Graduate Program

Communication Disorders and Sciences

Degree Name

Master of Science (MS)

Semester of Degree Completion

2005

Thesis Director

Gail Richard

Thesis Committee Member

Rebecca Throneburg

Thesis Committee Member

Lynn Calvert

Abstract

Professionals are encountering children with developmental disorders more often and with more diversity than ever before. Disorder labels are being introduced increasingly early in a child's life in order to qualify them for services. However, characteristics of developmental disorders overlap significantly in young children, with features beginning to differentiate as the child enters formal education at kindergarten age. Debate continues on whether the autistic spectrum is being over-diagnosed, based on increasing incidence and prevalence statistics.

Research has suggested that developmental disorders impact multiple developmental areas, including language, socialization, sensory, motor, and medical/physical aspects and skills. Therefore, distinguishing one developmental disorder from another can be challenging for professionals charged with diagnostic responsibilities. It is crucial that primary symptoms be differentiated from secondary or co-morbid conditions and deficits be viewed from a developmental perspective.

Currently, there are numerous specialized checklists and assessment tools used to assist in the diagnosis of autistic spectrum disorders. However, there is not an instrument that encompasses differential diagnostic categories across multiple types of developmental disorders. The Differential Assessment of Autism and Other Developmental Disorders (DAADD) is a screening instrument designed to differentiate among developmental disorders, including the autistic spectrum. The present study was designed to evaluate if the DAADD is a valid assessment tool for distinguishing among developmental disorders by comparing the DAADD results with actual diagnosis.

Three analyses were conducted based upon subject data. The analyses evaluated correspondence between actual diagnosis and the DAADD, whether the final diagnosis matched the highest disorder label percentage on the DAADD, and whether age was a factor in the accuracy of diagnosing developmental disorders. The data demonstrated a significant correlation between indications on the DAADD and final clinical diagnosis. Several emerging trends were also apparent within the statistical analyses, particularly in regard to age.

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