ObjectivesGuidelines recommend that smokers participate in four or more counseling sessions when trying to quit, but smokers rarely engage in multiple sessions. The “decoy effect” is a cognitive bias that can cause consumer preferences for a “target” product to change when presented with a similar but inferior product (a “decoy”). This study tested the use of a decoy to guide smokers’ selection of a target number of counseling sessions. During an online survey, adult tobacco users (N = 93) were randomized to one of two groups that determined the answer choices they saw in response to a question assessing their interest in multi-session cessation counseling. Group A choose between two sessions or a “target” of five sessions. Group B was given a third “decoy” option of seven sessions. Binary logistic regression was used to compare groups on the proportion of participants selecting the “target.”ResultsAmong 90 participants with complete data, a decoy effect was not found. There was no significant difference between groups in the proportion of participants selecting the target of five sessions (47% in Group B vs. 53% in Group A; aOR = 0.76, 95%CI 0.48–1.19).Trial Registration This study was retrospectively registered at clinicaltrials.gov on December 13, 2019 (NCT04200157)

Smoking consequences are seen disproportionately among low-SES smokers. We examine the self-regulatory strategy of mental contrasting with implementation intentions (MCII) as a smoking reduction tool and whether its effectiveness depends on subjective-SES. This pre-registered online experiment comprised a pre-screening, baseline survey, and follow-up. Participants reported past-week smoking, subjective-SES, perceived stress, and were randomized to an active control (n = 161) or MCII condition (n = 164). Data were collected via MTurk, during the U.S.’ initial wave of COVID-19. Participants were moderate-to-heavy smokers open to reducing or quitting. The primary outcome was self-reported smoking reduction, computed as the difference between recent smoking at baseline and follow-up. The secondary outcome was cessation, operationalized as self-reported 7-day point-prevalence abstinence at follow-up. Among those low—but not high—in subjective-SES, MCII (vs. control) improved smoking reduction by an average of 1.09 fewer cigarettes smoked per day, though this effect was not conclusive (p = 0.11). Similarly, quitting was descriptively more likely for those in the MCII than control condition, but the effect was non-significant (p = 0.11). Per an exploratory analysis, we observed that stress significantly moderated the condition effect (p = 0.01), such that MCII (vs. control) facilitated reduction among those experiencing high (p = 0.03), but not low stress (p = 0.15). Consistent with prior findings that MCII works best in vulnerable populations, MCII may be more effective for smoking reduction among high-stress than low-stress individuals. These findings contribute to growing research on income-related health disparities and smoking behavior change tools.