Successful vocational rehabilitation innovations: Building a better toolbox.
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| Title: | Successful vocational rehabilitation innovations: Building a better toolbox. |
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| Authors: | Foley, Susan M.1 Susan.Foley@umb.edu, Livermore, Gina2, Foley, Susan, Sevak, Purvi |
| Source: | Journal of Vocational Rehabilitation. 2020, Vol. 53 Issue 3, p257-260. 4p. |
| Subject Terms: | *Diffusion of innovations, *Employment of people with disabilities, *Vocational rehabilitation, Disability insurance, Social security |
| Abstract: | BACKGROUND: Kentucky Office of Vocational Rehabilitation (OVR) and Minnesota Vocational Rehabilitation Services (VRS) successfully participated in a randomized control trial of an intervention designed in partnership with more than 100 VR personnel and twenty state VR agencies to identify effective practices for increasing earnings outcomes of Social Security Disability Insurance (SSDI) beneficiaries receiving VR services. OBJECTIVE: This paper introduces articles in the Special Issue to tell the story of the SGA Model Demonstration from design, testing, and impact evaluation. METHODS: The SGA Model Demonstration began reviewing administrative data, collecting expert opinion, and exploring current practice in eight state VR agencies. After an eighteen-month period of capacity building, two state VR agencies randomized local offices and implemented a rapid coordinated team approach. RESULTS: State VR agencies are successfully participating in rigorous research activities including model demonstrations with experimental designs. CONCLUSIONS: Model demonstrations that include experimental designs are effective strategies to improve knowledge and build a better practitioner toolbox to advance employment outcomes of VR clients. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Vocational Rehabilitation is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
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