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http://dx.doi.org/10.15207/JKCS.2015.6.2.025

The Factors of Participating in a Smoking Cessation Program using Integrated Method of Decision Tree and Neural Network Algorithm  

Byeon, Haewon (Department of Speech Language Pathology & Audiology, Nambu University)
Publication Information
Journal of the Korea Convergence Society / v.6, no.2, 2015 , pp. 25-30 More about this Journal
Abstract
The purpose of this study was to analyze the factors that affects the participating in a smoking cessation program. Data were from the A Study on the Seoul Welfare Panel Study 2010. Subjects were 1,326 smokers aged 19 and older living in the community. Dependent variable was defined as experience of smoking cessation. Explanatory variables were included as age, gender, level of education, employment status, household income, marital status, drinking, self-reported health status, depression, disease, and physical activity. A prediction model was developed by the use of a Decision Tree and Neural Network Algorithm. In the Prediction model, self reported health status, disease, income, household income were significantly associated with participating in a smoking cessation program. Based this study, systematic education and development of programs are required.
Keywords
Datamining; Neural Network; Smoking Cessation Program; Decision tree; Convergence Science;
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Times Cited By KSCI : 2  (Citation Analysis)
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