Conference Paper

Prevalence and Placement Patterns of Children in Foster Care With Autism Spectrum Disorder

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Abstract

Background and Purpose: This study examines the prevalence of children with autism spectrum disorder (ASD) entering one large state child welfare system, and focuses attention on their pathways through the child welfare system. Autism spectrum disorder is a chronic developmental disorder estimated to affect 1 in every 88 children in the U.S. Less is known about the prevalence of ASD among children served in the child welfare system, or the ways in which large service systems respond to their needs. To identify placement patterns at the front end of entry, the study uses latent class analysis (LCA). Previous research has used a combination of methods to identify common patterns of placement. This paper will be among the first to apply LCA to a placement pattern analysis. Methods: The study uses linked administrative data in the Integrated Database on Children’s Services (IDB) in Illinois (IL) (Goerge, Van Voorhis, & Bong Joo Lee, 1994). The IDB is a relational database that combines administrative data from multiple state agencies. This study relies on linked data on children and their placement experiences from the IL DCFS and paid medical claims data for Medicaid services from the IL Department of Healthcare and Family Services. The study population (n=9,853) includes all children (3-18) entering foster care for the first time between FY 2006-2010 as a result of substantiated abuse or neglect. The LCA is based on the subpopulation that remained in care for at least 18 months (n=5,423). Categorical indicators used in the LCA include first type of placement, predominant placement type, restriction-level, stability-level, and any adverse events. The presence of a single latent class structure for children with and without ASD is assessed both statistically and through visual inspection. Results: The data do not support a single LCA for both the ASD and non-ASD groups. Goodness of fit statistics support the presence of a 3-class model for children with ASD, and a 4-class model for children without ASD. The hypothesis of measurement invariance for a 3-class model across groups was also rejected. Class 1 (High need; 34%) consists of children initially placed in congregate care, with the highest rates of adverse events, and few less restrictive placements. Class 2 (Step-up; 37%) consists of children initially placed in family settings and stepped-up to more restrictive care where stability is reached. Class 3 (Stable; 29%) consists of children placed in family settings who achieve stability early and remain in less restrictive settings. The analysis of covariates reveal that children ages 11 and older and children living in Cook County with ASD were less likely to be in the ‘Step-up’ or the ‘Stable classes compared to the ‘High Need’ class. Conclusions and Implications: Children with ASD were unique in terms of their “High Need” class when compared to the overall population of children in foster care. Both “High Need” and “Step-up” children with ASD warrant special attention from the child welfare system.

