Using treatment process data to predict maintained smoking abstinence

Objectives: To identify distinct subgroups of treatment responders and nonresponders to aid in the development of tailored smoking- cessation interventions for long-term maintenance using signal detection analysis (SDA). Methods: The secondary analyses (n = 301) are based on data obtained in our randomized clinical trial designed to assess the efficacy of extended cognitive behavior therapy for cigarette smoking cessation. Model 1 included only pretreatment factors, demographic characteristics, and treatment assignment. Model 2 included all Model 1 variables, as well as clinical data measured during treatment. Results: SDA was successfully able to identify smokers with varying probabilities of maintaining abstinence from end-of-treatment to 52-week follow-up; however, the inclusion of clinical data obtained over the course of treatment in Model 2 yielded very different partitioning parameters. Conclusions: The findings from this study may enable researchers to target underlying factors that may interact to promote maintenance of long-term smoking behavior change.