Modeling the Effect of Education on E-Cigarette Use Behavior From Youth to Young Adult
Disciplines
Longitudinal Data Analysis and Time Series | Multivariate Analysis | Statistical Models
Abstract (300 words maximum)
The purpose of this quantitative study is to determine which of the analyzed variables offered the greatest correlation between adolescents and the use of e-cigarettes and marijuana. The variables analyzed were obtained from the 2017 National Youth Risk Behavior Surveillance Survey (YRBSS) of the Centers for Disease Control and Prevention (CDC). The YRBSS is used to monitor young adolescents and examine the prevalence of health risk behaviors. Data was collected through a quantitative method which used a cross sectional study from the results of the YRBSS. Over 14,000 highschool students from across the United States in public and private schools were sampled. For this study, participants were asked a series of questions that may pertain to the health risk behavior of individuals. To analyze the data, logistic regression and principal component analysis coded through PYTHON were used to examine the significance amongst the YRBSS variables. For e-cigarettes and vaping, logistic regression results showed statistical significance for 6 variables: weapon carrying, gun carrying, physical fighting, marijuana use, and synthetic marijuana use. For marijuana use, logistic regression results showed statistical significance for 6 variables: age, weapon carrying, gun carrying, physical fighting, attempted suicide, and vaping use. There are clear correlations between substance usage and unsafe behavior. We want to identify the harmful effects of e-cigarettes and marijuana so that adolescents can be more informed on the effects the substances have on their physical and mental health.
Keywords: Adolescents, E-Cigarettes, Vaping, Marijuana, Python, Logistic Regression, Principal Component Analysis, United States, Education
Academic department under which the project should be listed
CSM - Mathematics
Primary Investigator (PI) Name
Pengcheng Xiao
Modeling the Effect of Education on E-Cigarette Use Behavior From Youth to Young Adult
The purpose of this quantitative study is to determine which of the analyzed variables offered the greatest correlation between adolescents and the use of e-cigarettes and marijuana. The variables analyzed were obtained from the 2017 National Youth Risk Behavior Surveillance Survey (YRBSS) of the Centers for Disease Control and Prevention (CDC). The YRBSS is used to monitor young adolescents and examine the prevalence of health risk behaviors. Data was collected through a quantitative method which used a cross sectional study from the results of the YRBSS. Over 14,000 highschool students from across the United States in public and private schools were sampled. For this study, participants were asked a series of questions that may pertain to the health risk behavior of individuals. To analyze the data, logistic regression and principal component analysis coded through PYTHON were used to examine the significance amongst the YRBSS variables. For e-cigarettes and vaping, logistic regression results showed statistical significance for 6 variables: weapon carrying, gun carrying, physical fighting, marijuana use, and synthetic marijuana use. For marijuana use, logistic regression results showed statistical significance for 6 variables: age, weapon carrying, gun carrying, physical fighting, attempted suicide, and vaping use. There are clear correlations between substance usage and unsafe behavior. We want to identify the harmful effects of e-cigarettes and marijuana so that adolescents can be more informed on the effects the substances have on their physical and mental health.
Keywords: Adolescents, E-Cigarettes, Vaping, Marijuana, Python, Logistic Regression, Principal Component Analysis, United States, Education