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1 AN EXAMINATION OF REPETITIVE AND RESTRICTED BEHAVIOR AND ASSOCIATED CHARACTERISTICS AMONG THOSE WITH AN AUTISM SPECTRUM DISORDER By CINDI GUADALUPE FLORES A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY O F FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012
2 2012 Cindi Guadalupe Flores
3 To m y family, friends, and teachers
4 ACKNOWLEDGMEN TS I extend sincere gratitude to those who provided support and made this dissertation possible. First, I would like to thank my advisor, John Kranzler, for his guidance on helping me develop my career and academic interests. I would like to thank my mento rs Soo Jeong Kim and Maria Coady for providing me opportunities to conduct research under their guidance I would also like to thank my committee members, Walter Leite for his help with data analysis as well as Diana Joyce and Maureen Conroy for their he lp with editing and their expert knowledge. I would like to acknowledge Emily Wray for her assistance with data collection, as well as the UF Child and Adolescent Psychiatry fellows and the staff of the UF Center for Autism and Related Disabilities (CARD) center for their assistance with participant recruitment. I would also like to thank my family members, in particular, my parents, Kam and Lupe Flores, who taught me the important value of hard work and perseverance; my siblings, Amy and Jason, for their l ove and support; my cousin, Keivan Stassun for his advising; and my aunt and uncle, Cori and Jim Welch, for introducing me to academia.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ..................... 9 CHAPTER 1 LITERATURE REVIEW ................................ ................................ .......................... 11 Classification Systems ................................ ................................ ............................ 12 Communication Deficits ................................ ................................ .......................... 16 Social Skills ................................ ................................ ................................ ............. 19 Restricted and Repetitive Behavior ................................ ................................ ......... 21 Types of Restricted and Repetitive Behavior ................................ .......................... 25 Intelligence and RRBI ................................ ................................ ............................. 30 Adaptive Functioning and RRBIs ................................ ................................ ............ 35 Co morbid Psychiatric B ehavioral Problems and RRBIs ................................ ......... 36 The Relationship of Age and RRBIs ................................ ................................ ....... 37 Purpose of Current Research Study ................................ ................................ ....... 38 2 METHODS ................................ ................................ ................................ .............. 43 Participants ................................ ................................ ................................ ............. 43 Instruments ................................ ................................ ................................ ............. 44 Health History Qu estionnaire ................................ ................................ ............ 44 Restricted and Repetitive Behaviors or Interests ................................ .............. 44 Intel lectual Functioning ................................ ................................ ..................... 45 Adaptive Functioning ................................ ................................ ........................ 47 Hyperactivity ................................ ................................ ................................ ..... 48 Statistical Analyses ................................ ................................ .......................... 49 3 RESULTS ................................ ................................ ................................ ............... 51 Data Screening ................................ ................................ ................................ ....... 51 Descriptive Statistics ................................ ................................ ............................... 52 Outcome Variables ................................ ................................ ........................... 52 Predictor Variables ................................ ................................ ........................... 52 Correlational Analysis ................................ ................................ ....................... 53 Confirmatory Factor Analysis ................................ ................................ .................. 54 Multiple Regression ................................ ................................ ................................ 56 Intelligence ................................ ................................ ................................ ....... 56
6 Age ................................ ................................ ................................ ................... 57 Hyperactivity ................................ ................................ ................................ ..... 57 Adaptive Functionin g ................................ ................................ ........................ 57 4 DISCUSSION ................................ ................................ ................................ ......... 77 Research Question 1: Factor Structure of the RBS R ................................ ............ 77 Research Question 2: Intelligence, Age, Hyperactivity, Adaptive Skills .................. 79 Intelligence ................................ ................................ ................................ ....... 79 Age ................................ ................................ ................................ ................... 80 Hyperactivity ................................ ................................ ................................ ..... 80 Adaptive Functioning ................................ ................................ ........................ 81 Convergent Validity ................................ ................................ ................................ 81 Limitations ................................ ................................ ................................ ............... 82 Summary and Implications for Future Research ................................ ..................... 83 APPENDI X A HEALTH HI STORY FORM ................................ ................................ ..................... 86 B RESIDUALS FOR COVARIANCES/CORRELATIONS/RESIDUAL CORRELATIONS ................................ ................................ ................................ ... 88 LIST OF REFERENCES ................................ ................................ ............................... 98 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 108
7 LIST OF TABLES Table page 3 1 Descriptive statistics for the entire sample ................................ ......................... 58 3 2 Descriptive statistics for the subsample ................................ .............................. 59 3 3 Descriptive statistics for outcome variables ................................ ........................ 60 3 4 Descriptive statistics for predictor variables ................................ ........................ 61 3 5 ) for factors from the 5 factor model ............ 62 3 6 Pearson product moment correlation for RBS R and ADI R Scores (N=64) ....... 63 3 7 Goodness of fit indices of the hypothesized latent fac tor models of the RBS R (N=205) ................................ ................................ ................................ ........... 64 3 8 Standardized factor loadings ................................ ................................ .............. 65 3 9 Correlations among the five factors ................................ ................................ .... 67 3 10 Correlations among the six factors ................................ ................................ ..... 68 3 11 RBS R item variance ................................ ................................ .......................... 69 3 12 Ad aptive functioning, age, hyperactivity, and intelligence for predicting stereotyped behavior ................................ ................................ .......................... 71 3 13 Adaptive functioning, age, hyperactivity, intelligence for predicting self injurious behavi or ................................ ................................ ............................... 72 3 14 Adaptive functioning, age, hyperactivity, intelligence for predicting compulsive behavior ................................ ................................ ........................... 73 3 15 Adaptive functionin g, age, hyperactivity, intelligence for predicting IS/Ritualistic behavior ................................ ................................ ......................... 74 3 16 Adaptive functioning, age, hyperactivity, and intelligence for predicting restricted behavior ................................ ................................ .............................. 75 3 17 Adaptive functioning, age, hyperactivity, and intelligence for predicting the sum RBS R Score ................................ ................................ .............................. 76
8 LIST OF FIGURES Figure page 1 1 Rival Models Evaluated ................................ ................................ ...................... 39
9 Abstra ct of Dissertation Presented to the Graduate School of the University of Florida Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy AN EXAMINATION OF REPETITIVE AND RESTRICTED BEHAVIOR AND ASSOCIATED CHARACTERIS TICS AMONG THOSE WITH AN AUTISM SPECTRUM DISORDER By Cindi Guadalupe Flores August 2012 Chair: John H. Kranzler Major: School Psychology Restricted and repetiti ve behaviors or interests (RRBIs ) are considered a key feature among those diagnosed with an Autism Spectrum Disorders (ASD). To date, most of the research on ASDs has focused on social and communication deficits with less attention on RRBIs. Recently, an increase in research has been conducted to better understand RR BIs within the ASD population. Given the significance of RRBIs, further research and refinement of previous research is needed to better understand their development, expression, assessment, related clinical features (e.g., cognitive ability, adaptive functioning, and hyperactivity), a nd treatment. One area that has attracted attention is the structure of RRBIs among those with an ASD. Factor analytic studies using rating scales measuring RRBIs have found that RRBIs represent a heterogeneous category. Currently, factor analytic studies conceptualize RRBIs as representing between two and six different types of behavior. The purpose of this study was to examine t he types of RRBIs among those with an ASD. In addition, associated clinical features were examined including the role of
10 intelli gence, age, adaptive functioning, and hyperactivity to measure their relationship to RRBI subtypes as well as overall repetitive behavior. Results of this study found that a five types of RRBIs, which consisted of the following domains: Stereotyped Behavi or, Self Injurious Behavior, Compulsive Behavior, Ritualistic/Sameness Behavior, and Restricted Behavior Internal consistency values for each of the factors were adequate. Results from the multiple regression analyses indicated that intelligence adaptive functioning, and hyperactivity were the only variables to predict RRBIs. Future research is needed to replicate the findings in this research study.
11 CHAPTER 1 LITERATURE REVIEW m schizophrenia. Kanner identified several behaviors that were particular to Autism in his The term Autism was a critical examinati on of 11 case studies of individuals who displayed behaviors that were consistent with what he felt to be an inherent lack of interest in other people. Some of the salient behaviors he identified included an inability to relate to others, failure to use la nguage in a meaningful way, a strong desire for things to stay the same, a lack of imaginative play, strong aptitude for rote memory, and repetitive motor behaviors and questioning (Kanner, 1943). Furthermore, abnormalities were present early in developmen t, which made Autism different from previous descriptions of psychosis and schizophrenia. described four case studies with average intelligence or better who had difficulty with cognitive abilities (Asperger, 1944). Later, Michael Rutter conducted a review of the lit erature related to Autism and highlighted four distinct areas associate d with the disorder, including communication impairment, social interaction impairment, repetitive behavior, and onset of symptoms prior to the age of three (Rutter, 1978 ). Since the wo rk of Kanner, Asperger, and Rutter, copious research has been conducted to better understand the characteristics, etiology and development of an Autism Spectrum Disorder (ASD).
12 ASDs are considered neurodevelopmental disorders that occur early in developme nt and are considered to have strong genetic underpinnings (Levitt & Campbell, 2009). Based on mono and dizygotic twin studies, the estimated heritability rate of ASD symptoms ranges between .64 and .92 (Bailey et al., 1995; Ronald et al., 2006; Steffenbu rg et al., 1989). Prevalence rates in the U nited States indicate that on average, one in 88 individuals have an ASD ( Center for Disease Control, 2012 ). Since the inception of ASDs as unique psychiatric conditions, significant increases in prevalence rates have been reported (Prior, 2003). The reason for the increase of ASD diagnoses is unknown at this time. While environmental factors may impact the development of ASDs, other factors such as c h anges in diagnostic methodology, increased awareness of ASD symp tomology or both, may have contributed to the upsurge of individuals diagnosed with an ASD (Gernsbacher, Dawson, & Goldsmith, 2005). Classification Systems The Diagnostic Statistical Manual (DSM) and the International Classification of Diseases (ICD) repr esent the most widely used cla ssification systems to diagnose psychiatric conditions, including ASDs. The International Classification of Diseases is the standard classification system for establishing a diagnosis internationally ; whereas the Diagnostic St atistical Manual is the standard classification system used in the United States. Both systems for classification have made significant revisions regarding the definition of Autism and related conditions. These changes have impacted how clinicians identify and treat those with an ASD. In the International Classification of Diseases, Ninth Edition (World Health Organization, 1978), Autism and disintegrative disorders were considered a psychiatric
13 condition and were nested in the category of childhood psychot ic conditions along with schizophrenia The categorization of Autism and disintegrative disorders as a psychotic condition reflected the prevailing view at that time, which viewed Autism as a predictor of psychosis (Laufer & Gair, 1969) The Diagnostic S tatistical Manual, Third Edition (American Psychiatric Association, 1980) classification system was a major advancement in the diagnosis of ASDs. For the first time, ASDs were introduced under the umbrella term Pervasive Developmental Disorders to capture the developmental nature and pervasive impact on overall functioning. In addition, the ASD diagnosis was recognized as a separate condition from childhood psychoses. The definition used in the DSM the presence of a Pervasive Developmental Disorder. There were some shortcomings with the DSM III classification system. For example, the definition in the DSM III was highly specific but was no t sensitive to determining the presence of an ASD, which led to significant revisions in the Diagnostic Statistical Manual, Third Edition, Revised (DSM III R ; Volkmar, Cohen, & Paul, 1986 ). The DSM III R criteria expanded the diagnostic definition to accou nt for differences in age and development and eliminated a specific age of onset as a core diagnostic feature despite significant reports indicating early onset as a hallmark feature of ASD. The criteria set forth for a diagnosis within the DSM III R were also found to be unsatisfactory because many individuals who were diagnosed with an ASD using the DSM III R were found to be false positives (Rutter & Schopler, 1992). In addition, those that had lower cognitive ability were more likely to receive a diagno sis whereas those
