Determinants Of Inmates Recidivism Rate In Kenya: The Case Of Kamiti Maximum Prison In Nairobi City County

ABSTRACT

This study seeks to find out precisely why ex-convicts are likely to repeat crime after incarceration in spite of the on-going rehabilitation at prison. The existing data from Kenya Prison division states that recidivism in Kenya prison continues to grow. The objective of the researcher in this perspective is to assess determinants of recidivism rate in Kenya focusing on Kamiti Maximum Prison. The key questions of interest are of what relevance is the rehabilitation programs offered in prison on recidivism, whether demographic characteristics of inmates determines recidivism rate and whether inmates sentence duration affect recidivism rate. Recidivism will be given specific attention by the researcher since it directly affects the Kenyan society both socially and economically. The study will adopt Relapse Prevention theory, which provides a mechanism to assess the performance of rehabilitation programmes on criminals behaviour change over time and avoid relapse. Relapse Prevention theory is a cognitive behaviour model with origin in Banduras, (1977) self-efficacy theory that presents a comprehensive and integrated framework for explaining the change process in psychotherapy. What “Works in reducing recidivism” theory, also referred to as evidenced-based practice, what works movement demonstrate that empirically and theoretically sound, well-defined programs that meet certain conditions can significantly reduce recidivism rate for offenders. The research will adopt descriptive research design to collect data; the design is useful, as it will help the researcher to collect data without altering the environment. Purposive sampling will be employed for prison warders and tutors. Stratified sampling will be used for prison inmates. Data will be collected by the use of questionnaire and interview guide. The questionnaire will entail both open and closed ended questions. Data collected from questionnaires will be coded, tabulated and analysed using SPSS (Statistical Package for Social Science) by both descriptive statistics, which comprise of mean and standard deviation to capture the features of the variables under study. Inferential statistics that include Chi square tests will also be used to analyse the relationship between the independent variables and the dependent variable.