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Executive functions of preschool children with autism spectrum disorders

ProQuest Dissertations and Theses, 2011
Dissertation
Author: Maria Colon-Torres
Abstract:
Every day, school professionals encounter the need for research-based assessment and intervention practices which target executive function profiles in preschool children with developmental delays. While current research focuses on describing characteristics of autistic tendencies during early childhood years, very few studies exist that compare preschool children's executive function profiles based on rating scales with performance-based assessment. The purpose of this study was to compare specific neurocognitive profiles of preschool-aged children with autism based on their performance on the NEPSY-II and on the teachers' ratings on the BRIEF-P. Additionally, this study used a quantitative design to explore whether age of symptoms onset, age of enrollment in Early Intervention services, and intensity of therapy services provided can differentiate learning profiles, particularly executive functions of preschool children with autism spectrum disorders. The sample of the study was composed of 12 preschool students ranging from 3 to 5 years of age. The sample's educational placement was an out-of-district placement. The sample was one of convenience. A number of conclusions were obtained pertaining to age of symptoms onset and support services provided by EI before the child's third birthday. An early age of symptoms onset was considered to predict eligibility for occupational therapy services. Also, EI services were found to be associated with lower performance on the Attention and Executive Functioning domain. Results from the interaction between Attention and Executive Functioning domain, Inhibit Self Control Index, and General Executive Composite, and the comparison between Social Perception domain and Flexibility Index, did not reveal significant differences when compared with profiles from the NEPSY: A Developmental Neuropsychological Assessment-2 nd Edition (NEPSY-II; Korkman, Kirk, & Kemp, 2007), and the Behavior Rating Inventory of Executive Functioning-Preschool Version (BRIEF-P; Gioia, Espy, & Isquith, 2003). The results drawn from the comparison between Memory and Learning, Emergent Metacognitive, and General Executive Composite ratings showed significantly different profiles. Lastly, this study offered recommendations for future research on executive functioning in preschool children with autism spectrum disorders (ASDs).

TABLE OF CONTENTS Chapter Page I INTRODUCTION……………………………………………….. 1

Autism as a Neuropsychological Disorder………………………. 3 Responses to Increasing Autism Rates…………………………... 5 Executive Functions and ASDs………………………………..…. 8 Neuropsychological Instruments of Executive Functioning……... 11 Statement of the Problem………………………………………… 15 Research Questions and Hypotheses……………………………... 17 Purpose of the Study……………………………………………… 23 Definition of the Terms…………………………………………… 23 Assumptions……………………………………………………… 27 Limitations of the Study………………………………………….. 27

II LITERATURE REVIEW………………………………………… 29 Autism: An Overview ……………………………………………. 29 Identification Issues: DSM-IV vs. IDEIA Criteria……………….. 34 Incidence and Prevalence Rates…………………………………... 39 Developmental Factors: Age of Symptoms Onset……………….. 41 Autism: Sex Ratio………………………………………………….. 43 Autism: Genetic Influences………………………………………... 44 Autism: Socioeconomic Status (SES) and Ethnicity Factors……. 44 Influence of Comorbid Factors ……………………………………. 46 Neuropsychology Trends and ASDs………………………………. 48 Neuro-behavioral Profiles during Early Childhood……………….. 54 Role of Executive Functions……………………………………..... 56 Components of Executive Functions Model……………………...... 57 Components of Executive Functions and Preschoolers with ASDs……………………………………………………………….. 80 Assessment of Executive Functions during Early Childhood…….. 86 Measures of Executive Functions in Young Children……………. 88 Performance-based measure……………………….……… 88 Teacher rating scale………………………………………. 96 School-based Interventions for Children with Autism…………… 103

III METHODS……………………………………………………….. 107 Introduction ………………………………………………………. 107 Research Design………………………………………………….. 107

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Chapter Page

Population………………………………………………………… 111 Sample…………………………………………………………….. 112 Assignment………………………………………………………… 115 Measurement: Variables…………………………………………… 115 Instruments………………………………………………………… 119 Developmental History……………………………………………. 119 Measures of Executive Functions…………………………………. 120 Performance-based measure.…………………………….... 120 Teacher rating scale…..…………………………………… 126 Procedures………………………………………………………… 131 Recruitment………………………………………………. 131 Power and Sample size……………………………………………. 135 Statistical Analysis………………………………………………... 137 Summary………………………………………………………….. 144

