Evidence map›Paper›PMID 31132095›Full record

Trial reportNicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco2020

Optimizing Warnings on E-Cigarette Advertisements.

Jessica L King, Allison Lazard, Beth A Reboussin, Leah Ranney, Jennifer Cornacchione Ross, Kimberly G Wagoner, Erin L Sutfin

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jessica L KingDepartment of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC.
Allison LazardSchool of Media and Journalism, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Beth A ReboussinDepartment of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC.
Leah RanneyLineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC.
Jennifer Cornacchione RossDepartment of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC.
Kimberly G WagonerDepartment of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC.
Erin L SutfinDepartment of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC.

Funding

Training & Education Program p294-308P50CA180907 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RIBISL, KURT M. · 2013 to 2017
$20.2M
NCI NIH HHS P50 CA180907
6 · The paper itself

Abstract

introductionWe examined the effect of visual optimizations on warning text recall.

methodsWe 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.

resultsThose 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 < .0001). We did not find differences for message effectiveness or appeal.

conclusionsVisual optimizations such as color may influence warning text recall and should be considered for new warnings. Research should continue exploring variations for advertisement warnings to maximize attention to warning text. IMPLICATIONS: This study examines the impact of visual optimizations on recall of the US Food and Drug Administration-mandated e-cigarette advertisement warning text. We found that color might influence warning text recall, but we did not find effects for shape or signal word. It is possible the newly mandated e-cigarette advertisement warnings, which are required to occupy at least 20% of the advertisement, are currently novel enough to attract attention. Future research should examine optimizations following implementation of the new advertisement warnings.

Indexed as

AdolescentAdultAdvertisingAttentionElectronic Nicotine Delivery SystemsFemaleHumansMaleMental RecallProduct LabelingSmokersUnited StatesUnited States Food and Drug AdministrationYoung Adult

Identifiers

PMID31132095
PMCPMC7171273

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.