Rehabilitation programs are critical for reducing recidivism rates and reintegrating offenders into the community. Despite the recognition that offenders face many challenges, few scholars have investigated the relationship between prisoners who receive more than 1 rehabilitation program and recidivism. The purpose of this quantitative, correlational cross-sectional study using archival data from a correctional facility in Barbados was to assess the relationship between age, education, employment, and multiple rehabilitation programs on recidivism. The conceptual framework of this study was grounded in the lifecycle theory, the social learning theory, the social cognitive theory, and the social disintegration theory. The primary research question examined how the variables of age, education, employment, and participation in more than 1 rehabilitation program predicted the dependent variable likelihood of recidivism at 1 year. Logistic regression was used to analyze data from 67 individuals. In this study, there were 3 major findings. First, participation in more than 1 rehabilitation program did not positively predict recidivism at 1 year. Second, the sociodemographic variables of age, education, and employment were not significantly related to recidivism at 1 year. Finally, the regression model was accurate in predicting nonrecidivism but was not correct in predicting who was likely to recidivate. The results of this study can contribute to positive social change as offenders receive help to overcome their psychological and social problems. At the community level, offenders who are employed are better able to find work and support their families. At the broader societal level, lower recidivism rates lead to reduced costs to maintain inmates and potential costs savings to the government.
|Advisor:||Rogers, Richard L.|
|Commitee:||Harris, Sandra M., Matthey, Sarah A.|
|School Location:||United States -- Minnesota|
|Source:||DAI 81/11(E), Dissertation Abstracts International|
|Subjects:||Criminology, Social research|
|Keywords:||Logistic regression, Multiple programs, Offender, Recidivism, Rehabilitation, Socio-econmomic variables|
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