IV RESULTS………………………………………………………… 145 Introduction………………………………………………………. 145 Complications of the Study………………………………………. 145 Computer Program to Analyze the Research Questions………… 147 Data Analysis……………………………………………………… 147 Demographic Information of the Sample…………………………. 147 Intervention Services and Comorbid Factors of the Sample……… 148 Statistical Assumptions……………………………………………. 149 Research Question One……………………………………………. 149 Research Question Two…………………………………………… 151 Research Question Three………………………………………….. 153 Research Question Four…………………………………………… 156 Research Question Five…………………………………………… 159 Research Question Six…………………………………………….. 160 Research Question Seven…………………………………………. 161 Summary………………………………………………………….. 163

V DISCUSSION……………………………………………………… 166 Internal and External Threats……………………………………… 184 Recommendations for Future Research …………………………... 186 Conclusions and Summary……………………………………….. 188

References…………………………………………………………. 193

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APPENDICES…………………………………………………….. 207 Appendix A: Site Sponsor Letter……………………………….. 208 Appendix B: Parent Consent Form……………………………... 209 Appendix C: Teacher Consent Form……………………………. 212 Appendix D: NEPSY-II Clinician Sample Report……………… 215 Appendix E: BRIEF-P Rating Scale Sample Items……………… 216

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LIST OF TABLES Table Page 1. Comparative Design………………………………………………….. 109 2. Current Research of Individuals with Autism………………………… 114 3. Measurement Variables for the Executive Functions of Preschool Children with ASDs: Research Questions, Latent Variables, Observed Variables, Instrument/Source, Validity, and Reliability for Questions One through Seven…………………………………………. 117 4. Constructs and Measures……………………………………………… 119 5. NEPSY-II Title Abbreviations and Brief Description of Each Subtest within a Domain………………………………………………………. 124 6. Description of BRIEF-P Scales and Indexes………………………….. 129 7. Timeline Procedures Covering the 2008-2010 School Years…………. 134 8. Previous Studies on Neuropsychological Functions on Individuals With ASDs and Reported Age and Sample Size……………………… 135 9. Research Questions, Hypotheses, Variables, and Statistical Assumptions for the Executive Functions of Preschool Children with ASDs……………………………………………………………... 142 10. Results of Correlations between Age of Symptoms Onset and Age of Enrollment in EI Services………………………………………….. 150 11. Results of a Regression Model on Age of Symptoms Onset and the Intensity of EI Services Provided to the Child Eligible for EI Services……………………………………………………………….. 151 12. Results of Correlations between Age of Symptoms Onset and Comorbid Factors…………………………………………………….. 153 13. Results of Correlations Age of Enrollment, Intensity of EI Services, and NEPSY-II Domains………………………………………………. 155 14. Results of Correlations Analysis of Age of Enrollment, Intensity of EI Services, and the BRIEF-P Indexes …………………………….. 158 15. Paired t-tests on the Attention and Executive Function Domain, the Inhibitory Self-Control Index, and the Global Executive Composite… 160 16. Paired t-tests on the Memory and Learning Domain, the Emergent Metacognitive Index, and the Global Executive Composite………….. 161 17. Paired t-tests on the Social Perception Domain, the Flexibility Index, and the Global Executive Composite……………..…………………… 162

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LIST OF FIGURES Figure Page 1. Latent variables of developmental status, age of symptoms onset, enrollment in early intervention program, comorbid factors, and intensity of early intervention services and performance on the NEPSY-II domains and BRIEF-P indexes………………………………. 22

2. A research path with the relationship among the variables age of symptoms onset, Enrollment in EI services, and comorbid factors associated with ASDs, as well as the instruments of executive functions of preschool children…………………………………………… 110

