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RESEARCH PAPER
Correlates of e-cigarette ad awareness and likeability in U.S. young adults
| 1 | Evaluation Science and Research, Truth Initiative, Washington, DC, USA |
| 2 | Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA |
| 3 | Zanvyl Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, USA |
| 4 | The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC, USA |
CORRESPONDING AUTHOR
Jessica M Rath
Evaluation Science and Research, Truth Initiative, 900 G. St., NW, Washington, DC, USA
Evaluation Science and Research, Truth Initiative, 900 G. St., NW, Washington, DC, USA
Submission date: 2016-11-11
Acceptance date: 2017-03-20
Publication date: 2017-04-04
Tob. Induc. Dis. 2017;15(April):22
KEYWORDS
ABSTRACT
Background:
Awareness and use of electronic cigarettes has rapidly increased among U.S. adults. The aim of this study was to examine awareness and likeability of e-cigarette print advertisements in a national sample of young adults and to examine ad likeability as a correlate of intended e-cigarette use among never e-cigarette users.
Methods:
Participants (n = 2110, unweighted) of the Truth Initiative Young Adult Cohort (January 2013) were randomized to see four print ads (blu, Fin, NJOY, and White Cloud). Bivariate analyses provided descriptive characteristics of all participants and multivariable logistic regression examined the relationships between the average likeability score (across all four ads), curiosity about e-cigarettes, and susceptibility to using e-cigarettes among respondents who had never used e-cigarettes.
Results:
Nearly 20% of participants reported awareness of the blu ad. Of the four e-cigarette ads, likeability was highest for the NJOY ad. Participants with higher ad likeability ratings had more than twice the odds of being curious to try an e-cigarette (AOR 2.33; 95% CI 1.84–2.95), try an e-cigarette soon (AOR 2.93; 95% CI 1.96–4.38), and try an e-cigarette if offered by best friend (AOR 2.48; 95% CI 1.95–3.15), after adjusting for other covariates. Current cigarette use was the strongest correlate of susceptibility to using an e-cigarette (p < .01) in the multivariable models.
Conclusions:
Higher ad likeability was correlated with greater susceptibility to try an e-cigarette among U.S. young adults. Future studies are needed to monitor how awareness and likeability of e-cigarette advertising influence patterns of e-cigarette and other tobacco use in young people.
Awareness and use of electronic cigarettes has rapidly increased among U.S. adults. The aim of this study was to examine awareness and likeability of e-cigarette print advertisements in a national sample of young adults and to examine ad likeability as a correlate of intended e-cigarette use among never e-cigarette users.
Methods:
Participants (n = 2110, unweighted) of the Truth Initiative Young Adult Cohort (January 2013) were randomized to see four print ads (blu, Fin, NJOY, and White Cloud). Bivariate analyses provided descriptive characteristics of all participants and multivariable logistic regression examined the relationships between the average likeability score (across all four ads), curiosity about e-cigarettes, and susceptibility to using e-cigarettes among respondents who had never used e-cigarettes.
Results:
Nearly 20% of participants reported awareness of the blu ad. Of the four e-cigarette ads, likeability was highest for the NJOY ad. Participants with higher ad likeability ratings had more than twice the odds of being curious to try an e-cigarette (AOR 2.33; 95% CI 1.84–2.95), try an e-cigarette soon (AOR 2.93; 95% CI 1.96–4.38), and try an e-cigarette if offered by best friend (AOR 2.48; 95% CI 1.95–3.15), after adjusting for other covariates. Current cigarette use was the strongest correlate of susceptibility to using an e-cigarette (p < .01) in the multivariable models.
Conclusions:
Higher ad likeability was correlated with greater susceptibility to try an e-cigarette among U.S. young adults. Future studies are needed to monitor how awareness and likeability of e-cigarette advertising influence patterns of e-cigarette and other tobacco use in young people.
REFERENCES (39)
1.
