore, according to
the manual, children were recruited from "cities" therefore, rural students were not
included. Children with biological risk factors, and those who were developmentally
delayed were included.
Internal consistency coefficients are in the .90s for the General Adaptive
Composite (GAC), except for birth to 3 months on the Parent Form. In terms of stability,
GAC correlations ranged from .86 to .92, with a retest interval ranging from 2 days to 5
weeks (M= 13 days). The skill area correlations ranged from .78 to .92 for the 2through 3-year-old age group; the GAC correlation for this group was .92. Interrater
reliability exceeded .80 for the GAC.
The 10 areas of adaptive behavior suggested by the AAMR, as well as a review of
the literature on adaptive behavior, served as the source for item development.
Intercorrelations among the various areas were typically in the .4Os and .5Os. Because
Confirmatory Factor Analysis results suggest the scale assesses a single factor,
interpretation of subtests and domain results should be avoided.
Concurrent validity studies indicated a moderate correlation with the Vineland
Adaptive Behavior Scales (VABS, Sparrow, Balla & Cicchette, 1984), and a correlation
of .18 with the short form of the Scale of Independent Behavior-Revised (SIB-R,
Bruininks, Woodcock, Weatherman & Hill, 1996). In addressing construct validity,
moderate correlations were found for ages 2-6 to 5-1 1 when compared with the WPPSI-3
(Wechsler, 2002).
Children diagnosed with cognitive impairment were shown to score significantly
lower than a matched control group of children without delayed cognitive development.
Children with developmental delays scored higher than children with cognitive
impairment. Young children diagnosed with PDD showed deficits in adaptive behavior.
Children with autism showed delays except on the Functional Pre-Academics subtest.
A cover letter describing this study, stamped envelope, and a consent form
indicating willingness to help recruit potential participants for this study were sent to
contacts in school-based programs (i.e., teachers and school administrators) and
physicians in Michigan and New York (Appendix D). Once the consent form was
returned, I sent cover letters and permission forms to the school or physicians that were
given to parents/caregivers of eligible children (Appendix E).
Parents/caregivers interested in participating in my study completed and returned
the permission form as well as a brief information sheet (Appendix F) to me in the
enclosed envelope indicating they would allow their child to participate. Once I received
the permission form, I contacted the parents/caregivers to obtain information about their
child (e.g., expressive language abilities) and scheduled a time to complete the
assessment. All assessments were conducted in the children's homes.
During the testing session, I administered the CAS-2 and the WPPSI-III to the
child. Afterwards, the parent/caregiver completed the GARS-2 and the ABAS-II rating
scales. Whether the CAS-2 or the WPPSI-III was administered first was determined by a
coin toss (CAS-2: heads; WPPSI-III: tails). For eight (50%) of participants the CAS-2
was administered first. Immediately after the assessment session, parents received
$25.00 for their participation in the project.
Whether a CAS-2 GCQ or NCQ was used was based on information gathered
from the child's parents on the child's expressive language abilities. The CAS-2 and
WPPSI-III were administered following instructions in the examiner's manual, except
that a research assistant was present to hand me CAS-2 test items to ensure a quick pace
of administration. The research assistants were doctoral graduate students in a school
psychology program. Both research assistants completed extensive coursework in
assessment and received one-to-one training to familiarize them with the study protocols
and the instruments used in the study. As mentioned above, I also had preferred edibles
and items available to provide each child with rewards as needed, for attempting to
complete tasks and for completion of tasks during the administration of the CAS-2.
After I completed the testing, I wrote a summary report for each child describing
the child's strengths and difficulties shown on the CAS-2. This report, a brief
questionnaire (Appendix G), and a return envelope were sent to parents. The
questionnaire was included to evaluate how helpful parents of children with autism
thought the CAS-2 results were.
The GARS-2 was completed by parents of participants to document the
occurrence of behaviors characteristic of autism for this sample. The GARS-2 Autism
Index (AI) describes a child's overall performance on the scale in terms of standard
scores. An AI of 85 or higher indicates that the probability of autism is very likely; for
the subscales, standard scores of 7 or higher indicate that the probability of autism is very
likely. Table 2 provides obtained AI scores for each child. On average (M= 91 .9), the
participants fell in the "Very Likely" category of autism based on parents' ratings,
supporting the children's diagnosis or classification as autistic. Three of the 16
participants fell in the "Unlikely" category of autism based on parents' ratings. Table 3
provides mean scores for the AI and the three subscales.
The ABAS-II was completed by parents to document each participant's level of
adaptive behavior functioning and provide further evidence in support of participants'
diagnosis or classification as autistic. The ABAS-II provides scores for 10 subscales,
three domain composites, and a General Adaptive Composite (GAC). Average subscale
scores fall within a range of 7 to 13, and average composites range from 85 to 115. Table
2 provides GAC composites obtained for each participant. On average (M= 68.9),
participants' overall GAC fell at least two standard deviations below the mean (i.e.,
standard scores 70 or lower). Appendix I provides mean scores for the ABAS-II
subscales and composites.
Table 2. Summary of Participant Scores.
Participant GARS- ABAS- CAS-2
n/a* *
Mean (SD)
n/a* *
*Scores <55 were not included in the calculation of mean or standard deviation
**n/a indicates that no GCQ score was calculated because the participant was nonvocal
Table 3. Summary of GARS-2 Ratings.
Stereotyped Behaviors
Social Interaction
Autism Index
% of Scores Very Likely
Probability Autism
It was hypothesized that participants would obtain ABAS-II scores consistent
with data reported in the ABAS-II manual for the autism clinical study. Similar to results
of the autism ABAS-II clinical study, the current study found on average, the majority of
subscale standard scores fell in the below average range (i.e., standard scores of less than
7). Exceptions were the Functional Pre-Academic (M= 8.4) and Motor (M= 7.1)
subscales. Similar to the sample of children in the ABAS-II autism clinical study, the
skill area showing the least deficit for participants of the current study was Functional
One-sample Mests were conducted to analyze ABAS-II ratings for the current
sample compared to the children in the ABAS-II autism clinical study. See Appendix I
for a complete summary of ABAS-II ratings for the current sample, the ABAS-II clinical
sample, and difference between the two groups. Analysis indicated no significant
difference between the groups for the majority of subscales and domains. Two
significant differences were noted. On average, the participants of the current study had
significantly lower ratings (M= 3.5, SE = .45) on the Self-care subscale than the ABASII clinical sample (M= 4.9, t (15) = -3.13,/? = .01). Ratings on the Motor subscale were
significantly higher for the current sample (M= 7.1, SE = .50) than for the ABAS-II
clinical sample (M= 5.9, ? (15) = 2.5, ? = .03). With the exception of these minor
differences, participants' ABAS-II scores were consistent with scores for the children
with autism in the ABAS-II clinical study. As hypothesized, based on the parents'
ratings, children in the current sample displayed adaptive behavior that was similar to that
of the children in the ABAS-II autism clinical sample. Thus, the second hypothesis was
Another related hypothesis was that participants' CAS-2 scores would correlate
with the children's ratings on the ABAS-II. To evaluate this hypothesis, Kendall's tau
correlation coefficients were calculated for nine variables. Kendall's tau is a non-
parametric correlation and was used rather than Spearman's coefficient because of the
small data set (Field, 2009). See Table 4 for the correlation matrix.
