Although there are many activities (e.g., transition services), derived from correlational research, that occur while students are in school that increase the likelihood of positive post-school outcomes, many teachers continue to provide services shown to have little to no effect on outcomes of students with disabilities. The purpose of this study was to operationally define the predictors of post-school success for educators to understand what is necessary to develop, implement, and evaluate secondary transition programs based on predictor research. Results conclude experts in the field reached consensus on an operational definition and set of essential program characteristics for each predictor of post-school success to aid practitioners in implementing these practices.

Youth with disabilities are less likely to enroll and complete postsecondary education than their nondisabled peers. Using a qualitative, cross-case design, we investigated the high school to college transition experiences of young adults diagnosed with Asperger syndrome (AS). Data sources included a family questionnaire, review of special education records, and multiple individual interviews (N = 27) with young adults with AS, family members, teachers, and rehabilitation counselors. Social skills, communication, and executive functioning challenges in high school continued into postsecondary education settings. Across cases, five reoccurring themes seemed to influence the transition from high school to postsecondary education: (a) motivation to attend college, (b) high levels of disability awareness, (c) intentional family supports, (d) coordinated transition planning, and (e) clear postschool goals.

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This study examined self-employment within the context of U.S. vocational rehabilitation (VR) to identify significant predictors of successful self-employment case closure, how these predictors changed over time, and whether there were differences in the likelihood of successful self-employment closure across states. To answer the research questions, five fiscal years (FYs) of RSA 911 data from 2003 to 2007, constituting more than a million cases, were analyzed using a two-level Hierarchical Linear Modeling (HLM). These years were selected because they occurred between the two most recent economic recessions. Statistically significant (p < 0.001) predictors of successful self-employment closure across the FYs were: gender, ethnicity, cost of VR services, education attainment, and public supports. The only difference occurred in FY 2004, when significant-disability status was also a significant predictor. Among the significant predictors, ethnicity had the largest effect, followed by education attainment and gender. States were significantly different in their likelihood of successful self-employment closures. Analyses of additional, more recent years of RSA data using HLM with other predictors are warranted to draw more definitive conclusions and develop substantive theoretical explanations. Limitations and implications of this study for researchers and VR agencies are discussed in conclusion.