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VR Employment Outcomes of Individuals with Autism Spectrum Disorders: A Decade in the Making

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Abstract

This study utilized hierarchical linear modeling analysis of a 10-year extant dataset from Rehabilitation Services Administration to investigate significant predictors of employment outcomes for vocational rehabilitation (VR) clients with autism. Predictor variables were gender, ethnicity, attained education level, IEP status in high school, secondary disability status, and total number of VR services. Competitive employment was the criterion variable. Only one predictor variable, Total Number of VR Services, was significant across all 10 years. IEP status in high school was not significant in any year. The remaining predictors were significant in one or more years. Further research and implications for researchers and practitioners are included.

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References

  • Alverson, C. Y., & Yamamoto, S. H. (2016). Employment outcomes of vocational rehabilitation clients with autism spectrum disorder. Career Development and Transition for Exceptional Individuals. doi:10.1177/2165143416629366.

    Google Scholar 

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.

  • Arbuckle, J. (2013). Amos 22 user’s guide. Crawfordville, FL: Amos Development Corporation.

    Google Scholar 

  • Cheak-Zamora, N., & Teti, M. (2015). “You think it’s hard now… It gets much harder for our children”: Youth with autism and their caregiver’s perspectives of health care transition services. Autism: The International Journal of Research and Practice, 19(8), 992–1001.

    Article  Google Scholar 

  • Cheak-Zamora, N. C., Farmer, J. E., Mayfield, W. A., Clark, M. J., Marvin, A. R., Law, J. K., & Law, P. A. (2014). Health care transition services for youth with autism spectrum disorders. Rehabilitation Psychology, 59(3), 340–348.

    Article  PubMed  Google Scholar 

  • Del Valle, R. D., Leahy, M. J., Sherman, S., Anderson, C. A., Tansey, T., & Schoen, B. (2014). Promising best practices that lead to employment in vocational rehabilitation: Findings from a four-state multiple case study. Journal of Vocational Rehabilitation, 41, 99–113. doi:10.3233/JVR-140708.

    Google Scholar 

  • HLM 7.0. (2014). Hierarchical linear modeling for windows version 7. [Computer Software]. Lincolnwood, IL: Scientific Software International (SSI), Inc.

  • Hox, J. J. (2002). Multilevel analysis. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • IBM (2013). SPSS statistics for windows version 22. [Computer Software]. Armonk, NY: IBM.

  • Individual with Disabilities Education Act (IDEA) and the National Center for Education Statistics (NCES). (2011). Oregon identification of children with disabilities: Student enrollment ages 6 to 21. Retrieved from http://www2.ed.gov/fund/data/report/idea/partbspap/2013/or-acc-stateprofile-11-12.pdf.

  • Kerlinger, F. N., & Lee, H. B. (2000). Foundations of behavioral research (4th ed.). Belmont, CA: Thomson Learning, Inc.

    Google Scholar 

  • Lawer, L., Brusilovskiy, E., Salzer, M. S., & Mandell, D. S. (2009). Use of vocational rehabilitative services for adults with autism. Journal of Autism and Developmental Disorders, 39, 487–494. doi:10.1007/s10803-008-0649-4.

    Article  PubMed  Google Scholar 

  • Leahy, M. J., Chan, F., Lui, J., Rosenthal, D., Tansey, T., Wehman, P., … Menz, F. E. (2014). An analysis of evidence-based best practices in the public vocational rehabilitation program: Gaps, future directions, and recommended steps to move forward. Journal of Vocational Rehabilitation, 41, 147–163. doi:10.3233/JVR-140707.

    Google Scholar 

  • Lipscomb, S., Haimson, J., Liu, A. Y., Burghardt, J., Johnson, D. R., & Thurlow, M. L. (2017). Preparing for life after high school: The characteristics and experiences of youth in special education. Findings from the National Longitudinal Transition Study 2012. Volume 2: Comparisons across disability groups: Full report (NCEE 2017-4018). Washington, DC: U.S. Department of Education, Institute of Education Sciences, National Center for Education Evaluation and Regional Assistance.

    Google Scholar 

  • Newman, L., Wagner, M., Cameto, R., & Knokey, A. M. (2009). The post-high school outcomes of youth with disabilities up to 4 -years after high school: A report of findings from the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2009-3017). Menlo Park, CA: SRI International. Available at www.nlts2.org/reports/2009_04/nlts2_report_2009_04_complete.pdf.

  • Newman, L., Wagner, M., Cameto, R., Knokey, A.-M., & Shaver, D. (2010). Comparisons Across Time of the Outcomes of Youth With Disabilities up to 4 Years After High School. A Report of Findings From the National Longitudinal Transition Study (NLTS) and the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2010-3008). Menlo Park, CA: SRI International.

  • Newman, L., Wagner, M., Knokey, A. M., Marder, C., Nagle, K., Shaver, D., Wei, X., with Cameto, R., Contreras, E., Ferguson, K., Greene, S., & Schwarting, M. (2011). The post-high school outcomes of young adults with disabilities up to 8 years after high school. A report from the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2011-3005). Menlo Park, CA: SRI International.

  • Oregon Department of Human Services. (2011) Oregon vocational rehabilitation services manual, Section 34; 25 May 2011.

