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Reinforcer pathology predicts relapse in smokers
Ángel García-Pérez1, Gema Aonso-Diego1, Sara Weidberg1
1Department of Psychology.
Summary
Higher delay discounting and cigarette demand intensity predict smoking relapse in individuals undergoing cessation treatment. Adapting strategies for these factors may reduce relapse risk.
Area of Science:
- Behavioral psychology
- Addiction science
- Public health
Background:
- Smoking cessation treatments aim to help individuals quit, but relapse remains a significant challenge.
- The reinforcer pathology model proposes that delay discounting and demand intensity influence substance use and relapse.
- Understanding predictors of relapse is crucial for developing effective interventions.
Purpose of the Study:
- To investigate if delay discounting and demand intensity predict smoking relapse up to 12 months post-treatment.
- To analyze the association between these two factors and the time to relapse in abstinent smokers.
Main Methods:
- Secondary analysis of data from 202 abstinent smokers who received smoking cessation treatment.
- Participants completed delay discounting and cigarette purchase tasks.
- Kaplan-Meier curves, log-rank tests, and Cox regression analyses were used to assess relapse predictors.
Main Results:
- Fewer years of smoking, higher delay discounting, and higher intensity of demand were associated with increased likelihood and faster relapse.
- Specifically, higher delay discounting (HR AUClog = .80, p = .019) and demand intensity (HR = 1.26, p = .019) predicted relapse.
Conclusions:
- Elevated delay discounting and demand intensity are significant predictors of smoking relapse after cessation treatment.
- These findings underscore the need to tailor smoking cessation strategies to address individual differences in delay discounting and cigarette demand.
- Targeting these factors may enhance treatment efficacy and reduce relapse rates.
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