Rehabilitation Research and Training Center on Disability Statistics and Demographics (StatsRRTC) John O’Neill Kessler Foundation Purvi Sevak Mathematica Policy Research Presented at State of the Science Conference, Washington, D.C. April 8, 2014 Rehabilitation Research and Training Center on Individual-Level Characteristics Related to Employment Among Individuals with Disabilities (IC-RRTC)

Measure disparities. Persistent employment gaps between people with and without disabilities. Understand the role of personal characteristics. Personal characteristics interact with the environment, programs and policies to influence employment outcomes. Better understand heterogeneity. Diversity among people with disabilities can help explain differential employment outcomes. Identify success stories and barriers. The population’s heterogeneity provides the variation within which facilitators and barriers can be identified. Motivations for the Center 2

Employment Rates, by Type of Disability Source: American Community Survey, pooled 2009–2011 file.

Employment Rates Among Individuals with Disabilities, by Race and Ethnicity Source: American Community Survey, pooled 2009–2011 file.

Employment Rates Among Individuals with Disabilities, by Educational Attainment Source:American Community Survey, pooled 2009–2011 file.

I.Synthesis of available knowledge. Review and synthesize existing employment research on individual-level characteristics II.New knowledge using existing data. Conduct analyses using existing national data sets to identify individual-level characteristics most strongly associated with employment- related outcomes III.New data leading to new knowledge. Create new knowledge on employment barriers and facilitators for individuals who are at risk of poor employment outcomes. Three Phases of IC-RRTC 6

Rehabilitation Research and Training Center on Disability Statistics and Demographics (StatsRRTC) Phase I: Synthesis of Available Knowledge

Synthesis of Existing Literature Literature on disability and employment is vast, but segmented across different disability populations Few studies control for differences in other characteristics that might be driving employment differences Certain potentially important barriers and facilitators to employment have not been thoroughly studied, including social capital, pain, and employer characteristics

Rehabilitation Research and Training Center on Disability Statistics and Demographics (StatsRRTC) Phase II: New Knowledge Using Existing Data

Tomorrow’s IC-RRTC Presentations Examine differences in employment outcomes by primary impairment status among: ‒ Social Security beneficiaries ‒ Clients of Vocational Rehabilitation (VR) Explore employment outcomes across other differences: ‒ Demographic characteristics ‒ Self-care and independent living needs ‒ Social capital

8:30 AM (Session 4, Panel 1) Purvi Sevak and John O’Neill –The Influence of age, gender, race & education on employment, earnings & hours worked Debra Brucker –The effect of self-care and independent living limitations on the probability of employment David Stapleton, moderator

9:40 AM (Session 5, Panel 1) David Mann –Employment, earnings, and primary impairments among benefits of Social Security disability programs John O’Neill and Purvi Sevak –Differential VR outcomes by 19 impairments, age, gender and education Debra Brucker –Social capital & employment outcomes Debra Wright, moderator

Rehabilitation Research and Training Center on Disability Statistics and Demographics (StatsRRTC) Phase III: New Data Leading to New Knowledge

Motivation for a New Survey Create new data leading to new knowledge on disability and employment Informed by preceding phases –Literature on disability and employment is vast, but segmented across different disability populations –Few studies control for differences in other characteristics that might be driving employment differences –Certain potentially important barriers and facilitators to employment have not been thoroughly studied, including social capital, pain, and employer characteristics

The Survey of Disability and Employment Designed and conducted by Mathematica, in partnership with Kessler, CSAVR, and other IC-RRTC partners. Focuses on the barriers and facilitators to employment faced by recent applicants to state Vocational Rehabilitation agencies (SVRAs).

Survey Content Individual characteristics ‒ Education and skills ‒ Health and disability ‒ Unmet needs ‒ Other individual characteristics Employment history ‒ Accommodations ‒ Workplace culture ‒ Workplace discrimination ‒ Job search Barriers and facilitators to employment ‒ Transportation ‒ Social engagement and supports ‒ Vocational rehabilitation referral and outreach ‒ Employment supports ‒ Additional topics of agencies’ interest

Survey Sample and Data Collection Sample members recruited from three to four SVRAs using AWARE software for data collection Goal to complete surveys with 3,000 applicants: ‒ Ages 25 to 60 ‒ Recently employed ‒ Across impairments/disability types 30-minute survey will be conducted by telephone To reduce participation barriers, interviewers will provide options such as teletypewriter, telecommunications relay service, instant messaging, voice amplification When these options are exhausted, interviewers will offer the option to complete with or by a proxy respondent

Analysis Plan Descriptive statistics and a narrative of findings will be posted on the study web site Multivariate analysis will be used to investigate the impact of measured barriers and facilitators, and their interaction with individual characteristics Estimates will be adjusted using sample weights and design factors

Value Added from New Data Insights gained will inform agencies on effectiveness of outreach and marketing activities Could serve as a baseline for follow-up surveys The survey design could be applied in the future to study applicants to other agencies

We Need Your Help! To survey VR applicants, we need cooperation from agencies ‒ RSA and NIDRR encourage participation Recruiting three agencies in the coming weeks ‒ Agencies provide applicant data to Mathematica ‒ Agencies will have an opportunity to provide input and feedback on the questionnaire ‒ Mathematica will do the rest!

Comments or Questions Please contact: –John O’Neill –Purvi Sevak