PURPOSE: To examine demographic and service factors affecting employment outcomes of people with orthopedic disabilities in public vocational rehabilitation programs in the United States. METHOD: The sample included 74,861 persons (55% men and 45% women) with disabilities involving the limbs or spinal column who were closed either as rehabilitated or not rehabilitated by their state-run vocational rehabilitation agencies in the fiscal year 2001. Mean age of participants was 41.4 years (SD = 11.2). The dependent variable is employment outcomes. The predictor variables include a set of personal history variables and rehabilitation service variables. RESULTS: The chi-squared automatic interaction detector (CHAID) analysis indicated that job placement services significantly enhanced competitive employment outcomes but were significantly underutilized (only 25% of the clients received this service). Physical restoration and assistive technology services along with support services such as counseling also contributed to positive employment outcomes. Importantly, clients who received general assistance, supplementary security income, and/or social security disability insurance benefits had a significant lower competitive employment rates (45%) than clients without such work disincentives (60%). CONCLUSION: The data mining approach (i.e., CHAID analysis) provided detailed information and insight about interactions among demographic variables, service patterns, and competitive employment rates through the segmentation of the sample into mutually exclusive homogeneous subgroups.
PURPOSE: To examine demographic and service factors affecting employment outcomes of people with orthopedic disabilities in public vocational rehabilitation programs in the United States. METHOD: The sample included 74,861 persons (55% men and 45% women) with disabilities involving the limbs or spinal column who were closed either as rehabilitated or not rehabilitated by their state-run vocational rehabilitation agencies in the fiscal year 2001. Mean age of participants was 41.4 years (SD = 11.2). The dependent variable is employment outcomes. The predictor variables include a set of personal history variables and rehabilitation service variables. RESULTS: The chi-squared automatic interaction detector (CHAID) analysis indicated that job placement services significantly enhanced competitive employment outcomes but were significantly underutilized (only 25% of the clients received this service). Physical restoration and assistive technology services along with support services such as counseling also contributed to positive employment outcomes. Importantly, clients who received general assistance, supplementary security income, and/or social security disability insurance benefits had a significant lower competitive employment rates (45%) than clients without such work disincentives (60%). CONCLUSION: The data mining approach (i.e., CHAID analysis) provided detailed information and insight about interactions among demographic variables, service patterns, and competitive employment rates through the segmentation of the sample into mutually exclusive homogeneous subgroups.
Authors: N Penel; M V Glabbeke; S Mathoulin-Pelissier; I Judson; S Sleijfer; B Bui; P Schoffski; M Ouali; S Marreaud; V Brouste; A Duhamel; P Hohenberger; J-Y Blay Journal: Br J Cancer Date: 2011-04-19 Impact factor: 7.640
Authors: A Ploquin; D Olmos; D Lacombe; R A'Hern; A Duhamel; C Twelves; S Marsoni; R Morales-Barrera; J-C Soria; J Verweij; E E Voest; P Schöffski; J H Schellens; A Kramar; R S Kristeleit; H-T Arkenau; S B Kaye; N Penel Journal: Br J Cancer Date: 2012-08-21 Impact factor: 7.640