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CHAPTER I INTRODUCTION Over the past decade, a growing number of preschool-aged children have been diagnosed with autism disorder and identified as eligible to receive special education and related services in public schools. The Individuals with Disabilities Education Improvement Act-2004 (IDEIA-2004) mandates all states to report specific childhood disabilities, including autism disorder. The IDEIA-2004 report revealed a steady increase in the number of children ages 3-22 being recorded in the autism eligibility category by their local educational agencies. Reports submitted by states in compliance with IDEIA-2004 also revealed a steady increase in the number of children ages 3-22 being recorded in the autism eligibility category by their local educational agencies. From the 1992-1993 school year to the 2005-2006 school year, the number of children eligible to receive special education services under the eligibility criteria of autism increased from 15,580 to 259,705 (www.cdc.gov/nchs and www.ideadata.org). According to the Autism Society of America (2003), the number of reported cases of autism in the U.S. had an annual growth rate of 10-17%, making it the fastest growing developmental disability in the country. The Centers for Disease Control and Prevention (CDC, 2004) had predicted that approximately 1 in 150 children born in the U.S. will be diagnosed with characteristics compatible with some form of autism by the age of three. A collaborative CDC (2004) study

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designed to monitor the prevalence and incidence of autism disorders in the U.S. revealed that the state of New Jersey had the highest prevalence of children with autism disorder of the 14 states included in the study. New Jersey reported a rate of 1 in 95 children. While the prevalence rate of autism in children ages 3-22 years continued to increase, in New Jersey the majority of the cases were attributed to the age group 3-10 years, which was estimated to represent an increase of 49.8% in the prevalence rate when compared to other age groups. The prevalence increase for young children with autism represented an extreme concern due to the wide range of characteristics presented in preschool children with autism. Many preschool children diagnosed with autism disorder exhibit a heterogeneous and inconsistent profile of strengths and weaknesses, which have been associated with a neurological etiology. Therefore, the increased prevalence of autism in preschool-aged children and the lack of developmentally appropriate assessment instruments, have led to poorly tailored interventions. This has been shown to hamper the consistent acquisition of skills and further generalization of previously acquired skills in individuals with autism (Griffith, et al., 1999; Pennington, et al., 1997; Pennington & Ozonoff, 1996). Despite the need to provide specialized interventions during early childhood years, school professionals responsible for determining eligibility for Early Intervention (EI), such as school psychologists, are faced with assessment challenges, which impacts the quality of services offered to this population of

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young children with autism. Research has found that an integrative and comprehensive model of determining an individual’s unique pattern of learning based on a neuropsychological model of assessment may shed light on tailored and effective early intervention (EI) practices for young children with the disorder (Filipek, Accardo, Baranek, Cook, Dawson, Gordon, et al. 1999; Harris, Handleman, Gordon, Kristoff, & Fuentes, 1991; Hoyson, Jamieson, & Strain, 1984; Joseph, 1999; Lord, 1997; Pennington & Welsh, 1995; Pennington & Ozonoff, 1996; Stone, 1997). Consequently, it is pivotal for school professionals to increase awareness about and accurately identify the unique patterns of strengths and weaknesses of young children with autism. In this way, they can facilitate the children’s path to achieve functional lives to the best of their abilities (Filipek, et al., 1999; Sparrow, Marans, Klin, Carter, Volkmar, & Cohen, 1997; Volkmar, Klin, Szatmari, Lord, Campbell, Freeman, et al., 1994). Autism as a Neuropsychological Disorder According to the CDC Autism and Developmental Disabilities Monitoring Network (CDC-2007) and the National Institute of Mental Health (NIMH-2007), autism is one of a group of disorders known as Autism Spectrum Disorders (ASDs). This group of neuropsychological disorders includes core-defining characteristics related to impairments in language development, social development, and ritualistic/repetitive behaviors (American Psychiatry Association, 1994).

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Language difficulties associated with autism affect the child’s ability to understand and interact with the world. The language difficulties are directly associated with delays in social pragmatic development, which affect skills such as representational play, eye contact, and attention during interactive socially- mediated activities (Adrien, Lenoir, Martineau, Perrot, Hameury, Larmande, et al., 1993; Osterling & Dawson, 1994). Social deficits and ritualistic behaviors manifest themselves in the form of a need for sameness, preference for symmetry, and systems of arranging preferred objects (Welsh & Pennington, 1988). Social impairments have been identified as an early indicator of autism-like tendencies in young children. These impairments adversely impact the child’s ability to form relationships that facilitate play, imitation, and imagination skills, which are essential in developing relationships and learning social roles (Gillberg, 1989). The last component of the triad of symptoms that defines ASDs are behaviors related to seemingly ritualistic adherence to activities and behaviors with apparently limited pragmatic purpose (Griffith, Pennington, Wehner, & Rogers, 1999; Joseph, 1999; Lord, 1997; Stone, Lee, Ashford, Brissie, et al., 1999). Traditionally, these behaviors have been studied and discussed in a medical framework based on neurological etiology (Damasio & Maurer, 1978; Diamond & Doar, 1989; Minshew, Sweeney, & Bauman, 1997). However, more recent autism research illustrates a strong relationship between certain repetitive stereotyped behaviors and executive functions, which refers to the ability to over-

