There is abundant evidence that smokers experience abstinence-induced deficits in cognitive function (Jacobsen et al., 2005
; Mendrek et al., 2006
; Myers et al., 2008
). Data from the current study extend this work by demonstrating, for the first time in healthy treatment-seeking smokers, that these abstinence-induced cognitive deficits predict short-term smoking resumption. Specifically, among participants receiving placebo (i.e., abstinent, no medication), slower reaction time on the most difficult trials of a working memory task (i.e., the 3-back task) predicted faster smoking resumption during a 7-day simulated quit attempt. Importantly, our model controlled for baseline, “smoking as usual” reaction time, which bolsters our interpretation that the observed deficits are likely to be abstinence-induced.
These data are consistent with prior studies of smokers with comorbid psychiatric illness. For example, among smokers with schizophrenia, slower reaction time at baseline reduced the odds of continuous abstinence 4 weeks after quitting (Culhane et al., 2008
). In formerly depressed smokers, slower reaction time predicted increased risk of relapse at 12-month follow-up (Kassel et al., 2007
). Our data extend these findings by showing that subtle differences in reaction time after 3 days of abstinence predict fewer days to smoking resumption in a non-psychiatric population of smokers.
While further research is needed, emerging support for the role of cognitive function in smoking relapse has implications for treatment development. Consistent with prior evidence for reversal of withdrawal-related cognitive deficits in animals and human smokers treated with varenicline (Patterson et al., 2009
; Raybuck et al., 2008
), abstainers and relapsers receiving varenicline in the current trial had comparable reaction times. Thus, part of varenicline's efficacy for smoking cessation may be attributable to its effects on cognitive performance during abstinence (Patterson et al., 2009
). Further evidence suggests that some smokers may be more susceptible to cognitive deficits and altered brain function in abstinence, such as those carrying the val allele of the catechol-0-methyltransferase (COMT Val158
Met) gene (Loughead et al., 2008
). Interestingly, deficits in this prior study were most pronounced during the 3-back task, consistent with the current evidence that 3-back performance is the best predictor of smoking relapse. Taken together, these data support the premise that the development of treatments, both behavioral and pharmacologic, to enhance post-abstinence cognitive performance could be a viable strategy to improve cessation outcomes. Results from this line of research could potentially support the use of cognitive performance tasks as an early screening tool for treatment efficacy and to characterize individual differences in relapse risk.
While this is the first study of cognitive deficits and relapse in healthy treatment-seeking smokers, there are some limitations. The sample size of each group, while large for a human laboratory study, is relatively small for assessing predictors of smoking resumption. Second, this study assessed days to smoking resumption over a brief 7-day period in a simulated quit attempt, and the relationship between cognitive performance and days to relapse during a clinical trial may be different. Third, the definition of abstinence used in this study (CO ≤10ppm), although appropriate for a smoking cessation trial, may also be considered too liberal for a human laboratory of smoking lapses. Finally, only two cognitive tasks were included in this study. Larger studies that include a broader range of cognitive tasks and assess abstinence in a clinical trial would be an important next step to elucidate the role of cognitive deficits in smoking relapse and treatment response.