Using treatment process data to predict maintained smoking abstinence

Am J Health Behav. 2010 Nov-Dec;34(6):801-10. doi: 10.5993/ajhb.34.6.14.

Abstract

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.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Cognitive Behavioral Therapy / methods
  • Female
  • Humans
  • Male
  • Middle Aged
  • Models, Psychological
  • Outcome and Process Assessment, Health Care / methods*
  • Randomized Controlled Trials as Topic
  • Secondary Prevention
  • Signal Detection, Psychological
  • Smoking Cessation / methods*
  • Tobacco Use Disorder / classification
  • Tobacco Use Disorder / prevention & control*
  • Tobacco Use Disorder / therapy*