A longitudinal analysis of predictors of quitting smoking among participants in a self-help intervention trial

Addict Behav. Mar-Apr 1994;19(2):159-73. doi: 10.1016/0306-4603(94)90040-x.

Abstract

Predictors of 7-day abstinence from smoking were identified among participants in a randomized self-help smoking-cessation intervention trial conducted from 1985 to 1988 in Seattle, WA. Subjects were adult smokers belonging to a health maintenance organization who responded to an offer of free quitting assistance. Self-reported smoking status was assessed at 8, 16, and 24 months following enrollment. Predictors of abstinence were identified by longitudinal data analysis using Generalized Estimating Equations (GEEs), a modeling approach which handles repeated-measures data and accommodates time-dependent as well as time-independent covariates. Seventeen items emerged as significant (p < .05) predictors, with odds ratios ranging from 1.3 to 2.1. While much of the previous work in smoking-cessation research has focused on demographic and smoking history variables, results of this study indicate that emphasis should also be placed on psychosocial/motivational factors and quitting activities as important predictors of abstinence. Longitudinal data analysis represents a powerful technique for handling correlated (repeated measures) data, which may prove very useful for future studies of smoking cessation as well as other dynamic processes.

Publication types

  • Clinical Trial
  • Randomized Controlled Trial
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Confounding Factors, Epidemiologic
  • Female
  • Health Status
  • Humans
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Models, Statistical
  • Multivariate Analysis
  • Prevalence
  • Risk Factors
  • Self Care / psychology
  • Smoking Cessation / psychology*
  • Smoking Cessation / statistics & numerical data
  • Time Factors