Development of a Risk Score to Predict Short-term Smoking Relapse Following an Inpatient Smoking Cessation Intervention

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This study aimed to investigate the factors affecting smoking relapse and to develop predictive models among Korean national 5-day smoking cessation program participants. The subjects were 518 smokers and follow-up was continued for 6 months after discharge. A predictive logistic model and risk score were developed from the multivariate logistic models and compared using the area under the receiver operating characteristic curve (area under the curve [AUC]). The smoking relapse rate within 6 months after program participation was 38.4%. The AUCs of the logistic regression model and risk score model were similar (odds ratio [OR] = 0.69, 95% confidence interval [CI] [0.64, 0.75]; 0.69, 95% CI [0.63, 0.74], respectively) in the development data set, and those of the risk score model were similar between the development and validation data sets (OR = 0.68, 95% CI [0.59, 0.77]). The risk score used by the six risk factors could predict smoking relapse among participants who attended a 5-day inpatient smoking cessation program.

키워드

smoking cessationrisk factorspredictionCLINICAL-USE
제목
Development of a Risk Score to Predict Short-term Smoking Relapse Following an Inpatient Smoking Cessation Intervention
저자
Shin, Hwang SikPark, Yoon HyungLee, Sung SooCho, Yong JinKwon, Jun TackChang, YoungsLee, Mee-RiHwangbo, Young
DOI
10.1177/10105395241240949
발행일
2024-05
유형
Article
저널명
Asia-Pacific Journal of Public Health
36
4
페이지
329 ~ 336