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ride or inhibit basic behavioral responses such as behaviors which might become self-fulfilling (i.e., spinning objects around or watching the object spinning around, enjoying the dizziness effect after spinning, avoiding a non-preferred activity) (Pennington & Welsh, 1995; Joseph, 1999; Sparrow, et al., 1997; Volkmar, et al., 1994). Responses to Increasing Autism Rates Recently, the Centers for Disease Control and Prevention (CDC-2007) and the National Institute of Mental Health (NIMH-2007) demonstrated that while the incidence of autism continues to increase drastically, it remains difficult to determine the accuracy of incidence rates due to contributing factors, such as the stage at which the individual developed autism and the degree of involvement of other skills. Previous studies sponsored by the CDC showed an increase in autism rates compared to the 1980s and 1990s. IDEA-Data Analysis System (IDEA- DANS) documented that in the U.S., over 25,000 preschool-aged children with a diagnosis of autism were entitled to receive special education services in the 2004-2005 school year, compared to over 20,000 in the 2003-2004 school year, and close to 15,000 in the 2000-2001 school year. The reported increase in autism rate became visible from the first multi-states collaborative study designed to monitor the prevalence and incidence of autism in the United States. As a result, effective research neuropsychological learning profiles of preschool children with ASDs are needed to improve traditional assessment practices and to

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enhance the coordination of specialized interventions, thereby maximizing their potential across all developmental components. Chris Smith, co-chairman of the Congressional Coalition on Autism Research and Education (CARE; www.house.gov.chrissmith), has argued that the data obtained from the aforementioned study becomes a roadmap to further advance research, treatment, and the education programs created to assist, understand, and treat individuals with ASDs. Due to the complexity of the neuropsychological characteristics presented in ASDs, the individual’s development is impacted throughout his/her lifespan. For example, a group of young children with autism disorder might demonstrate polarized patterns of neuropsychological strengths and weaknesses based upon different factors such as age of symptoms onset, EI, genetic factors, and overall neurocognitive skills (Adrien, et al., 1993; Filipek, et al., 1999). According to the Autism Society of America, (ASA, 2003) an increasing number of students with disabilities, including autism, are entering regular education settings. Currently, there are no specific blood tests, x-rays, or medical diagnostic procedures to confirm or diagnose autism. Although the current guidelines used to identify children with autism (APA, 1994) represent a consensus regarding a diagnosis, the guidelines merely constitute a categorical description of a complex brain-based disorder. Lord (1997) and Minshew, et al. (1997) suggested that marked emphasis on categorical definitions of autism overlooks critical developmental considerations and possibly leads to inaccurate

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diagnosis of the disorder, consequently impacting overall developmental outcomes. A neuropsychological model derived from specific brain-based profiles of strengths and weaknesses perhaps could provide an accurate understanding of autism as a life-long and complex disorder and ultimately provide specialists with more effective interventions at earlier stages. (Pennington & Ozonoff, 1996). Using a neuropsychological model to differentiate a set of complex skills and to provide treatment for children with ASDs involves a two-fold challenge for specialists, particularly for those practicing in educational settings (Ozonoff, 1997; Pennington & Ozonoff, 1996). First, ASDs do not present homogeneous cognitive or behavioral characteristics. The CDC-2004 classified ASDs as a group of developmental disabilities, which includes autism disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS), atypical autism, Asperger syndrome, Rett’s syndrome, and Childhood Disintegrative Disorder, making the broad diagnosis category of Pervasive Developmental Disorders (PDDs; APA, 1994). As a result, different types of autism disorders may have distinct patterns of cognitive and behavioral functions and possibly warrant tailored and specialized methods of diagnosis and intervention. Despite the evidence for existent behaviorally-based symptoms associated with autism, a challenge for school professionals is that the DSM-IV (1994) criteria provide little information essential to understanding the child’s behavior and its impact on his or her learning process.

