Título : A Longitudinal Analysis of Gambling Predictors among Adolescents |
Autor : Botella Guijarro, Álvaro Lloret-Irles, Daniel Segura-Heras, José Vicente Moriano, Juan Antonio Cabrera-Perona, Victor |
Editor : MDPI |
Departamento: Departamentos de la UMH::Estadística, Matemáticas e Informática |
Fecha de publicación: 2020 |
URI : https://hdl.handle.net/11000/32303 |
Resumen :
Although gambling is forbidden for minors, the prevalence of gambling among adolescents is increasing. In order to improve preventive interventions, more evidence on predictors of gambling onset is needed. A longitudinal study was proposed to (1) establish the prevalence of gambling; (2) identify factors associated with gambling behavior the following year; and (3) adjust a model to predict gambling behavior. A cohort of 1074 students (13–18 years old) was followed for 12 months. The prevalence of gambling reached 42.0% in the second measure. Boys gambled 2.7 times more than girls, and the highest percentages of gambling onset showed up between 13 and 14 years old. Gambling onset and maintenance was associated with gender, age, sensation-seeking, risk perception, self-efficacy for not gambling, parents’ attitude towards gambling, group pressure (friends), subjective norm, exposure to advertising, accessibility, normative perception, gambling in T1 and parents gambling behavior. Gender, gambling in T1 and risk perception were significant in all three logistic adjusted regression models, with the fourth variable being sensation seeking, peer pressure (friends) and accessibility, respectively. It is suggested that universal prevention should be aimed preferably at children under 15 years old and to alert regulators and public administrations to the directly proportional relationship between accessibility and gambling onset.
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Palabras clave/Materias: gambling adolescence generalized linear model (GLM) risk factor |
Área de conocimiento : CDU: Ciencias puras y naturales: Matemáticas |
Tipo documento : application/pdf |
Derechos de acceso: info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : https://doi.org/10.3390/ijerph17249266 |
Aparece en las colecciones: Artículos Estadística, Matemáticas e Informática
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