Aims: Nicotine dependence is characterised by hypervaluation of tobacco and hypovaluation of tobacco-free alternative rewards. However, a substantial number of people successfully give up tobacco smoking. This is the first study to apply a computational model of value-based decision-making (VBDM) to account for recovery from nicotine addiction.
Methods: Pre-registered, cross-sectional design. 51 current smokers and 51 ex-smokers were recruited. Participants completed a two-alternative forced choice task in which they chose between either two valenced smoking-related images (in one block) or two valenced animal (control) images (in a different block). On each block, participants pressed a key to select the image that they previously rated most positively. We applied a drift-diffusion model (DDM) to the reaction time and accuracy data to estimate evidence accumulation (EA) processes and response thresholds during the different blocks.
Results: There were no significant differences in EA rates for smoking stimuli or animal stimuli in current smokers compared to ex-smokers. However, ex-smokers had significantly higher response thresholds compared to current smokers when they were making smoking-related choices (p = .01, d = .45), although there were no group differences in responses thresholds when they were making choices between animal pictures.
Conclusions: Recovery from nicotine addiction was characterised by increased cautiousness when making value-based decisions about smoking images. However, contrary to hypotheses, EA rates during value-based decision-making did not differ between current and former smokers.