Cigarette smoking is the leading cause of preventable death in the United States, accounting for one out of every five deaths (CDC, 2012). In particular, smoking prevalence rates are high among socioeconomically-disadvantaged women; for example, over 40% of women with less than 12 yrs education smoke, compared to 28% and 16% among those with some college and undergraduate degrees (SAMHSA, 2010). Smoking cessation rates are particularly low among low-SES women with co-occurring alcohol use disorders, and these substances are frequently used together (Kahler et al., 2010; Businelle et al., 2013). Therefore, interventions that reduce both alcohol and smoking among heavy alcohol-using women are vitally needed to reduce rates of smoking-related morbidity and mortality in this vulnerable population.
Counseling approaches that incorporate problem solving, skills training and social support are effective for reducing smoking in the general population (Fiore et al., 2008). However, given the high rates of smoking among alcohol-using women, they may be inadequate for in this population. Contingency management (CM) interventions, which provide tangible reinforcers contingent upon smoking abstinence or reduction to a criterion level, are highly-efficacious interventions for reducing cigarette smoking and other drug use in low-SES women (Higgins et al., 2012). Within the theoretical framework of operant conditioning, increasing the availability of an alternative reinforcer weakens the amount of control that the drug has over the user’s behavior, especially when obtaining the alternative reinforcer is contingent on behaviors incompatible with drug use (Higgins, 1997). The tenets of CM interventions include (1) arranging the environment such that the target behavior can be readily and objectively detected, (2) providing a tangible reinforcer when the target behavior occurs, and (3) withholding reinforcement when the target behavior does not occur (Higgins et al., 1994).
Although CM interventions clearly are effective at promoting smoking reductions, there are several challenges associated with translating CM into an effective clinical treatment for smoking. Perhaps the most significant challenge is the frequent monitoring necessary to objectively verify smoking abstinence using breath carbon monoxide (CO), the most convenient objective measure of smoking status. Because of the short half-life of CO (5-6 hours), CO levels must be measured at least twice per day in order to verify continuous abstinence. Recent CM-smoking studies have addressed this feasibility challenge by providing study participants with breath CO monitors and laptop computers or smartphones to use in their own natural environments (e.g., Dallery, Raiff & Grabinski, 2013). Participants are taught how to use their smartphones to text videos of themselves providing a breath CO level to a research staff member, twice per day. After the study staff has determined that the breath CO sample meets the abstinence criterion, participants are informed of the amount that they have earned for that sample.
Given the high rates of smoking in low-SES women, investigating the additive impact of an in-person brief counseling intervention and a phone-based CM intervention is an important next step in examining effective methods to reduce the impact of smoking in this population.