Optimizing Warnings on E-Cigarette Advertisements

Abstract

Introduction: We examined the effect of visual optimizations on warning text recall. Methods: We used Amazon's Mechanical Turk to recruit 1854 young adult (18-34 years) electronic cigarette (e-cigarette) users or susceptible nonusers. We conducted a between-subjects 3 × 2 × 2 experiment to examine the influence of color (black text on white background [BW] vs. black on yellow [BY] vs. yellow on black [YB]), shape (rectangle vs. novel), and signal word (presence vs. absence of the word "warning"). We randomized participants to view one of 12 warnings on a fictional e-cigarette advertisement. We coded open-ended recall responses into three categories: (1) recalled nothing, (2) recalled something, (3) recalled the concept. We examined main effects on warning text recall using multinomial regression. We examined differences in attention, perceived message effectiveness, and appeal. Results: Those exposed to BW or BY warnings were more likely than those exposed to YB to recall something (AOR = 1.6, AOR = 1.5, respectively) or the concept (OR = 1.4, BW). Those exposed to novel shape (44.7% novel vs. 37.9% rectangle; p =. 003) or color (44.5% BY vs. 41.9% YB vs. 37.5% BW; p =. 04) warnings were more likely to report attention to the warning. In aided recall, those exposed to the signal word were more likely than those not exposed to select the correct response (64.0% vs. 31.3%; p