14 who were higher functioning were less likely to be identified as having an ASD (Siegel, Vukicevic, & Spitzer, 1990) As a result of concerns regarding the accuracy of the criteria outlined in the DSM III R when determining an ASD diagnos is, further refinement of the diagnostic criteria was conducted through an extensive field trial and alignment of the criteria with the definition set forth in the International Classification of Diseases, Tenth Edition (ICD 10). The criteria established in the Diagnostic and Statistical Manual, Fourth Edition (DSM IV; American Psychological Association, 1994) was intended to improve the accuracy of an ASD diagnosis Although the DSM IV ASD criteria share features of the ICD 10 in order to create a unive rsally accepted definition, they are not entirely the same. For example, the ICD 10 incorporates different criteria depending on the purpose of the diagnosis (i.e., research versus clinical). The DSM IV was slightly modified and was renamed the DSM IV TR ( American Psychological Association, 2000), which is the most recent version of the DSM. Currently, t he disorders that comprise ASDs include Autism (AS), and Pervasive Developmental Disorder, Not Otherwise Specified (PDD NOS). Although the defining characteristics of each disorder differ to some degree, a ccording to the DSM IV TR, Autism is differentiated from other disorders through the presence of impairments in three core areas : communication, social skill functioning, and RRBIs. Comm unication impairment is characterized by either a delay in development or complete lack of spoken language; for those who can use speech, a significant impairment in sustaining conversations with others; and a lack of imaginative or imitative play. Social skill impairments are characterized by the failure to engage in
15 nonverbal interactions (e.g., making eye contact); develop age appropriate friendships; engage in social or emotional reciprocity. Restricted and repetitive behavior or interests are character ized by strict adherence to routines or rituals; preoccupation with a restricted behavior that is abnormal in terms of its intensity; preoccupation with parts of objects; and stereotyped and repetitive motor behaviors (e.g., hand flapping). To receive a d iagnosis of having Autism an individual must exhibit six domains, with at least two social skill impairment s, one communication impairment, and one significant cognitive or c ommunication impairment and must have at least two social skill impairments and one RRBI. To receive a diagnosis of PDD NOS, an individual must exhibit at least two criteria, with one social skill impairment and one communication impairment or RRBI. In or der to receive a diagnosis for an ASD, these behaviors must be present prior to the age of three (American Psych iatric Association, 2000). Although these areas have been widely accepted as key features of ASD s the identification of these three areas as t hree distinct areas has been based primarily on clinical observations and case studies rather than empirical research (Szatmari et al., 2006). Thus, it is possible that using these three separate core areas to determine whether a diagnosis is present may n ot adequately reflect the phenotypic nature of ASDs. Results of research examining the structure of ASD symptoms have been discrepant; however, many factor analytic studies suggest social and communication deficits are highly correlated and should be col la psed as a single factor (Frazier et al., 2008; Lord et al., 2006; Snow, Lecavalier, & Houts, 2009) and RRBIs should represent
16 a separate factor. In a review of 13 papers examining the factor structure of ASD symptomology, the majority of analyses resulted in the authors recommending a conceptualization of social and communication deficits as being collapsed into a social communication factor and RRBIs as being a separate factor (Kuenssberg, McKenzie, & Jones, 2011). Proposals for the ASD diagnostic criteria in the upcoming DSM V, due for publication in 2013, have suggested changes that are in accord with previous research studies regarding the structure of ASDs. The DSM V Task Force is proposing that a diagnosis of ASD should be based on two domains, Social Communication Deficits and RRBIs (A merican P sychiatric A ssociation 2012). In addition, a proposal has been made Developmental Disorders. Elimination of other diagnostic t erms is likely, such as PDD V are in the process of being revised and have not been finalized. The following sections will describe each core area in detail; however, it is impor tant to note that these areas do not often occur in isolation and can overlap. For example, social interactions are impacted by nonverbal and verbal communication and vice versa. In addition, repetitive forms of communication may be considered a form of re petitive behavior. Communication Deficits Information about the development of language is essential to understanding ASDs. When compared to typically developing children, those with an ASD tend reach speech and language milestones later, and their langua ge development tends to have abnormal features; however, there is significant variation in patterns of language
17 acquisition for those with ASD. For example, those with Asperger Syndrome have no communication delays or mild impairmen ts, while some diagnosed with Autism or PDD NOS may never develop speech and language (A merican P sychiatric A ssociation 2000) Recent reports indicate that the rate of those who do not acquire speech with ASD is decreasing, which is possibly a result of improvements in early det ection and interv ention (Goldstein, 2002). D evelopmental delays in the area of speech and communication tend to be one of the most salient features of ASD and are the most frequently reported feature of ASD by parents (Di Giacomo & Frombonne, 1998; Short & Schopler, 1988). During infancy, those with Autism tend to demonstrate nonverbal communication behaviors that deviate from what is expected based on age related norms. Typically developing infants engage in a wide variety of methods to communicate nonver bally before acquiring speech. For example, typically developing infants will reach towards an object to suggest a desire for something or push something away to suggest refusal. These methods of nonverbal communication reflect the desire to interact and c ommunicate as well as an understanding of appropriate communication. Those diagnosed with Autism engage in these behaviors less frequently, which has been related to impairments in joint attention and the inability to imitate others (Osterling, Dawson, & M unson, 2002). In addition to displaying less frequent nonverbal methods of communication, prelinguistic children diagnosed with Autism frequently display abnormal speech production. For example, in a study comparing children with and without an ASD, those with an ASD engaged in babbling behavior at a similar rate to
18 those without an ASD; however, those with an ASD had more speech distortions and were more likely to squeal, growl, and yell (Sheinkopf, Mundy, Oller, & Steffens, 2000). The nature of speech an d language difficulties can change over the course of with approximately 25% of children with an ASD showing language regression between the ages of 12 and 18 months (Kurita, 1985). Another salient feature of Autism is the frequent prese nce of echolalia. Researchers have indicated two types of echolalia, immediate and delayed (Rydell & Miranda, 1996) Immediate echolalia occurs when one repeats what others have said using similar intonation or when one repeats words or phrases in a persis tent manner immediately after hearing the stimulus. Delayed echolalia occurs several hours to days later and occurs repeatedly. Individuals with higher levels of functioning tend to have less severe communication impairments; however, most have difficulty in the area of pragmatic language development, or the ability to use appropriate language based on the social context. Even those with very mild speech and language impairments are unable to use language that is consistent with the social milieu (Ramberg, Ehlers, Nyden, Johanssen, & Gillberg 1996) For example, those who have difficulty with pragmatic language m ay have difficulty engaging in a conversation which alternates in a back and forth manner ; may have difficulty establishing a joint frame of refere nce for the interaction; may make insensitive comments because of a lack of awareness regarding social norms; may not they should stand near someone else during a conve rsation (Baltaxe, 1977; Ramberg et
19 al., 1996) These deficits also have a significant impact the ability to create and sustain meaningful social interactions. Social Skills fea ture of Autism (Volkmar et al., 2005). Individuals diagnosed with an ASD exhibit impairments in various aspects of social processing, including eye contact, joint attention, play and leisure time, and peer relationships. In terms of eye contact, typicall y developing infants prefer stimuli resembling the (Hainline, 1978). Those diagnosed with Autism tend to fail to establish eye contact patterns similar to typically developing i nfants (Volkmar & Mayes, 1990). This lack of eye contact appears to be significantly impaired in infants with Autism when compared to those with developmental delays or those with intellectual disability (Jones, Carr, & Klin, 2008). Parents with children d iagnosed with Autism have reported that during early childhood avoidance of eye contact is common and often under reported, as indicated in retrospective research using home videos (Clifford & Dissanayake, 2009). These behaviors, in turn, negatively impact the nature of the caregiver child relationship. As a result of limited eye contact between the caregiver and the child, it is difficult to establish develop quality intera ctions also impacts the ability to engage in communication that includes the exchange of information that includes additional variables within the environment. For example, an infant may cry and point to their bottle to signal that they are hungry, and the n alternately gaze at their bottle to their caregiver. Engaging in these types of behaviors requires joint attention, which tends to be impaired in those
20 diagnosed with Autism and interferes with every domain of social interaction, including the ability to imitate appropriate social skills, develop social interactions, and engage in reciprocal play (Charman & Baron Cohen, 1994) A research study evaluating how children play indicated those with an ASD tend to play with toys and others in a markedly differe nt manner compared to typically developing peers, including rigid repetitive and stereotyped play (Sherman, Shapiro & Glassman, 1983). For example, a child may line toys up and then repeat this behavior several times. If this play is disrupted or altered, it can engender feelings of anx iety and frustration within the child with Autism. In addition, children with Autism tend to select toys on the basis of how they taste, feel, or move rather than for symbolic play. When engaging with others, those with Auti sm tend to be passive or odd in their approach with peers. In a study of 235 adolescents and adults with Autism almost half of the Krauss, Seltzer, 2004 as cited in Vo lkmar et al., 2005). Research examining differences between those with Asperger Syndrome versus those with Autism have found that individuals with Asperger Syndrome tend to be socially isolated. A major difference in social interaction between those with Asperger Syndrome versus those with Autism is that they are more likely to approach others but do so in an odd or inappropriate way. For example, those with Asperger Syndrome tend to engage in one sided conservation about a circumscribed interest. In addit ion, those with Asperger Syndrome tend to approach others in an awkward fashion and may not be able to pick up on social cues (e.g., a yawn may indicate boredom; Klin & Volkmar 1997 as cited in Volkmar et al., 2005).
21 Recent theory suggests that those wi th an ASD may have difficulty engaging in quality social interactions as a result of difficulty reading the emotions of others. Those with an ASD often have difficulties identifying emotional states of others which researchers have attrib uted to the failur e to develop the ability to recognize how others are feeling, in terms of their beliefs, desires, and intentions (Volkmar et al., 2005). The others thus leading to p oor socialization and communication. Restricted and Repetitive Behavior Although the presence of restricted and repetitive behaviors is one of the core features of ASD, they have been the subject of less attention than social and communication impairments (Lewis & Bodfish, 1998; Turner, 1999) As a result, many equivocal conclusions and unanswered questions exist regarding RRBIs within the ASD population. Until recently, RRBIs were often considered a result of social interac tion and communication deficits ( Baren Cohen, Tager Flusberg, & Cohen, 2000). However, there is evidence that RRBIs are distinctive from social and communicative performance. For example, those with high functioning Autism which is characterized by mild symp toms of social and communication deficits can have significant impairments in the area of RRBI (Szatmari, Bryson, Boyle, Streiner, & Duku, 2003). Furthermore, individuals without an ASD diagnosis who have disorders that are characterized by social impairm ents, language impairments (e.g., specific language impairment and social anxiety) or both, do not necessarily display RRBIs. Conversely those without an ASD diagnosis who have disorders that are characterized by RRBIs (e.g., Obsessive Compulsive D isorde r) do not necessarily display communication or social deficits. Family studies examining the heritability of ASDs suggest that genes
22 controlling RRBIs are likely independent of genes controlling social or communication deficits (Ronald et al., 2006; Silver man et al., 2002). Comparative studies examining RRBIs between those diagnosed with an ASD developmental disability (e.g., intellectual disability ), psychia tric disorders (e.g., Obsessive Compulsive Disorder), or neurologically based conditions (e.g., To syn drome) have been conducted to shed light on how RRBIs manifest in those with ASD relative to other impairments (Lewis & Bodfish, 1998). In a study comparing stereotypic behaviors among 18 5 adults diagnosed with severe intellectual disability wi th ASD versus 1, 060 adults diagnosed with severe intellectual disability without ASD using the Diagnostic Assessment for Severe Handi caps, Second Edition (DASH II; Matson, 1995), 75% of those with ASD and intellectual disability had stereotypy behavior tha t exceeded the cutoff score on the stereotypy subscale whereas only 7% of those diagnosed with intellectual disability alone displayed stereotypy behaviors that exceeded the stereotypy subscale cutoff score (Matson et al., 1996). Similar results were found in a study comparing repetitive behavior between those with Autism versus those with intellectual disability matched on relevant subject characteristics (i.e., age, gender, and intelligence; Evans & Gray, 2000). Overall, research comparing those with ASD versus those with intellectual disability has found that those with ASD had higher levels of repetitive behaviors than those with intellectual disability Additionally, those with an ASD report ed greater levels of severity in the following domains: compuls ions, self injurious behavior, and stereotyped motor behavior In terms of sameness behaviors and ritualistic behavior, those diagnosed with ASD tend to display more frequent insistence on sameness and
23 ritualistic behaviors compared to those without an ASD diagnosis (Bodfish, Symons, Parker, & Lewis, 2000) Research has also compared obsessive and compulsive behavior among those with Autism versus those with Obsessive Compulsive Disorder ( OCD ) an anxiety disorder characterized by unwanted thoughts and fee lings that lead to feeling driven to perform a behavior in order to reduce anxious thoughts and feelings (American Psychiatric Association, 2000). A research study comparing those with Autism versus OCD found those with Autism were more likely to hoard, to uch in patterns, engage in self injurious behavior and were less likely to engage in checking behavior, report thoughts related to aggression, and desire symmetry. In addition, those with Autism displayed less complex obsessions, and reported higher levels of obsessions than compulsions (McDougle et al. 1995) In a study comparing ASD to Prader Willi Syndrome a rare genetic disorder characterized by hypotonia, an insatiable appetite, and low levels of sex hormones, both groups shared similar levels of RR BIs (Greaves, Prince, E vans, & Charman, 2006). When examining individual items, those with ASD were more likely to line up objects, focus on minor details, and have specific food preferences whereas those with PWS were more likely to collect and store it ems. Although RRBIs are not specific to ASD, generally those with ASD tend to display a greater number and more severe levels of repetitive and restrictive behaviors when compared to other disorders (Bodfish et al., 2000; Greaves et al., 2006; Matson et al ., 1996; McDougle et al., 1995). The examination of RRBIs in research has been subject to limitations as a result of a lack of consensus in terminology, operational definitions, and validated assessment
