Journal of the Korea Convergence Society (한국융합학회논문지)

Korea Convergence Society (한국융합학회)
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The Factors of Participating in a Smoking Cessation Program using Integrated Method of Decision Tree and Neural Network Algorithm

인공신경망 분석과 결정트리 융합에 의한 금연 프로그램 참여 결정 요인

  • Byeon, Haewon (Department of Speech Language Pathology & Audiology, Nambu University)
  • 변해원 (남부대학교 언어치료청각학과)
  • Received : 2015.01.28
  • Accepted : 2015.04.20
  • Published : 2015.04.30
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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.

이 연구는 신뢰성 있는 국가통계 데이터를 이용하여 지난 1년 간 금연 시도 경험 결정 요인 모형을 구축하고 개발된 모형을 근거로 금연 프로그램 참여 표적 집단 예측에 관한 기초 자료를 제공하였다. 분석대상은 2010년 서울시복지패널조사를 완료한 19세 이상 흡연자 1,326명이다. 결과변수는 지난 1년간 금연 시도 경험으로 정의하였고, 설명변수는 연령, 성, 최종학력, 현재 취업 상태, 가구 월 평균 총 소득, 배우자 유무, 음주 여부, 주관적 건강상태, 정기적인 운동 여부, 지난 한 달 간 우울증상 여부, 현재 순환기, 내분비계, 근골격계, 호흡기계, 이비인후 질환, 간질환, 비뇨기계질환 등 질병 여부로 설정하였다. 분석방법은 인공신경망 분석과 결정트리모형을 이용하였다. CART 알고리즘을 이용한 금연 프로그램 참여 모형을 구축한 결과, 유의미한 요인은 질병 여부, 주관적 건강 상태, 가구 월 평균 총소득이었다. 이 결과를 기초로 금연 프로그램의 성공적인 시행을 위해서 표적 대상의 특성을 고려한 프로그램 개발 및 교육이 요구된다.

Keywords

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