Citation: |
Moore, C.L., & Wang, N. (2016). A national benchmark investigation of return-to-work outcome rates between African American, Native American or Alaskan Native, Latino, Asian American or Pacific Islander, and Non-Latino White veterans served by state vocational rehabilitation agencies: Application of bootstrap data expansion.
Journal of Vocational Rehabilitation, 45
(2),
133-147.
|
Title: |
A national benchmark investigation of return-to-work outcome rates between African American, Native American or Alaskan Native, Latino, Asian American or Pacific Islander, and Non-Latino White veterans served by state vocational rehabilitation agencies: Application of bootstrap data expansion |
Authors: |
Moore, C.L., & Wang, N. |
Year: |
2016 |
Journal/Publication:
|
Journal of Vocational Rehabilitation |
Publisher: |
IOS Press |
DOI: |
https://doi.org/10.3233/JVR-160818
|
Full text: |
http://content.iospress.com/articles/journal-of-vocational-rehabili...
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Peer-reviewed? |
Yes
|
NIDILRR-funded? |
No
|
Background: |
Research examining the provision of effective state vocational rehabilitation agency (SVRA) sponsored services is pertinent to improving successful return-to-work outcomes among veterans of color (i.e., African Americans, Native Americans or Alaska Natives, Latinos, and Asian Americans or Pacific Islanders versus non-Latino Whites). To date, however, scant attention has been paid to examining these target groups’ outcome patterns. |
Purpose:
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This study employed a stratified bootstrap data expansion approach to assess the relationship between race/ethnicity, gender, level of educational attainment at closure and return-to-work among veterans with a signed individualized plan for employment (IPE). |
Study sample: |
National fiscal year (FY) 2013 Rehabilitation Services Administration (RSA)-911 case records (N?=?11,603) were extracted and re-sampled across multiple trials using bootstrap procedures to increase logistic regression model accuracy. |
Data collection and analysis:
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Descriptive and multivariate statistics were utilized to analyze data. Access frequencies and return-to-work percentage rates were generated, compared, and reported for the five comparison groups. Next, bootstrap resample techniques were applied to increase the efficiency of validation procedures for predictive logistic regression analyses, and the final predictive model was used to evaluate the return-to-work rates across racial/ethnic target groups, gender, and level of educational attainment at closure. The Statistical Analysis System (SAS), desktop version 9.4, was used in these calculations (SAS Institute, 2014). |
Findings:
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The findings indicated that African American and female veterans were statistically significantly less likely to return-to-work compared to non-Latino White and female veterans, respectively. Return-to-work probabilities were ‘poorest’ for African American veterans followed by Native Americans or Alaska Natives, Asian Americans or Pacific Islanders, Latinos, and then non-Latino Whites. |
Conclusions:
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These findings warrant new service (e.g., greater SVRA and U.S. Department of Veterans Affairs’ (VA) co-service provision) and policy initiatives. |