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Many of the neuropsychological instruments used over the past three decades have failed to address neuropsychological functions in preschool-aged children (Flanagan & Nuallain, 2001; Harris, et al., 1991; Lord, 1995; Stone, 1997). In the past, neuropsychological tests focused on the assessment of adults with brain disorders, and only a few of them included children as part of their standardization sample (Ozonoff, Pennington, & Rogers, 1991). Sparrow, et al. (1997) argued that when using traditional standardized tests, a profile of neuropsychological functions in children with ASDs cannot be fully assessed and interpreted, since assessing loss of skills in adults with brain disorders is not comparable to assessing developmentally-acquired skills or lack of acquired skills in children with developmental disorders. Furthermore, given the heterogeneity of ASDs symptoms, it is difficult to correlate individual performance results to a larger group, in part because individual discrepancies may be influenced by the psychometric properties of the instruments used rather than by individual profiles of strengths and weaknesses. Executive Functions and ASDs Executive functions (EF) theory has become a major perspective for explaining symptoms associated with autism disorder (Pennington & Ozonoff, 1996; Pennington, Rogers, Bennetto, Griffith, Reed, & Shyu, 1997; Rogers, 1998). Executive functions are brain-based skills, which begin to develop during the first years of life and are associated with the pre-frontal cortex. Specifically, EF refers to the processes that underlie flexible goal-directed behavior, such as

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inhibiting dominant responses, creating and maintaining goal-related behavior, and using temporal-sequencing behavior (Burgess, Alderman, Evans, Emslie, & Wilson, 1998). Therefore, difficulties associated with EF may provide explanations for the consistently discrepant performance of young children with ASDs. Damasio and Maurer (1978) and Griffith, Pennington, Wehner, and Rogers (1999) demonstrated that children with autism exhibited cognitive difficulties, which impacted their ability to plan and to problem-solve. Even though the relationship between EF and preschool children with autism has not been extensively studied, researchers have supported the notion that pervasive disorders appear to be related to deficits in executive functions in individuals with autism (Ozonoff, Rogers, & Pennington, 1991; Pennington & Ozonoff, 1996). Researchers seeking to understand the relationship between executive functions and autism disorder have identified brain structures that are directly related to social, behavioral, and communication impairments. Specifically, executive function impairments have been associated with damage to the prefrontal cortex (Fuster, 2000; Luria, 1966). The relationship between deficits in EF and individuals diagnosed with autism has gained support in regard to an overlapping group of symptoms associated with the third category in the autism triad, restricted and repetitive interests and behaviors (Griffith, et al., 1999; Stone, Lee, Ashford, Brissie, et al., 1999). Other categories of the autism triad, such as language and social aspects, appear to be less related to EF; however, researchers have suggested that EF may be tied to other cognitive domains that govern

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language and social development (Ozonoff, Pennington, & Rogers, 1991). Stone (1997) documented that impairments of EF may be related to both language and social functions, as in the case of an individual’s inability to inhibit repetitive verbal responses in a given situation, which may cause autism-like behaviors that negatively impact social interactions and language. Pennington and Ozonoff (1996) showed that executive dysfunction was pervasive in autism, and those individuals with autism exhibited a different range of symptoms when compared to other individuals with neurodevelopmental disorders. EF also affects interaction among mental operations, which enables an individual to disengage from the immediate context in order to guide behavior by reference to mental models or future goals (Hughes, 1996; Volkmar, Chawarska, & Klin, 2005). Interaction among these mental operations is critical for the development of working memory, response inhibition, and planning in young children (Ozonoff, 1997; Pennington & Welsh, 1995). An area of growing interest in pediatric neuropsychology is the relationship between deficits of EF, problem solving and planning ability, and inhibitory control in young children with ASDs (Joseph, 1999; Ozonoff, Cook, Coon, Dawson, Joseph, Klin et al., 2004; Pennington & Ozonoff, 1996; Russell, 1997). Several decades ago, most of the cognitive research focused on neuropsychological functioning of adults with brain disorders (Damasio & Maurer, 1978; Luria, 1966). During the last two decades, more researchers have begun to closely examine the relationship of neuropsychological aspects of learning in young children, particularly those who

