Objective: Blu's 'Something Better' advertising campaign ran in popular print magazines in 2017. The campaign included advertisements with fake warnings conveying positive messages, which mimicked the Food and Drug Administration (FDA)'s warning requirements for electronic cigarette (e-cigarette) advertisements that took effect in 2018. We report adolescent males' recall of these fake warnings and how exposure to fake warnings affected recall of other advertisement components, including the actual warning or health risks, brand and product.
Methods: Ohio males ages 12-19 years (N = 775; 73.8 % white non-Hispanic) were randomly assigned to view an e-cigarette advertisement with or without a fake warning. Afterward, they were asked what they remembered most about the advertisement. Responses were qualitatively coded. Statistical analyses included survey-weighted descriptive statistics and logistic regression.
Results: Of participants who viewed an e-cigarette advertisement with a fake warning, 27.0 % reported the fake warning was what they remembered most, and 18.8 % repeated the fake warning message. Participants viewing advertisements with a fake warning had lower odds of recalling the actual warning or health risks (OR = 0.29; 95% CI: 0.11 to 0.77) or brand (OR = 0.43; 95% CI: 0.22 to 0.85), compared with participants viewing other e-cigarette advertisements.
Conclusions: Adolescents viewing an advertisement with a fake warning were less likely to recall the advertisement's actual warning or health risks. Although e-cigarette advertisements now carry large FDA-mandated warnings, this tactic could be used for cigarette advertisements that continue to carry small warnings in the USA. Findings underscore the necessity of tobacco advertisement surveillance and study of advertisements' effects on adolescents.
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http://dx.doi.org/10.1136/tobaccocontrol-2018-054805 | DOI Listing |
J Med Internet Res
December 2024
Institute for Global Tobacco Control, Department of Health, Behavior and Society, Johns Hopkins University, Baltimore, MD, United States.
In 2019, we launched a web-based longitudinal survey of adults who frequently use e-cigarettes, called the Vaping and Patterns of E-cigarette Use Research (VAPER) Study. The initial attempt to collect survey data failed due to fraudulent survey submissions, likely submitted by survey bots and other survey takers. This paper chronicles the journey from that setback to the successful completion of 5 waves of data collection.
View Article and Find Full Text PDFJ Appl Psychol
August 2024
Department of Psychology, Western University.
Numerous faking warning types have been investigated as interventions that aim to minimize applicant faking in preemployment personality tests. However, studies vary in the types and effectiveness of faking warnings used, personality traits, as well as the use of different recruitment settings and participant samples. In the present study, we advance a theory that classifies faking warning types based on ability, opportunity, and motivation to fake (Tett & Simonet, 2011), which we validated using subject matter expert ratings.
View Article and Find Full Text PDFR Soc Open Sci
November 2023
The Royal Society, London, UK.
The rapid advancement of 'deepfake' video technology-which uses deep learning artificial intelligence algorithms to create fake videos that look real-has given urgency to the question of how policymakers and technology companies should moderate inauthentic content. We conduct an experiment to measure people's alertness to and ability to detect a high-quality deepfake among a set of videos. First, we find that in a natural setting with no content warnings, individuals who are exposed to a deepfake video of neutral content are no more likely to detect anything out of the ordinary (32.
View Article and Find Full Text PDFJ Med Internet Res
August 2023
Institute for Public Health and Nursing Research, University of Bremen, Bremen, Germany.
Background: Health-related misinformation on social media is a key challenge to effective and timely public health responses. Existing mitigation measures include flagging misinformation or providing links to correct information, but they have not yet targeted social processes. Current approaches focus on increasing scrutiny, providing corrections to misinformation (debunking), or alerting users prospectively about future misinformation (prebunking and inoculation).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!