{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:26:55Z","timestamp":1777451215886,"version":"3.51.4"},"reference-count":54,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2019,4,13]],"date-time":"2019-04-13T00:00:00Z","timestamp":1555113600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Autism in Adulthood"],"published-print":{"date-parts":[[2019,6,1]]},"abstract":"Abstract<\/jats:title>\n \n Background:<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Methods:<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Results:<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Conclusions:<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Lay Summary<\/jats:title>\n \n \n Background:<\/jats:italic>\n <\/jats:bold>\n Achieving employment is an important milestone on the road to adulthood. Having a job is related to financial independence, health, and well-being but can also provide a sense of belonging and opportunities for inclusion. Transition-age youth on the autism spectrum (TAY-ASD) may find that getting and keeping a job is more difficult than it is for their peers with other types of disabilities. Vocational rehabilitation (VR) is a public source of support for employment for people with disabilities in the United States, and TAY-ASD are increasingly using VR services. However, whether youth receive VR services, and whether they gain employment following VR services, is highly dependent on which state they live in. We do not yet fully understand why state VR services vary so dramatically.\n <\/jats:p>\n \n \n About This Study:<\/jats:italic>\n <\/jats:bold>\n New federal legislation, the Workforce Innovation and Opportunity Act, aims to reach students with disabilities with vocational services during secondary school (junior high and high school). Few studies exist to help us understand how well VR services are reaching students and what are the effects of these services. We tested new ways to measure VR services for TAY-ASD and also tested whether we could group states according to their results on these measurements. We wondered whether any groups of states performed better than other groups.\n <\/jats:p>\n 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.<\/jats:p>\n \n \n What This Study Tells Us:<\/jats:italic>\n <\/jats:bold>\n We identified five groups of states, which each had a unique pattern of how they performed on these measures. We named the groups\u2014also called classes\u2014according to their strengths. Class 1 had\n above average employment rates<\/jats:italic>\n but below average performance on other measures. Class 2 had\n timely services<\/jats:italic>\n , meaning that these states finished youth's employment plans on time, so that they could access services. Class 3 had both\n timely services<\/jats:italic>\n and\n early reach<\/jats:italic>\n to students, meaning that the students began services during secondary school. Class 4 had\n early reach<\/jats:italic>\n to secondary students but low performance on other measures. Finally, Class 5 had\n above average performance on all measures<\/jats:italic>\n . States in this class excelled at reaching students, developing employment plans quickly, enrolling students in services, and achieving employment by the time VR services ended. We then determined which states were most likely to belong in each class.\n <\/jats:p>\n 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.<\/jats:p>\n <\/jats:sec>","DOI":"10.1089\/aut.2018.0018","type":"journal-article","created":{"date-parts":[[2019,3,6]],"date-time":"2019-03-06T09:12:12Z","timestamp":1551863532000},"page":"101-111","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":8,"title":["Identifying Patterns of State Vocational Rehabilitation Performance in Serving Transition-Age Youth on the Autism Spectrum"],"prefix":"10.1177","volume":"1","author":[{"given":"Anne M.","family":"Roux","sequence":"first","affiliation":[{"name":"A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jessica E.","family":"Rast","sequence":"additional","affiliation":[{"name":"A.J. Drexel Autism Institute, Drexel University, Philadelphia, Pennsylvania."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kelly","family":"Nye-Lengerman","sequence":"additional","affiliation":[{"name":"Research and Training Center on Community Living, Institute on Community Integration, University of Minnesota, Minneapolis, Minnesota."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Purtle","sequence":"additional","affiliation":[{"name":"Department of Health Management and Policy, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angela","family":"Lello","sequence":"additional","affiliation":[{"name":"Advocacy and Family Services, Autism Speaks, Washington, District of Columbia."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul T.","family":"Shattuck","sequence":"additional","affiliation":[{"name":"A.J. 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