King BA, Patel R, Nguyen KH, Dube SR. Trends in awareness and use of electronic cigarettes among US adults, 2010–2013. Nicotine Tob Res. 2015;17:219–27.
2.
McMillen RC, Gottlieb MA, Shaefer RM, Winickoff JP, Klein JD. Trends in Electronic Cigarette Use Among U.S. Adults: Use is Increasing in Both Smokers and Nonsmokers. Nicotine Tob Res. 2014;17:1195–202.
3.
Delnevo CD, Giovenco DP, Steinberg MB, Villanti AC, Pearson JL, Niaura RS, Abrams DB. Patterns of electronic cigarette use among adults in the United States. Nicotine Tob Res. 2016;18:715–9.
4.
U. S. Department of Health and Human Services. The Health Consequences of Smoking—50 Years of Progress. A Report of the Surgeon General. Atlanta: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2014.
5.
Kornfield R, Huang J, Vera L, Emery SL. Rapidly increasing promotional expenditures for e-cigarettes. Tob Control. 2015;24:110–1.
6.
Truth Initiative: Vaporized: Youth and young adult exposure to e-cigarette marketing. Washington, D.C.; 2015.
7.
Davis RM, Gilpin EA, Loken B, Viswanath K, Wakefield M. Monograph 19: The role of the media in promoting and reducing tobacco use. In: NCI Tobacco Control Monograph Series. Rockville: National Cancer Institute; 2008.
8.
Vakratsas D, Ambler T. How advertising works: What do we really know? J Mark Res. 1999;63:26–43.
9.
Haley RJ, Baldinger AL. The arf copy research validity project. J Advert Res. 2000;40:114–35.
10.
Duke JC, Lee YO, Kim AE, Watson KA, Arnold KY, Nonnemaker JM, Porter L. Exposure to electronic cigarette television advertisements among youth and young adults. Pediatrics. 2014;134:e29–36.
11.
Pokhrel P, Fagan P, Kehl L, Herzog TA. Receptivity to e-cigarette marketing, harm perceptions, and e-cigarette use. Am J Health Behav. 2015;39:121–31.
12.
American Legacy Foundation. Vaporized: E-cigarettes, Advertising and Youth. Washington, DC: Legacy; 2014.
13.
Farrelly MC, Duke JC, Crankshaw EC, Eggers ME, Lee YO, Nonnemaker JM, Kim AE, Porter L. A Randomized Trial of the Effect of E-cigarette TV Advertisements on Intentions to Use E-cigarettes. Am J Prev Med. 2015;49:689–93.
14.
Villanti AC, Rath JM, Williams VF, Pearson JL, Richardson A, Abrams DB, Niaura RS, Vallone DM. Impact of exposure to e-cigarette advertising on susceptibility and trial of e-cigarettes and cigarettes in U.S. young adults: A randomized controlled trial. Nicotine Tob Res. 2015; in press.
15.
Durbin D, Waxman H, Harkin T, Rockefeller JD, Blumenthal R, Markey EJ, Brown S, Reed J, Boxer B, Merkley J, Pallone F. Gateway to Addiction?: A survey of popular electronic cigarette manufacturers and targeted marketing to youth. 2014.
16.
Villanti A, Vargyas E, Beck R, Niaura R, Pearson J, Abrams D. FDA regulation of tobacco: Integrating science, law, policy and advocacy. Am J Public Health. 2011;101:1160–2.
17.
Family Smoking Prevention and Tobacco Control Act. U.S. Congress. In Public Law No:111-31, vol. HR 1256; 2009.
18.
Cobb CO, Villanti AC, Graham AL, Pearson JL, Glasser AM, Rath JM, Stanton CA, Levy DT, Abrams DB, Niaura R. Markov Modeling to estimate the population impact of emerging tobacco products: a proof-of-concept Study. Tob Regul Sci. 2015;1:129–41.
19.
