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ACOMS+ 및 학술지 리포지터리 설명회

  • 한국과학기술정보연구원(KISTI) 서울분원 대회의실(별관 3층)
  • 2024년 07월 03일(수) 13:30
 

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장기적 금연유지 요인 탐색 : 입원 금연 프로그램 참여자 2년간 추적 검증

Decision-Tree Model of Long-term Abstention from Smoking L 2- Years Following Smoking Cessation Program

한국심리학회지: 건강 / The Korean Journal of Health Psychology, (P)1229-070X; (E)2713-9581
2004, v.9 no.4, pp.903-922
서경헌 (삼육대학교)
유제민 (강남대학교)

초록

본 연구에서는 데이터 마이닝을 이용하여 인구통계학적 변인, 신체․생리적 변인, 흡연행동 변인, 및 심리적 변인들로 2년 동안의 금연 유지 요인을 탐색하려고 하였다. 본 연구의 대상자는 입원 금연 프로그램에 참여한 73명이었는데, 이들의 평균 연령은 44.89(SD=9.61)세 이었으며, 남성이 65명이고 여성이 8명이었다. Fagerstrom의 니코틴 의존도 검사, 아이젱크 성격검사, 다차원적 대처 척도, 및 Jerusalem과 Schwarzer의 자기효능감 척도로 얻은 정보와 다양한 의학적 검사의 측정치가 분석에 포함되었다. 43가지 변인들을 동시에 투입하여 금연 지속기간을 예측하는 의사결정 나무분석을 실시하였다. 분석 결과, 적극적 대처, 신경증적 경향성, 정신병적 경향성자기비판, 사회적 지원 추구, 고밀도 콜레스테롤(HLD), 및 혈당 수준이 2년 동안의 장기적 금연 유지를 예측하는 가장 영향력 있는 요인으로 나타났다. 2년 동안 추적한 결과, 적극적으로 대처하고 신경증적 경향성과 정신병적 경향성이 낮은 사람들은 평균 646.25일 동안 금연을 유지한 반면에, 적극적으로 대처하지 않고 고밀도 콜레스테롤 수치가 낮으면서 사회적 지원을 추구하지 않는 사람들은 평균 17.83일 동안만 금연을 유지했다. 본 연구를 통해 금연의 장기적 유지에 생물․심리․사회적 변인이 어떤 역할을 하는지 확인할 수 있었다.

keywords
smoking cessation, hospitalized smoking cessation program, data mining, biopsychosocial variables, smoking cessation, hospitalized smoking cessation program, data mining, biopsychosocial variables, 금연, 입원 금연 프로그램, 데이터 마이닝, 생물·심리·사회적 변인

Abstract

This study aims to investigate predictors of long-term (2 years) abstention from smoking with demographic profiles, physical and physiological variables, smoking behaviors, and psychological variables. Participants were 73 smokers (65 males, 8 females) participated in a hospitalized smoking cessation program whose mean age was 44.89 (SD=9.61). Participants completed questionnaires and psychological tests including: Fagerstrom Test for Nicotine Dependence, Eysenck Personality Inventory, Multidimensional Coping Scale, and Jerusalem and Schwarzer's Self-Efficacy Scale. And data from variety of clinical measurements were included for analysis. To identify participants abstention, researchers followed them for 2 years. Data Mining Decision Tree was performed with 43 variables by Answer Tree 3.0v. Decision Tree model included significant variables for abstention as predictors, such as active coping, neuroticism, psychoticism, self-criticism, High Density Lipoprotein (HLD), seeking social support, level of glucose. Decision Tree model showed that those who coped actively, were less neurotic and psychotic, had abstained for average of 646.25 days/2 years, while those who coped unactively, had low level of HDL, were unlikely to sought social support, had abstained only for average of 17.83 days/2 years. These results suggest roles of biopsychosocial variables for long-term successful smoking cessation.

keywords
smoking cessation, hospitalized smoking cessation program, data mining, biopsychosocial variables, smoking cessation, hospitalized smoking cessation program, data mining, biopsychosocial variables, 금연, 입원 금연 프로그램, 데이터 마이닝, 생물·심리·사회적 변인

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한국심리학회지: 건강