Understanding quit patterns from a randomized clinical trial: Latent classes, predictors, and long-term abstinence

Publication date: Available online 21 February 2019

Source: Addictive Behaviors

Author(s): Lorra Garey, Kara Manning, Danielle E. McCarthy, Matthew W. Gallagher, Justin M. Shepherd, Michael F. Orr, Norman B. Schmidt, Blaz Rodic, Michael J. Zvolensky

Abstract

Objective

Tobacco dependence treatment is recognized as a dynamic, chronic process comprised of several specific phases. Of these phases, the Cessation phase is the most critical as it has demonstrated the strongest relation to quit success. Yet, little is understood about smoking trajectories during this period. The current study aimed to address gaps in the smoking research literature and advance understanding of the dynamic quit process unique to completing an integrated smoking treatment by evaluating quit behavior during the Cessation phase.

Method

Two hundred and sixty-seven treatment seeking smokers enrolled in a clinical trial to evaluate the efficacy of a novel, integrated smoking cessation treatment (46.1% male; M_age = 39.25, SD = 13.70) were included in the present study. Repeated-measure latent class analysis was employed to evaluate quit patterns from quit day through day 14 post-quit.

Results

Results supported a four-class solution: Consistent Quitters, Non-Quitters, Relapsers, and Delayed Quitters. Predictors of class membership included age, number of prior quit attempts, motivation to quit smoking, and quit day smoking urges. Moreover, class membership was significantly associated with 6-month abstinence.

Conclusion

Results suggest that there are four relevant classes of quit behavior, each with specific predictor variables including age, motivation to quit, smoking urges, and number of quit attempts, and that these classes relate to long-term abstinence. These results have the potential to inform manualized smoking cessation treatment interventions based on relevant subgroups of quit behavior.

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