Integrated Program to Improve Competitive Employment in Dually Diagnosed Clients.
This project has completed its research activities and is now closed. Check REHABDATA for documents.
Howard University. Department of Psychiatry. 2041 Georgia Avenue, NW. Washington, DC 20060.
E-mail:talim@howard.edu. Principal Investigator: Tanya Alim, MD. Public Contact Phone: 202/865-6611. Fax: 202/865-3068. Project Number: 90IF0085 (formerly H133G140261). About grant numbers. Start Date: October 1, 2014. Length: 36 months. NIDILRR Officer: Shelley Reeves. NIDILRR Funding: FY 14 $200,000; FY 15 $200,000; FY 16 $200,000; FY 17 $0 (No-cost extension through 9/29/2018). Abstract: This study extends the research on the Individual Placement and Support (IPS) model, a well-established evidence-based supported employment model for people with severe mental illness, to people with a dual diagnosis of severe mental illness and opioid use. Individuals who are dually diagnosed with severe mental illness and substance use face multiple barriers to recovery. This group also faces lower employment levels, which is even more pronounced for African Americans in urban areas. The project integrates the IPS model with a highly successful treatment program employing medication-assisted therapy to reduce opioid use, combined with a tailored cognitive behavior therapy approach. Using a randomized controlled design, this study evaluates whether IPS improves employment outcomes over a 12-month period. The project’s secondary goal is to assess whether employment lessens substance use and psychiatric symptoms, and improves quality of life and healthy friendships. A qualitative sub-study examines staff and client experiences with this innovative employment program. This study is being conducted by senior clinician-researchers from the Department of Psychiatry at Howard University in collaboration with Dartmouth University. Descriptors: African Americans, Dual diagnosis, Employment, Employment outcomes, Psychiatric disabilities, Section 21, Substance abuse.
Documents in REHABDATA:
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