24 tools to measure RRBIs (Lewis & Bodfish, 1998). Gene rally, among those diagnosed with an ASD, RRBIs include a wide variety of maladaptive behaviors including, but not limited to, s tereotyped behavior compulsions, obsessions, rituals, sameness behaviors, self injurious behavior, and a narrow set of interest s (Lewis & Bodfish, 1998) Stereotypies are repetitive motor movements that may not serve a clear purpose (e.g., hand flapping spinning, and rocking ); compulsions are repetitive behaviors that one feels driven to perform in order to reduce anxiety or dist ress; obsessions are pervasive thought patterns that can engender anxiety; rituals are repetitive behaviors that are governed by rules without a clear purpose (e.g., touching in patterns); sameness behaviors reflects a strong desire for things to be the sa me (e.g., wanting the furniture to stay in the same location); self injurious behaviors are repetitive behaviors that cause harm or have the potential to cause harm to the individual (e.g., head banging or skin picking); and circumscribed interests or havi ng a narrow interest and perseveration on that particular topic (e.g., an intense interest in natural disasters that deviates from typically developing children). The expression of RRBIs varies in the frequency, typology, and level of intensity across ind ividuals with an ASD. According to the DSM IV TR, this domain is defined as (American Psych iatric Association, 2000 p. 75 ). To determine whether this criteria is me t, clinicians are responsible for determining whether the client has displayed at least one of the following behaviors: (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
25 flapping or twisting or complex whole body movements; or (d) persistent preo ccupation with par ts of objects. Although the behaviors outlined in the DSM IV TR are varied, they share similar characteristics, including repetition, persistence, inflexibility, and developmental inappropriateness. In addition, these behaviors tend to co occur rather than occur in isolation and are more pervasive for those with severe ASD symptoms (Bodfish & Lewis, 2002 ). Recently, research has begun to evaluate the phenotype of RRBIs among those diagnosed with an ASD. Types of Restricted and Repetitive Behavior Debate ex ists over the number of RRBI subtypes that exist within those diagnosed with an ASD. In order to identify the phenotypic structure of RRBIs, studies have used Factor Analysis methodology to determine the number of RRBI subtypes. Factor analysis methodology allows researchers to examine whether items on the rating scale are correlated to form an underlying latent construct that are reflected in the measured variables (Field, 2009). Factor analysis allows researchers to possibly reduce a set from a group of i nterrelated variables to a smaller set of factors. Factor analytic studies with samples diagnosed with ASD describe the RRBI domain as having multiple factors, thus suggesting that RRBIs represent a heterogeneous category (Cuccaro et al., 2003; Georgiades, Papageorgiou, & Anagnostou, 2010; Mirenda et al., 2010; Mooney, Gray, Tonge, Sweeney, & Taffe, 2009; Snow et al. 2009; Szatmari et al., 2006). To date most factor analytic studies use d the Autism Diagnostic Interview, Revised (ADI R ; Le Couteur, Lord, & Rutter, 2003 ) a measure consisting of 111 items. The ADI R is administered in a semi structured interview format with a parent or
26 caregiver. The ADI R is designed to help clinicians differentiate ASD from other conditions ( e.g., intellectual disability), by collecting information on the core areas of impairment present in ASDs (i.e., social interaction, communication, restricted and repetitive behaviors) in addition to age of onset. Although the ADI R was not intended to serve as a comprehensive measure o f RRBIs, there are several items related to the RRBI domain that have been used in factor analytic studies. The majority of these studies have found two factors, including restricted and repetitive sensory motor behavior (RMSB) and insistence on sameness ( IS) (Cuccaro et al., 2003; Mooney et al., 2009; Richler, Huerta, Bishop, & Lord, 2010; Shao et al., 2003; Szatmari et al., 2006). In addition, these studies have found that RSMB and IS account for approximately 32% to 36% of the variance in RRBIs. Specifi cally, Cuccaro et al. (2003) used Principal Component Analysis (PCA) and Factor Analysis (FA) with promax rotation to estimate the number of factors using 12 items from the ADI R. The sample consisted of 207 individuals between the ages of 3 and 21. A two factor model was selected, which consisted of repetitive and sensory motor behaviors and insistence on sameness. Shao et al. (2003) conducted a PCA with a sample size of 221 between the ages of 3 and 21. Results also yielded a two factor model, including r epetitive and sensory motor behaviors and insistence on sameness. Szatmari et al. (2006) used PCA with a varimax rotation to determine the presence of two three and four factor solutions using 11 items from the ADI R. The sample consisted of 339 indiv iduals with a mean age of 8.4 years. A two factor model was Mooney et al. (2009) used Exploratory Factor Analysis (EFA) and applied Principal
27 Factoring as the extraction method with12 ADI R items. Results also yiel ded a two factor model. Richler, Bishop, Kleinke, and Lord (2007) used Confirmatory Factor Analysis (CFA) to examine items from the ADI R and also found support for a two factor model. Lam, Bodfish, and Piven (2 008) added three items (i.e., unusual preoccupations, unusual attachments, and circumscribed interests) from the ADI R using an initial PCA with a varimax rotation. Subsequently, information from the PCA was used to guide the EFA using the generalized leas t squares discrepancy function with a target rotation. Results indicated a three factor model, including the repetitive motor behavior factor, insistency on sameness, and circumscribed interests These three domains accounted for 52 % of the variance. Lam regarding the issue of having a limited number of items when examining the factor structure of RRBIs. A major limitation to using the ADI R is the lack of items measuring RRBI behaviors. Because the ADI R was not intended serve as a comprehensive measure of RRBIs, it is possible that the ADI R does not adequately measure RRBIs for those with an ASD. To address this limitation, factor analytic studies have begun to use the Repetitive Behavior Scal e Revised (RBS R ; Bodfish, Symons, & Lewis, 1999 ), a rating scale intended to capture a wide range of RRBIs for those with ASD (Georgiades et al. 2010; Lam & Aman, 2007; Mirenda et al., 2010). The RBS R is comprised of 43 items, which compose six sub scal e s: Stereotyped Behavior (i.e., movements that have no clear purpose and occur repeatedly); Self injurious Behavior (i.e., behaviors that have the potential to harm one self); Compulsive Behavior (i.e., behavior that an individual feels
28 driven to perform a nd must occur in a specific way); Ritualistic Behavior (i.e., performing a particular behavior in the same way with particular rules set by the individual); Sameness Behavior (i.e., insisting that things stay the same); and Restricted Behavior (i.e., limite d interests; Bodfish et al. 2000 ). Factor analytic studies using the RBS R have yielded varied findings regarding the factor structure of RRBIs. For example, Georgiades et al. (2010) conducted Principal Factor Analysis (PFA) to examine the factor structu re of RRBIs using the RBS R in a sample that ranged between the ages of 2 and 48 years Two factors similar to the RSMB and IS factors that have been found when analyzing the factor structure of the ADI R were identified. The first factor, which resembled the RSMB domain, included self injurious behavior and stereotyped behavior whereas the second factor, which resembled the IS domain, included compulsions, rituals, sameness, and restricted behavior. Lam and Aman (2007) conducted Exploratory Factor Analysi s (EFA) in a sample ranging between the ages of 3 and 48 and found five factors: (Factor 1) ritualistic and sameness behavior combined; (Factor 2) stereotyp ed behavior; (Factor 3) self injurious behavior; (Factor 4) compulsive behavior; and (Factor 5) rest ricted behavior Both Georgiades et al. (2010) and Lam & Aman (2007) used a wide age range to examine the factor structure of RRBIs. Mirenda et al. (2010) is the only published study that has examined the factor structure of RRBIs as measured by the RBS R with a narrow age using Confirmatory Factor Analysis (CFA) including 287 preschool aged children between the ages of two and five with ASD. An evaluation of six competing models was conducted and based on
29 previous research. The first model included all R BS R subtypes: stereotyped behavior, self injurious behavior, compulsive behavior, ritualistic behavior, and restricted behavior The second model included (Factor 1) stereotyped behavior, self injurious behavior, restricted behavior ; and (Factor 2) compul sive behavior, ritualistic behavior, and insistence on sameness. The third model included (Factor 1) stereotyped behavior and restricted behavior ; (Factor 2) self injurious behavior; and (Factor 3) ritualistic behavior, compulsive behavior, and insistence on sameness behavior. The fourth model included (Factor 1) stereotyped and restricted behavior ; (Factor 2) self injurious behavior; (Factor 3) compulsive behavior; and (Factor 4) ritualistic behavior and insistence on sameness. The fifth model included (Fa ctor 1) stereotyped behavior; (Factor 2) self injurious behavior; (Factor 3) compulsive behavior; (Factor 4) restricted behavior ; and (Factor 5) ritualistic behavior and insistence on sameness. The sixth model included (Factor 1) stereotyped behavior; (Fac tor 2) self injurious behavior; (Factor 3) compulsive behavior; (Factor 4) ritualistic behavior; (Factor 5) restricted behavior ; and (Factor 6) insistence on sameness. It is important to note that it is unclear how the three factor and four factor model s w ere derived. The three factor model deviates from the only study to yield a three factor model using the ADI R: Repetitive Sensory Motor Behaviors, Circumscribed Interests, and Insistence on Sameness (Lam et al., 2008). In addition, research studies to dat e have not selected a four factor model. Mirenda et al. (2010) found support for a three and five factor model on the basis of model fit and parsimony. The structure of the five Mirenda et al. (2010)
30 r ecommend the use of the three factor model for genetics research and the five factor model for research evaluating treatment effects In sum, factor analysis research suggest those with an ASD have multiple RRBIs. Results from the ADI R suggest a two or three factor model. These results are limited because the ADI R may not adequately sample RRBIs. As a result, factor analytic studies using the RBS R, a comprehensive measure of RRBIs, suggest a two three or five factor model. Possible explanations fo r the variability in determining the number of factors include differences in the measurement of RRBIs, type of factor analytic method employed, and sample characteristics. Although variability in the number of RRBI subtypes exists, research has begun to examine whether subject characteristics are related to RRBI subtypes. Similar to the two factor model identified in many factor analytic studies, Turner (1999) proposed two o (e.g., stereotyped body movements, dyskinesias, self injurious behavior, and repetitive behavior, strong attachments to objects, and circumscribed interests) repet itive behaviors. The basis for the theoretical organization of RRBIs was based on the review of the literature examining RRBIs and cognitive ability. Turner (1999) suggests that lower order RRBIs may be influenced by lower cognitive ability and higher orde r RRBIs may be influenced by higher cognitive ability. The next section will explore research studies examining the relationship between intellectual functioning and RRBIs. Intelligence and RRBI Research studies evaluating t he cognitive aspect of RRBIs ha ve found some To illustrate, in a study
31 comparing RRBIs among those with Autism versus those with Asperger Syndrome or PDD NOS, those with Autism had significantly higher RSMB behaviors where as those with Asperger Syndrome had significantly higher IS behaviors (Szatmari et al., 2006). Lam (2004), found those with stereotypic behaviors and self injurious behaviors were more likely to have severe/profound ID Those demonstrating restricted behav ior were more likely to have mild to moderate levels of intellectual impairment. A limitation to the study was the measurement of cognitive ability, which was measured by asking the parent or caregiver to identify whether the severity of mental retardation was mild, biased manner. Militerni, Bravaccio, Falco, Fico, and Palermo (2002) st udied RRBIs among 121 participants between the ages of 2 and 11 using items from the Yale Brown Obsessive Compulsive Scale (Y BOCS ; Goodman et al., 1989 ), the Childhood Autism Rating Scale (CARS ; Schopler, Reichler, & Renner, 1986 ), the Aberran t Behavior C hecklist (ABC; Aman & Singh, 1986), the Stereotyped Behavior using the Griffiths Scale of Mental Development (Griffiths, 1976) or the Wechsler Intelligence Scale for Children, Third Edition (WISC III, Wechsler, 1991). Th ose who were between the ages of 2 and 4 were administered the Griffiths Scale of Mental Development whereas those between the ages of 7 and 11 were administered the WISC III. The entire sample was divided into three subgroups, low IQ (<35), medium IQ (36 70), and high IQ (>70). They found that sensory and repetitive motor behaviors in Autism occurred more frequently in those with low levels of cognitive
32 functioning whereas complex repetitive activities and echolalia were more common in those with high leve ls of cognitive functioning. However, IS and a need for routines were not related to cognitive functioning. A limitation to the study included the measurement of intelligence. Combining intelligence tests in a single study and dividing the tests into three different groups presents measurement error. Furthermore, administration of intelligence tests on those between the ages of 2 and 4 may not accurately measure their intelligence. Intellectual functioning tends to become stable around the age of five (Bayl ey, 1949). Bishop, Richler, and Lord (2006) compared the nonverbal intelligence quotient (NVIQ) and verbal intelligence quotient (VIQ) on the severity of RSMB versus IS behavior The NVIQ and VIQ were established using the Mullen Scales of Early Learning (MSEL; Mullen, 1995) or the Differential Ability Scales (DAS; Elliot, 1990). Repetitive behavior was measured using the ADI R (Le Couteur et al., 2003 ) They found that RSMBs were negatively related to NVIQ and VIQ; however, IS was not related to NVIQ or VIQ. Similar findings were reported in a study by Richler et al. (2010), which utilized a longitudinal approach using different intelligence tests depending on the severity of ASD symptoms. For those that were two years old or did not have the language abi lity to be administered the WISC 3 (Wechsler, 1991) or the DAS (Elliot, 1990), were administered the MSEL. Because the MSEL does not yield a separate NVIQ and VIQ score, the authors derived these scores using an extrapolation procedure (see Richler et al. 2007 for a complete description). Findings indica ted that NVIQ was more strongly and negatively related to RSMB behaviors than IS behaviors (Richler et al., 2010) In a separate study comparing those with ASD versus those with
33 ASD with an intellectual di sability (ID), those with a comorbid diagnosis of ASD and ID had greater levels of stereotyped movements and self injurious behaviors. Having a comorbid diagnosis of ASD and ID was not related to IS, CI, or compu lsive behaviors (Esbensen, Seltzer, Lam, & B odfish 2009). Gabriels, Cuccaro, Hill, Ivers, and Goldson (2005) conducted a study of 14 participants to evaluate RRBIs using the RBS R and their relationship with cognitive ability using the Leiter R. These researchers examined RRBIs in those with low N VIQ scores, which was defined as an intelligence quotient (IQ) score equal to or less than 56 (N = 6) versus those with high IQ scores, which was defined as an IQ score of equal to or greater than 97 (N = 8) Their findings indicated that those with low N VIQs had higher levels of RRBIs (Gabriels et al., 2005). There were no significant differences between high versus low NVIQ among the six different subtypes of RBBIs with the exception of sameness behaviors. Those with lower NVIQ had significantly higher r ate s of sameness behaviors A major limitation of this study was the small sample size of fourteen children and youth. It is quite possible that the small number of participants limited the ability to detect differences. The significant relationship betwe en lower NVIQ and higher sameness behavior contr adicts research suggesting that intelligence was not related to sameness behavior as measured by the Y BOCS or ADI R (Bishop et al., 2006; Esbensen et al., 2009; Militerni et al., 2002). However, t hese result s support Bartak and which found that insist ence on sameness occurred in 82% of their sample diagnosed with Autism and Intellectual disability as compared to 4 2% of their sample diagnosed with Autism only.