Table 4. Correlations between scores obtained on the CAS-2, WPPSI-III, and ABAS-II.
1. CAS-2 GCQ
2. CAS-2 NCQ
.86** -
.55** .72** -
.62** .72** .87** -
.59** .61** .73** .64** -
.56** .48** .52** .42*
7. ABAS-II Cone
.68** .62** .63** .50** .81** -
8. ABAS-II Social
.50** .42*
9. ABAS-II Prac
*p<.05. **/><.01.
.53** .43*
.51** .41*
.81** .68** .79** .65** .67** -
Although there was a significant relationship between CAS-2 NCQ and ABAS-II
GAC ratings, r = .56, ? (one-tailed) <.01, a significant correlation was not found between
the CAS-2 GCQ and ABAS-II GAC, r = .33. Thus, hypothesis 1 was only partially
supported because the overall CAS-2 GCQ did not correlate significantly with the
ABAS-II GAC, but the CAS-2 NCQ did.
Additional correlations were calculated to evaluate the relationship between
WPPSI-III scores and ABAS-II GAC ratings. There was a significant correlation
between ABAS-II GAC ratings and WPPSI-III Full Scale scores, r =.48,/? (one-tailed)
<.01; WPPSI-III Verbal Scale scores, r = .52, ? (one-tailed) <.01; and WPSSI-III
Performance Scale scores, r = A2,p (one-tailed) <.01.
Two additional hypotheses were concerned with the percentage of participants
who fell in the cognitively impaired range on the CAS-2. These two hypotheses stated
that fewer than 75% of the nonverbal participants would have a NCQ in the cognitively
impaired range, and for those children who were verbal, fewer than 75% would have a
GCQ in the cognitively impaired range. These hypotheses were evaluated by calculating
the percentage of participants who received a GCQ or NCQ at or below 70 (two standard
deviations below the mean and the cut-off point for cognitive impairment).
A GCQ quotient was obtained for 1 1 participants, the remaining 5 were nonvocal
making it impossible to obtain a GCQ for them. Five of the 1 1 (45.5%) obtained a GCQ
at or below 70, and 2 of the 5 obtained a GCQ at or below 55 (3 standard deviations
below the mean). A NCQ was obtained for all 16 participants. Seven participants
obtained a NCQ at or below 70 (43.8%), and 4 of the 7 obtained a NCQ at or below 55.
These results indicate that fewer than 75 percent of participants obtained a GCQ or NCQ
at or below 70, thus both hypotheses 3 and 4 were supported.
A WPPSI-III Full Scale score was obtained for all 16 participants. Six (37.5%)
participants obtained a WPPSI-III Full Scale score at or below 70, and five of the six
obtained a Full Scale score at or below 55. A WPPSI-III Performance Scale score was
obtained for all 16 participants. Eight of the 16 (50%) participants obtained a WPSSI-III
Performance Scale score at or below 70, and 3 of the 8 obtained a Performance Score at
or below 55. Thus, less than 75% of the children obtained WPPSI-III Full Scale and
Performance (nonverbal) results in the cognitively impaired range also. See Figure 1 for
a summary of CAS-2 and WPPSI-III scores falling at or below 70 and at or below 55.
The next three hypotheses indicated that participants' CAS-2 GCQ or NCQ would
be higher than their WPPSI-III Full Scale quotient, their CAS-2 NCQ would be higher
than their CAS-2 GCQ, and their WPPSI-III Performance Scale quotient would be higher
than their Verbal Scale quotient. These hypotheses were evaluated through pairedsamples ¿-tests. Due to the number of Mests conducted, a more stringent .01 alpha level
was used. In the CAS-2 manual the lowest quotient possible is 55 and 6 participants
obtained raw scores that fell below 55. Although obtained results below 55 were
included in the data for the percentage of scores falling below 70, scores falling below 55
were excluded from the analyses evaluating differences between means. Consequently,
GCQ scores for 9 participants and NCQ from 12 participants were used in the following
analyses. Results indicated no significant difference between the CAS-2 GCQ (M= 86.7,
SD = 23.1) and WPPSI-III Full Scale quotients (M= 80.8, SD = 15.1, t (8) = 1.4, ? = .21).
Also, no significant difference was found between participant CAS-2 NCQs (M= 82.3,
SD = 19.8) and WPPSI-III Full Scale quotients (M= 78.3, SD = 15.0, t (1 1) = 1.3, ? =
.21). Thus, hypotheses 5 and 6 were not supported because there were no significant
differences between participants' performance on the WPPSI-III and CAS-2.
In evaluating performance across verbal and nonverbal scales on the CAS-2 and
WPPSI-III, results revealed that WPPSI-III Verbal Scale quotients (M= 78.6, SD = 21.3)
were not significantly different than WPPSI-III Performance Scale quotients (M= 68.6,
SD = 14.1, t (15) = 2.8, ? = .02). Participants' CAS-2 GCQs (M= 86.7, SD = 23.1) were
not significantly different than their CAS-2 NCQ (M= 85.44, SD = 21.3, t (8) = 0.6, ? =
.59). No significant differences were noted between verbal and nonverbal scales on the
CAS-2 and WPPSI-III, thus hypothesis 7 was not supported.
Although differences between means were not significant, it seems worthwhile to
examine the profile patterns for participants on the CAS-2 and WPPSI-III. On the CAS2, 55.6% of participants demonstrated a GCQ > NCQ profile, 33.3% of participants
demonstrated a NCQ > GCQ profile, and 11.1% demonstrated no difference across GCQ
and NCQ scores. On the WPPSI-III, 62.5% of participants demonstrated a Verbal Scale
> Performance Scale pattern, 31.3% demonstrated a Performance Scale > Verbal Scale
profile, and 6.3% showed no difference across scales. When examining participants'
performance for the WPPSI-III Full Scale and Performance scales, 37.5% demonstrated a
Full Scale > Performance Scale pattern, 43.8% demonstrated a Performance Scale > Full
Scale profile, and no difference was found for 18.8% of participants.
On average, participants had the highest subtest score on the WPPSI-III Receptive
Vocabulary subtest (M= 6.8) and the lowest mean score on the Block Design subtest (M
= 3.0). For the Information and Object Assembly subtests average scores were 5.5 and
6.6, respectively.
