Article Details

Research Database: Article Details

Citation:  Migliore, A., Timmons, J., Butterworth, J., & Lugas, J. (2012). Predictors of employment and postsecondary education of youth with autism. Rehabilitation Counseling Bulletin, 55 (3), 176-184.
Title:  Predictors of employment and postsecondary education of youth with autism
Authors:  Migliore, A., Timmons, J., Butterworth, J., & Lugas, J.
Year:  2012
Journal/Publication:  Rehabilitation Counseling Bulletin
Publisher:  Sage Publications (US)
DOI:  https://doi.org/10.1177/0034355212438943
Full text:  http://journals.sagepub.com/doi/abs/10.1177/0034355212438943    |   PDF   
Peer-reviewed?  Yes
NIDILRR-funded?  No

Structured abstract:

Background:  Employment and postsecondary education outcomes of youth with autism are a concern because they are weaker than those of youth with other disabilities. Although transition outcomes of this group remain bleak, the demand for services, especially vocational rehabilitation (VR) services, is increasing. This increase in the number of youth with autism seeking rehabilitation services has prompted an increased interest in research about predictors of transition outcomes for this population. Key predictor of employment outcomes is the range of services provided by the VR program. Most report that earnings at VR closure are positively correlated with receipt of job placement services. Other services positively correlated with earnings include supported employment, on-the-job training, business vocational training, work adjustment, and diagnosis and treatment. n contrast, Moore et al. (2002) reported no correlation between services and earnings. We are not aware of any studies that focused on predictors of postsecondary education outcomes for adults with disabilities in the VR program.
Purpose:  To increase our understanding about predictors of transition outcomes of youth with autism. This article addresses the following research questions: RQ 1: What demographic characteristics and VR services predict closures in integrated employment? RQ2: What demographic characteristics and VR services predict higher hourly earnings and weekly work hours? RQ3: What demographic characteristics and VR services predict improving youth’s postsecondary education?
Setting:  RSA911 data set,fiscal year 2008
Study sample:  2,913 youth with autism who met the following criteria: (a) had autism as either a primary or secondary disability, (b) were 16 to 26 years old at application, (c) did not have integrated employ- ment at application, and (d) received VR services.
Intervention:  VR services as a binary (yes/no) variable: assessment, counseling and guidance, job readiness training, job search, job placement, on-the-job supports, college, miscellaneous training, and “other services.” Postsecondary participation : having attended a postsecond- ary education program, whether or not a degree was awarded.
Control or comparison condition:  N/A
Data collection and analysis:  We performed descriptive analyses—frequencies and means—to provide overall information about predictor and outcome variables. Then we ran stepwise backward binary logistic regression to test the relationships between the predictors and the outcomes that were measured as categorical variables—integrated employment and postsecondary education improvement. Moreover, we adopted the backward approach, instead of the forward approach, because it reduces the risk of discarding suppressor variables (Field, 2009; Tabachnick & Fidell, 2001). Finally, we ran two linear multiple regressions to test the relationships between predictors and outcomes that were measured as continuous variables—earnings and work hours.
Findings:  The odds of gaining employment were greater for youth who received job placement services, yet only 48% of youth received this service. In addition, postsecondary education was among the strongest predictors of better earnings, yet only 10% of youth received college services. More detail, some of the demographic characteristics and VR services contributed to explaining employment outcomes. The greatest contributor to predicting employment was the provision of job placement services. Other important predictors of integrated employment included improved postsecondary education since application, shorter time in the VR program, receiving miscellaneous training, not receiving college services, and being male. The multiple regressions showed that some of the demographic characteristics and VR services contributed to explaining the outcome of hourly earnings. The strongest predictors of higher earnings included receiving college services and participating in postsecondary education. Job placement did not contribute to explaining earnings. The strongest predictors of a higher number of work hours included improved postsecondary education, receiving college services, and not receiving SSI or SSDI benefits. The second logistic regression did not yield conclusive find- ings for predicting postsecondary education improvement. The predictor variables were able to increase the correct prediction of postsecondary education improvement only by 2%, from 87% to 89%.
Conclusions:  The findings of this study have implications for practice and for research. On the basis of these findings, we recommend providing job placement services to a larger number of job seekers and development of approaches that lead to rapid implementation of job placement. Only 48% of youth with autism received job placement services. Yet the odds of exiting the VR program with jobs was 4 times greater for youth who received job placement services compared with youth who did not. We also recommend researching the reasons for the high percentage of youth who exited the VR program without receiving job placement services, and what actions are needed to increase the provision of placement services to youth with autism. In addition, postsecondary education may be an important intermediate outcome that warrants a stronger emphasis among the array of available VR services. At the same time, due to the relatively moderate effect sizes of these regression models, they recommend investigating additional variables currently not included in the RSA911 data set.

Disabilities served:  Autism / ASD
Populations served:  Transition-age youth (14 - 24)
Other
SSI and SSDI recipients
Interventions:  Job search and placement assistance
On-the-job training and support
Rehabilitation counseling
Supported employment
Training
Vocational rehabilitation
Outcomes:  Employment acquisition
Increase in hours worked
Wages
Other