34 In sum, research investiga ting the relationship between lower cognitive ability and lower order RRBIs and higher cognit ive ability and higher order RRBIs provide conflicting results. Generally, categorization of RRBIs. A major lim itation to the studies examining the role of intelligence on RRBI subtypes has been the measurement of cognitive functioning. Presently, research studies primarily use categorical methods to measure cognitive functioning by asking rater s to indicate the se verity of cognitive impairment or quantify IQ by using a mixture of different intelligence tests (Bishop et al., 2006; Esbensen et al., 2009; Lam, 2004; Militerni et al., 2002; Richler et al., 2010) The problem with using a myriad of IQ tests is that litt le is known whether IQ performance among those with ASD is correlated across different measures of intelligence. Only one study to date has used a single IQ measure along with the RBS R; however, their small sample size of 14 participants may have limited the statistical power to determine whether differences were present (Gabriels et al., 2005). Furthermore, most studies examining the relationship between IQ and RRBI expression has emphasized RSMB and IS behaviors, with little at tention to other RRBI domai ns. Another area of exploration is the examination of adaptive functioning on the manifestation of RRBIs. Research studies have consistently found that those with ASD have significantly lower adaptive functioning as compared to cognitive functioning (Liss et al., 2001 ; Volkmar et al., 1993 ). The relationship between IQ and adaptive functioning tends to be strongest for those with low IQ scores (C arpentieri & Morgan, 1996; Liss et al., 2001) Very few studies have examined the relationship between adaptive
35 functioning and restricted and repetitive behaviors. The next section describes the current literature examining the relationship between adaptive functioning and RRBIs. Adaptive Functioning a nd RRBIs Evans and Gray (2000) conducted a study comparing RRBIs in typically developing children along with those with Down syndrome matched on developmental level measured by the Vineland Adaptive Behavior Scales Screener and found that both groups showed the same levels of repetitive, ritualistic, and compulsive beh avior. These results suggest that adaptive functioning may also impact the severity of RRBIs. Liss et al. (2001) compared Autistic children who had low IQ scores or scores less than 80 versus those with high IQ scores, or scor es equal to or greater than 80. They found that those who had high IQ scores had adaptive behaviors that were negatively correlated with total score of restricted and repetitive behaviors as measured by the Wing checklist (Wing, 1985) In a study examining risk facto rs for self injur ious behavior, those with lower adaptive functioning were more likely to engage in self injurious behaviors (Baghdadli, Pascal, Grisi, & Aussilloux, 2003). Recent research examining restricted and repetitive behavior subtypes using the ADI R found that ad aptive functioning as measured by the Vineland Adaptive Behavior Scales, Second Edition (VABS II ; Sparrow, Cicchetti, & Balla, 2005 ) had a significant negative correlation with RSMBs. In other words, those with higher levels of adaptive functioning had low er levels of RSMBs. However, adaptive functioning was not significantly correlated with IS (Cuccaro et al., 2003; Szatmari et al., 2006). There is evidence to suggest that while RSMBs are more closely related to developmental level, IS behaviors tend to ha ve a familial basis and tend to be related to communication deficits (Szatmari et al., 2006). Similar to the research examining intelligence and
36 repetitive behavior, future research is needed to examine the relationship between adaptive functioning and RRB I subtypes. In addition, using scales that measure comprehensive RRBI behaviors may also improve our understanding of RRBIs among those with an ASD. The following section examines co morbid conditions that are often observed in those diagnosed with an AS D. Co morbid Psychiatric Behavior al Problems and RRBIs Those diagnosed with ASDs often experience psychiatric and behavioral symptoms beyond the core characteristics used to determine a diagnosis. Actual rates of mental health problems are not available b ecause much of our understanding of co morbid psychiatric conditions has been determined via clinical case reports or studies with small sample sizes. Estimates of those with ASD and mental health problems range between 4% and 58% (Lainhart, 1999). In a po pulation based study of youth and young adults, approximately 40% of those with Autism reported having at least one mental health breakdown (Bryson & Smith, 1998). Psychiatric conditions often reported in those with ASDs include depression (Howlin, 2000), anxie ty disorders (Green et al., 2006 ), and bipolar disorder (Howlin, 2000). In a review of psychiatric conditions of 200 individuals diagnosed with ASD, over half of the sample was diagnosed with depression or anxiety disorders (Howlin, Good e Hutton, & R utter, 2004). Mental health problems affect both low and high functioning individuals with ASD. However, identifying psychiatric disorders are difficult because of the manifestation of core symptoms. For example, those with low cognitive functioning, comm unication deficits or both, may have difficulty expressing their symptoms. In addition, those with obsessions, hypersensitivity, flat affect, and echolalia may be misidentified as having symptoms of psychopathology. In terms of behavioral problems, those with ASD tend
37 to have high levels of inattention, irritability, and hyperactivity (Gabriels et al., 2005). In a study examining the influence of in attention, irritability, and hyperactivity, after controlling for IQ and adaptive functioning hyperactivity was the only behavior significantly related to total RRBI scores on the RBS R. These researchers did not examine the influence of hyperactivity on RRBI subtypes. In a study by Hattori et al. (2006), those with ASD were compared to those with Attention Def icit Hyperactivity Disorder (ADHD) The results indicated that they had similar levels of restricted and repetitive behaviors. Future research is needed to better understand the unique role hyperactivity may have on the severity of RRBIs. Furthermore, it i s also important to consider the unique role development may have on the expression of RRBIs. The next section includes research examining the trajectory of RRBIs and subtypes over time. The Relationship of Age and RRBIs Cross sectional and longitudinal st udies suggest that age is associated with differences in RRBI manifestat ion in those with ASD (Esbense n et al. 2009; Mirenda et al., 2010; Richler et al., 2010). Cross sectional research examining age related changes have generally found that RRMB tend to abate as individuals become older (Esbensen et al. 2009; Lam & Aman, 2007) and are negatively related to adaptive functioning (Cuccaro et al., 2003; Szatmari et al., 2006); however, the trajectory of IS behavior is not as clear. For example, Bishop et al (2006) and Mirenda et al. (2010) reported that IS behaviors increase with age whereas Esbensen et al. (2009) reported a decline. It is possible that the research design may have been responsible for these differences. Bishop et al. (2006) and Mirenda e t al. (2010) used a younger sample with a narrower age range wh ile Esbensen et al. (2009) used a sample between the ages of 2 and 62. Th e only longitudinal study to date examining age r elated patterns, using data
38 collected from the ADI R at ages two, thre e, five, and nine. Results indicated that RRMB were elevated at a young age and remained elevated over time and IS behavior were reported low at a young age and increased over tim e (Richler et al., 2010). Purpose of Current Research Study Although recent research has begun to explore the area of RRBIs, further research is needed to e xpand our understanding of RRBIs as well as associated features related to RRBIs. Research examining the factor structure of RRBIs using the ADI R has found two (i.e., RSMBs a nd IS ; Cuccaro et al., 2003; Mooney et al. 2009; Richler et al., 2010; Szatmari et al., 2006) and three factors (i.e., RSMBS, IS, and CI) (Lam et al., 2008). Research using the RBS R has found two (Georgiades et al., 2010), three (Mirenda et al., 2010), and five factors (Lam & Aman, 2007; Mirenda et al., 2010). These inconsistencies have been associated varying statistical procedures and instruments used to measure of the structure of RRBIs as well as the use of a wide age ranges. Therefore, the primary p urpose of this investigation is to determine the number of RRBI subtypes when using the RBS R by examining which CFA model is the best fitting with a school age sample ranging between the ages of 5 to 21 us ing CFA procedures The models used in the study were based on results from previous factor analytic research using the ADI R and RBS R and theory The one factor model included all six subscales in order to test the null hypothesis. The two factor model consisted of: (Factor 1) stereotyped behavior res tricted behavior and self injurious behavior; and (Factor 2) compulsive, ritualistic, and sameness behavior. The three factor model consisted of: (Factor 1) stereotyped behavior and self injurious behavior; (Factor 2) compulsive, ritualistic, and sameness behavior; and (Factor 3) restricted behavior This study
39 examined the three factor model based o The five factor model consisted of: (Factor 1) stereotyped behavior ; (Factor 2) self injurious behavior; (Factor 3) compulsive behavior; (Factor 4) ritualistic and sameness behavior; and (Factor 5) restricted behavior The six factor model was based on the theoretical model created by the authors of the RBS R and consisted of : (Factor 1) stereotyped behavior; (Factor 2) sameness b ehavior; (Factor 3) self injurious behavior; (Factor 4) compulsive behavior; (Factor 5) ritualistic behavior; (Factor 6) restricted behavior Figure 1 1 Rival Models Evaluated 1 Factor Model Stereotyped Behavior Self Injurious Behavior Compulsive Behavior Ritualistic Behavior Sameness Behavior Restricted Behavior 2 Factor Model Stereotyped Behavior Self Injurious Behavior Restricted Behavior Compulsive Behavior Ritualistic Behavior Sameness Behavior 3 Factor Model Stereotyped Behavior Self Injurious Behavior Compulsive Behavior Ritualistic Behavior Sameness Behavior Restricted Behavior
40 Figure 1 1 Continued 5 Factor Model Stereotyped Behavior Self Injurious Behavior Compulsive Behavior Ritualistic Behavior Sameness Behavior Restricted Behavior 6 Factor Model Stereotyped Behavior Self Injurious Behavior Compulsive Behavior Ritualistic Behavior Sameness Behavior Restricted Behavior
41 A secondary purpose of this study was to examin e whether intelligence, adaptive functioning, hyperactivity, and age predict RRBI subtypes and overall repetitive behavior after determining the number of RRBI subtypes. A subset of the sample was used because not all of the participants were administered an intelligence test. The purpose of evaluating the role of intelligence, adaptive functioning, hyperactivity, and age was to address how individual characteristics may be related to RRBIs Having an understanding of associated characteristics and their re lationship to RRBIs may help improve our knowledge of RRBIs and inform intervention methods. In terms of intelligence, this study examined higher order and lower order RRBIs on the basis of cognitive ability using a singl e intelligence measure in a moderately large sample. A major limitation to previous research examining the role of cognitive ability has been the measurement of intelligence. Previous research has quantified IQ by asking parents to check off their functioning while other studies have included a mixture of intelligence tests (Bishop et al., 2006; Esbensen et al., 2009; Lam, 2004; Militerni et al., 2002) In addition, many studies have treated IQ has a categorical variable rather than treating it as a continuous behavior. Only one study to date has used a single nonverbal intelligence measure along with the RBS R; however, this research study had a small sample size of 14 and treated intelligence as being either high, equal to or greater than 97, or lo w, equal to or less than 56. The present research study used a single nonverbal intelligence test, the Leiter Revised (Roid & Miller, 1997). In addition, intelligence was measured as a continuous variable. Based on previous findings, it is hypothesized th at lower cognitive ability will
42 pr edict higher levels of lower order RRBIs (Bishop et al., 2006; Esbensen et al., 2009; Militerni et al., 2002). Previous findings have not consistently found significant and positive relationships between h igher cognitive a bility and increased levels of higher order RRBIs; therefore, it is unclear whether higher cognitive functioning will be related to higher order RRBIs. predicts that higher cognitive ability w ill be related to increased endorsements of higher order RRBIs. In addition to intelligence, this study will examine the relationship between adaptive functioning and RRBIs. Lower adaptive functioning is predicted to be related to higher overall repetitive behavior. To date, research has not examined the role of adaptive functioning on a wide variety of RRBI subtypes. This study hopes to clarify whether adaptive functioning is related to RRBI subtypes using a comprehensive measure of RRBIs. In terms of hyp eractivity, it is hypothesized that hyperactivity will predict a greater frequency of RRBIs based on the work of Gabriels and colleagues (2005). However, research to date has not examined the role of hyperactivity on RRBI subtypes; therefore, this research study hopes to clarify whether hyperactivity ha s a differential impact on RRBI subtypes. In line with previous findings regarding the relationship between age and RRBIs, it is hypothesized that lower order RRBIs would decrease as age increased; however, i t is hypothesized that the inverse of this relationship will occur for higher order RRBIs.
43 CHAPTER 2 METHODS Participants Participants consisted of 205 individuals between the ages, in months of 60 and 246. The average age was 122 months (SD = 41.4 ), with approximately half of the sample being between the ages of 60 and 108 months. There were more males (80.5%) than females (19.5%). The ratio of males to females is consistent with the Center for Disease Control (2012 ) finding, which estimates that ASD prev alence rates are 4 to 5 times higher for males as compared to females. The ethnic background was 83.4% non Hispanic and 16.6% Hispanic. A majority of the participants reported their racial background was w hite ( 82.4 %), followed by b lack ( 6.8 %), and other ( 10.8 %). The subsample consisted of 78 individuals with a mean age, in months, of 119.91 (SD = 41.4 ). There were 87.2% males and 12.8% females. The ethnic background of the subsample consisted of 90.7% non Hispanic and 9.3% Hispanic. The racial breakdown w as 78 .2 % white and 2 1.8 % other. It should be noted that black, Asian, American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander and other were due to the small number of participants in each catego ry. Participants were selected based on their participation in at least one out of three ASD research studies at the University of Florida. In order to qualify for participation in these studies, participants must have had a clinical diagnosis of an ASD pr ior to participation. Participants were recruited primarily through their participation in the Center for Autism and Related Disabilities (CARD) and through the Psychiatry department at the University of Florida. This sample is primarily drawn from a rural area in the southeast area and may not reflect urban or other regional populations.