The last hypothesis indicated that because the CAS-2 taps educationally relevant
skills, parents will rate summary reports of children's performance on the CAS-2 as
helpful. Parents of 13 participants (81.3%) completed and returned the CAS-2 report
questionnaire. The questionnaire items focused on parents' opinions of the summary
report they were sent outlining specific strengths and difficulties for their child, as well
recommendations to help remediate difficulties. The questionnaire involved five items
rated on a 1 to 5 scale (1 = Strongly Agree, 2 = Agree; 3 = Neutral; 4 = Disagree; 5 =
Strongly Disagree). Mean ratings across the five items ranged from 1.1 to 2.5. On
average, parents reported finding the summary report to be clear and easy to understand
(M= 1.1, SD = 0.3); helped them learn something new about their child (M= 2.5, SD =
1.0); described important skills (M= 1.7, SD = 0.6); contained recommendations that
were practical/easy to use (M= 1 .3, SD = 0.5), and recommendations that were effective
(M= 1 .6, SD = 0.7). Based on parent ratings' of the summary report, hypothesis 8 was
All participants had previously been classified as autistic through their school
system or diagnosed with the disorder by medical personnel. A screening measure, the
GARS-2, completed by their parents provided further confirmation of the condition. All
but 3 of the 16 participants fell in the "Very Likely" category for autism on the GARS-2
AI. On average, the participants fell in the "Very Likely" category of autism for the
GARS-2 AI and subscales (Stereotyped Behaviors, Communication, and Social
Further, overall results and skill area performance for parents' ratings of their
children's adaptive behavior were consistent with those found in the ABAS-II autism
clinical sample. Except for two subdomains (Self-Care and Motor), no significant
differences were found between these groups. Furthermore, similar to the children in the
ABAS-II autism clinical study, the skill area showing the least deficit for participants of
the current study was Functional Pre-Academics. Thus, the data on adaptive behavior
provides additional evidence for the classification or diagnosis of autism for the current
Limitations of resources prevented additional independent verification of autism
for the study participants. However, the children's prior classifications or diagnoses, the
large majority ofresults from the GARS-2, and the comparison of ratings oftheir
adaptive behavior with that of the ABAS-II autism sample suggest that children in the
current sample were 3-year-olds with autism.
When evaluating the relationship between adaptive behavior ratings and scores on
the cognitive tests, significant correlations were found between the CAS-2 NCQ and
ABAS-II GAC, and between all WPPSI-III composite scores and ABAS-II GAC. No
significant relationship was found between the CAS-2 GCQ and ABAS-II GAC.
Swanson, Bradley-Johnson, Johnson, and O'Dell (2009) found a significant correlation
between the GCQ and the GAC of .46 (rc = .61,;? <.01) for 20 normally developing 2year-olds. In the current study a CAS-2 GCQ could be obtained for only 9 of the 16
participants, whereas CAS-2 NCQ and WPPSI-III scores were obtained for 12 and 16
participants, respectively. Although it is unclear why a significant relationship was not
found for the CAS-2 GCQ and the ABAS-II GAC, the small number of GCQ results
available for analysis may have been a factor, or for children with autism there may not
be a strong relationship between these two results. If future studies include a larger
sample size it would be possible to more accurately evaluate the relationship between
CAS-2 GCQ and the ABAS-II GAC. A power analysis and a sample size planning table
would be useful aides in determining the necessary sample size (Cohen, 1992a, 1992b).
One purpose ofthis study was to evaluate whether the commonly reported
percentages of cognitive impairment in individuals with autism of 75 to 85% (American
Psychiatric Association, 2000; Carpentieri & Morgan, 1996; Joseph, Tager-Flushbery &
Lord, 2002; Newson & Hovanitz,1997; Scheuffgen, Happe, Anderson & Frith, 2000,
Shriver et al., 1999; Sigman, 1998) are accurate. Results of this study on the CAS-2
GCQ, CAS-2 NCQ, WPPSI-III Full Scale, and WPPSI-III Performance Scale with 3year-olds showed that considerably less than 75% of participants scored in the
cognitively impaired range (i.e., at or below 70). The percentages ranged from 38 to 50%
depending on the test and type of score (overall or nonverbal) used.
Several factors may have contributed to the differences from previous research.
One factor that may contribute, at least in part, to this inconsistency is the young age of
the children included in the study. Although previous studies have included younger
children (e.g., Carpentieri & Morgan, 1996 included children as young as 4-years-old;
Joseph et al., 2002 included children as young as 3-years-old), no studies involved only
3-year-olds; instead studies included individuals from a wide range of ages. Thus, it may
be the case that the percentage of children classified as autistic and functioning in the
cognitively impaired range may vary with age. Perhaps children with the most severe
symptoms of autism are those typically identified when they are as young as 3, but more
children with less severe symptoms may be identified as autistic when they are older and
their symptoms become evident, thus increasing the percentage in the cognitively
impaired range at older ages.
Another contributing factor may be the participants' participation in early
intervention services. Although data were not collected on whether participants were
receiving early intervention services, it is reasonable to assume they were. Participants
were identified as individuals diagnosed or classified as children with autism by
pediatricians or school-based early intervention providers, thus they were very likely to
be receiving services. Previous research has clearly demonstrated the effectiveness of
early intensive behavioral intervention for skill acquisition and in decreasing
inappropriate behavior for children with autism (see Makrygianni & Reed, 2010 for a
recent meta-analytic review). More specifically, large effect sizes have been found for
the improvement in cognitive abilities for children with autism. Although the current
participants were 3 years of age, thus unlikely to have been involved in early intervention
services for an extended time period, data suggest the duration of early intervention
services may not be as important as other characteristics of early intervention programs
(e.g., intensity, quality; Makrygianni & Reed, 2010). Therefore, it is possible that early
intervention services provided to participants had a positive impact on their cognitive
functioning regardless of the duration of such programming. Future studies could include
data regarding early intervention services participants are receiving to allow for an
evaluation of their potential influence on cognitive functioning.
A third factor is the small number of participants. Because ofthe small sample
size the results may not represent the level of cognitive functioning of the population of
3-year-old children with autism. To further evaluate the percentage of children with
autism functioning in the cognitively impaired range, future studies could obtain a larger
A final contributing factor may be the increase in the diagnosis of autism over the
past several years. Large increases in autism spectrum diagnoses have been well
documented in the literature (Kogan et al., 2009; Mulvihill et al., 2009). The literature
indicates that 1% of children in the United States have an autism spectrum disorder
diagnosis. This figure represents a 57% increase in diagnosis over a period of 4 years
(2002 to 2006). One potential implication of an increase in diagnostic rates is that
children with less severe impairment are being indentified. Previously, it might have
been the case that a diagnosis of autism was reserved for only those individuals with the
most severe impairments. As a result, there would have been a high concentration of
individuals with autism functioning in the cognitively impaired range. However, if
individuals with less severe impairment are increasingly being identified, this would
dilute the percentage of individuals with autism also functioning in the cognitively
impaired range.
