One-year smoking trajectories among established adult smokers with low baseline motivation to quit

Introduction: The majority of smokers do not intend to quit in the near term, making unmotivated smokers a key group to target in public health efforts. Although it is often assumed that continuing smokers will have stable rates of smoking over time, limited research has addressed this issue, particularly among smokers not seeking treatment. In the current study, the aims were to (1) characterize the trajectory of naturalistic smoking among unmotivated smokers and (2) examine relationships between naturalistic smoking trajectories and other smoking-related variables. Methods: The study sample comprised 579 control-group (ie, untreated) smokers within a parent clinical trial, who completed a total of nine assessments over 1 year. Results: Trajectory modeling identified four smoking trajectory groups: stable (72%), shallow decreasers (20%), steep decreasers (5%), and increasers (3%). Membership in the decreasing groups was associated with higher motivation to quit, greater history of quit attempts, and higher cigarettes per day. Females were more likely to be in the increasing versus stable group. Conclusions: Findings provide needed information on stability and change in cigarette consumption over the course of 1 year among an untreated sample of smokers and identified baseline sociodemographic and smoking-related predictors of smoking trajectory group. Refining understanding of these groups is critical in updating population-based tobacco policy modeling efforts and informing cessation induction efforts that capitalize on naturalistic changes in smoking rate over time. Implications: In the current study, we found that approximately 25% of smokers who endorsed low quit motivation at baseline reduced their cigarette consumption over the course of a year, while 3% increased their cigarette consumption and the majority of smokers (72%) maintained a stable pattern. Refining understanding of smoking trajectories is critical in updating population-based tobacco policy modeling efforts and informing cessation induction efforts that capitalize on naturalistic changes in smoking rate over time.