44 Participants were excluded from participating in the study if they reported having cerebral palsy or other neuromotor conditions as well as sensory conditions (i.e., blind ness or deafness) because these conditions are also associated with RRBIs. studies and participants were treated in accord with the American Psychological (2002) Each study varied in terms of the data collected; however, there was significant overlap in methodology. For example, all participants had a parent or caregiver fill out rating scales related to r estricted and repetitive behavior, adaptive functioning, hyperactivity, and social communication. In addition, a subset of the sample was administered intelligence tests. Table 3 1 presents descriptive data regarding participants. Instruments Health Histor y Questionnaire page questionnaire designed by the researchers to collect age, gender, ethnicity, race, classroom type, interventions, the type of ASD diagnosis, the name of the clinician who made the diagnosis, whether other clinical diagnoses were present, the type of medication prescribed within the last three months, and whether family members have been diagnosed with ASD and/or co morbid medi cal conditions. Restricted and Repetitive Behaviors or Interests The Repetitive Behavior Scale Revised (RBS R; Bodfish et al. 2000 ) was administered to capture a wide range of RRBIs. The RBS R has a total of 43 items, which com prise six subscales, includ ing s tereotyped behavior, self injurious behavior,
45 compulsive behavior, ritualistic behavior, sameness behavior, and restricted behavior The items are rated on a Likert scale ranging from zero (i.e., the behavior does not occur) to three (i.e., the behavi or occurs and is a severe problem). The subscales and items were conceptually grouped based on clinical experience. interview of Bodfish (2004) the aut hors of the rating scale conducted Principal Components Analysis and found support fo r six components corresponding to the original subscales based on the following criteria: scree test, eigenvalues >1, coefficient alpha >.60, salient loading >.30, item total correlations between .20 and .70 ( Bodfish, 2004, as cited in Lam, 2004) I nter ra ter reliability ranged between .55 (Sameness Behavior) to .78 (Self Injurious Behavior) and test retest coefficie nts ranged between .52 (Ritualistic Behavior) and .96 (Restricted Behavior ) In a separate study, internal consistency of factors ranged betwee n .78 (Restricted Behavior ) and .91 (Ritualistic/Sameness Behavior; Lam & Aman, 2007). Intellectual Functioning In 1997, Roid and Miller revised the Leiter International Performance Scale to create the Leiter International Performance Scale Revised (Leite r R), a measure used to assess the cognitive functioning for those between the ages of 2 and 20 years, 11 months. The Leiter R is administered in a non verbal format where the examiner and examinee communicate without using speech, allowing for the assessm ent of children for whom traditional, verbally loaded intelligence tests may not be appropriate. This includes students who are hearing impaired, have limited English proficiency, and have moderate to severe speech or language impairments. The Leiter R is particularly useful for those with an ASD because there are minimal to no language requirements, all subtests are untimed, and the structure of the test is similar across subtests, which may
46 make it easier for those who display insistence on sameness behav iors to transition into new activities (Tidmarsh & Volkmar, 2003). For this study, four subtests that comprise the Brief IQ Screener composite were administered: Figure Ground, Form Completion, Sequential Order, and Repeated Patterns. The tasks that compr ise the Leiter R include identifying a figure embedded in a larger picture, recognizing an object based on an array of its segmented parts, putting picture cards in sequential order, and selecting a picture that completes a sequence. To obtain an IQ score the sum of subtest scaled scores are converted to a scaled score (M = 100; SD = 15). The test was normed on a sample of 1, 719 individuals. The sample was carefully selected to be representative of individuals at these ages in the United States. The demo graphic background of the sample was diverse in terms of socio economic background, ethnic background, and geographic location, and was based on 1993 population survey collected by the United States Census Bureau. Internal consistency reliabilities from t he Brief IQ Screener ranged from .88 to .90 and test retest reliability coefficients ranged from .88 to .96. Test retest reliability coefficients on subtest performance ranged from .70 to .88. In a study examining concurrent validity between the original Leiter and the Leiter R among 26 individuals diagnosed with an ASD, there was a high correlation of .87 for the Brief IQ score (Tsatsanis et al., 2003). A separate study evaluating the profile of scores within those with an ASD as well as comparisons with those who are typically developing or developmentally delayed without an ASD found that those with an ASD demonstrated relative strengths in the ability to select objects from a larger picture and focus on process information focusing on specific details a nd relative weaknesses in the
47 areas of abstract thought and concept formation ( Kuschner, Bennetto, & Yost, 2007 ). This contrasted with patterns of nearly equivalent abilities in the comparison groups and supports theories such as having weak central cohere nce, or limited ability to view an entire perspective because of attention given to smaller details. Further information regarding the psychometric properties of this instrument can be found in the Leiter R Adaptiv e F unctioning Sparrow et al. (2005) created the Vineland Adaptive Behavior Scales, Second Edition (VABS II), a norm referenced measure, to assess the adaptive functioning for those between the ages of zero and 90. The VABS II allows caregivers and teacher s to Parent/Caregiver Rating Form collects information from the primary caretaker to obtain an overall composite of adaptive functioning along with subscale scores in a variety of domains, including communication, daily living skills, socialization, and motor development. The two forms differ in the format in which they are administered (i.e., ch The test was normed on a random sample of 760 individuals. The demographics of the norm sample were based on the Current Population Survey, March 2001. Within each age group, there were ap proximately equal proportions of males to females matched on important demographic characteristics: race/ethnicity, socio economic status, and geographic location. In addition, the norm sample was stratified on educational placement to ensure the proportio nal representation of those with disabilities. Internal consistency reliabilities, using the split half method, were generally
48 high, with more than half of the Pearson correlation coefficients being above .90 and only 6% being below .80. When examining the correlations between the Survey Interview Form and the Parent/Caregiver Rating Form, median correlation coefficients ranged betw een .75 and .98. T he VABS II had sufficient test retest reliabilities and inter rater reliability across different age ranges. The utility of the VABS II is also apparent when evaluating those with an ASD. Individuals with autism generally have lower adaptive functioning scores as compared to the normative sample. The lowest scores were in the areas of socialization as well as sk ills associated with expressiveness and leisure (Sparrow et al., 2005). Validity of the VABS II was based on test content, evaluation of response bias, test structure criterion related validity, and an analysis of clinical subgroup functioning. Further in formation regarding the psychometric properties of this instrument can be found in the VABS II et al., 2005). Hyperactivity The Aberrant Behavior Checklist (Aman, Singh, Stewart & Field, 1985) is a 58 item checklist with five d omains: (1) Irritability, Agitation, Crying; (2) Lethargy, Social Withdrawal; (3) Stereotyp ic Behavior; (4) Hyperactivity; and (5) Inappropriate Speech. Parents or caregivers are asked to rate items on a four point Likert scale ranging from zero (i.e., not at all a problem) to three (i.e., the problem is severe in nature). The hyperactivity composite from the ABC was used to measure hyperactivity, which consists of 16 items. The structure of the ABC was developed using factor analysis which has been suppor ted in independent validation studies (Aman et al., 1985; Brinkley et al., 2007). e ff i cients ranging from .86 to .94
49 across all subscales and indicated sufficient internal consistency (Aman et al. 1985). In addition, c onfirmatory factor analysis yielded a moderate fit for a five factor model within a sample of 275 individuals with an ASD (Brinkley et al., 2007). The five factors were labeled Irritability, Lethargy, Stereotypy, Hyperactivity, and Inappropri ate Speech. Factor l oadings ranged from .46 to .83. C onvergent validity was established by comparing the ABC with respect to an analogous scale, the Behavior Problems Inventory (BPI ; Peterson & Zill, 1986). M ultiple regression analyses indicated the BPI pr edicted ABC subscale scores (Hill, Powlitch, & Furniss, 2008) In addition, the ABC has been found to be sensitive to measuring behavioral interventions using pharmacological interventions (Aman et al., 2003; Aman, Binder, & Turgay, 2004). In a randomized controlled study examining the effects of Risperidone, an anti psychotic medication, improvements in disruptive behavior and hyperactivity were identified following treatment (Aman et al., 2004). Statistica l Analyses Data were screened prior to conducting the analyses in order to examine whether there were any violations of assumptions as well as the presence of outliers. Descriptive statistics were conducted for all demographic, outcome, and predictor variables. To examine the main objective of this study a CFA was conducted for all rival models (i.e., one two three five and six factor model) using the Mplus statistical software program ( Muthn & Muthn, 1998 2010 ). After establishing the covariance between each of the variables, a model fitting p rocedure was conducted using the Weighted Least Squares Mean and Variance Adjusted (WLSMV) estimator In accordance with recommendations from previous literature (Hu & Bentler, 1999), model fit was evaluated using multiple methods, including an absolute fi t index (i.e., chi square
50 test), a parsimony correction index (i.e., root mean square error of approximation), and comparative fit indices (i.e., Comparative Fit Index and Tucker Lewis Index). The criteria for acceptable values for an acceptable goodness o f fit were based on the work of Bollen and Long (1993), Dimitrov (2006), and Hu and Bentler (1999). The ratio of chi square to degrees of freedom was set at a value less than 2 as an indication of acceptable fit. For RMSEA, the criteria were set at .08 for the lower bound indicator of goodness of fit, and .06 as an indicator of a well fitting model. For the Comparative Fit Index (CFI) and the Tucker Lewis Index (TLI), the value was set at a value of less than .90 for the lower bound indicator for an adequat e model of fit and values above .95 as a well fitting model. Furthermore, the goodness of fit of a mo del was also conducted using the Maximum Likelihood (ML) estimator in order to obtain the Akaike Information Criterion (AIC) and the Bayesian Information C riterion (BIC). Generally, models with the lowest AIC and BIC values are considered to fit the data better as compared to the aforementioned methods, because these indices compare models by accounting for the complexity of each (Brown, 2006). To address th e secondary obje ctive of the study, simultaneous multiple regression analyses using PASW 13.0 were conducted to exami ne how subject characteristics predict factor scores based on results from the CFA, as well as the RBS R sum score. Multiple regression ana lyses included the same independent variables : intelligence, age hyperactivity, and adaptive functioning T he dependent variable included the RBS R sum score as well as factor scores.
51 CHAPTER 3 RESULTS The results of this study are divided into four sec tions. The first section includes data screening procedures that were conducted in advance to evaluate whether assumptions guiding the specific analyses were met. The second section includes descriptive statistics for relevant variables in the study and co rrelation analys e s to examine whether there were significant relationships between the RBS R and ADI R. The third section includes the results of the CFA. The fourth section includes the results of multiple regression analyses examining whether intelligenc e, age, adaptive functioning, and hyperactivity predict RBS R sum and factor scores. Data Screening When conducting statistical analyses to test hypotheses, appropriate conclusions can be drawn when assumptions that are particular to the analysis are sati sfied. Therefore, prior to conducting the analyses all variables used in the study were screened. Descriptive statistics for the entire sample and subsample can be found in Tables 3 1 and 3 2. Means, standard deviations, skewness and kurtosis values can be found in Tables 3 3 and 3 4. According to an analysis using the Mahalanobis Distance statistic, there were no statistically significant multivariate outliers. Tolerance values suggested that there was no statistically significant multicollinearity in the data. Univariate normality was assessed by examining scatter plots along with skewness and kurtosis values for each variable. According to Finney and DiStefano (2006), absolute values of skewness and kurtosis beyond 2 and 7, respectively, may indicate a la ck of univariate normality. For all variables included in the study skewness and kurtosis
52 values were within normal limits. Skewness values ranged from .936 to 1.961 and kurtosis values ranged from .040 to 4.146. Descriptive Statistics Outcome Variables Table 3 3 displays the mean ratings and standard deviations for outcome variables measured in the study, including stereotyped behavior, self injurious behavior, ritualistic/sameness behavior, compulsive behavior, restricted behavior and the RBS R Sum Sco re. Item endorsements on the RBS R were similar to endorsements from other ASD samples (Flores et al., 2011). Internal consistency for this measure was calculated ween .74 and .91 for all five factors, indicating adequate or better internal consistency. These results support alues between .78 and .91 (see T able 3 5). Predictor Variables Table 3 4 displays predictor varia bles measured in the study. Approximately half of the sample was between the ages of 60 and 108 months, with a mean age of 120.4 months (SD = 45.3 ). The mean score for hyperactivity was (M = 19.8 ; SD = 11.7 ). This finding is similar to Capone et al. (2005) who reported a mean hyperactivity score of 20.8 (SD = 10) for 61 individuals diagnosed with an ASD. The mean score for Intelligence was 90.1 (SD = 25.6 ) and lower than the scores in the standardization sample (M=100). These findings are consistent with a report of 129 individuals diagnosed with an ASD and administered the Leiter R who had a mean IQ score of 89.6 (SD = 23; Grondhuis, Mulick, & Aman, 2010) Adaptive Functioning (M = 77.2 ) were also lower than the scores in the standardization sample (M = 10 0). These results were
53 expected given deficits in socialization and communication. These findings are in accord with Sparrow et al. (2005). Correlational Analysis Table 3 6 displays a correlation matrix between the RBS R subscales and ADI R items related to repetitive behavior. The correlation matrix included the six subscales that comprise the RBS R as well as the thirteen items that comprise the Interests and Behaviors composite on the ADI R. In addition, an item measuring self injurious behavior and an item measuring verbal rituals from the ADI R were included in the analysis based on their relevance to repetitive behavior among those with an ASD. Although repetitive communication is not included in the RBS R, the Verbal Rituals item was significantly a nd positively correlated only with stereotyped behavior (r = .21, p < .01) Repetitive Use of Objects was significantly and positively correlated with Stereotyped Behavior (r = .32, p < .05), Restricted Behavior (r = .34, p < .01) and the Sum score (r = 29, p < .05) Unusual Sensory Interests was significantly and positively correlated with Stereotyped Behavior (r = .34, p < .01) Self Injurious Behavior (r = .27, p < .05) Restricted Behavior (r = .25, p < .05), and the Sum score (r = .27, p < .05) Sens itivity to Noise was significantly and positively correlated with Compulsive Behavior (r = .32, p < .01) Ritualistic Behavior (r = .29, p < .05), and the Sum score (r = .28, p < .05). Negative Responses to Sensory Stimuli was significantly and positively correlated with Self Injurious Behavior (r = .34, p < .01) Difficulty with Minor Changes in Routine was significantly and positively correlated with Insistence on Sameness (r = .48, p < .01) and the Sum score (r = .34, p < .01) Resistance to Trivial Chan ges in routine was significantly and positively correlated with Stereotyped Behavior (r = .27, p < .05) Self Injurious Behavior (r = .31, p < .05) Compulsive Behavior (r = .35, p < .01) Insistence
54 on Sameness (r = .28, p < .05) and the Sum score (r = 36, p < .01) Hand and Finger Mannerisms was significantly and positively correlated with Stereotyped Behavior (r = .34, p < .01) Stereotyped Body Movements was significantly and positively correlated with Stereotyped Behavior (r = .43, p < .01) and the S um score (r = .30, p < .05) Self Injury was significantly and positively correlated with Stereotyped Behavior (r = .35, p < .01) Self Injurious Behavior (r = .68, p < .01) Ritualistic Behavior (r = .28, p < .05) and the Sum score (r = .32, p < .05) Unu sual preoccupations, Circumscribed Interests, Compulsions and Rituals, Unusual Attachments to Objects, and Midline Hand Movements were not significantly correlated with the RBS R subscales or total score. Confirmatory Factor Analysis An examination of the RBS R factor structure was conducted using CFA with the Mplus software program. Scores for each of the 43 items were entered into the analysis using the entire sample (N = 205). Five individual models were tested: (Model 1) a one factor or general factor model consisting of all 43 items; (Model 2) a two factor model consisting of (Factor 1) ster eotyped behavior restricted behavior and self injurious behavior; and (Factor 2) compulsive behavior rit ualistic behavior, and sameness behavior; (Model 3) a thr ee factor model consisting of (Factor 1) stereotyped behavior and self injurious behavior; (Factor 2) compulsive behavior ritualistic behavior and sameness behavior; and (Factor 3) restricted behavior ; (Model 4) a five factor model consisting of (Factor 1) stereotyped behavior ; (Factor 2) self injurious behavior; (Factor 3) compulsive behavior; (Factor 4) ritualistic and sameness behavior; and (Factor 5) restricted behavior ; and (Model 5) a six factor model consisting of (Factor 1)
55 stereotyped behavior; (Factor 2) sameness behavior; (Factor 3) self injurious behavior; (Factor 4) compulsive behavior; (Factor 5) ritualistic behavior; (Factor 6) behavior As can be seen in Table 3 7, the six factor model had the best goodness of fit, based on multiple crite ria as well as the lowest AIC and BIC values. A follow up analysis of the standardized solutions for the six factor model was conducted to evaluate the correlations of each factor within the six factor model. There was a high correlation between the fourth and fifth factor, indicating that they are very similar and could be combined (see Table 3 10) As a result, the five factor model was selected as the best fitting model based on the high correlation and parsimony. ) Based on the inter factor correlation s in Table 3 9, moderate to high correlations were indicated across all factors ranging from .46 (Ritualistic/Sameness and Self Injurious Behavior) and .80 (Ritualistic/Sameness and Compulsive Behavior) The high correlations are not consistent with previ ous findings; however, a similar pattern was found in a study by Lam and Aman (2007), which reported inter factor correlation coefficients between .14 (Ritualistic/Sameness and Self Injurious Behavior) and .55 (Ritualistic/Sameness and Self Injurious Behav ior and Compulsive Behavior). These results are not consistent with factor correlation coefficients between .31 (Compulsive Behavior and Self Injurious Behavior) and .66 (Ritualistic/Sameness and Restric ted Behavior ). When examining individual items, the only item with a low factor loading, or a value <.05, was for item 5, object usage (spins or twirls objects, twiddles or slaps or throws objects, lets objects fall out of hands). Item variance ranged fr om .25 (item 5) to .84 (item 35; see Table 3 11). Those with the lowest item variances were items 5, 36,
56 and 14, with variances of .25, .26, and .30, respectively. The residuals for covariances, correlations, and residual correlations are provided in Appen dix B. The highest value was .265, which was between items 20 (Hoarding/Saving) and 36 (Likes the same CD/tape/record or piece of music played continually; Likes the same movie/video or part of movie/video) Multiple Regression Several simultaneous multi ple regression analyses were conducted with a subset of the main sample to test whether intelligence, age, hyperactivity, and adaptive functioning predicted overall RRBI and subtype scores. The RRBI subtypes were determined by the results from the CFA. The significance tests for these analyses show the effect of each variable after controlling for all of the other variables in the model. Simultaneous Multiple Regression anal yses are presented in Tables 3 12 through Table 3 17 Intelligence Lower Intelligenc e was hypothesized to have a negative relationship with lower order RRBIs, or, lower intelligence would be related to increased levels of lower order RRBIs, including stereotyped behavior and self injurious behavior. Higher intelligence was hypothesized to be positively related to higher order RRBIs, with increased intelligence predicting increased levels of higher order RRBIs, including IS and ritualistic behavior combined, restricted behavior and compulsive behavior. Level of intelligence was found to be a significant predictor of higher IS and ritualistic behavior combined ( t = 2.3 p < .05) There was not a statistically significant relationship between intelligence and stereotyped behavior, self injurious behavior, restricted behavior compulsive behav ior, or overall RRBI.
