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

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


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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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The Korean Journal of Health Psychology