  • Raudenbush, S., & Bryk, A. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage Publications.

    Google Scholar 

  • Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., Congdon, R. T., & du Toit, M. (2011). HLM 7: Hierarchical linear and nonlinear modeling. Lincolnwood, IL: Scientific Software International, Inc.

    Google Scholar 

  • Rehabilitation Act of 1973. P. L. 105–220, 20 United States Code § 9201.

  • Rehabilitation Services Administration. (2008). Reporting manual for the case service report (RSA-911): State-federal program for vocational rehabilitation. Washington, D.C.: United States Department of Education, Office of Special Education and Rehabilitative Services.

  • Rehabilitation Services Administration. (2013). Reporting manual for the case service record report (RSA-911): State-federal program for vocational rehabilitation. Washington, D.C.: United States Department of Education, Office of Special Education and Rehabilitative Services.

  • Revell, G., Smith, F., & Inge, K. (2009). An analysis of self-employment outcomes with the federal/state vocational rehabilitation system. Journal of Vocational Rehabilitation, 31, 11–18.

    Google Scholar 

  • Roux, A. M., Rast, J. E., Anderson, K. A., & Shattuck, P. T. (2016). National autism indicators report: Vocational rehabilitation. Philadelphia: Life Course Outcomes Research Program, A. J. Drexel Autism Institute, Drexel University.

    Google Scholar 

  • Sanford, C., Newman, L., Wagner, M., Cameto, R., Knokey, A. M., & Shaver, D. (2011). The post-high school outcomes of young adults with disabilities up to 6 years after high school. Key findings from the National Longitudinal Transition Study-2 (NLTS2) (NCSER 2011- 004). Menlo Park, CA: SRI International.

  • Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 147–177.

    Article  PubMed  Google Scholar 

  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin Company.

    Google Scholar 

  • Sung, C., Sanchez, J., Kuo, H.-J., Wang, C.-C., & Leahy, M. J. (2015). Gender differences in vocational rehabilitation service predictors of successful competitive employment for transition-aged individuals with autism. Journal of Autism and Developmental Disorders, 45, 3204–3218. doi:10.1007/s10803-015-2480-z.

    Article  PubMed  Google Scholar 

  • Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Pearson Education, Inc.

    Google Scholar 

  • Tamhane, A. C., & Dunlop, D. D. (2000). Statistics and data analysis: From elementary to intermediate. Upper Saddle River, NJ: Prentice-Hall, Inc.

    Google Scholar 

  • Test, D. W., Mazzotti, V. L., Mustian, A. L., Fowler, C. H., Kortering, L. J., & Kohler, P. H. (2009). Evidence-based secondary transition predictors for improving post-school outcomes for students with disabilities. Career Development for Exceptional Individuals, 32, 160–181.

    Article  Google Scholar 

  • U.S. Census Bureau. (2008). Americans with disabilities: 2005household economic studies. (Current Population Reports by Matthew W. Brault). Retrieved June 1, 2009, from http://www.census.gov/prod/2008pubs/p70-117.pdf.

  • U.S. Census Bureau. (2012a). Selected economic characteristics for the civilian noninstitutionalized population by disability status—2012 American Community Survey 1-year estimates. Retrieved February 2, 2015 from http://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_12_1YR_S1811&prodType=table.

  • U.S. Census Bureau. (2012b). Americans with disabilities: 2010household economic studies. (Current Population Reports by Matthew W. Brault). Retrieved February 2, 2015, from http://www.census.gov/prod/2012pubs/p70-131.pdf.

  • U.S. Department of Labor Office of Disability Employment Policy (2017). May 2017 Disability Employment Statistics Ages 16 years and over. Retrieved June 21, 2017, from https://www.dol.gov/odep.

  • Yamamoto, S. H., & Alverson, C. Y. (2013). Successful vocational outcomes: A multilevel analysis of self-employment through U.S. vocational rehabilitation agencies. Journal of Vocational Rehabilitation, 38(1), 15–27. doi:10.3233/JVR-120617.

    Google Scholar 

  • Yamamoto, S. H., & Alverson, C. Y. (2014). Factors of successful self-employment through vocational rehabilitation for individuals with disabilities. Journal of Career Assessment, 23(2), 318–335.

    Article  Google Scholar 

  • Yamamoto, S. H., & Alverson, C. Y. (2016). Individuals with disabilities in self-employment through vocational rehabilitation: Predictors of successful case closures from 2008 to 2012. Journal of Career Assessment. doi:10.1177/1069072716639862.

    Google Scholar 

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Funding

No funding was received for this study.

Author Contributions

CYA conceived of the study, participated in the design and interpretation of the data, and drafted the manuscript. SHY participated in the conceptualization and design of the study, performed the statistical analysis, participated in the interpretation of the data, and drafted the manuscript.

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Correspondence to Charlotte Y. Alverson.

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This article does not contain any studies with human participants performed by any of the authors.

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Alverson, C.Y., Yamamoto, S.H. VR Employment Outcomes of Individuals with Autism Spectrum Disorders: A Decade in the Making. J Autism Dev Disord 48, 151–162 (2018). https://doi.org/10.1007/s10803-017-3308-9

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  • DOI: https://doi.org/10.1007/s10803-017-3308-9

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