57 Age Lower age was hypothesized to be related to lower order RRBIs whereas higher age was hypothesized to be related to higher order RRBIs. Results indicated that age was not significantly related to RRBI subtypes or overall RRBIs. Hy peractivity Hyperactivity was predicted to be positively related to RRBI subtypes and overall RRBIs. Results indicated that higher levels of hyperactivity predicted higher levels of stereotyped behavior ( t= 3.9, p<.01 ) self injurious behavior ( t= 3.2, p<. 01 ) IS and ritualistic behavior ( t= 4.7, p<.01 ) restricted behavior ( t= 3.5, p<.01 ) and compulsive behavior ( t=2.6 p < .01) In addition, high levels of hyperactivity predicted higher behaviors of overall RRBIs ( t=5.3 p < .01) Adaptive Functioning Ad aptive functioning was predicted to have a negative relationship with subtypes as well as overall RRBIs. Adaptive functioning was negatively and significantly related to restricted behavior ( t= 2.9 p < .01) However, adaptive functioning was not significa ntly related to the other RRBI domains.
58 Table 3 1. Descriptive statistics for the entire sample Characteristics N % Mean SD Range Sex 205 Male 165 80.5 Female 40 19.5 Age at assessment (Months) 205 100 120.4 45.3 60 247 Ethnicity 193 Non Hispanic 161 83.4 Hispanic 32 16.6 Race 195 White 155 82.4 Black 20 6.8 Other 20 10.8
59 Table 3 2 Descriptive statistics for the subsample Characteristics N % Mean SD Range Sex 78 Male 68 87.2 Female 10 12.8 Age at assessment (Months) 78 100 119.9 41.38 60 247 Ethnicity 75 Non Hispanic 7 90.7 Hispanic 68 9.3 Race 73 White 61 78.2 Other 12 21.8
60 Table 3 3 Descriptive stati stics for o utcome v ariables Outcome and Predictor Variables Mean SD Skewness Kurtosis Range Repetitive Behavior Sum Score 31.5 19.7 1. 1 1.4 2 95 Stereotyped Behavior 4.7 3.7 .9 4 .59 0 16 Self Injurious Behavior 3.1 4. 3 1.9 4.1 0 20 Compulsive Behavio r 5.1 4. 4 1.4 2.4 0 21 Insistence on Sameness/Ritualistic Beh. 14.1 9. 5 .64 .04 0 42 Restricted Behavior 4.1 2.9 .79 .14 0 12
61 Table 3 4 Descriptive statistics for p redictor v ariables Outcome and Predictor Variables Mean SD Skewness Kurtosis Range Intelligence 90.1 25.6 .61 .4 7 36 135 Hyperactivity 19. 8 11. 7 .29 .6 6 0 46 Age (Months) 119.9 41. 4 .7 1 30 60 247 Adaptive Functioning 77. 2 16.1 .1 9 .28 42 119
62 Table 3 ) for factors from the 5 factor model Fact ors RBS R Items Stereotyped Behavior 1 6 .7 4 Self Injurious Behavior 7 14 .8 3 Compulsive Behavior 15 22 .8 4 Ritualistic/Sameness Behavior 23 39 .91 Restricted Behavior 40 43 .77
63 Table 3 6. Pearson product moment correlation for RBS R and ADI R Scores (N=64) Variable Stereo SIB Compul Ritual IS Restricted Sum Verbal Rituals .38 ** .18 .18 .16 .05 .24 .14 Unusual Preoccupations .21 .07 .02 .06 .10 .15 .02 Circumscribed Interests .04 .15 .06 .21 .07 .22 .15 Repetitive Use of Objects .32* .16 .24 .19 .19 .34** .29* Compulsions/Rituals .12 .09 .21 .09 .22 .13 .19 Unusual Sensory Interests .34** .27* .18 .19 .09 .25* .27* Sensitivity to Noise .24 .09 .32* .29* .23 .06 .28* Neg. Response to Sensory Stimuli .17 .34** .15 .16 .08 08 .23 Difficulty With Minor Changes in Routine .14 .24 .16 .23 .48** .03 .34** Resistance to Trivial Changes .27* .31* .35** .19 .28* .21 .36** Unusual Attachments to Objects .07 .06 .17 .66 .01 .02 .01 Hand and Finger Mannerisms .34** .22 .24 .1 0 .04 .13 .22 Stereotyped Body Movements .43** .22 .17 .13 .22 .18 .30* Midline Hand Movements .13 .06 .01 .21 .14 .13 .07 Self Injury .35** .68** .17 .05 .04 .28* .32* Note:* significant at p value <.05; ** significant at p value <.01
64 Table 3 7 Goodness of fit indices of the hypothesized latent factor models of the RBS R (N=205) Model 2 d f RMSEA CFI TLI AIC BIC Model 1 (one factor) 1683.3** 860 .07 .86 .85 17513.7 18085.3 Model 2 (two factors) 1367.7** 859 .05 .91 .91 17276.9 17851.8 Model 3 (three factors) 1287.2** 857 .05 .93 .92 17196.7 17778.2 Model 4 (five factors) 1141.2** 850 .04 .95 .95 17033.6 17638.4 Model 5 (six factors) 1111.1** 845 .04 .95 .95 17007.6 17629.0 Note: significant at p value <.05; ** signif icant at p value <.01
65 Table 3 8 Standardized f actor l oadings Items Stereo. Behavior Self Injurious Behavior C ompuls. Behavior Rit/Same ness Behavior Restricted Behavior 1. Whole Body .66 2. Head .70 3. Hand/Finger .60 4. Locomotion .62 5. Object Usage .50 6. Sensory .79 7. Hits Self with Body Part .82 8. Hits Self Against Surface or Object .79 9. Hits Self with Object .88 10. Bites Self .75 11. Pulls .65 12. Rubs or Scratches Self .68 13. Inse rts Finger or Object .75 14. Skin Picking .55 15. Arranging/Ordering .74 16. Completeness .78 17. Washing/Cleaning .68 18. Checking .75 19. Counting .79 20. Hoarding/Saving .68 21. Repeating .73 22. Touch/Tap .61 23. Eating/Mealtime .64 24. Sleeping/Bedtime .68 25. Self Care Bathroom and Dressing .75 26. Travel/Transportation .83 27. Play/Leisure .68 28. Communication/Social Interactions .56 29. Insists that Things Remain in the Same Places .75 30. Objects to Visiting New Places .59 31. Becomes Upset if Interrupted in what he/she is Doing .78 32. Insists on Walking in a Particular Pattern .75 33. Insists on Sitting at the Same Place .71 34. Dislike s Changes in Appearance of Behavior of the People Around him/her .74
66 Table 3 8 Continued Items Stereo. Behavior Self Injurious Behavior C ompuls. Behavior Rit/Sameness Behavior Restricted Behavior 35. Insists on Using a Particular Door .91 36. Likes the same CD, tape, record or piece of music played continually; Likes same movie/video or part of movie/video .51 37. Resists changing activities; Difficulty with transitions .70 38. Insists on same routine, household, sc hool, or work schedule everyday .78 39. Insists that specific things take place at specific times .78 40. Fascination, preoccupation with one subject or activity .80 41. Strongly attached to one specific object .80 42. Pr eoccupation with part(s) of object rather than the whole object .80 43. Fascination, preoccupation with movement/things that move .68
67 Table 3 9 Correlations among the five factor s Factors 1 2 3 4 5 1. Stereotyped Behavior 1.0 2. Self Injurious Behavior .63 1.0 3. Compulsive Behavior .70 .50 1.0 4. Ritualistic/Sameness Behavior .58 .46 .80 1.0 5. Restricted Behavior .65 .50 .68 .67 1.0
68 Table 3 10. Correlations among the six factor s Factors 1 2 3 4 5 1. Stereotyped Behavior 1.0 2. Self Injurious Behavior .52 1.0 3. Compulsive Behavior .69 45 1.0 4. Ritualistic .33 32 73 1.0 5. Sameness Behavior .38 .47 .68 .83 6 Restricted Behavior 52 47 64 66 1.0
69 Tab le 3 1 1 RBS R item variance Items R Squared Estimate S.E. Est./S.E. P Value Residual Variance 1. Whole Body .44 .09 <.05 .56 2. Head .49 .11 <.05 .51 3. Hand/Finger .37 .08 <.05 .64 4. Locomotion .38 .08 <.05 .62 5. Object Usage .25 .08 <.05 .75 6. Sensory .62 .08 <.05 .38 7. Hits Self with Body Part .67 .08 <.05 .33 8. Hits Self Against Surface or Object .62 .08 <.05 .38 9. Hits Self with Object .77 .09 <.05 .23 10. Bites Self .57 .10 <.05 .44 11. Pulls .43 .09 <.05 .56 12. Rubs or Scratche s Self .46 .10 <.05 .54 13. Inserts Finger or Object .56 .13 <.05 .44 14. Skin Picking .30 .09 <.05 .70 15. Arranging/Ordering .55 .07 <.05 .45 16. Completeness .61 .06 <.05 .39 17. Washing/Cleaning .47 .07 <.05 .53 18. Checking .56 .10 <.05 .44 19. Counting .64 .08 <.05 .36 20. Hoarding/Saving .46 .07 <.05 .54 21. Repeating .54 .08 <.05 .46 22. Touch/Tap .38 .07 <.05 .62 23. Eating/Mealtime .40 .07 <.05 .60 24. Sleeping/Bedtime .46 .07 <.05 .55 25. Self Care Bathroom and Dressing .56 .06 <.05 .44 26. Travel/Transportation .68 .06 <.05 .32 27. Play/Leisure .46 .06 <.05 .54 28. Communication/Social Interactions .32 .06 <.05 .68 29. Insists that Things Remain in the Same Places .56 .05 <.05 .44 30. Objects to Visiting New Places .35 .07 <.05 .65 31. Becomes Upset if Interrupted in what he/she is Doing .62 .06 <.05 .34 32. Insists on Walking in a Particular Pattern .56 .08 <.05 .44 33. Insists on Sitting at the Same Place .51 .07 <.05 .50 34. Dislikes Changes in Appearance of Behavior of th e People Around him/her .55 .06 <.05 .45
70 Table 3 1 1 Continued Items R Squared Estimate S.E. Est./S.E. P Value Residual Variance 35. Insists on Using a Particular Door .84 .08 <.05 .16 36. Likes the same CD, tape, record or piece of music played continually; Likes same movie/video or part of movie/video .26 .06 <.05 .74 37. Resists changing activities; Difficulty with transitions .48 .06 <.05 .52 38. Insists on same routine, household, school, or work schedule everyday .61 .05 <.05 .39 39. Insists that specific things take place at specific times .64 .06 <.05 .39 40. Fascination, preoccupation with one subject or activity .64 .07 <.05 .36 41. Strongly attached to one specific object .64 .08 <.05 .36 42. Preoccupation with part(s) of obj ect rather than the whole object .63 .07 <.05 .37 43. Fascination, preoccupation with movement/things that move .46 .08 <.05 .54
71 Table 3 1 2 Adaptive functioning, age, hyperactivity and intelligence for predicting stereotyped behavior Predi ctor Variables SE t Age (Months ) .20 .0 1 1.9 Hyperactivity .4 2 .0 3 3.9 ** Adaptive functioning .1 5 .0 3 1. 3 Intelligence .05 .0 2 .4 9 F 8.2 ** Adj. R 2 .2 8 R 2 .3 2 Note:* significant at p value <.05; ** significant at p value <.01
72 Table 3 1 3 Adaptive functioning, age, hyperactivity, intelligence for predicting self injurious behavior Predictor Variables SE t Age (Month s) .0 6 .01 .50 Hyperactivity .3 7 .04 3.1 ** Adaptive functioning .08 .0 4 .65 Intelligence .00 .02 .0 2 F 3.6 Adj. R 2 .12 R 2 .1 7 Note:* significant at p value <.05; ** significant at p value <.01
73 Table 3 1 4 Adaptive functioning, age, hyperactivity intelligence for predicting compulsive behavior Predictor Variables SE t Age (Mont h s) .1 9 .01 1. 7 Hyperactivity .34 .04 2.6 Adaptive functioning .0 8 .0 4 .59 Intelligence .10 .02 .84 F 4.1 ** Adj. R 2 .14 R 2 .1 9 Note:* significant at p value <.05; ** significant at p value <.01
74 Table 3 1 5 Adaptive functionin g, age, hyperactivity intelligence for predicting IS/Ritualistic behavior Predictor Variables SE t Age (Months ) .14 .01 1. 4 Hyperactivity .50 .0 4 4.7 ** Adaptive functioning .0 2 .03 .1 4 Intelligence .2 6 .0 2 2.3 F 14.2 ** Adj. R 2 .2 8 R 2 .3 2 Note:* significant at p value <.05; ** significant at p value <.01
75 Table 3 1 6 Adaptive functioning, age, hyperactivity and intelligence for predicting restricted behavior Predictor Variables SE t Age (Month s) .1 1 .0 1 1. 1 Hyperactivi ty .36 .0 3 3.5 ** Adaptive functioning .3 4 .02 2.9 ** Intelligence .0 7 .01 .61 F 10.2 ** Adj. R 2 .3 3 R 2 .36 Note:* significant at p value <.05; ** significant at p value <.01
76 Table 3 1 7 Adaptive functioning, age, hyperactivity and in telligence for predicting the sum RBS R Score Predictor Variables SE t Age (Months ) .1 8 .0 5 1.8 Hyperactivity .54 .17 5.3 ** Adaptive functioning .0 6 .1 4 .5 3 Intelligence .03 .08 .27 F 10.5 ** Adj. R 2 .3 4 R 2 .37 Note:* significan t at p value <.05; ** significant at p value <.01
77 CHAPTER 4 DISCUSSION The primary aim of this study was to examine the best fitting factor structure of a variety of RRBIs in a sample of individuals diagnosed with an ASD. The secondary aim was to evaluate whether intelligence, age, adaptive functioning, and hyperactivity significantly predicted the severity of RRBIs, as defined by the best fitting factor structure. A discussion regarding the most salient findings from each research question, implications f or future research, limitations regarding the study will be discussed in the following sections. Research Question 1: Factor Structure of the RBS R The primary goal of the study was to examine the factor structure of the RBS R. Factor analysis allows resea rchers to examine patterns of relationships among a wide variety of different behaviors that have been measured empirically. Those behaviors that are correlate d are combined to form a group, or factor. To date, most of the research evaluating the factor st ructure of RRBIs has utilized the ADI R. Research examining the factor structure of RRBIs using the ADI R has found two (i.e., RSMBs and IS; Cuccaro et al., 2003; Mooney et al. 2009; Richler et al., 2010; Szatmari et al., 2006) and three fac tors (i.e., RS MBS, IS, and CI; Lam et al., 2008). A limitation to using the ADI R as a measure of RRBIs is that this particular measure was not developed with the intentions to serve as a comprehensive measure of RRBIs. Recent research has begun to examine the RBS R, w hich is a comprehensive measure of RRBIs for those diagnosed with an ASD. Research using the RBS R has found two (Georgiades et al., 2010), three (Mirenda et al., 2010), and five factors (Lam & Aman, 2007; Mirenda et al., 2010). These inconsistencies have been associated
78 varying statistical procedures and instruments used to measure of the structure of RRBIs as well as the use of a wide age ranges. The factor structure of the RBS R has been previously subject to empirical evaluation; therefore, the CFA met hod was employed to evaluate five competing models, which included one two three five and six factor solutions, rather than using exploratory methods. The three (2008) study rather than Mirenda et al. support. Although Mirenda et al. (2010) utilized the RBS R in their study, information regarding how the three factor model was derived was not provided. The findings of this study support the notion that RRBIs in those diagnosed with an ASD are multifaceted. Based on multiple fit indices, the CFA results found support for a six factor model and five factor model. An analysis of standardized solutions indicated that factors 4 and 5 were highly correlated and, th erefore, could be combined. In addition, the descriptive categories of the Ritualistic subscale and Sameness Behavior subscale are quite similar. The RBS factor solution was selected as the best fitting model, which included Stereotyped Behavior, Self Injurious Behavior, Compulsive Behavior, Ritualistic Beha vior/Sameness Behavior, and Restricted Behavior These results are in accord with the findings by Lam and Aman (2007) and Mirenda et al. (2010), who also reported a five factor structure consisting of the same subscales. The three factor solution also had acceptable fit, which may be useful in some instances, including genetic qualitative trait locus studies.
