Smoking is the leading preventable cause of death and disease in the United States. Although multiple clinic and phone based smoking cessation treatments have been proven effective, most smoking cessation attempts are unaided and unsuccessful. Furthermore, smoking prevalence in socioeconomically disadvantaged adults is higher and cessation rates are lower than among adults with higher socioeconomic status. Previous research has indicated multiple causes of high cessation failure among socioeconomically disadvantaged smokers including greater exposure to other smokers, and higher levels of stress and nicotine cravings. One recent study found that smartphone based ecological momentary assessments (EMAs) can be used to identify moments of high smoking lapse risk in the hours preceding a lapse. Specifically, EMA data were used to create a six-item smoking lapse risk estimator that identified 80% of all smoking lapses within 4 hours of the first lapse. This lapse risk estimator was included as a key component of the smartphone based Smart Treatment (Smart-T) smoking cessation app. The Smart-T app assesses risk for smoking lapse multiple times per day and automatically tailors treatment content based upon an individual's current risk for lapse and currently experienced lapse triggers. Smart-T includes other components (e.g., on demand tips for coping with cravings, stress, mood; benefits of quitting; one click call to the smoking cessation helpline; smoking cessation medication tips). The single arm Smart-T pilot study (N=59) indicated very promising 3 month biochemically verified cessation rates and analyses of EMA data indicated that tailored treatment content attenuated targeted lapse triggers. The proposed study (N=450) will compare the longer-term effects of the Smart-T smoking cessation app with the free and publically available NCI QuitGuide smoking cessation app (Aim 1). It is hypothesized that significantly more participants randomized to the Smart-T condition will be abstinent 26 weeks after a scheduled quit date than those assigned to the QuitGuide app.
The second aim of the proposed study will determine if Smart-T messages that are tailored to address key smoking lapse risk variables in real- time (i.e., urge, stress, cigarette availability, cessation motivation) reduce participant ratings of these lapse risk variables compared with similar situations that do not receive this tailored content (QuitGuide group). Automated, tailored, low burden, and easily accessible interventions may be used to help socioeconomically disadvantaged smokers, a population with substantial barriers that have hampered the use of traditional smoking cessation treatments, to quit smoking. Thus, this intervention has the potential to deliver a significant public health impact to exactly those who need it most.
Socioeconomically disadvantaged adults are more likely to smoke and less likely to successfully quit smoking than those of higher socioeconomic status, even when validated smoking cessation treatments are used. The proposed study will determine whether an automated smoking cessation application that tailors treatment content to the needs of socioeconomically disadvantaged smokers in real-time can reduce lapse risk and increase successful smoking cessation. By addressing lapse triggers as they arise, this type of dynamic, low burden, and always available smoking cessation app may reduce smoking lapse and thereby reduce morbidity and mortality in socioeconomically disadvantaged smokers.
