A LONGITUDINAL ANALYSIS OF PREDICTORS OF QUITTING SMOKING AMONG PARTICIPANTS IN A SELF-HELP INTERVENTION TRIAL

Predictors of 7-day abstinence from smoking were identified among part icipants in a randomized self-help smoking-cessation intervention tria l conducted from 1985 to 1988 in Seattle, WA. Subjects were adult smok ers belonging to a health maintenance organization who responded to an offer of free quitting assistance. Self-reported smoking status was a ssessed at 8, 16, and 24 months following enrollment. Predictors of ab stinence were identified by longitudinal data analysis using Generaliz ed Estimating Equations (GEEs), a modeling approach which handles repe ated-measures data and accommodates time-dependent as well as time-ind ependent covariates. Seventeen items emerged as significant (p < .05) predictors, with odds ratios ranging from 1.3 to 2.1. While much of th e previous work in smoking-cessation research has focused on demograph ic and smoking history variables, results of this study indicate that emphasis should also be placed on psychosocial/motivational factors an d quitting activities as important predictors of abstinence. Longitudi nal data analysis represents a powerful technique for handling correla ted (repeated measures) data, which may prove very useful for future s tudies of smoking cessation as well as other dynamic processes.