Predictors of smoking reduction and cessation in young adults

Objectives. This study identified predictors that were significantly associated with smoking cessation and with the reduction in the number of cigarettes smoked by young adults.

Methods. Multiple regression and logistic regression models were calculated to predict changes in cigarette smoking behaviors at three months and six months following a smoking cessation intervention.

Results. The multiple regression model predicting the reduction of smoking was significant at three months (R-square=0.22, F(7,62)=2.57, p=0.02), though, it was not significant at six months (R-square=0.16, F(7,48)=1.32, p=0.26). Outcome expectations (t(62)=-2.04, p=0.05) and the number of past quit attempts (t(62)=-2.19, p=0.03) were significant predictors of the reduction in the number of cigarettes smoked at three months while controlling for the other predictors. Logistic regression models predicting the odds of quitting smoking were significant at three months (likelihood ratio chi-square(8)=19.38, p=0.01) and six months (likelihood ratio chi-square(8)=22.72, p=0.00). At six months self-efficacy (chi-square(1)=4.94, p=0.03), the number of past quit attempts (chi-square(1)=6.32, p=0.01), and the number of cigarettes smoked (chi-square(1)=4.75, p=0.03) were significant predictors of the odds of quitting smoking while controlling for the other predictors.

Conclusions. Young adult smokers who had made more prior quit attempts and had outcome expectations consistent with a greater readiness to change were more likely to reduce the number of cigarettes smoked at three months. Additionally, smokers who were more likely to quit at six months smoked fewer cigarettes, were more confident they could abstain from smoking and had made more prior attempts to quit.