Although less than 75% of participants fell in the cognitively impaired range,
significant differences between mean scores on the CAS-2 and WPPSI-III were not
found. A primary purpose of the current study was to attempt to identify assessment
practices that circumvent problems commonly encountered when testing individuals with
autism. It was suggested that these difficulties might negatively influence scores
obtained on standardized intelligence tests. As such it was hypothesized that the use of a
test (i.e., the CAS-2) that does not have timed items and involved toys children usually
find interesting, in combination with preferred items/edibles and a fast administration
pace (facilitated by a second administrator to help hand the primary evaluator test
materials) would result in obtaining significantly higher scores than on a measure (i.e.,
the WPPSI-III) that did not include these materials or involve these procedures. Results
did not support these hypotheses. Thus, at least for 3-year-olds diagnosed with autism,
the use of cognitive measures with toys and no timed items, and the use of fast pacing
and preferred items do not appear to enhance test performance and may not be necessary.
However, previous research has demonstrated enhanced test performance when
correct responses were followed by reinforcement during standardized intelligence
testing for other groups of young children (e.g., Bradley-Johnson, Johnson, Shanahan,
Rickert, & Tardona, 1984). A limitation ofthe current study was the lack of empirical
support that preferred items functioned as reinforcers. This limitation likely affected the
outcome of this study because providing preferred items contingent on appropriate test
behavior might not serve the purpose of maintaining motivation and desired behavior
(Mason, McGee, Farmer-Dougan, & Risley, 1989; Wacker, Berg, Wiggings, Muldoon, &
Cavanaugh, 1985). Future studies should systematically identify and evaluate preferred
items to ensure that they are reinforcing.
One potential avenue to evaluate the reinforcing value of objects or activities is to
incorporate caregiver generated items into a choice assessment, because this
methodology is associated with identifying potent reinforcers (Fisher, Piazza, Bowman,
& Amari, 1996). Furthermore, it will be important for future studies to specify when and
how frequently during testing reinforcement was provided. Another line of research
could evaluate whether procedures implemented during the current study might show
different effects for older individuals with autism.
Several previous studies reported lower scores on verbal measures than on
measures of performance, particularly for younger children (e.g., Filipek et al., 2000;
Joseph, Tager-Flushbery & Lord, 2002; Sigman, 1998). Results from the current study
did not find significant differences between CAS-2 GCQ and NCQ scores, or WPPSI-III
Verbal Scale and WPPSI-III Performance Scale scores. The CAS-2 GCQ involves both
verbal and nonverbal items, whereas the verbal and performance items are separated on
the WPPSI-III composites. However, some previous research (Joseph et al., 2002)
suggests that the verbal < nonverbal profile is the most distinct cognitive profile for
students with autism. Although verbal/performance differences were not significant in
the current study a majority ofthe participants demonstrated a GCQ > NCQ and WPPSIIII Verbal Scale > WPPSI-III Performance Scale pattern of performance. The difference
was from 1 to 16 points for 5 of the 9 children on the CAS-2 and from 1 to 44 points for
10 of the 16 children on the WPPSI-III. Thus, the tendency for 3 -year-olds in this study
who were verbal was to receive higher verbal than performance results on both measures.
Perhaps verbal difficulties may not be as apparent at 3 years of age. Future studies could
evaluate if young children with autism, who initially display a performance < verbal
profile, eventually demonstrate the common verbal < performance pattern as language
expectations increase with age.
Whether the tendency for participants who were verbal to receive higher verbal
than performance results reflected a true verbal advantage is questionable. Although the
WPPSI-III Full Scale includes a number of verbal items and the test includes a Verbal
composite, the test was essentially a nonverbal measure for the current sample of 3-yearolds. An examination of core items on the WPPSI-III 2-6 through 3-11 Form indicated
that no items on the Receptive Vocabulary, Block Design or Object Assembly subtests
require a verbal response. For the Information subtest the first 9 items do not require a
verbal response, but 24 of the 25 remaining items do. For the current sample, only 4 of
the 16 participants provided at least one correct response after item 9 on this subtest.
Thus, for 12 participants, the WPPSI-III Full Scale did not require a verbal response and
was essentially a nonvocal measure. This might be why a significant performance >
verbal result found in prior studies was not found for the current sample.
In addition, specific subtest patterns have been reported for children with autism.
On the Wechsler Scales, previous literature suggests that Block Design is usually the
highest subtest (Filipek et al., 2000; Joseph et al., 2002), whereas, for 3-year-olds in the
current study Block Design was typically the lowest. However, prior studies involved a
wider age span than only 3-year-olds. Some studies reported Object Assembly as the
highest (Newson & Hovanitz, 1997). Performance on Object Assembly was second
highest for the current sample. The current sample generally scored the highest on the
Receptive Vocabulary subtest. The Comprehension subtest is typically the lowest for
these children (Filipek et al., 2000), however this subtest is not administered to 3-yearolds. Current results provide some evidence that WPPSI-III Performance subtest patterns
may vary with age. Future studies could systematically evaluate subtest patterns in
individuals with autism by including a wide range of ages and evaluate performance by
Caregivers of participants were sent summary reports based on their child's
performance on the CAS-2 (Appendix H presents an example of a summary report).
Parents indicated recommendations were effective. Therefore, it seems practical to
incorporate the CAS-2 into assessments of young children with autism, as parents find
the results provided by this measure useful. However, in future studies, it would be
important to objectively determine if recommendations were actually implemented and if
the children acquired the skills. Follow-up testing using the CAS-2 is one mechanism by
which this potential outcome could be evaluated. From the standpoint of social validity,
these results regarding the reports are important and encouraging. Additional studies
could evaluate the extent to which information provided by the CAS-2 is useful for
teachers of children with autism, as well as applicable for children with autism of other
Future studies are needed to address gaps in the literature regarding best practices
for testing the cognitive functioning of individuals with autism, particularly by age level.
Further research is needed to better understand the cognitive profiles of individuals with
autism, particularly at young ages. As data from this study suggest, young children with
autism may perform differently than older children. Additional research might be helpful
in interpreting cognitive testing results and providing clinically useful recommendations.
Until additional research on the use of procedures aimed at circumventing difficulties
encountered when testing the cognitive ability of individuals with autism is available,
examiners will continue to struggle to obtain the best performance from many individuals
with autism.
R340.1715 Autism defined; determination.
Rule 15
(1) Autism means a lifelong developmental disability that is typically manifested
before 30 months of age. Autism is characterized by disturbances in the rates and
sequences of cognitive, affective, psychomotor, language, and speech
(2) The manifestation of the characteristics specified in subrule (1) of this rule and
all of the following characteristics shall determine if a student has autism:
(a) Disturbance in the capacity to relate appropriately to people, events,
and objects
(b) Absence, disorder, or delay of language, speech, or meaningful
(c) Unusual or inconsistent response to sensory stimuli in 1 or more of the
following: (i) sight, (ii) hearing, (iii) touch, (v) pain, (v) balance, (vi)
smell, (vii) taste, (viii) The way a student holds his or her body.
(d) Insistence on sameness as shown by stereotyped play patterns,
repetitive movements, abnormal preoccupation, or resistance to change.
(3) To be eligible under this rule, there shall be an absence of the characteristics
associated with schizophrenia, such as delusions, hallucinations, loosening of
associations, and incoherence.