79 Research Question 2: Intelligence, Age, Hyperactivity, Adaptive Skills Intelligence Results examining the role of intelligence on RRBIs found that hi gher intelligence significantly predicted higher levels of Insistence on Sameness and Ritualistic Behavior combined. Intelligence was not a significant predictor for Stereotyped Behavior, Self Injurious Behavior, Compulsive Behavior, Restricted Behavior a nd the Sum Repetitive Behavior Score. This study is the first to examine the role of intellectual functioning as a continuous variable using a single intelligence test with a moderately large sample. which postulates the existence by insistence on sameness, compulsive behavior, restricted behavior and repetitive language. Turner hypothesized that lower order behaviors were related to lower cognitive ability whereas higher order behaviors were related to higher cognitive ability. These results did not support the results from Gabriels et al. (2005) study, which found significantly higher levels of Sameness Behavior in those with low levels of cognitive ability, as measured by the Leiter R, which was defined as an IQ score < 56. Although this study did not find support in accord with previous theory and research, it is important to consider the limitations in the cognitive assessment of those with neurodevelopmental disorders. It is quite possible that the intelligence scores may be impacted by ASD symptomology.
80 Age Resul ts from a series of multiple regression analyses indicated that age was not found to be a significant predictor for Stereotyped Behavior, Compulsive Behavior, Self Injurious Behavior, Ritualistic/Sameness Behavior, and Restricted Behavior Previous studies regarding other classes of repetitive behaviors have been inconsistent. For example, Esbense n et al. (2009 ) found that age was negatively and significantly correlated with the five subscales of the RBS R used in this study. Other studies have reported tha t older age is related to insistence on sameness behavior (Bishop et al., 2006; Richler et al., 2010). More research is needed to evaluate the relationship between age and repetitive behavior subtypes. A limitation to evaluating the role of age on RRBIs fo r this study was an issue of restricted range with over half of the sample being younger than 120.4 months (10.0 years); therefore, this result should be interpreted with caution. It is possible that having a restricted age range limited to ability to exam ine patterns that may have emerged for older participants. Hyperactivity Results indicated that hyperactivity was a significant predictor for all RRBIs. Higher levels of hyperactivity significantly predicted higher levels of Stereotyped Behavior, Self Inj urious Behavior, Compulsive Behavior, Ritualistic/Sameness Behavior, Restricted Behavior and the Sum Repetitive Behavior score. This finding supports a previous research study of 14 participants, which found hyperactivity was significantly correlated with the Sum Repetitive Behavior score on the RBS R, even after controlling for NVIQ. This is the first study to date to examine the role of hyperactivity on subscale scores. Future research should examine the role of hyperactivity on RRBIs using rating scales
81 that were designed to comprehensively measure hyperactive behavior. In addition, future studies should evaluate whether interventions such as behavioral interventions and/or medication used for the treatment of hyperactive behavior improve or reduce RRBIs in frequency and/or severity. Adaptive Functioning Results indicated that adaptive functioning was a significant predictor for Restricted Behavior Specifically, a decrease in adaptive functioning significantly predicted higher levels of Restricted Behav ior Adaptive functioning was not a significant predictor of other RRBI domains. Convergent Validity In the area of RRBIs, the RBS R and ADI R have demonstrated strong psychometric characteristics and have allowed researchers and practitioners to measure repetitive behavior particular to those diagnosed with an ASD. The convergent validity of the RBS R was assessed by comparing subscale scores with items on the ADI R. The ADI R has 15 items measuring repetitive behavior. The verbal rituals item was include d to explore whether verbal rituals was related to RRBIs, as the RBS R does not include verbal rituals as a repetitive behavior. The majority of the s ignificant correlations ranged from having a weak to strong positive relationship ranging from a low of 25 to a high of .68. Furthermore, five items from the ADI R were not significantly correlated with any of the RBS R subscales. The weak correlations among the RBS R and ADI R may be related to many factors, including the way each rating scale is completed. The RBS R is completed independently by a parent or caregiver whereas the ADI R is administered in an interview format. In addition, the RBS R subscales include multiple items measuring each domain, whereas the ADI R includes individual
82 items targeting ea ch domain. These factors may also explain discrepancies regarding factor studies that have used the RBS R versus ADI R. Further research is needed to refine the measurement of RRBIs. Limitations This study is subject to several limitations. This sample may not be truly representative of all individuals with an Autism Spectrum Disorder. Parents who participated in the research study were more likely to be from a rural locale in the southeast. They may also be more concerned, involved, and have access to par ticipation in research projects as compared to other parents with a child diagnosed with an ASD. In addition, the sample consisted of a wide age range, with over half of the sample being restricted between the ages of 5 and 9. As a result, interpretations of the findings may have limited generalizability. The questionnaires and rating scale information collected from participants was response bias. The assessment methods u sed to measure restricted and repetitive behaviors or interests, adaptive functioning, age, and hyperactivity were selected due to the ability to collect a variety of information in a brief time period, research evidence supporting their psychometric prope rties and the ability to quantify subtle differences in the degree of the impairment. Although direct observations could validate the presence of RRBIs, these behaviors do not always occur frequently and are not always present in all settings. Therefore, o bservational data may not be sufficient in capturing a comprehensive RRBI profile of an individual but could be usef ul in validating parent reports.
83 Moreover, Intellectual functioning was measured using the Leiter R, which is administered in a nonverbal fo rmat. It is possible that different results may have emerged if participants were administered a different intelligence test presented in a nonverbal and/or verbal format. Furthermore, the ASD diagnosis was based on parent report and was not verified. Howe ver, over 80% of the sample had a Social Communication Questionnaire (SCQ ; Rutter, Bailey, & Lord, 2003 ) score equal to or greater than 15. Research has shown that a total score equal to or greater than 15 is suggestive of a high probability of having an A SD (Rutter et al., 2003). Furthermore, the analyses methods were selected based on the research questions and the size of the sample. More complex multivariate analyses would provide more accurate and informative representations of the relationships betwee n predictor and dependent variables; however, a larger sample size would have been required. Despite these limitations, this study adds to the body of knowledge suggesting that RRBIs represent a heterogeneous category with five different subtypes. In addi tion, hyperactivity was found to have a significant role on all repetitive behaviors. This study found partial studies with larger sample sizes and confirmed ASD diagnoses are nee ded to validate these findings. Furthermore, continued research is needed to add more detailed information regarding the development and treatment of RRBIs as well as associated characteristics. Summary and Implications for Future R esearch The results of t he current study indicate that RRBIs when measured using the RBS R are comprised of five domains, including Stereotyped Behavior, Self Injurious
84 Behavior, Compulsive Behavior, Ritualistic/Sameness Behavior, and Restricted Behavior Internal consistency val ues were a dequate with values between .74 and .91 These results are consistent with previous studies evaluating the internal consistency of the RBS R. Age was not found to be a significant predictor for any of the RRBI subtypes. This result may have occur red because this sample was restricted in age. Research results regarding the relationship between age and RRBI subtypes have not been entirely consistent. Future research is needed to clarify the role age has on repetitive behavior. Higher levels of hype ractivity significantly predicted higher RRBIs overall as well as within each subtype. This result has implications for future research regarding possible impact of interventions targeting hyperactivity as a treatment of RRBIs. Future research should evalu ate the effect of behavioral and pharmacological interventions targeting hyperactivity on overall RRBIs as well as RBI subtypes. Furthermore, treatment studies should evaluate whether the acquisition of positive behavior occurs simultaneously as RRBIs decr ease. Lower adaptive functioning predicted higher levels Restricted Behavior Adaptive functioning was not a significant predictor for Stereotyped Behavior, Self Injurious Behavior, Compulsive Behavior Ritualistic/Sameness Behavior and the Sum RRBI score Future studies should evaluate how RRBIs develop over time using a longitudinal design. This type of research could provide information regarding the nature of RRBIs as well as provide insight into other factors that may impact RRBIs (e.g., age, experie nces, and interventions). In addition, specificity in how the sample is stratified
85 may provide precise information regarding the manifestation of RRBIs. Stratifying samples by verbal versus nonverbal ability, age, language ability, and RRBI profiles may he lp improve our knowledge and better inform interventions. Furthermore, treatment studies are needed to better understand how to reduce problem behavior. McDougle, Kresch, and Posey (2000) cite research supporting the efficacy of Clomipramine and Fluvoxami ne as a treatment method for the reduction of repetitive behaviors within an ASD sample. Both medications are often used for the treatment of repetitive thoughts and repetitive behavior. Behavioral interventions are also needed to better understand thei r impact on overall functioning. Future studies should examine treatment effects on RRBI subtypes as well. Finally, the RBS R demonstrated adequate psychometric properties and may be a useful method for determining ASD diagnosis as well as measuring treatm ent effects. Future ratings scales measuring RRBIs within the ASD population should also consider whether verbal rituals should be included within the RRBI classification system. Differences in RRBI subtypes suggest that we should examine RRBI subtypes wi thin those diagnosed with ASD and other disorders that have RRBIs present. Given the high inter factor correlations, f uture research should examine whether a hierarchical model better represent RRBIs. Perhaps there is a general RRBI factor which explains the correlations among factors. Furthermore understanding the structure of RRBIs may guide diagnostic classifications.