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have been impacted by life-long disorders such as ASDs. While there has been an increase of empirical research on school-aged children and subsequent methods to improve psychometric properties of neuropsychological instruments, research that provides empirical support to the EF construct in preschool children with autism remains scarce (Filipek, et al., 1999; Harris, et al., 1991; Harris & Handleman, 2000; Lord, 1997). Neuropsychological Instruments of Executive Functioning Researchers (Filipek et al. 1999; Flanagan & Nuallain, 2001; Griffith, Pennington, Wehner, & Rogers, 1999; Joseph, 1999; Rogers, 1998; Zelazo, Carter, Reznick, & Frye, 1997) strongly supported that individuals with autism cannot be consistently identified by their neuropsychological profiles of EF. Despite an increase in professional literature interested in exploring the relationship between deficits in EF and individuals with autism, the literature continues to be limited in exploring deficits in executive functioning in preschool children with autism. According to the research of Isquith, Crawford, Espy, and Gioia (2005), well-researched, standardized diagnostic instruments can differentiate ASD characteristics in young children at an early age. Moreover, earlier and accurate differentiation of such complex brain-related behaviors, combined with effective interventions, can be implemented to help the young child with autism achieve his or her greatest functional potential. Current practices in the use of neuropsychological instruments advocate a comprehensive, developmental model to categorize neuropsychological functions

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in the pediatric population with disabilities. The NEPSY: A Developmental Neuropsychological Assessment-2 nd Edition (NEPSY-II; Korkman, Kirk, & Kemp, 2007), which became standardized as a pediatric neuropsychological instrument, has demonstrated the ability to discriminate patterns of basic neuropsychological functions, specifically frontal and prefrontal lobe functioning across disabilities. The NEPSY-II provides a flexible and comprehensive model, based on Luria’s theory, to categorize patterns of abilities or deficiencies in complex behaviors, such as tactile perception, visual perception, basic psychomotor skills, and other functions (Korkman, Kemp, & Kirk, 2001). The theory developed by Luria (1966) constitutes the theoretical basis for the development of the NEPSY-II. Luria believed that the integration and independence of different parts of the brain were necessary for complex cognitive processes to occur. This integration of functional systems was a central component of Luria’s theory (1966). In his theory, Luria considered cognitive processes to be dynamic, functional systems characterized by a specific aim and carried out as complex patterns of participating sub-processes (Korkman, Kemp, & Kirk, 2001). With the NEPSY-II, Luria’s theory was represented as the assessment of complex sub-components of cognitive functions that can be impaired in ways that are comparable to that which occurs in the breakdown of a complicated system (Korkman, Kirk, & Kemp, 2007). Indeed, the NEPSY-II was designed to assess both qualitative and quantitative aspects of sub-components of complex cognitive functions that require contributions from several functional

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domains. Conceptually, the integration of Luria’s theoretical view and the NEPSY-II analysis identified complex, disordered functions by separating all sub- processes that would normally participate in that particular function. Another reliable method of neurodevelopmental screening, especially for evaluation of executive functions in school-aged children, includes behavior rating scales completed by external raters (e.g., parents or teachers). Gioia, Isquith, and Guy (2001) emphasized the relevance of combining both observational rating scales and results from other assessment measures in order to support clinical data derived from standardized measures of executive functions. The integration of empirically-based and developmentally-based data regarding executive functioning becomes pivotal to closely examining the impact on a child’s academic and social development, especially considering the heterogeneous characteristics presented in developmental disorders such as ASDs. The Behavior Rating Inventory of Executive Functioning-Preschool Version (BRIEF-P; Gioia, Espy, & Isquith, 2003) is a standardized rating scale developed with the purpose of increasing the understanding of everyday situations related to specific domains of executive functioning in children from 2 to 5 years of age. The BRIEF-P is a 63-item performance-based rating scale that measures four specific domains of executive functioning: Inhibit Shift, Emotional Control, Working Memory, and Plan/Organize. By using an in-depth observation process, primarily completed by the child’s teacher or parent, the BRIEF-P leads to clinical results and a comprehensive profile analysis of a range of behavioral

