Abstract
Abstract
Background:
Transition-age youth on the autism spectrum (TAY-ASD) face many challenges when attempting to find and keep employment. Vocational rehabilitation (VR) is a key public source of support for employment for people with disabilities in the United States, and TAY-ASD increasingly use VR services. However, rates of VR service utilization and employment outcomes are known to vary dramatically across states for these youth, for reasons that are not fully understood.
Methods:
This study aimed to examine a set of indicators for measuring the state VR performance in serving TAY-ASD, compared with youth with other disabilities, and to identify classes of homogenous patterns of state performance across these indicators. We used latent profile analysis (LPA) to model patterns of state performance in serving TAY-ASD.
Results:
We identified five classes of states with unique patterns of performance across four key indicators (service receipt, early reach, timely services, and employment rates) and then matched states to each class based on their probability of inclusion. One class featured above average performance across all four indicators, and approximately one-fourth of states had a high probability of membership in this class.
Conclusions:
Identification of states with patterns of more efficient and effective VR service delivery for TAY-ASD will help target efforts to learn how states are delivering, organizing, and coordinating VR services for these youth. The use of methods like LPA may also be beneficial for examining performance within other autism-related service systems in the United States and internationally.
Lay Summary
We used the VR data for the 50 states and Washington DC to test the following four things: how often TAY-ASD received VR services if they were eligible for them; how often these youth applied for VR services during secondary school; how often their employment plan was finished on time; and how often they got a job after VR services. We compared youth on the autism spectrum with youth with other disabilities and found that they did about the same on these measures.
This study gives us another way to think about how states are doing in delivering VR services to TAY-ASD. By studying states that have better overall performance, versus others, we can identify what states might be doing differently. Learning about how some states are adapting VR services for TAY-ASD and the innovations they are using is important information for other states who wish to improve their VR services. The methods we used may also be helpful for examining the performance of other autism-related service systems in the United States and internationally.
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