Predicting vocational rehabilitation outcomes of young adults with specific learning disabilities: Transitioning from school to work

Abstract

Individuals with specific learning disabilities are a heterogeneous group with varied academic challenges and cognitive processing challenges. The manifestations of specific learning disabilities interfere with the acquisition of academic skills and impede vocational success. This study analyzed the Rehabilitation Services Administration (RSA) case service report (RSA-911) data for fiscal year (FY) 2007 to examine effects of demographic characteristics and employment outcomes of persons with specific learning disabilities. The RSA-911 FY 2007 dataset was examined via the chi-squared automatic interaction detector (CHAID) analysis. The CHAID analysis was utilized to extract predictive information for rehabilitation outcomes for individuals with specific learning disabilities. The exhaustive CHAID analysis allowed the segmentation of the large group of people into homogeneous subgroups (i.e., end groups). Results illuminate those demographic characteristics most salient to successful rehabilitation outcomes for consumers with specific learning disabilities. The chi-squared automatic interaction detector (CHAID) analysis indicated that public support significantly enhanced competitive employment outcomes.

Education and Employment Outcomes from the RSA Data File for Transition-Age African American, White, and Hispanic Youth with Learning Disabilities

“…At ap pli ca tion for VR ser vices there were high lev els of hav ing less than a high school ed u ca tion for all youth in this study. The rates of hav ing less than a high school ed u ca tion for par tic i pants in this study were higher than has been reported pre vi ously for youth with LD (Gon za lez et al, 2011;Thurlow, 2012). White youth had the high est rates of less than a high school ed u ca tion, with Af ri can Amer i can youth hav ing rates be tween White and His panic youth.…”

“…Re cent re search has in di cated a drop out rate of 14.7% for youth with LD (Thurlow, 2012). How ever, drop out rates have been re ported as high as 58.5% for youth with LD who re ceived vo ca tional re ha bil i ta tion (VR) services (Gonzalez, Rosenthal, & Kim, 2011).…”

“…The pur pose of this study was to ex am ine ed u ca -tion and em ploy ment out comes, and re la tion ships among de mo graphic and VR case ser vice vari ables for Af ri can Amer i can, White, and His panic youth with LD aged 15 -18 years. The age range of 15 to 18 years at the time the in divid ual ap plied for VR ser vices was used to cap ture youth with LD ear lier in their high school years as it has been noted that youth within this age range may be more likely to drop out of school (Gon za lez et al, 2011). Even though states may man date school at ten dance un til grad u a tion or un til the age of 16 years, and some states re quire stu dents to stay in school until age 17 or 18 years, prior research has shown that youth with LD may drop out of school as early as 15 to 16 and 1/2 years of age (Stearns & Glennie, 2006;Thurlow, 2012…”

Youth With Disabilities at the Crossroads

“…Nationally, 44% of transitionage SSA beneficiaries who applied for and received VR services were employed at the time of case closure. In comparison, nationally, of all non-SSA VR youth who 2004-2011ACS 2004ACS -2006DAF. N = 413,285.…”

Differential vocational rehabilitation service patterns and outcomes for transition-age youth with specific learning disabilities: Implications in the COVID-19 era

“…Additionally, 56% of people with SLD and co-occurring intellectual disabilities obtained competitive employment after receiving VR services (Dunham et al, 2000). More recently, Gonzalez et al (2011) revealed that 62.4% of youth with SLD obtained competitive employment after receiving VR services. Most of the VR services for individuals with SLD were on-the-job training, job coaching, and counseling services (Dunham et al, 2000).…”