Descriptive statistics were presented as mean and standard deviation, or frequency and percentage, for continuous and categorical data, respectively. Testing of variables for normality was examined using visual (histogram and probability graphs) and analytical methods (Kolmogrov-Simirnov/Shapiro-Wilk tests). The demographic and clinical characteristics of the individuals, who currently smoked or quit at the time of the phone calls, were compared. The comparisons between independent study groups were made using the Mann-Whitney U and chi-squared tests, respectively. Univariate comparisons were used to determine the demographic and clinical variables, which are the candidates for multivariate analyses to identify the independent predictors of long-term abstinence. A p≤0.20 was considered the threshold in the univariate comparisons for the relevant parameter to be included in the multivariate analyses. The multivariate analyses were conducted using logistic regression analysis, and the model fit was evaluated using the Hosmer-Lemeshow test. A p<0.05 was considered to be statistically significant in univariate and multivariate analyses, which were conducted using PASW 18 (IBM Inc., Armonk, NY) software.

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