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manifestations associated with executive functions. The clinical results obtained from the child’s performance allow the examiner to establish associations between the child’s behavior and specific domains of executive functions and to design specific interventions at earlier stages of development (Gioia, Espy, & Isquith, 2003). The increasing movement toward better understanding and awareness of a neuropsychological model to measure an individual’s level of executive functioning has been shown across professional literature. A growing body of research supports the neuropsychological model as an explanation for the inconsistent performance of executive functions of preschool children with ASDs and its overall impact on the child’s daily functioning (Griffith, et al., 1999; Lord, 1997; Ozonoff, Pennington, & Rogers, 1991; Pennington, Rogers, Bennetto, Griffith, Reed, & Shyu, 1997). The NEPSY-II (Korkman, Kirk, & Kemp, 2007) and the BRIEF-P (Gioia, Espy, & Isquith, 2003) have been employed as reliable measures to distinguish specific patterns of basic neuropsychological functions in preschool-aged children. However, there is still a need for exploring research and comparing neuropsychological patterns of executive functions of preschool children with ASDs. Therefore, the comparison of both empirically-based data and developmentally-based rating scales of executive functions is critical to closely examine the impact on a child’s daily functioning in the context of heterogeneous characteristics presented in developmental disorders such as ASDs.

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Statement of the Problem The number of epidemiological studies of ASDs has grown in recent years, including studies aimed at increasing the level of awareness and improving collaboration among families, researchers, educational agencies, and other professionals when dealing with children whose lives are impacted ASDs (Centers for Disease Control and Prevention; Filipek, et al., 1999; Fombonne, 1999). A multidisciplinary consensus panel endorsed by the American Academy of Neurology and Child Neurology Society (Filipek, et al., 1999) reviewed and made recommendations based on the existing research regarding the screening and diagnosis of autism. The panel stated that diagnostic practices require multiple methods employed across multiple settings and should be performed by trained mental health and medical providers. Additionally, the panel emphasized that practitioners need to be familiar with current research-based intervention practices, an essential factor to improve developmental outcomes for young children with autism (Filipek, et al., 1999). In 2001, the National Research Council reiterated the complex nature of the autism diagnosis process, noting that “the level of expertise required for effective diagnosis and assessment of children with autism may require the services of individuals or a team of individuals, other than those traditionally involved” (p. 186). Recently, an increasing number of research studies in pediatric neuropsychology have shown empirical evidence of deficits of executive functions in young children with autism (Griffith, et al., 1999; Pennington, et al.,

Full document contains 229 pages
Abstract: Every day, school professionals encounter the need for research-based assessment and intervention practices which target executive function profiles in preschool children with developmental delays. While current research focuses on describing characteristics of autistic tendencies during early childhood years, very few studies exist that compare preschool children's executive function profiles based on rating scales with performance-based assessment. The purpose of this study was to compare specific neurocognitive profiles of preschool-aged children with autism based on their performance on the NEPSY-II and on the teachers' ratings on the BRIEF-P. Additionally, this study used a quantitative design to explore whether age of symptoms onset, age of enrollment in Early Intervention services, and intensity of therapy services provided can differentiate learning profiles, particularly executive functions of preschool children with autism spectrum disorders. The sample of the study was composed of 12 preschool students ranging from 3 to 5 years of age. The sample's educational placement was an out-of-district placement. The sample was one of convenience. A number of conclusions were obtained pertaining to age of symptoms onset and support services provided by EI before the child's third birthday. An early age of symptoms onset was considered to predict eligibility for occupational therapy services. Also, EI services were found to be associated with lower performance on the Attention and Executive Functioning domain. Results from the interaction between Attention and Executive Functioning domain, Inhibit Self Control Index, and General Executive Composite, and the comparison between Social Perception domain and Flexibility Index, did not reveal significant differences when compared with profiles from the NEPSY: A Developmental Neuropsychological Assessment-2 nd Edition (NEPSY-II; Korkman, Kirk, & Kemp, 2007), and the Behavior Rating Inventory of Executive Functioning-Preschool Version (BRIEF-P; Gioia, Espy, & Isquith, 2003). The results drawn from the comparison between Memory and Learning, Emergent Metacognitive, and General Executive Composite ratings showed significantly different profiles. Lastly, this study offered recommendations for future research on executive functioning in preschool children with autism spectrum disorders (ASDs).