(4) A determination of impairment shall be based upon a comprehensive evaluation by a
multidisciplinary evaluation team. The team shall include, at a minimum, a psychologist
or psychiatrist, an authorized provider of speech and language services, and a school
social worker.
A. A total of six (or more) items from (1), (2), and (3), with at least two from (1), and one
each from (2) and (3):
(1) qualitative impairment in social interaction, as manifested by at least two ofthe
(a) marked impairment in the use of multiple nonverbal behaviors such as eye-to-eye
gaze, facial expression, body postures, and gestures to regulate social interaction
(b) failure to develop peer relationships appropriate to developmental level
(c) a lack of spontaneous seeking to share enjoyment, interests, or achievements with
other people (e.g., by a lack of showing, bringing, or pointing out objects of interest)
(d) lack of social or emotional reciprocity
(2) qualitative impairments in communication as manifested by at least one of the
(a) delay in, or total lack of, the development of spoken language (not accompanied by an
attempt to compensate through alternative modes of communication such as gesture or
(b) in individuals with adequate speech, marked impairment in the ability to initiate or
sustain a conversation with others
(c) stereotyped and repetitive use of language or idiosyncratic language
(d) lack of varied, spontaneous make-believe play or social imitative play appropriate to
developmental level
(3) restricted repetitive and stereotyped patterns of behavior, interests, and activities, as
manifested by at least one of the following:
(a) encompassing preoccupation with one or more stereotyped and restricted patterns of
interest that is abnormal either in intensity or focus
(b) apparently inflexible adherence to specific, nonfunctional routines or rituals
(c) stereotyped and repetitive motor mannerisms (e.g., hand or finger flapping or twisting,
or complex whole-body movements)
(d) persistent preoccupation with parts of objects
B. Delays or abnormal functioning in at least one of the following areas, with onset prior
to age 3 years: (1) social interaction, (2) language as used in social communication, or (3)
symbolic or imaginative play.
C. The disturbance is not better accounted for by Rett's Disorder or Childhood
Disintegrative Disorder.
A pervasive developmental disorder defined by the presence of abnormal and/or impaired
development that is manifest before the age of 3 years, and by the characteristic type of
abnormal functioning in all three areas of social interaction, communication, and
restricted, repetitive behaviour. The disorder occurs in boys three to four times more
often than in girls.
Diagnostic Guidelines
Usually there is no prior period of unequivocally normal development but, if there is,
abnormalities become apparent before the age of 3 years. There are always qualitative
impairments in reciprocal social interaction. These take the form of an inadequate
appreciation of socio-emotional cues, as shown by a lack of responses to other people's
emotions and/or a lack of modulation of behaviour according to social context; poor use
of social signals and a weak integration of social, emotional, and communicative
behaviours; and, especially, a lack of socio-emotional reciprocity. Similarly, qualitative
impairments in communications are universal. These take the form of a lack of social
usage of whatever language skills are present; impairment in make-believe and social
imitative play; poor synchrony and lack of reciprocity in conversational interchange; poor
flexibility in language expression and a relative lack of creativity and fantasy in thought
processes; lack of emotional response to other people's verbal and nonverbal overtures;
impaired use of variations in cadence or emphasis to reflect communicative modulation;
and a similar lack of accompanying gesture to provide emphasis or aid meaning in
spoken communication.
The condition is also characterized by restricted, repetitive, and stereotyped patterns of
behaviour, interests, and activities. These take the form of a tendency to impose rigidity
and routine on a wide range of aspects of day-to day functioning; this usually applies to
novel activities as well as to familiar habits and play patterns. In early childhood
particularly, there may be specific attachment to unusual, typically non-soft objects. The
children may insist on the performance of particular routines in rituals of a nonfunctional
character; there may be stereotyped preoccupations with interests such as dates, routes or
timetables; often there are motor stereotypies; a specific interest in nonfunctional
elements of objects (such as their smell or feel) is common; and there may be a resistance
to changes in routine or in details of the personal environment (such as the movement of
ornaments or furniture in the family home).
In addition to these specific diagnostic features, it is frequent for children with autism to
show a range of other nonspecific problems such as fear/phobias, sleeping and eating
disturbances, temper tantrums, and aggression. Self-injury (e.g. by wrist-biting) is fairly
common, especially when there is associated severe mental retardation. Most individuals
with autism lack spontaneity, initiative, and creativity in the organization of their leisure
time and have difficulty applying conceptualizations in decision-making in work (even
when the tasks themselves are well within their capacity). The specific manifestation of
deficits characteristic of autism change as the children grow older, but the deficits
continue into and through adult life with a broadly similar pattern of problems in
socialization, communication, and interest patterns. Developmental abnormalities must
have been present in the first 3 years for the diagnosis to be made, but the syndrome can
be diagnosed in all age groups.
All levels of IQ can occur in association with autism, but there is significant mental
retardation in some three-quarters of cases.
* autistic disorder
* infantile autism
* infantile psychosis
* Kanner's syndrome
Differential Diagnosis
Apart from the other varieties of pervasive developmental disorder it is important to
consider: specific developmental disorder of receptive language (F80.2) with secondary
socio-emotional problems; reactive attachment disorder (F94.1) or disinhibited
attachment disorder (F94.2); mental retardation (F70-F79) with some associated
emotional/behavioural disorder; schizophrenia (F20.- ) of unusually early onset; and
Rett's syndrome (F84.2).
* autistic psychopathy (F84.5)
Date: Year, Month
Dear Pediatrician/School Administrator,
I am completing a research study investigating the cognitive levels of 3-year-old
children diagnosed with autism. Specifically, the goal of my study is to avoid many of the
difficulties often associated with the assessment of children with autism, in hopes of
obtaining more accurate results. The results from the study will have implications
regarding the assessment of cognitive abilities for these children. The data collected from
this study will appear in my dissertation, which will fulfill partial requirements for my
degree, Doctor of Philosophy in School Psychology, at Central Michigan University.
Your help is requested in recruiting participants for this research. The following
criteria will be used to select children for the study: (a), age 3 years, 0 months through 3
years, 1 1 months and (b). diagnosed with autistic disorder by a physician or psychologist.
Children will be given two tests of cognitive development and parents will be asked to
complete two rating scales. Testing will be done at Central Michigan University or in the
child's residence and will take about 45 to 75 minutes. Because of tests I will use for the
study, I cannot include children with severe hearing, visual and motor impairments. For
participating, I will give the parents of each child $25.00 and a summary report
describing their child's strengths and areas to work on next.
If you can assist me in locating these children, please sign the enclosed
permission form and return it in the enclosed envelope. Once I receive that form, I will
bring or send you copies of a cover letter and permission form to give to parents whose
children may qualify for the study. If you have any questions or concerns, do not hesitate
to contact me at 989-774-3403, or you can contact my thesis supervisor at Central
Michigan University, Dr. Sharon Bradley-Johnson, at 989-774-6480.
