Optimal TTM Tailoring for Population Cessation (STAR)

• Smoking cessation (quit) rate [ Time Frame: 24 months ] [ Designated as safety issue: No ]
  Self-report point prevalence abstinence
  
  

Smoking remains one of the biggest causes of premature morbidity and mortality. Nicotine addiction continues to challenge researchers to optimize their best interventions, and these challenges increase with efforts to integrate smoking cessation into multiple behavior change research and dissemination. Tailored intervention strategies have demonstrated effectiveness, yet much research remains to be done exploring optimal tailoring strategies. Transtheoretical model (TTM) tailored feedback on all 14 variables has been demonstrated to be a robust population cessation strategy across studies, producing 22-25% quit rates at 18-24 month final timepoints. This proposal seeks to find a subset of these variables that is optimal for tailoring, both minimizing response burden while maximizing effectiveness. Addiction variables have been demonstrated to predict smoking outcomes across studies as well, so we will integrate tailored feedback using TTM and addiction variables into an enhanced tailoring group. Enhanced addiction tailored feedback that both helps unmotivated smokers reduce their addiction and helps motivated smokers quit could lead to a breakthrough in population cessation. This proposal tests four types of TTM-tailoring for smoking cessation in an additive design: no treatment control group; Minimal tailoring (stage only); Moderate tailoring (stage, pros, cons, efficacy); Full TTM tailoring (all 14 TTM variables); and Enhanced TTM tailoring plus addiction variables. Smokers will be randomized to one of five treatment groups and evaluated at baseline, 6 months, 12 months, and 24 months. Treatment groups will receive tailored feedback at baseline, 6 months, and 12 months. Analyses will compare treatment groups on quit rates at the final timepoint to see how effectively each treatment helps smokers to quit. A series of mediation and moderation analyses will examine how each treatment works. This study has the potential to find an optimal tailoring strategy for population cessation that could accelerate future multiple behavior change research and dissemination efforts.