Article Details

Research Database: Article Details

Citation:  Chan, F., Cheing, G., Chan, J.Y.C., Rosenthal, D.A., & Chronister, J.A. (2006). Predicting employment outcomes of rehabilitation clients with orthopedic disabilities. Disability and Rehabilitation, 28 (5), 257-270.
Title:  Predicting employment outcomes of rehabilitation clients with orthopedic disabilities
Authors:  Chan, F., Cheing, G., Chan, J.Y.C., Rosenthal, D.A., & Chronister, J.A.
Year:  2006
Journal/Publication:  Disability and Rehabilitation
Publisher:  Taylor & Francis
Full text:   
Peer-reviewed?  Yes
NIDILRR-funded?  Yes
Research design:  Database mining

Structured abstract:

Background:  Work is fundamental to persons with disabilities having some sort of independence and quality of life. Vocational rehabilitation services measure their effectiveness largely on employment outcomes of their clients. Employment outcomes of clients and thus what services should be offered to them can be predicted to some degree using data mining techniques such as the chi-squared automatic interaction detector (CHAID). Using CHAID to study data sets can yield a wealth of information about that data set.
Purpose:  The purpose of this study was to use CHAID to mine the Rehabilitation Service Administration (RSA)-911 data set to determine what influences employment rates of rehabilitation clients with orthopedic disabilities.
Setting:  This study included individuals with orthopedic disabilities served by multiple vocational rehabilitation agencies in various settings.
Study sample:  The study participants (N=74,861) had their data mined from the RSA-911 database. All of the cases were closed by public rehabilitation agencies in fiscal year 2001. The sample was 55% male. European Americans numbered 73.2% of the sample. The mean age of the participants was 41.4 years. Forty-three percent of the sample completed high school and 28% had some college education. Eighty-eight percent had a severe disability.
Control or comparison condition:  The employment outcome was the comparison condition.
Data collection and analysis:  Variables that predicted employment outcomes were grouped into personal variables: gender, race, disability severity, age, education, and government benefits and rehabilitation variables. Rehabilitation variables consisted of: receiving an initial assessment, medical restoration, post-secondary education, business and vocational training, adjustment training, on the job training, miscellaneous training, substantial counseling and guidance, job finding services, job placement, transportation, maintenance, personal assistive services, rehab engineering, assistive technology, and other. Data was analyzed using CHAID.
Findings:  Job placement services significantly enhanced employment outcomes but were very much underutilized (only 25% of the study sample used them). Clients that had work disincentives such as social security disability insurance had lower employment rates than clients without such disincentives.
Conclusions:  The CHAID analysis proved to be an effective approach for examining the data set and interpreting relationships between variables. Vocational rehabilitation counselors should be aware of the predictors to employment that this study suggests.

Disabilities served:  Orthopedic impairments
Populations served:  Race: White / Caucasian
Interventions:  Vocational rehabilitation
Outcomes:  Employment acquisition
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