Predictors
teasing
REGRESSION
Exploratory post hoc analyses using logistic regression identified age, education, and DTQ as baseline variables associated with smoking cessation outcomes. Considering the exploratory nature of these analyses, the relatively small number of participants in the different baseline categories, and that none of these baseline variables had statistically significant correlations for all 5 smoking cessation outcomes, caution should be used in the interpretation of these data. Accordingly, we have limited our interpretations to a qualitative assessment. However, a review of the literature also reveals previous identification of these variables as associated with smoking cessation.Several studies have reported that older age is associated with smoking cessation [The finding that a lower educational level (no college experience) was associated with a higher likelihood of biochemically confirmed abstinence has also been reported elsewhere [Finally, a higher DTQ at study entry was associated with a lower likelihood of self-reported 30-day PPA in the Pivot group and a higher likelihood in the QuitGuide group. Approaching the DTQ metric used in this study as a general proxy for self-efficacy, the literature predominantly supports the association between higher self-efficacy and a greater likelihood of cessation and between lower self-efficacy and a lower likelihood of cessation and a greater likelihood of relapse [Overall, the data related to predictors of cessation are nuanced and likely heavily influenced by the presence, type, and use of a cessation program and by the cessation program characteristics. For example, some populations may respond better to specific program tools or delivery mechanisms than others. The value of these analyses is that they highlight variables of interest for future study designs and assist in teasing out optimal pairings between populations and cessation approaches.