Social factors influencing participation of Jaramogi Oginga Odinga university of science and technology students in Sports betting in Bondo sub-county, Kenya

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Abstract/Overview

The legalization of betting in Kenya has resulted in widespread availability of betting in the society compared to when gambling was exclusive to casinos and clubs. A poll carried out in six African countries established that sports betting prevalence was highest among Kenyan youth, at 76%, notably among university students, with regrettable consequences. Despite being a social activity, inadequate studies had explicitly examined the social contexts of sports betting among university students. Demographic profiles were yet to be examined in existing studies on sports betting yet demographic characteristics had been identified as risk factors for gambling in general. The influence of subjective norms such as family, peer and social pressures on betting behaviour had not been adequately examined. The relationship between marketing and the attitudes of sports bettors was also not well understood. The main objective of the study was to examine the social factors influencing the participation of Jaramogi Oginga Odinga University of Science and Technology students in sports betting. The specific objectives were to; examine the influence of demographic profiles on the betting behaviour of students; establish the association between subjective norms and the betting behaviour of students and to assess the association between marketing and the attitude of students towards betting. The study was anchored on the Theory of Planned Behaviour (Ajzen, 1985). A correlational research design was adopted. A sample size of 385 respondents out of a target population of 10,090 undergraduate students was derived from Yamane’s Formula (1967). Stratified random sampling was utilized to ensure proportional representation of each school according to its population. Quantitative and qualitative data were collected using a structured questionnaire and a focus group discussion guide. Data for objective 1 were analysed using logistic regression to establish the predictors of betting behaviour where P-values of
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