Article Details

Research Database: Article Details

Citation:  Rosenthal, D.A., Dalton, J.A. & Gervey, R. (2007). Analyzing vocational outcomes of individuals with psychiatric disabilities who received state vocational rehabilitation services: A data mining approach. International Journal of Social Psychiatry, 53 (4), 357-368.
Title:  Analyzing vocational outcomes of individuals with psychiatric disabilities who received state vocational rehabilitation services: A data mining approach
Authors:  Rosenthal, D.A., Dalton, J.A. & Gervey, R.
Year:  2007
Journal/Publication:  International Journal of Social Psychiatry
Publisher:  Sage
DOI:  https://doi.org/10.1177/0020764006074555
Full text:  http://proxy.library.vcu.edu/login?url=http://isp.sagepub.com/conte...    |   PDF   
Peer-reviewed?  Yes
NIDILRR-funded?  No
Research design:  Database mining

Structured abstract:

Background:  Poor vocational rehabilitation outcomes are seen for those with psychiatric disabilities; 80% to 85% are unemployed nationally. The authors claim that a lack of research into vocational rehabilitation services and outcomes is the cause for the high unemployment rates.
Purpose:  The purpose of the study is to examine factors that affect vocational outcomes in the vocational rehabilitation process for people with psychiatric disabilities who received state Vocational Rehabilitation (VR) services.
Setting:  The Rehabilitation Services Administration FY 2001 Case Service Report (RSA-911)was analyzed using data mining. This study included individuals with psychiatric disabilities served by multiple vocational rehabilitation agencies in various settings.
Study sample:  Participants in the study included only individuals who had a status code of 26 (working) or status code of 28 (not working).
Intervention:  The independent variables were: gender, age, race, severity of disability, education, benefits, rehabilitation services provided.
Control or comparison condition:  The dependent variable included were the status codes 26 or 28.
Data collection and analysis:  The Exhaustive Chi-Square Automatic Interaction Detector (CHAID) data mining technique was used. The technique requires the use of categorical values; therefore, age and education (continuous variables) were recoded into categories. Decision trees "were used to generate rules for the classification of this dataset" (p. 360). SPSS AnswerTree 2.0 statistical software was used for the data analysis.
Findings:  Those who were receiving job placement and counseling services, did not receive any government benefits, attended special education in high school, graduated from high school or had college experience, and received comprehensive assessment and vocational training were the most likely to be employed. Those who did not receive job placement services but did receive counseling, restorative and transportation services, and government benefits were the most likely to remain unemployed.
Conclusions:  An increase in the number of persons diagnosed with a psychiatric disability is expected as services are provided by public rehabilitation services rather than community-based services. Rehabilitation professionals should be made aware of the unique challenges and trained in the use of the Individual Placement and Support model.

Disabilities served:  Chronic mental illness
Interventions:  Individual Placement and Support (IPS) model of supported employment
Outcomes:  Employment acquisition