86 APPENDIX A HEALTH HISTORY FORM Please answer the following questions. If you are uncomfortable with any question, do not answer i t. Best estimates are fine if you cannot remember specific details. Thank you! Your name: Last: First: Your Relationship to Child: Mother Father Other (please spec ify): Last: First: Male Female birth date: Mailing Address: Street: City: State: Zip code: Phone number: Primary: Secondary: Hispanic or Latino Not Hispanic or Latino e: White Black or African American Asia American Indian/Alaska Native Native Hawaiian/Other Pacific Islander Other (please specify): Nam e of School: Classroom Type: Regular ESE Other (please specify): Services receiving: Speech Therapy Occupational Therapy Physical Therapy Social Skills Other (please specify): Past M edical History Has your child been diagnosed with any of the following medical disorders? If so, please check box. Seizure disorder Tics or Tourette syndrome Fragile X syndrome Fetal Alcohol syndrome Other medical or genetic condition (ple ase specify): Sensory: Blind (If yes, in both eyes? Yes No) Deaf (If yes, in both ears? Yes No) Physical: Walking independently Walking with assistance Wheelchair bound Past Psychiatric History Diagnosis, if any: Autism Asperger PDD NOS Autism Spectrum Disorder Other (please specify): Name of clinician who diagnosed your child with an autism spectrum disorder: Profession: Psychiatrist Pediatrician Psychologist Other (please specify): Medicatio n History Is your child currently on, or has been on within the last 3 months, any of the following medications? Yes No If yes, please complete the following:
87 Antipsychotic medication (check box, if any): Risperdal Abilify Sero quel Geodon Clozaril Haldol Navane Prolixin Thorazine Stelazine Other (please specify): Stimulant (check box, if any): Adderrall Vyvanse Dexedrine Ritali n Focalin Concerta MetadateCD Daytrana Strattera Other (please specify): Antidepressant (check box, if any): Prozac or Fluoxetine Zoloft Celexa Paxil Lexapro Luvox Effexor Elavil Remeron Wellbutrin Tofranil Desipramine Other (please specify): Mood stabilizer (check box, if any): Lithium Depakote Tegretol Lamictal Trileptal Topamax Other (please specify): Other (OTC, supplement or diet) If any, please specify: Family History Has anyone related to the child (biological parents, grandparents, brothers/sisters) been diagnosed with any of the following illnesses? Please check the box and sp ecify the relationship. Check box, if any: If yes, specify who: Autism Asperger Other Pervasive Developmental Disorder (PDD NOS) Attention Deficit Hyperactivity D isorder Bipolar Disorder Depression A nxiety Obsessive Compulsive Disorder Tics or Tourette syndrome Schizophrenia Other (please specify):
88 APPENDIX B RESIDUALS FOR COVARI ANCES/CORRELATIONS/R ESIDUAL CORRELATIONS RBSR1 RBSR2 RBSR3 RBSR4 RBSR5 ________ ________ ________ ________ ________ RBSR1 RBSR2 0.113 RBSR3 0.023 0.042 RBSR4 0.119 0.145 0.063 RBSR5 0.095 0.046 0.008 0.029 RBSR6 0.074 0.127 0.019 0.043 0.006 RBSR7 0.025 0.054 0.004 0.077 0.023 RBSR8 0.090 0.130 0.078 0.033 0.011 RBSR9 0.073 0.120 0.102 0.049 0.063 RBSR10 0.126 0.094 0.007 0.036 0.033 RBSR11 0.021 0.194 0.116 0.084 0.034 RBSR12 0.074 0.073 0.107 0.191 0.058 RBSR13 0.000 0.040 0.042 0.130 0.015 RBSR14 0.034 0.060 0.064 0.145 0 .037 RBSR15 0.092 0.089 0.060 0.062 0.055 RBSR16 0.062 0.078 0.062 0.075 0.076 RBSR17 0.044 0.136 0.026 0.076 0.106 RBSR18 0 .070 0.035 0.041 0.201 0.060 RBSR19 0.064 0.004 0.085 0.101 0.069 RBSR20 0.020 0.017 0.105 0.097 0.090
89 RBSR21 0.114 0.043 0.036 0.045 0.074 RBSR22 0.124 0.070 0.162 0.077 0.088 RBSR23 0.104 0.183 0.015 0.041 0.132 RBSR24 0.031 0.090 0.037 0.1 39 0.082 RBSR25 0.116 0.115 0.093 0.041 0.097 RBSR26 0.071 0.040 0.049 0.113 0.023 RBSR27 0.061 0.148 0.106 0.014 0.047 RBSR 28 0.112 0.084 0.085 0.124 0.065 RBSR29 0.018 0.042 0.072 0.069 0.109 RBSR30 0.119 0.083 0.074 0.021 0.050 RBSR31 0.026 0.014 0.013 0.072 0.009 RBSR32 0.087 0.058 0.010 0.029 0.120 RBSR33 0.095 0.033 0.133 0.013 0.008 RBSR34 0.089 0.089 0.033 0.097 0.102 RBSR35 0.075 0.061 0.004 0.222 0.063 RBSR36 0.081 0.010 0.105 0.039 0.067 RBSR37 0.012 0.099 0.096 0.068 0.036 RBSR38 0.090 0.126 0.027 0.065 0.053 RBSR39 0.045 0.054 0.034 0.004 0.097 RBSR40 0.068 0.017 0.036 0.080 0.037 RBSR41 0.012 0.153 0.007 0.012 0.079 RBSR42 0.033 0.085 0.060 0.143 0.181 RBSR43 0.213 0.079 0.019 0.026 0.229
90 RBSR6 RBSR7 RBSR8 RBSR9 RBSR10 ________ ________ ________ ________ ________ RBSR7 0.038 RBSR8 0.132 0.075 RBSR9 0.186 0.062 0.085 RBSR10 0.091 0.003 0.039 0.147 RBSR11 0.119 0.038 0.048 0.045 0.042 RBSR12 0.167 0.119 0.137 0.133 0.053 RBSR13 0.005 0.061 0.151 0.162 0.126 RBSR14 0.134 0.160 0.131 0.123 0.004 RBSR15 0.133 0.041 0.176 0.176 0.125 RBSR16 0.094 0.046 0.024 0.032 0.059 RBSR17 0.004 0.018 0.016 0.006 0.004 RBSR18 0.005 0.026 0.098 0.073 0.044 RBSR19 0.038 0.002 0.178 0.099 0.098 RBSR20 0.107 0 .011 0.016 0.054 0.065 RBSR21 0.013 0.061 0.016 0.035 0.026 RBSR22 0.181 0.096 0.027 0.163 0.041 RBSR23 0.028 0.073 0.072 0.079 0.008 RBSR24 0.098 0.015 0.125 0.101 0.078 RBSR25 0.073 0.017 0.021 0.040 0.012 RBSR26 0.084 0.055 0.085 0.050 0.0 28 RBSR27 0.062 0.112 0.170 0.129 0.016
91 RBSR28 0.002 0.031 0.028 0.106 0.035 RBSR29 0.097 0.170 0.007 0.042 0.169 RBSR30 0.0 47 0.011 0.135 0.167 0.126 RBSR31 0.027 0.014 0.092 0.153 0.104 RBSR32 0.082 0.059 0.009 0.109 0.139 RBSR33 0.113 0.041 0.005 0.104 0.186 RBSR34 0.026 0.032 0.046 0.075 0.016 RBSR35 0.041 0.050 0.144 0.041 0.024 RBSR36 0.036 0.064 0.087 0.150 0.042 RBSR37 0.043 0.030 0.094 0.009 0.062 RBSR38 0.030 0.065 0.074 0.003 0.018 RBSR39 0.107 0.022 0.040 0.029 0.009 RBSR40 0.074 0.046 0.063 0.110 0.140 RBSR41 0.175 0.015 0.019 0.099 0.058 RBSR42 0.020 0.104 0.059 0.219 0.111 RBSR43 0.022 0.010 0.020 0.071 0.102 RBSR11 RBSR12 RBSR13 RBSR14 RBSR15 ________ ________ ________ ________ ________ RBSR12 0.073 RBSR13 0.019 0.041 RBSR14 0.147 0.240 0.029 RBSR15 0.060 0.011 0.018 0.003
92 RBSR16 0.137 0.019 0.069 0.045 0.088 RBSR17 0.018 0.093 0.123 0.005 0.014 RBSR18 0.064 0.077 0.115 0.032 0.138 RBSR19 0.080 0.035 0.026 0.046 0.066 RBSR20 0.197 0.043 0.106 0.107 0.070 RBSR21 0.042 0.064 0.018 0.130 0.088 RBSR22 0.056 0.078 0.195 0.073 0.027 RBSR23 0.100 0.031 0.027 0.029 0.023 RBSR24 0.066 0.038 0.095 0.018 0.149 RBSR25 0.221 0.079 0.046 0.103 0.064 RBSR26 0.005 0.023 0.078 0.007 0.029 RBSR27 0.010 0.021 0.028 0.043 0.012 RBSR28 0.097 0.051 0.095 0.064 0.051 RBSR29 0.229 0.089 0.211 0.073 0.144 RBSR30 0.103 0.063 0.011 0.075 0.123 RBSR31 0.166 0.040 0.141 0.013 0.089 RBSR32 0.071 0.115 0.009 0.059 0.036 RBSR33 0.117 0.077 0.091 0.048 0.021 RBSR34 0.113 0.066 0.109 0.024 0.017 RBSR35 0.164 0.108 0.051 0.129 0.065 RBSR36 0.007 0.105 0.012 0.066 0.004 RBSR37 0.197 0. 092 0.086 0.104 0.047 RBSR38 0.048 0.014 0.044 0.056 0.035
93 RBSR39 0.126 0.059 0.050 0.048 0.076 RBSR40 0.056 0.109 0.078 0.081 0.023 RBSR41 0.022 0.152 0.045 0.048 0.075 RBSR42 0.099 0.082 0.046 0.016 0.009 RBSR43 0.008 0.120 0.045 0.156 0.03 2 RBSR16 RBSR17 RBSR18 RBSR19 RBSR20 ________ ________ ________ ________ ________ RBSR17 0.053 RBSR18 0.025 0.176 RBSR19 0.094 0.034 0.029 RBSR20 0.184 0.093 0.074 0.102 RBSR21 0.081 0.047 0.012 0.119 0.063 RBSR22 0.118 0.032 0.060 0.054 0.032 RBSR23 0.014 0.018 0.053 0.111 0.084 RBSR24 0.013 0.039 0.062 0.025 0.029 RBSR25 0.055 0.016 0.087 0.051 0.025 RBSR26 0.050 0.002 0.0 54 0.052 0.027 RBSR27 0.054 0.007 0.032 0.076 0.091 RBSR28 0.041 0.095 0.007 0.027 0.037 RBSR29 0.048 0.014 0.094 0.019 0.014 RBSR30 0.033 0.027 0.034 0.064 0.128 RBSR31 0.128 0.034 0.030 0.019 0.053
94 RBSR32 0.103 0.006 0.077 0.038 0.071 RBSR33 0.076 0.081 0.001 0.099 0.097 RBSR34 0.071 0.015 0.022 0.056 0.041 RBSR35 0.083 0.156 0.010 0.004 0.017 RBSR36 0.126 0.158 0.087 0.074 0.001 RBSR37 0.123 0.088 0.130 0.116 0.012 RBSR38 0.084 0.009 0.006 0.027 0.047 RBSR39 0.027 0.025 0.102 0.115 0.056 RBSR40 0.004 0.127 0.010 0.027 0.169 RBSR41 0.069 0.178 0.070 0.066 0.145 RBSR42 0.043 0.005 0.106 0.017 0.019 RBSR43 0.019 0.028 0.059 0.020 0.108 RBSR21 RBSR22 RBSR23 RBSR24 RBSR25 ________ ________ ________ ________ ________ RBSR22 0.108 RBSR23 0.083 0.056 RBSR24 0.037 0.043 0.159 RBSR25 0.037 0.070 0.136 0.070 RBSR26 0.048 0.026 0.096 0.031 0.077 RBSR27 0.045 0.064 0.165 0.084 0.002 RBSR28 0.014 0.010 0.041 0.075 0.093 RBSR29 0.026 0.103 0.055 0.043 0.163
95 RBSR30 0.014 0.104 0.050 0.139 0.161 RBSR31 0.048 0.078 0.055 0.096 0.045 RBSR32 0.067 0.010 0.066 0.192 0.129 RBSR33 0.070 0.001 0.049 0.097 0.017 RBSR34 0.021 0.028 0.046 0.012 0.030 RBSR35 0.045 0.060 0.037 0.056 0.078 RBSR36 0.135 0.038 0.123 0.087 0.265 RBSR37 0.046 0.140 0.021 0.066 0.076 RBSR38 0.038 0.090 0.121 0.074 0.031 RBSR39 0.052 0.060 0.170 0.087 0.052 RBSR40 0.073 0.019 0.002 0.011 0.057 RBSR41 0.065 0.029 0.036 0.055 0.045 RBSR42 0.106 0.015 0.073 0.123 0.069 RBSR43 0.060 0.004 0.005 0. 137 0.057 RBSR26 RBSR27 RBSR28 RBSR29 RBSR30 ________ ________ ________ ________ ________ RBSR27 0.029 RBSR28 0.052 0.141 RBSR29 0.013 0.025 0.088 RBSR30 0.078 0.003 0.110 0.082 RBSR31 0.093 0.014 0.055 0.085 0.080 RBSR32 0.097 0.010 0.161 0.052 0.061
96 RBSR33 0.028 0.019 0.123 0.024 0.017 RBSR34 0.033 0.055 0.027 0.027 0.059 RBSR35 0.065 0.105 0.050 0.089 0.024 RBSR36 0.039 0 .080 0.159 0.034 0.013 RBSR37 0.093 0.071 0.118 0.105 0.025 RBSR38 0.088 0.108 0.055 0.058 0.000 RBSR39 0.104 0.030 0.021 0.005 0.004 RBSR40 0.076 0.094 0.179 0.014 0.031 RBSR41 0.073 0.035 0.026 0.013 0.004 RBSR42 0.013 0.072 0.157 0.099 0.0 46 RBSR43 0.076 0.039 0.039 0.044 0.038 RBSR31 RBSR32 RBSR33 RBSR34 RBSR35 ________ ________ ________ ________ ________ RBSR32 0. 037 RBSR33 0.014 0.114 RBSR34 0.016 0.029 0.025 RBSR35 0.101 0.057 0.033 0.002 RBSR36 0.103 0.057 0.002 0.016 0.067 RBSR37 0.171 0.112 0.001 0.011 0.088 RBSR38 0.010 0.008 0.033 0.003 0.010 RBSR39 0.024 0.019 0.021 0.034 0.050 RBSR40 0.026 0.011 0. 117 0.008 0.095
97 RBSR41 0.099 0.011 0.054 0.100 0.080 RBSR42 0.004 0.100 0.005 0.038 0.007 RBSR43 0.008 0.058 0.038 0.006 0.115 RBSR36 RBSR37 RBSR38 RBSR39 RBSR40 ________ ________ ________ ________ ________ RBSR37 0.086 RBSR38 0.090 0.138 RBSR39 0.101 0 .089 0.187 RBSR40 0.210 0.028 0.016 0.046 RBSR41 0.122 0.049 0.038 0.077 0.072 RBSR42 0.000 0.021 0.097 0.201 0.113 RBSR43 0 .051 0.002 0.110 0.126 0.118 RBSR41 RBSR42 RBSR43 ________ ________ ________ RBSR42 0.118 RBSR43 0.144 0.158
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108 BIOGRAPHICAL SKETCH Cindi Guadalupe Flores was born and raised in San Bernardino, CA. She earned her B.A. in p sychology and child develop ment from California State University, San Bernardino. Subsequently, she moved to Florida to enroll in the school psychology doctoral program at the University of Florida. Since then Cindi has been a part of various research and practica experiences to cu ltivate her professional career, including undergraduate teaching, research, and worki ng in school legal, and clinical settings in the greater Gainesville area. She has had the opportunity to work with unique populations, including migrant children and fa milies, English language learners, foster care children and youth, and those diagnosed with an ASD or Prader Willi Syndrome. Cindi completed her pre doctoral internship with Hillsborough County Public Schools in Florida Cindi will begin working as a postd oc for the Department of Psychiatry at Shands Hospital in July 2012.