Additionally, ifthe child's parent/caregiver request it, you will be sent a copy of
my findings regarding the child.
I appreciate your time and consideration in helping me with my study. I look
forward to hearing from you.
Jason Vladescu
Doctoral School Psychology Candidate
Central Michigan University
Consent to Participate:
, agree to assist in the study being carried out
by Jason Vladescu at Central Michigan University entitled, "Cognitive functioning in
children with autism: Circumventing common assessment problems". I will help to
recruit participants for the study by providing parents will information regarding the
Signature of Pediatrician/School Administrator
Signature of Researcher
Date: Year, Month
Dear Parent/Caregiver,
I am a doctoral student in the School Psychology Program working under the
supervision of Dr. Sharon Bradley-Johnson, a faculty member ofthe Psychology
Department at Central Michigan University. I am conducting a research project for my
dissertation with 3-year-old children who have an autism diagnosis. I am investigating
the cognitive levels ofthese children. The goal of the study is to avoid many of the
difficulties often found when testing children with autism, in the hope of obtaining more
accurate results.
Because your child's age is between 3 years, 0 months and 3 years, 1 1 months
and your child has an autistic disorder diagnosis, I would appreciate your assistance. If
you would be willing to help with this project, please read and initial/sign the enclosed
forms and return them in the enclosed envelope. Your child's participation or non-
participation in this study will not affect his/her school program or medical care.
Unless you request it, information collected will be kept confidential and results
will not be given to the child's school or physician.
I would appreciate your help and hope you will be willing to allow your child to
participate in my study. Thank you for your time and cooperation.
Jason Vladescu
Doctoral School Psychology Candidate
Central Michigan University
Parent Permission/Consent Form
Title of Project: Cognitive functioning in children with autism: Circumventing common
assessment problems
Investigators: Jason Vladescu & Dr. Sharon Bradley-Johnson
Phone: 989-775-3403
Your son/daughter is invited to participate in a research project because he/she is
between 3 years, 0 months and 3 years, 1 1 months old and has a diagnosis of autistic
disorder. Information below will help you make an informed decision on whether or not
to allow your child to participate. If you have any questions about the project, please ask.
The goal of my study is to avoid many of the difficulties often found when
assessing children with autism, in hopes of obtaining more accurate results. The results
from the study will have implications regarding the assessment of cognitive abilities for
these children. In addition, I will give participating parents a summary report of their
child's cognitive strengths and difficulties. Hopefully, this will be useful in helping
parents determine what skills their child has learned and what skills would be appropriate
to teach next.
Each child will be given two tests to assess their cognitive abilities. This will take
45 to 75 minutes. Parents will be asked to complete two rating scales: one is used to help
in the diagnosis autism and one that describes the child's daily living skills. Once the
testing is completed, parents will be given $25.00 and be sent a summary report of their
child's performance, as well as recommendations to improve difficulties.
The data collected from this study will appear in my written dissertation, which
will fulfill the partial requirements for the degree, Doctor of Philosophy (Ph.D.) in School
Parental responsibilities for this study will include:
(1). Allowing the researcher to give two tests that measures the cognitive abilities to your
child. The tests will take approximately 45-75 minutes to complete.
(2). Parents completing an adaptive rating behavior scale. Completing this form will take
approximately 20 minutes to complete.
(3). Completing an autism rating scale. Completing this form will take approximately 510 minutes.
(4). Bringing your child to the Psychology Laboratory at Central Michigan University or
allowing the researcher to come to your home to complete the testing.
(Initial here after reading)
(5). Completing a brief questionnaire regarding the summary report you will receive after
the testing of your child.
You may be present in the room with your child for all the testing, along with the
researcher and research assistant.
Any information obtained during this study that could identify you or your child
will be kept strictly confidential. Background information about your child will be used
only to describe the children in the project. The information may be published in
scientific journals or presented at scientific meetings but the names of parents and
children will be kept strictly confidential. Children will be give a code name to use for
any records in the study and the key for the code will be kept separate from protocols in a
locked cabinet and destroyed upon completion of the study. At any time in the study you
may withdraw your child and all information collected on your child will be destroyed
Participation is voluntary. No known discomfort or risk is involved for children
participating. Children typically enjoy the attention and opportunity to play with the toys.
If any procedure for the study is changed, you will be informed and your consent
obtained for the revised procedure.
If you agree to let your child participate, please complete and return the attached
forms as soon as possible in the enclosed envelope. You will be given a signed and dated
copy of this form to keep.
If you have any questions, please do not hesitate to ask them. If you have
additional questions later, we will be happy to answer them. Questions or concerns can be
directed to the researchers:
Jason Vladescu
Sharon Bradley-Johnson, Ed.D
Further questions can be brought to the attention of the Human Subject Protection
Coordinator of the Institutional Review Board (IRB office) at 989-774-6777.
Thank you very much for your help with this project.
(Initial here after reading)
Consent to Participate:
I understand the purpose of the study and issues around consent. I have read the
above information and agree to participate in this study and allow my child to participate.
I have received a copy of this consent form for my own records.
Name of Parent(s) or Guardian(s):
Signature of Parent(s) or Guardian(s):
Child's Name:
Examiner's Name:
Examiner's Qualifications:
In my judgment, the parent(s) or guardian(s) is voluntarily and knowingly giving
informed consent to participate in this research study.
Name of researcher:
Signature of Researcher:
Completed by: Mother:
Child's age:
Child's date of birth:
Child's gender: Girl:
Child's race/ethnicity:
White Non-Hispanic:
Native American (i.e., American Indian):
Asian American:
Please list which:
Please list which:
Name of test(s) used to diagnosis your child?
Name two rewards your child would most enjoy earning (can include specific foods
and/or toys):
Parent's race/ethnicity:
White Non-Hispanic:
Native American (i.e., American Indian):
Asian American:
Please list which:
Please list which:
Highest Grade Completed By Mother:
Less than High School:
High School Graduate or GED:
Some College or Technical School (1-3 years):
Bachelor's Degree:
Master's, Professional or Doctoral Degree:
Urban/Suburban (population of 2,500 or more):
Rural (0 to 2,499):
Phone Number where you can be reached (please include area code):
Best time to call you to arrange an appointment:
Completed by parent(s) or guardian(s)
Please indicate how you would rate the following based on the investigators' summary
(Circle your answer)
1 . Clear and easy
to understand
2. Learned something
new about my
3. Described
important skills
4. Recommendations
were practical and AGREE
easy to use
5. Recommendations AGREE
will be effective
Andrew's Summary Report
Language. Andrew demonstrated an understanding of position words including:
in, under, together, up, down, around, next to, and awayfrom. He also correctly pointed
to familiar objects such as a bird and a sock and demonstrated an understanding of the
pronouns your and him,
Language skills Andrew may benefit from practicing include the position words
top and infront of, and the pronouns / and she.
Early Reading. Andrew turned pages one-at-a-time and pointed to pictures I
named in a book.
An important skill to develop next is turning books right-side-up
Early Math. He understood math concepts such as all, full, tall, and more.
