Employment Service Systems Research and Training Center

1. Employment Service Systems Research and Training Center Developing an Evidence Base for Evaluation Research David Vandergoot, Ph.D., Co-Principal Investigator Robert Stensrud, Ph.D. Co-Principal Investigator The ESSRTC is supported through Grant No. H133B040014 to Hunter College, City University of New York from National Institute on Disability and Rehabilitation Research, U.S. Department of Education.

2. ESSRTC Projects • Study RSA 911 to Identify Predictors of Unsuccessful Closures • Study Best Practices in VR Counselors • Study Current Consumer Satisfaction with VR and One-Stop Services • Study One-Stop Collaboration and Integration • Study Provider Collaboration Around Demand Side Services • Demonstrate Models for Predicting Employment of People with Disabilities for State Planning • Design Employment Service Systems to Develop and Demonstrate Evidence-Based Practices

3. ESSRTC Products • Employer Openness Survey • Consortium for Employment Success Model • VR Current Consumer Satisfaction Survey • VR Closed Consumer Satisfaction Survey • VR Consumer Satisfaction Follow-Up Survey • Employment Prediction Model • DigitalChalk Training Modules

4. RSA 911 National DataClosed Before Plan Initiated (Status 30)

5. New York VR (VESID) DataClosed Before Plan Initiated (Status 30)

6. RSA 911 National DataClosed After Plan Initiated (Status 28)

7. Comparison – National vs. State Data

8. Consumer Satisfaction Survey • Current Consumer Satisfaction with VR and Partner Services • Consumer Satisfaction at Case Closure • Consumer Satisfaction at 12-Month Follow-Up • Tied to Case Data • Tied to Service Self-Assessment Data • Can Be Tied to Employment Forecasting Model

9. VESID Survey12 month Response Rates Response rate: 595 of 5003 surveys returned (11.9% response rate) Response rate by closure status: Status 26: 410 of 2730 (15%) Status 28: 185 of 2273 (8.1%)

10. Employment Outcomes

11. Weekly Earnings

12. Health Benefits from Job

13. Opportunities for Advancement

14. More Financially Independent

15. Improved Job Skills

16. Because of Job QOL Improved

17. Participation in Work-Related Social Events

18. Because of Job Able to Meet More People

19. Satisfaction with Job

20. Overall Satisfaction

21. Ability to Reach Counselor

22. Time to Receive Services

23. Treatment by Reception Staff

24. Treatment by Counseling Staff

25. Job Choice and Skills Matched

26. Understanding Services

27. Participation in Planning Services

28. Planning for Job or Training

29. Informed about Hearing

30. Recommend VESID

31. Employment Forecasts for State VR Agencies • Develop a prediction model to forecast the employment of people with disabilities • Work with officials from the Iowa VR, Iowa DOL, and Iowa SSA to develop a prototype of the VR State Plan section dealing with future needs • Apply to Assessment of One-Stop Performance • Apply to Services for Ticket Holders • Apply to Transitioning Services • Apply to State Budgeting Process

32. Forecasting • Available Labor Force • Employment By Industry • Employment By Occupation • Employment By Firm Size • Occupational Wage Estimates • Unemployment Rates • Available Jobs Per Worker

33. Forecasting for Consumers We will adapt this work to address the employment of people with disabilities by integrating existing data sources that have not been effectively integrated before and used for state-level planning and program development

34. Disability Data Sources • Census Bureau • Rehabilitation Services Administration • Social Security Administration • Federal Department of Labor

35. Result An improved mechanism by which state VR agencies can develop plans and budgets based on sound data and identified areas where promising practices might be implemented. This would enable agencies to better target unserved and underserved populations and direct outreach to regions and employment sectors with greater hiring potential.It can be adapted to transition planning for youth with disabilities.

36. Comprehensive StatewideNeeds Assessment Model Implementation Planning Review of Literature Resource Assessment VR SYSTEM Analysis of Extant Data Random Survey (Interview) Key Informant Interviews Focus Group

37. Toward Evidence-Based Practices • Dependent Variables • Current Consumer Satisfaction • Satisfaction At Closure • Follow-Up Satisfaction • Casefile Data • Moderating Variables • Forecasting Model • Collaboration • Independent Variables • Promising Practices • Grant Applications and External Evaluation

38. Online Training Partnerships • A virtual classroom, DigitalChalk, that allows learners to adapt the learning portal to their learning needs, including a note taking capability • It utilizes synchronized audio, video, power point presentations, downloadable documents, learning assessments, and certification credentialing • Closed captioning can be turned on/off from portal • The training can be accessed at any time and at the learners’ desired pace • ESSRTC can assist agencies in designing best practice training

39. Disability Stats RTC • Five year project funded by NIDRR • Hunter College lead agency • Partners • New Editions • Mathematica Policy Research • Center for Essential Management Services

40. Mission The Rehabilitation Research and Training Center on Disability Statistics and Demographics (StatsRRTC) will facilitate evidence-based decision making in many different service and policy arenas to benefit persons with disabilities, leading to improved education and employment outcomes

41. VR Data Processes & Analyses Utilizes a combination of formats, including workshops, conferences, the DigitalChalk Learning Platform, and our Webinar Series to work with the 80 general and blind vocational rehabilitation (VR) state agencies.

42. VR Data Processes & Analyses Yr 1 • Develop network of VR state agency personnel with focus on data, research and evaluation • Conduct assessment of their needs regarding disability data/statistics • Collect information on their current data collection, analysis and reporting practices

43. VR Data Processes & Analyses Yr 2 • Inquire into evidence regarding validity and reliability of these data collection processes • Coalesce these practices into a “menu of practices” that documents the different data collected and how they are used • Develop a set of promising practices based on what we observe in the field. • Field test these practices

44. VR Data Processes & Analyses Yrs 3-5 • Convey the menu and promising practices back to the agencies (State of Science) • In collaboration with the training participants, develop plans for future research aimed at improving data collection, analysis, and reporting.