Recovery from nicotine addiction: A diffusion model decomposition of value-based decision-making in current smokers and ex-smokers

Abstract

Introduction: A considerable number of people successfully give up tobacco smoking. Tobacco choice in nicotine dependent individuals is determined by greater expected drug value; however, less is known about the underlying mechanisms through which people quit smoking. The aim of this study is to explore whether computational parameters of value-based decision-making characterise recovery from nicotine addiction. Methods: This study was pre-registered. Using a between-subject design, current daily smokers (n = 51) and ex-smokers who used to smoke daily (n = 51) were recruited from the local community. Participants completed a two-alternative forced choice task in which they chose between either two tobacco-related images (in one block) or tobacco-unrelated images (in a different block). On each block, participants pressed a key to select the image that they had rated most positively during a previous task block. A drift-diffusion model was fitted to the reaction time and error data to estimate evidence accumulation (EA) processes and response thresholds during the different blocks. Results: Compared to current smokers, ex-smokers had significantly higher response thresholds when making tobacco-related decisions (p = .01, d = .45), although there were no significant group differences during tobacco-unrelated decisions. Furthermore, there were no significant group differences in EA rates when making tobacco or tobacco-unrelated decisions. Conclusions: Recovery from nicotine addiction is characterised by greater cautiousness when making value-based decisions about tobacco-related cues.