Smoking is the leading preventable cause of death and disease in the U.S. Each year approximately 30% of smokers try to quit, with the vast majority of attempts (~90%) ending in relapse. This is complicated by treatment barriers related to cost and accessibility. Identifying cost effective ways to aide in cessation success, which can be widely disseminated, remains vitally important. According to the dual-process model of substance use, addiction develops via an imbalance between effortful control and automatic psychological processes. The affective processing model suggests that during withdrawal, automatic psychological processes increase implicit drug seeking motivation. Implicit motivation is hypothesized as the underlying mechanism through which automatic psychological processes exert control over behavior. Research suggests that behavioral impulse control may attenuate the association between implicit motivation and substance use. Response inhibition, one form of behavioral impulse control, is the ability to inhibit behavioral responses to salient approach cues. Smokers tend to have less behavioral impulse control. In addition, poor behavioral impulse control makes individuals more vulnerable to various risk factors associated with relapse (e.g., positive expectancies, higher craving during abstinence, etc.). Improving smoking relevant behavioral impulse control may affect multiple indices of relapse. Research in cognitive retraining has shown that response inhibition can be modified through training. Recently this has been extended to training using mobile devices. The development of mobile interventions which specifically target underlying mechanisms of addiction may provide a novel adjunct to current cessation programs. The current proposal builds on previous research by implementing a response inhibition training paradigm in the context of a cessation trial. It is hypothesized that this task will reduce the likelihood of relapse following a quit attempt. Furthermore, it is hypothesized that training effects will operate via decreases in implicit motivation and global craving. If successful, the current study will provide evidence for a relapse prevention tool that can (1) increase overall cessation success and (2) be widely and easily dispersed.
This project seeks to decrease the likelihood of relapse during a quit attempt by modifying smoking specific behavioral response inhibition using mobile technology. If successful this project will provide evidence for a scientifically supported cessation application that can be downloaded to mobile devices (e.g., smartphones) through mobile marketplaces. The ability to widely disseminate a scientifically valid application that increases the likely of cessation success could have significant public health implications.