Dissertation (Ed.D.)--University of Toledo, 2008. / Typescript. "Submitted as partial fulfillment of the requirements for The Doctor of Education Degree in Educational Administration and Supervision." Bibliography: leaves 114-120.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 59-66). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1996. / Typescript. Vita. Includes bibliographical references (leaves 59-66). Also available on the Internet.

Thesis (Ph. D.)--Ohio State University, 2009. / Title from first page of PDF file. Includes vita. Includes bibliographical references (p. 101-112).

Thesis (Ph. D.) University of Missouri-Columbia, 2006. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on August 1, 2007) Includes bibliographical references.

Thesis (Ed.D.)--University of West Florida, 2006. / Title from title page of source document. Document formatted into pages; contains 103 pages. Includes bibliographical references.

The media has the ability to influence societal perceptions about important issues. This study involved a dual examination of content and effects of news media representations of a prominent health issue—autism spectrum disorder (ASD) that now affects 1 in 88 individuals (CDC, 2013). Study 1 examined the presence of attributions of ASD and signaling “stigma” cues in news media and Study 2 investigated the effects of attributions of ASD emphasized in news media on community members’ emotions, behavioral intentions, and behaviors toward the disability. Study 1 revealed associations between certain attributions and signaling “stigma” cues and indicated news circulation plays a role in the appearance of cause attributions and social skill deficit cues. The results also illuminated intriguing trends in the presence of certain attributions of ASD and signaling “stigma” cues in news media over the past 16 years. Study 2 shed light on the direct and indirect effects of attributions about ASD emphasized in news stories on community members’ emotions, behavioral intentions, and actual behaviors; these findings partially align with attribution theory. This research provides a holistic understanding about the presence and power of language emphasized in news stories about ASD. Implications and directions for future research are discussed.

Thesis (Ed.D.)--Boston University / Through written survey and recorded interviews a snapshot in time was taken on how theorists of five promising approaches- Applied Behavioral Analysis, TEACCH, Daily Life Therapy, Miller Method, and DIR- think about children on the autism spectrum. Some of the findings include agreement on the need for a better definition of autism, the need for treatment-based research for developing and maintaining best practice, that the diversity of needs of people on the autism spectrum requires a wide range of approaches, and a general sense that people with autism have many valued strengths to contribute to society. Other findings include extensive use of non standardized assessments along with judicious employment of standardized instruments. Finally, all the theorists - some of home have spent more than 4 decades helping children with autism - all feel that the work they have done can be useful to youth with other challenges as well.

Modern Autism Spectrum Disorder (ASD) research has shifted in focus from explaining a debilitating childhood illness to helping individuals of all ages, cultures, and intelligence navigate their social problems. Understanding of the adult perspective has also grown massively since the autism diagnosis changed in the Diagnostic Statistical Manual, Fifth Edition (DSM-5) in 2013 and has brought into question how the neurodevelopmental disorder affects the individual. Anxiety symptoms in ASD, like the existence of camouflaging, have proven unique only to ASD, and recent findings suggests that the cause of anxiety in autistic individuals may be due to fundamental differences in communication that affect both the level of care received by the individual as well as the effectiveness of social interaction with neurotypical peers. This systematic review consolidates recent findings in research on the characteristics of anxiety disorders in autism spectrum disorder, from presentation to treatment options and quality of life surrounding an individual with both comorbidities. Results show not only an atypical anxiety presentation, but a concerning look at the state of autistic research as a whole.

Our motivation for this work is to develop an autonomous robot system that is able to perform autism intervention therapy. Autism spectrum disorder (ASD) is a common type of neurodevelopmental disorder that affects millions of people in the United States alone. The best way of treating ASD and help people with ASD learn new skills is through applied behavior analysis (ABA, i.e. autism intervention therapy). Because of the fact that people with ASD feel less stressful in a predictable and simple environment compared to interacting with other people and autism intervention therapy provided by professional therapists are generally expensive and inaccessible, it would be beneficial to build robots that can perform intervention therapy with children without a therapist/instructor present. In this research, we focus on the task of detecting engagement/disengagement levels of a child in a therapy session as a first step in designing a therapy robot. In this work, we mainly utilize an RGB-D camera, namely the Microsoft Kinect 2.0, to extract kinematic joint data from the therapy session. We also set up a child study with the Kid’s Creek therapy center to recruit children with ASD and record their interactions with a therapist while working on a touch-screen based game on a tablet. After carefully selecting features derived from skeletons’ movements and poses, we showed that our system can produce an accuracy of 97% when detecting engagements and disengagements using cross-validation assessment.