Skills to practice next with Andrew include understanding the concepts little,
empty, short, ma fewer, as well as holding up the correct number of fingers to indicate
his age.
Early Handwriting. Andrew used an appropriate writing position, and
successfully copied a circle, vertical line and a plus sign from pictures. Also, he
successfully drew a horizontal line after watching me draw one.
He held the pencil with a fist rather than with his fingers. Practice using an
approximate 3-finger grasp and holding the pencil about 1 inch from the tip will give him
better control of the pencil. Use of a colorful pencil gripper may help him remember
where to hold the pencil.
Enabling Behaviors. This subtest assesses physical and verbal imitation a skill
important for school success. In terms of imitation, Andrew imitated a couple of words
and gestures. Imitation is important because it helps children learn new skills quickly and
practice other skills. It will be important to continue practicing skills related to imitating
both words and gestures with Andrew so that he becomes even better at imitating others.
Children with Autism
ABAS-II Autism
Mean Difference
Samplesof the Two
4.4 (3.7)
4.1 (2.4)
7.8 (3.9)
Scores -2
5.3 (2.2)
5.4 (2.7)
4.2 (2.9)
4.5 (3.3)
4.9 (3.3)
3.9 (2.8)
5.9 (2.6)
6.0 (3.4)
3.5 (1.8)
6.7 (3.0)
5.1 (2.7)
7.1 (2.0)
76.1 (17.7)
Social Domain
Community Use
Functional PreAcademics
Home Living
Health and
4.7 (3.2)
5.6 (3.3)
8.4 (3.6)
Scores -2
t value
? value
Practical Domain
67.9 (12.0)
General Adaptive 68.9 (14.6)
Cases with > 2 skill areas -2 SD
Cases with > 1 adaptive domain
Cases with > 1 adaptive domain
or the GAC -2 SD
Note. -2 SD = 2 or more SDs below the mean.
*p < .05.
Akshoomoof, N. (2006). Use of the Mullen Scales of Early Learning for the assessment
of young children with autism spectrum disorders. Child Neuropsychology, 12,
American Academy of Pediatrics. (2001). Developmental surveillance and screening of
infants and young children. Pediatrics, 108(1), 192-196.
American Psychiatric Association. (2000). Diagnostic and Statistical Manual ofMental
Disorders (4th ed., text rev.). Washington, D.C.: Author.
Autism Society of America. (2003). Autism Facts. Retrieved May 23, 2005 from the
World Wide Web:
Autism Society of America. (2003). Definition of Autism. The Advocate: Newsletter of
the Autism Society ofAmerica, 26, 3.
Bayley, N. (1993). Bayley Scales ofInfant Development (2nd ed.). San Antonio, TX:
The Psychological Corporation.
Bradley-Johnson, S., Johnson, C, Shanahan, R., Rickert, V., & Tardona, D. (1984).
Effects of token reinforcement on WISC-R performance of black and white, low
socioeconomic second graders. Behavioral Assessment, 6, 365-373.
Bradley-Johnson, S. & Johnson, CM. (2001). Cognitive Abilities Scale (T ed.). Austin,
Bristol, M. M., Cohen, D.J., Costello, E.J., Denckla, M., Eckberg, T. J., Kallen, R.,
Kraemer, H. C, . . .Spence, M. A. (1996). State of the science in Autism: Report
to the National Institutes of Health. Journal ofAutism and Developmental
Disorders, 26, 121-157.
Bruiniks, R.H., Woodcock, R.W., Weatherman, R.F., & Hill, B.K. (1996). Scales of
Independent Behaviors - Revised. Itasca, IL: Riverside Publishing Company.
Butter, E. M., Mulick, J. A., & Metz, B. (2006). Eight case reports of learning recovery in
children with pervasive developmental disorders after early intervention.
Behavioral Interventions, 21, 227-243.
Carpentieri, S., & Morgan, S.B. (1996). Adaptive and intellectual functioning in autistic
and nonautisitc retarded children. Journal ofAutism and Developmental
Disorders, 26, 611-620.
Cohen, J. (1992a). A power primer. Psychological bulletin, 112, 155-159.
Cohen, J. (1992b). Statistical power analysis. Current Directions in Psychological
Science, 7,98-101.
Cohen, M. (1997). Children 's Memory Scale. San Antonio, TX: The Psychological
Eaves, L.C., & Ho, H.H. (2004). The very early identification of Autism: Outcome to
age 4 1/2 - 5. Journal ofAutism and Developmental Disorders, 34, 367-378.
Elliott, CD. (1990). Differential Ability Scales. San Antonio, TX: The Psychological
Field, A. (2009). Discovering statistics using SPSS: Sage Publications Ltd.
Filipek, P.A., Accardo, P.J., Ashwal, S., Baranek, G.T., Cook, Jr., E.H., Dawson, G.,
Gordon, B., ... Volkmar, F.R. (2000). Practice parameter: Screening and
diagnosis of autism: Report of the quality standards subcommittee of the
American Academy ofNeurology and the Child Neurology Society. Neurology,
55, 468-479.
Fisher, W., Piazza, C, Bowman, L., & Amari, A. (1996). Integrating caregiver report
with systematic choice assessment to enhance reinforcer identification. American
Journal ofMental Retardation, 101, 15-25.
Fombonne, E. (2003). The prevalence of Autism. Journal ofthe American Medical
Association, 289, 87-89.
Freeman, BJ., Rahbar, B., Ritvo, E.R., Bice, T.L., Yokota, A., & Ritvo, R. (1991). The
stability of cognitive and behavioral parameters in Autism: A twelve-year
prospective study. Journal ofthe American Academy ofChild andAdolescent
Psychiatry, 30, 479-482.
Freeman, B.J., & Cronin, P. (2002). Diagnosing Autism Spectrum Disorder in young
children: An update. Infants and Young Children, 14, 1-10.
French, D. (2001). Pictorial Test ofIntelligence (2nd ed.). Austin, TX: PRO-ED.
Geiger, D.M., Smith, D.T., & Creaghead, N.A. (2002). Parent and professional
agreement on cognitive level of children with autism. Journal ofAutism &
Developmental Disorders, 32, 307-312.
Gilliam, J. E. (2006). Gilliam Autism Rating Scale (2nd ed.). Austin, TX: PRO-ED.
Harris, S. L., & Handleman, J. S. (2000). Age and IQ at intake as predictors of placement
for young children with autism: A four- to six-year follow-up. Journal ofAutism
and Developmental Disorders, 30, 137-142.
Harrison, P.L., & Oakland, T. (2003). Adaptive Behavior Assessment System (2n
ed.). San Antonio, TX: Harcourt Assessment Incorporated.
Individuals with Disabilities Education Improvement Act of 2004, Pub. L. 108-446, 118
Stat. 2647, 2004 Enacted H.R. 1350; 108 Enacted H.R. 1350. To be codified at 20
U.S.C. 1400 et seq.
