Identifying factors that promote successful vocational rehabilitation case closure: Comparison of individual characteristics,VR experiences and state economic conditions

Abstract

BACKGROUND:

Despite the series of public policies being implemented to strengthen vocational rehabilitation (VR) services, individuals with disabilities remained at the substantial deficit in employment outcomes compared with individuals without disabilities.

OBJECTIVE:

We aimed to examine effects of vocational rehabilitation services on the employment outcomes for people with disabilities while accounting for individual characteristics and state economic conditions. Findings had implications for VR program improvement.

METHOD:

We used the RSA-911 data covering cases from 2015 to 2017, in addition to state unemployment rate and poverty rate in 2017 to address the research questions. A logistic regression model was estimated with Generalized Estimating Equations to predict the probability of successful case closure by individual demographic characteristics, number of VR services received, and state economic conditions.

RESULTS:

State economic conditions were not associated with employment outcomes among VR participants. Being female, Black, having physical disabilities, and not having a job at application were disadvantageous in employment outcomes. The more varieties of vocational services that individuals received, the higher odds of successful case closure.

CONCLUSIONS:

VR services have significant beneficial impact on individual employment outcomes. The strongest beneficial impact may be achieved by providing a combination of different types of services that are designed to help individuals find or sustain employment.

Keywords

Vocational rehabilitation disabilities employment vocational services economy

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References

Anand,

, & Honeycutt,

T. C.

(2020). Long-term outcomes for transition-age youth with mental health conditions who receive postsecondary education support. Journal of Disability Policy Studies, 30, 223–232. https://doi.org/10.1177/10442073198480.

Brucker,

D. L.

, & Henly,

(2019). Job quality for Americans with disabilities. Journal of Vocational Rehabilitation, 50, 121–130. https://doi.org/10.3233/JVR-180994.

Bureau of Labor Statistics (2021, February). Persons with a disability: Labor force characteristics news release. Economic News Release USDL-20-0339. Retrieved from https://www.bls.gov/news.release/pdf/disabl.pdf.

Carter,

E. W

, Austin,

, & Trainor,

A. A.

(2012). Predictors of postschool employment outcomes for young adults with severe disabilities. Journal of Disability Policy Studies, 23, 50–63. https://doi.org/10.1177/1044207311414680.

Chan,

J. Y

, Wang,

, Ditchman,

, Kim,

J. H

, Pete,

, Chan,

, & Dries,

(2014). State unemployment rates and vocational rehabilitation outcomes: A multilevel analysis. Rehabilitation Counseling Bulletin, 57, 209–218. https://doi.org/10.1177/0034355213509855.

Chan,

, Wang,

, Fitzgerald,

, Muller,

, Ditchman,

, & Menz,

(2016). Personal, environmental, and service-delivery determinants of employment quality for state vocational rehabilitation consumers: A multilevel analysis. Journal of Vocational Rehabilitation, 45, 5–18. https://doi.org/10.3233/JVR-160806.

Dutta,

, Gervey,

, Chan,

, Chou,

, & Ditchman,

(2008). Vocational rehabilitation services and employment outcomes for people with disabilities: A United States study. Journal of Occupational Rehabilitation, 18, 326–334. https://doi.org/10.1007/s10926-008-9154-z.

Hardin,

J. W

, & Hilbe,

J. M.

(2013). Generalized estimating equations (2nd ed.). CRC Press.

Liang,

, & Zeger,

S. L.

(1986). Longitudinal data analysis using generalized linear models, Biometrika, 73, 13–22.

10.

Luca,

D. L.

, & Sevak,

(2020, January). Scheduling uncertainly and employment of young adults with disabilities. Center for Retirement Research at Boston College CRR WP 2020-5. Retrieved from https://collections.nlm.nih.gov/catalog/nlm:nlmuid-101761863-pdf.

11.

Martin,

F. H.

(2010). Racial variation in vocational rehabilitation outcomes: A structural equation modeling approach. Rehabilitation Counseling Bulletin, 54, 26–35. https://doi.org/10.1177/0034355209360420.

12.

Pete,

J. P

, Diallo,

, Kaya,

, Brooks,

, Allen,

, Bezyak,

, & Chan,

(2015). Vocational rehabilitation as a public health intervention for young African American men with substance use disorders. Journal of Vocational Rehabilitation, 43, 149–157. https://doi.org/10.3233/JVR-150764.

13.

Poppen,

, Lindstrom,

, Unruh,

, Kkurana,

, & Bullis,

(2017). Preparing youth with disabilities for employment: An analysis of vocational rehabilitation case services data. Journal of Vocational Rehabilitation, 46, 209–224. https://doi.org/10.3233/JVR-160857.

14.

U.S Department of Education (n.d.). PD-16-04: Revision of Policy Directive (PD) 14-01 instructions for the completion of the Case Service Report (RSSA-911) for the State Vocational Rehabilitation Services Programand the State Supported Employment Services Program. Retrieved from https://www2.ed.gov/rschstat/eval/rehab/911-data.html.

15.

Wagner,

M. M

, Newman,

L. A

, & Javitz,

H. S.

(2014). The influence of family socioeconomic status on the post-high school outcomes of youth with disabilities. Career Development and Transition for Exceptional Individuals, 37, 5–17. https://doi.org/10.1177/2165143414523980.

16.

Wehman,

, Sima,

, Ketchum,

, West,

M. D

, Chan,

, & Luecking,

(2015). Predictors of successful transition from school to employment for youth with disabilities. Journal of Occupational Rehabilitation, 25, 323–334. https://doi.org/10.1007/s10926-014-9541-6.