How Does Relaxing the Algorithm for Autism Affect DSM-V Prevalence Rates?
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Although it is still unclear what causes autism spectrum disorders (ASDs), over time researchers and clinicians have become more precise with detecting and diagnosing ASD. Many diagnoses, however, are based on the criteria established within the Diagnostic and Statistical Manual of Mental Disorders (DSM); thus, any change in these diagnostic criteria can have a great effect upon children with ASD and their families. It is predicted that the prevalence of ASD diagnoses will dramatically decrease with the adoption of the proposed DSM-5 criteria in 2013. The aim of this current study was to inspect the changes in prevalence first using a diagnostic criteria set which was modified slightly from the DSM-5 criteria (Modified-1 criteria) and again using a set of criteria which was relaxed even a bit more (Modified-2 criteria). Modified-1 resulted in 33.77 % fewer toddlers being diagnosed with ASD compared to the DSM-IV, while Modified-2 resulted in only a 17.98 % decrease in ASD diagnoses. Children diagnosed with the DSM-5 criteria exhibited the greatest levels of autism symptomatology, but the Mod-1, Mod-2, and DSM-IV groups still demonstrated significant impairments. Implications of these findings are discussed.
KeywordsBISCUIT Autism DSM-5 Prevalence
- Alfonso, V. C., Rentz, E. A., & Chung, S. (2010). Review of the Battelle developmental inventory, second edition. Journal of Early Childhood and Infant Psychology, 6, 21–40.Google Scholar
- Athanasiou, M. (2007). Review of the Battelle developmental inventory, 2nd Edn, by J. Newborg. Mental Measurements Yearbook, 17.Google Scholar
- Baton, L. R., & Spiker, D. (2007). Review of the Battelle developmental inventory, 2nd Edn, by J. Newborg. Mental Measurements Yearbook, 17.Google Scholar
- Bliss, S. L. (2007) Test reviews: Newborg, J. (2005). Battelle developmental inventory second edition. Journal of Psychoeducational Assessment, 25, 409–415.Google Scholar
- Elbaum, B., Gattamorta, K. A., & Penfield, R. D. (2010). Evaluation of the Battelle developmental inventory, 2nd edition, screening test for use in states’ child outcomes measurement systems under the Individuals with Disabilities Education Act. Journal of Early Intervention, 12, 255–273.CrossRefGoogle Scholar
- Gould, J. (1982). Social communication and imagination in children with cognitive and language impairments. Ph.D. thesis, University of London.Google Scholar
- Leech, N. L., Barrett, K. C., & Morgan, G. A. (2008). SPSS for intermediate statistics: Use and interpretation. New York: Psychology Press.Google Scholar
- Matson, J. L., Belva, B. C., Horovitz, M., & Bamburg, J. (2012). Comparing symptoms of autism spectrum disorders in a developmentally disabled adult population using the current DSM-IV-TR diagnostic criteria and the proposed DSM-5 diagnostic criteria. Journal of Developmental and Physical Disabilites. doi:10.1007/s10882-012-9278-0.Google Scholar
- Matson, J. L., Boisjoli, J., & Wilkins, J. (2007). Baby and infant screen for children with aUtIsm traits (BISCUIT). Baton Rouge, LA: Disability Consultants, LLC.Google Scholar
- Matson, J. L., Wilkins, J., Sharp, B., Knight, K., Sevin, J. A., & Boisjoli, J. A. (2009b). Sensitivity and specificity of the baby and infant screen for children with autism traits (BISCUIT): Validity and cut-off scores for autism and PDD-NOS in toddlers. Research in Autism Spectrum Disorders, 3, 924–930.CrossRefGoogle Scholar
- Newborg, J. (2005). Battelle developmental inventory (2nd ed.). Itasca, IL: Riverside.Google Scholar