Breaking the Criminogenic Cycle: Exploring Parental Influences on Juvenile Delinquency in Nairobi and Mombasa Counties, Kenya

There has been a rise in juvenile delinquency worldwide, particularly in developing countries such as Kenya. Failures in interventions point to the possible inefficacy of the measures, misdiagnosis, or scanty analysis of the security problem. This was precipitated by mixed results and insufficient documented research. There has been therefore a need to comprehensively confirm, analyze, and document the relationships between various criminogenic situational predictors and juvenile delinquency in Kenya. The purpose of this study thus was to examine the relationship between parental characteristics and juvenile delinquency in Nairobi and Mombasa counties in Kenya. For this purpose, the researcher hypothesized that there is no statistically significant predictive relationship between parental characteristics and juvenile delinquency in Nairobi and Mombasa counties. This was both evaluated on both non-delinquents and delinquents to establish clear relations. The study was anchored on Social Learning theory. The study adopted a Concurrent Nested mixed-method Research approach with a qualitative component being embedded in a quantitative Causal-Comparative Research Design. The target population of the study was 2,908,950 juveniles in the two counties. The accessible population was 235,861 respondents, out of which a sample of 400 was drawn, from which the researcher got 360, a response rate of 90%. The researcher drew the sample using a disproportionate stratified random sampling thus ensuring representation of both delinquents and non-delinquents in each county. The delinquent population entailed both delinquents who had committed minor violations and delinquents who had committed serious violations. Delinquents who had committed serious violations were drawn from borstal institutions, while those who had committed minor violations were drawn from the Probation Department. The non-delinquents were drawn from county secondary schools in each of the counties. Random sampling was done using the Excel data analysis tool pack. In addition, 12 respondents were selected purposively from the authorities dealing with children matters, 6 from each county. The total sample size attained was thus 372 respondents. A face-to-face interview questionnaire and an in-depth key informant interview schedule were the main instruments of data collection. Binary logistic regression was conducted on the quantitative data at a 95% confidence interval (CI) and a p-value