Joseph, R.M., Tager-Flishberg, H., & Lord, C. (2002). Cognitive profiles and social communicative functioning in children with autism spectrum disorder. Journal
ofChild Psychology and Psychiatry, 43, 807-821.
Kanner, L. (1943). Autistic disturbances of affective contact. Nervous Child, 2, 817-850.
Klin, A., Chawarska, K., Paul, R., Rubin, E., Morgan, T., Wisner, L., & Volkmar, F.
(2004). Autism in a 15-month-old child. American Journal ofPsychiatry, 161,
Klinger, L.G., & Dawson, G. (1996). Autistic Disorder. In E. J. Mash & R.A. Barkley
(Eds.), Child Psychopathology (pp. 311-339). New York: Guilford Press.
Kogan, M., Blumberg, S., Schieve, L., Boyle, C, Perrin, J., Ghandour, R., ... van Dyck,
P. C. (2009). Prevalence of parent-reported diagnosis of autism spectrum disorder
among children in the US, 2007. Pediatrics, 124, 1395-1403.
Krug, D.A., Arick, J.R., & Almond, PJ. (1993). Autism Screening Instrumentfor
Educational Planning (2nd ed.). Austin, TX: PRO-ED.
Lincoln, A.J., Courchesne, E., Kliman, B.S., Elmasian, R., & Allen, M. (1988). A study
of intellectual abilities in high-functioning people with autism. Journal ofAutism
and Developmental Disorders, 18, 505-523.
Lincoln, A.J., Courchesne, E., Allen, M., Hanson, E., & Ene, M. (1998). Neurobiology of
Asperger syndrome: Seven case studies and quantitative magnetic resonance
imaging findings. In E. Schopler, G. Mesibov, & LJ. Kunce (Eds.), Asperger
syndrome or high-functioning autism? (pp. 146-166). New York: Plenum.
Lovaas, O.I. (1981). Teaching developmentally disabled children: The ME book.
Baltimore, Maryland: University Park Press.
Lovaas, O.I. (1987). Behavioral treatment and normal educational and intellectual
functioning in young Autistic children. Journal ofConsulting and Clinical
Psychology, 55, 3-9.
Lovaas, O.I. (1993). Long-term outcome for children with autism who received early
intensive behavioral treatment. American Journal on Mental Retardation, 94,
Lovaas, O.I. (2003). Teaching individuals with developmental delays: Basic intervention
techniques. Austin, TX: PRO-ED.
Mason, S. A., McGee, G. G., Farmer-Dougan, V., & Risley, T. R. (1989). A practical
strategy for ongoing reinforcer assessment. Journal ofApplied Behavior Analysis,
22, 171-179.
Morgan, S.B., Campbell, J.M., & Jackson, J.N. (2003). Autism and mental retardation. In
M.C. Roberts (Ed.), Handbook ofPediatric Psychology (pp. 510-528). New York:
The Guilford Press.
Mulvihill, B., Wingate, M., Kirby, R.S., Pettygrove, S., Cunniff, C, Meaney, F.J., Miller,
L., . . .Doernberg, N. (2009). Prevalence of autism spectrum disorders - Autism
and Developmental Disabilities Monitoring Network, United States, 2006.
Morbidity and Mortality Weekly Report Summaries, 58, 1-20
New York State Department of Health: Early Intervention Program. (1999). Clinical
practice guideline: The guideline technical report: Autism/pervasive
developmental disorders: Assessment and interventionfor young children (age 03 years). New York: Author.
Newson, C, & Hovanitz, CA. (1997). Autistic disorder. In EJ. Mash & L.G. Terdal
(Eds.), Assessment ofChildhood Disorders (pp. 408-452). New York: Guilford
Newsom, C. (1998). Autistic disorder. In EJ. Mash & R.A. Barkley (Eds.), Treatment of
childhood disorders (pp. 416-467) . New York: Guilford Press.
Ozonoff, S., Goodlin-Jones, B.L. & Solomon, M. (2005). Evidence-based assessment of
autism spectrum disorders in children and adolescents. Journal ofClinical Child
and Adolescent Psychology, 34 (3), 523-540.
Scheuffgen, K., Happe, F., Anderson, M., & Frith, U. (2000). High "intelligence," low
"IQ"? Speed of processing and measured IQ in children with Autism.
Development Psychopathology, 12, 83-90.
Shriver, M. D., Allen, K. D., & Mathews, J.R. (1999). Effective assessment of the shared
and unique characteristics of children with autism. School Psychology Review,
28, 538-558.
Sigman, M. (1998). The Emanuel Miller Memorial Lecture 1997: Change and continuity
in the development of children with autism. Journal ofChild Psychology &
Psychiatry, 39, 817-827.
Sparrow, S.S., Balla, D.A., & Cicchetti, D.V. (1984). Vineland Adaptive Behavior Scale.
Circle Pines, MN: American Guidance System.
Swanson, J., Bradley-Johnson, S., Johnson, C, & Rubenaker, O. (2009). The Cognitive
Abilities Scale-Preschool Form: Studies of concurrent criterion-related, construct,
and predictive criterion-related validity. Journal ofPsychoeducational
Assessment, 27, 46-56.
The Psychological Corporation. (2001). Wechsler Individual Achievement Test (2 ed.).
San Antonio, TX: Author.
United States Government Accountability Office. (2005). Report to the chairman and
ranking minority member, subcommittee on human rights and wellness,
committee on government reform, House ofRepresentatives: Special education:
Children with autism. Document number: GAO-05-220. Document Distribution
Center: Washington, DC.
Vacca, J. J. (2007). Incorporating interests and structure to improve participation of a
child with autism in a standardized assessment: A case study analysis. Focus on
Autism and Other Developmental Disabilities, 22, 51-59.
Wacker, D. P., Berg, W. K., Wiggins, B. Muldoon, M., & Cavanaugh, J. (1985).
Evaluation of reinforcer preferences for profoundly handicapped students.
Journal ofApplied Behavior Analysis, 18, 173-178.
Wechsler, D. (1989). Wechsler Preschool and Primary Scale ofIntelligence - Revised.
San Antonio, TX: The Psychological Corporation.
Wechsler, D. (1991). The Wechsler Intelligence Scalefor Children (3rd ed.). San Antonio,
TX: The Psychological Corporation.
Wechsler, D. (2002). Wechsler Preschool and Primary Scale ofIntelligence (3rd ed.). San
Antonio, TX: The Psychological Corporation.
Wetherby, A. M., Woods, J., Allen, J., Cleary, J., Dickinson, H., & Lord, C. (2004). Early
indicators of autism spectrum disorders in the second year of life. Journal of
Autism and Developmental Disorders, 34, 473-493.
Wicks-Nelson, R., & Israel, A.C. (2000). Behavior Disorders ofChildhood. Upper
Saddle River, NJ: Prentice-Hall.
World Health Organization. (2003). International Statistical Classification ofDiseases
and Related Health Problems (10th ed.). Retrieved March 24, 2005 from the
World Wide Web:
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