Data analysis will be performed using the Statistical Package for Social Science. In particular, we will use inferential statistics (independent-samples t-test and χ2 test) to examine the homogeneity between the QI and CDTQ groups. We will conduct logistic regression analyses to calculate the odds ratio (OR) and 95% confidence interval (CI) for smoking outcomes, i.e. self-reported and biochemical validated quit rates, self-reported smoking reduction rates and number of quit attempts. We will apply mixed between-within subjects analysis of variance (ANOVA) to determine whether CDTQ is more effective than QI in enhancing self-efficacy (perceived importance, difficulty and confidence) for quitting smoking. We shall adopt the principle of intention to treat. Subjects who are lost to follow-up, refuse to participate in biochemical validations, or withdraw from the study are considered unable to quit or reduce smoking. Depending on the amount and distribution of missing data, other methods, e.g. sensitivity analysis and multiple imputation technique will be used if necessary.