Villanti AC, Rath JM, Williams VF, Pearson JL, Richardson A, Abrams DB, Niaura RS, Vallone DM. Impact of exposure to electronic cigarette advertising on susceptibility and trial of electronic cigarettes and cigarettes in US young adults: a randomized controlled trial. Nicotine Tob Res. 2015;ntv235.
20.
Chang L, Krosnick JA. National surveys via RDD telephone interviewing versus the internet comparing sample representativeness and response quality. Public Opin Q. 2009;73:641–78.
21.
Yeager DS, Krosnick JA, Chang L, Javitz HS, Levendusky MS, Simpser A, Wang R. Comparing the Accuracy of RDD Telephone Surveys and Internet Surveys Conducted with Probability and Non-Probability Samples. Public Opin Q. 2011;75:709–47.
22.
Rhodes DJ, Radecki Breitkopf C, Ziegenfuss JY, Jenkins SM, Vachon CM. Awareness of breast density and its impact on breast cancer detection and risk. J Clin Oncol. 2015;33:1143–50.
23.
Grande D, Mitra N, Shah A, Wan F, Asch DA. Public preferences about secondary uses of electronic health information. JAMA Intern Med. 2013;173:1798–806.
24.
Kumar S, Quinn SC, Kim KH, Daniel LH, Freimuth VS. The impact of workplace policies and other social factors on self-reported influenza-like illness incidence during the 2009 H1N1 pandemic. Am J Public Health.2012;102:134–40.
25.
Fowler Jr FJ, Gerstein BS, Barry MJ. How patient centered are medical decisions?: Results of a national survey. JAMA Intern Med. 2013;173:1215–21.
26.
Rath JM, Villanti AC, Abrams DB, Vallone DM. Patterns of tobacco use and dual use in US young adults: the missing link between youth prevention and adult cessation. J Environ Public Health. 2012;2012:679134.
27.
American Association for Public Opinion Research. Standard Definitions: Final Dispositions of Case Codes and Outcome Rates for Surveys. 8th ed. Chicago: AAPOR; 2015.
28.
Evans N, Farkas A, Gilpin E, Berry C, Pierce JP. Influence of tobacco marketing and exposure to smokers on adolescent susceptibility to smoking. J Natl Cancer Inst. 1995;87:1538–45.
29.
Mowery PD, Farrelly MC, Haviland ML, Gable JM, Wells HE. Progression to established smoking among US youths. Am J Public Health. 2004;94:331–7.
30.
Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol.1995;57:289–300.
31.
Richardson A, Ganz O, Stalgaitis C, Abrams D, Vallone D. Noncombustible tobacco product advertising: how companies are selling the new face of tobacco. Nicotine Tob Res. 2014;16:606–14.
32.
Anderson SJ. Marketing of menthol cigarettes and consumer perceptions: a review of tobacco industry documents. Tob Control. 2011;20 Suppl 2:ii20–28.
33.
Gardiner PS. The African Americanization of menthol cigarette use in the United States. Nicotine Tob Res. 2004;6:S55–65.
34.
United States of America v. Philip Morris USA, Inc., et al. Order #34 -Remand [http://www.tobacco-on-trial.co...]. Accessed on 22 Feb 2017.
35.
Kelly B, Squiers L, Bann C, Stine A, Hansen H, Lynch M. Perceptions and plans for prevention of Ebola: results from a national survey. BMC Public Health. 2015;15:1136.
37.
Ηalbesleben JR, Whitman MV. Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias. Health Serv Res. 2013;48:913–30.
38.
Heeren T, Edwards EM, Dennis JM, Rodkin S, Hingson RW, Rosenbloom DL. A comparison of results from an alcohol survey of a prerecruited Internet panel and the National Epidemiologic Survey on Alcohol and Related Conditions. Alcohol Clin Exp Res. 2008;32:222–9.
39.
Garrett J, Dennis JM, DiSogra CA. Non-response bias: Recent findings from address-based panel recruitment. In: Annual Conference of the American Association for Public Opinion Research. Chicago, IL. 2010.
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2.
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3.
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4.
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5.
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6.
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