Introduction: Advancing the understanding of smoking cessation requires a complex and nuanced understanding of behavior change. To this end, ecological momentary assessments (EMA) are now being collected extensively. The time-varying effect model (TVEM) is a statistical technique ideally suited to model processes that unfold as behavior and nicotine dependence change. Coefficients are expressed dynamically over time and are represented as smooth functions of time. Methods: The TVEM approach is demonstrated using data from a smoking-cessation trial. Time-varying effects of baseline nicotine dependence (a time-invariant covariate) and negative affect (a time-varying covariate) on urge to smoke during a quit attempt were estimated for monotherapy, combination therapy, and placebo groups. SAS syntax for conducting TVEM is provided so that readers can adapt it for their research. Results: During the first 2 days after quitting, the association between negative affect and craving was significantly stronger among individuals in the placebo group, suggesting an early positive impact of treatment. For the monotherapy and combination therapy groups, during the second week of the quit attempt, baseline dependence was less strongly related to craving compared with the placebo group, indicating a different positive impact of treatments later in the quit attempt. Conclusions: The results reveal information about the underlying dynamics that unfold during a quit attempt and how monotherapy and combination therapy impact those processes. This suggests possible mechanisms to target in an intervention and indicates timepoints that hold the greatest promise for effective treatment. TVEM is a straightforward approach to examining time-varying processes embedded in EMA.
All Science Journal Classification (ASJC) codes
- Public Health, Environmental and Occupational Health