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Overview Conceptual foundation and brief history of the latent class model Why select a categorical latent variable approach? Scope of this book Empirical example of LCA: Adolescent delinquency Empirical example of LTA: Adolescent delinquency About this book The examples in this book Software Additional resources: The book's web site Suggested supplemental readings Points to remember What's next
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Overview Empirical example: Positive health behaviors Preparing to conduct LCA with covariates LCA with covariates: Model and notation Hypothesis testing in LCA with covariates Interpretation of the intercepts and regression coefficients Empirical examples of LCA with a single covariate Empirical example of multiple covariates and interaction terms Multiple-group LCA with covariates: Model and notation Grouping variable or covariate? Use of a Bayesian prior to stabilize estimation Binomial logistic regression Suggested supplemental readings Points to remember What's next
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The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis. The use of the AIC criterion in the factor analysis is particularly interesting when it is viewed as the choice of a Bayesian model. This observation shows that the area of application of AIC can be much wider than the conventional i.i.d. type models on which the original derivation of the criterion was based. The observation of the Bayesian structure of the factor analysis model leads us to the handling of the problem of improper solution by introducing a natural prior distribution of factor loadings.
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This article reviews the results of 43 studies published since 1966 that provided estimates for the prevalence of pervasive developmental disorders (PDDs), including autistic disorder, Asperger disorder, PDD not otherwise specified, and childhood disintegrative disorder. The prevalence of autistic disorder has increased in recent surveys and current estimates of prevalence are around 20/10,000, whereas the prevalence for PDD not otherwise specified is around 30/10,000 in recent surveys. Prevalence of Asperger disorder is much lower than that for autistic disorder and childhood disintegrative disorder is a very rare disorder with a prevalence of about 2/100,000. Combined all together, recent studies that have examined the whole spectrum of PDDs have consistently provided estimates in the 60-70/10,000 range, making PDD one of the most frequent childhood neurodevelopmental disorders. The meaning of the increase in prevalence in recent decades is reviewed. There is evidence that the broadening of the concept, the expansion of diagnostic criteria, the development of services, and improved awareness of the condition have played a major role in explaining this increase, although it cannot be ruled out that other factors might have also contributed to that trend.
Despite concerns about the restrictiveness of care and treatment procedures and settings for special populations, the concept of restrictiveness has seldom been defined or measured. This study describes the development of the Restrictiveness of Living Environments Scale (ROLES) for measuring the restrictiveness of residential settings for children and youths, including their own homes. Based on a literature review, the authors defined restrictiveness in terms of limits placed on freedom of movement or choice by the physical facility, by rules or requirements, and by conditions of entry and departure. The definition, along with a list of 27 residential settings for children, was sent to 389 child care professionals, who were asked to rate the restrictiveness of the settings on a 10-point scale, using a rating method designed to yield an interval scale. Ratings from 159 respondents, rounded to the nearest .5, were used to determine the relative position of the settings on the scale.
Article
Although it is now recognized that children may exhibit widespread symptoms of stress following exposure to abuse or neglect, the impact of traumatic experiences on children with pervasive developmental disorders has received little attention. The present paper describes a strategy devised to assess the long-term effects of abuse on a group of children who had attended a specialist autistic school where physical and emotional mistreatment of pupils was well documented. Because most of the children had very limited communication skills, the evidence relied heavily on retrospective parental reports. Despite the problems inherent in using such data it was possible to derive reliable measures that could be used to test hypotheses about predicted patterns of behavioral change, based on work with other children who have been abused. In most cases, too, parental reports could be corroborated by information from other sources. Consistent patterns in both the nature and timing of behavioral disturbances were found, which seemed to relate specifically to the period of abuse at the school.
Article
Circumstances of maltreatment and the presence of disabilities. An electronic merger of the records of all pediatric patients. Detailed record analysis of circumstances of maltreatment and the presence of disabilities. Differences between the Hospital and Residential samples, maltreatment and perpetrator characteristics, disability/maltreatment relationships, and their implications for primary health care are discussed.
Article
To assess the prevalence of abuse and neglect among a population of children identified as a function of an existing disability, relate specific types of disabilities to specific types of abuse, and to determine the effect of abuse and neglect on academic achievement and attendance rates for children with and without disabilities. An electronic merger of school records with Central Registry, Foster Care Review Board, and police databases was followed by a detailed record review of the circumstances of maltreatment. Analyses of the circumstances of maltreatment and the presence of disabilities established a 9% prevalence rate of maltreatment for nondisabled children and a 31% prevalence rate for the disabled children. Thus, the study established a significant association between the presence of an educationally relevant disability and maltreatment. Children with disabilities are 3.4 times more likely to be maltreated than nondisabled peers. School professionals need to be cognizant of the high base rate of maltreatment among the children they serve. Disability status needs to be considered in national incidence studies of maltreatment.
Article
: To provide a clinically useful analysis of the extent to which autism and Asperger syndrome coexist with other disorders. Selective review of the literature detailing data pertaining to symptoms and disorders sometimes encountered in connection with autism or Asperger syndrome. A large number of medical conditions, psychiatric disorders and behavioural and motor dyscontrol symptoms are associated with autism and Asperger syndrome. Comorbidity is to be expected in autism spectrum disorders -directly or indirectly. Comorbid conditions may be markers for underlying pathophysiology and suggest a more varied treatment approach. There is a great need for in-depth research into this area, meaning that the exclusion criteria of current diagnostic manuals, i.e. those that rule out a diagnosis of autism in some disorders, and a diagnosis of certain other disorders in autism may have to be revised.
Article
Little theoretical work exists that proposes general mechanisms for how public policies may influence child development. This article argues that dynamic systems theories may be useful in illuminating such processes, as well as highlighting gaps in current research at the intersection of public policy analysis and developmental science. A brief review of dynamic systems theories as they are currently utilized in other areas of developmental science is provided, as well as a statement of why they may help advance research in public policy and child development. Five principles of dynamic systems theories are presented and discussed using examples from research that address the question, "How do current antipoverty and welfare reform policies affect children?" Also presented are examples of hypotheses and research questions that each principle may generate for future work. The concluding section presents challenges that each principle poses for research methodology, and potential uses of the dynamic systems approach for developing and integrating policy and program initiatives.
Article
To examine racial differences in the age at which Medicaid-eligible children first receive an autistic disorder (AD) diagnosis and to examine time in mental health treatment until an AD diagnosis was received. Philadelphia Medicaid specialty mental health claims identified 406 children who received services in 1999 for AD. Claims from 1993-1999 were used to identify the date of first mental health visit, first receipt of AD diagnosis, and number of visits occurring between those dates. Linear regression was used to examine the relationship among race, age at first diagnosis of AD, time in mental health treatment, and number of visits until the diagnosis was made. On average, white children received the AD diagnosis at 6.3 years of age, compared with 7.9 years for black children (p <.001). White children entered the mental health system at an earlier age (6.0 versus 7.1 years, p =.005); however, after adjusting for age, sex, and time eligible for Medicaid, black children required more time in treatment before receiving the diagnosis. Important disparities exist in the early detection and treatment of autism. These disparities may be the result of differences in help-seeking, advocacy and support, and clinician behaviors.