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Optimizing Images for an E-Cigarette Messaging Campaign: Liking and Perceived Effectiveness

Stevens, Elise M
Keller-Hamilton, Brittney
Mays, Darren
Unger, Jennifer B
Wackowski, Olivia A
West, Julia C
Villanti, Andrea C
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Abstract

Introduction: Given the prevalence of electronic vapor product (EVP) use among young people in the US, there is a need for effective vaping education campaigns. This study tested 32 images for liking and perceived effectiveness (PE) to identify optimal images for a messaging campaign.

Method: Images were selected from current campaigns, warning labels, and other images based on young adult reasons for use. Images were coded for the presence of (1) people, (2) vapor, (3) device, (4) color, and (5) similarity to warning label image. Young adults (n = 200) were recruited from the Amazon Mechanical Turk platform. Participants were randomly assigned to view and rate six of the 32 images on liking as well as PE, which measured the potential impact of the image to discourage vaping appeal and use.

Results: Images containing vapor and/or a device or e-liquid were not well-liked but were perceived as effective in discouraging vaping (ps < 0.05). Images from warning labels were also not well-liked but were perceived as significantly more effective than those not from a warning (p < 0.01). Liking and effectiveness of features was similar for both EVP users and non-users.

Discussion: Images with specific features were rated as less likable but rated as higher on PE. However, the consistency of image features rated as effective by EVP users and non-users supports the utility of similar imagery for vaping prevention and reduction efforts.

Source

Stevens EM, Keller-Hamilton B, Mays D, Unger JB, Wackowski OA, West JC, Villanti AC. Optimizing Images for an E-Cigarette Messaging Campaign: Liking and Perceived Effectiveness. Int J Environ Res Public Health. 2021 Dec 9;18(24):12989. doi: 10.3390/ijerph182412989. PMID: 34948597; PMCID: PMC8700893.

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DOI
10.3390/ijerph182412989
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34948597
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Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).Attribution 4.0 International