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. 2017 Jul 5;20(8):954–961. doi: 10.1093/ntr/ntx155

A Randomized Trial of the Effect of Youth Appealing E-Cigarette Advertising on Susceptibility to Use E-Cigarettes Among Youth

Alisa A Padon 1,✉, Kirsten Lochbuehler 2, Erin K Maloney 2, Joseph N Cappella 2
PMCID: PMC6037103  PMID: 29106669

Abstract

Introduction

Very little is known about how e-cigarette marketing is being perceived by youth, and the potential effect it will have on youth vaping and smoking behaviors. This limits the ability to identify youth-focused marketing efforts and to design effective policies for the regulation of e-cigarette marketing content and placement.

Methods

A sample of 417 nonsmoking youth (mean age = 15, SD = 1.3) were randomly assigned to either view four e-cigarette ads with low youth appeal, four e-cigarette ads with high youth appeal or four control ads. After exposure, participants completed covert and overt measurements of e-cigarette and tobacco cigarette attitudes and susceptibility to use.

Results

Youth in an e-cigarette ad condition were more likely to select an e-cigarette item in a product choice task compared to control, and had more positive e-cigarette beliefs. Contrary to hypotheses, youth in the low youth appeal condition reported greater susceptibility to trying e-cigarettes and tobacco cigarettes compared to control.

Conclusions

Exposure to any e-cigarette advertising may play a role in teens’ decision to initiate e-cigarette and tobacco cigarette use. As the Food and Drug Administration now has regulatory authority over the marketing of e-cigarettes, regulations on e-cigarette advertising are suggested.

Implications

Teens are increasingly being exposed to e-cigarette advertising, and many places are considering e-cigarette regulations, yet we know very little about how e-cigarette advertisements might influence youth tobacco use. This study utilized a novel dataset of e-cigarette ads coded for youth appeal and presented them to a sample of 417 nonsmoking teens in a randomized controlled design to test the effect of features on youth susceptibility to initiating e-cigarette and tobacco cigarette use. The findings inform evidence-based recommendations for regulating the marketing of e-cigarettes.

Introduction

With a significant increase in e-cigarette marketing in the past half-decade,1,2 and youth rates of e-cigarette use on the rise,3 there is concern that e-cigarette marketing may be recruiting young, nonsmokers who start using e-cigarettes and then become at risk for developing a nicotine addiction and graduating to tobacco cigarettes.1,3 Marketing has the ability to shape consumer behavior often without our awareness.4 The 2012 Surgeon General’s report found that exposure to advertisements and promotions by the tobacco industry is causally related to smoking initiation in youth and young adults,5 and many e-cigarette brands are mirroring the marketing tactics of cigarette advertising.6–8 Even advertising using primarily antismoking messaging has been found to increase the perception among nonusers that e-cigarettes are less harmful, and the likelihood of having tried e-cigarettes.9 As of August 2016, the US Food and Drug Administration has the authority to restrict e-cigarette advertising and promotions,10 and the 2016 Surgeon General’s Report set a goal of curbing e-cigarette advertising likely to attract youth.11 But research on marketing content likely to attract youth and young adults is an understudied area with certain limitations. There has been some work examining the presence of marketing features that may appeal to youth in current e-cigarette ads,8,12 but no work examining the relationship between exposure to such features in e-cigarette advertisements and youth intentions to use electronic and tobacco cigarettes. Further, explicit measures of youth perceptions and behavior may lack construct validity when the area of study is sensitive or stigmatizing such as in the case of youth tobacco use.13 Participants may be unwilling to provide truthful responses,14 or may lack well-formed attitudes if the behavior, such as use of electronic cigarettes, is new to them. In these cases, covert measures present an alternative for avoiding the limitations of self-report.15,16

This project explored the effect that exposure to various e-cigarette advertisements has on youth electronic and tobacco cigarette-related beliefs and intentions using both explicit and implicit measures of attitudes and susceptibility toward trying tobacco and e-cigarette products. Two main hypotheses were tested: (1) exposure to e-cigarette ads will have a positive impact on explicit and implicit measures of youth susceptibility to trying e-cigarettes or tobacco cigarettes compared to youth exposed to control ads; (2) exposure to e-cigarette ads with high youth appeal will have a greater positive impact on measures of youth susceptibility to trying e-cigarettes or tobacco cigarettes compared to e-cigarette ads with low youth appeal or control ads.

Methods

Design and Data Collection

Eligible participants completed a baseline survey and were then randomly assigned to either a low youth appeal e-cigarette ad condition, a high youth appeal e-cigarette ad condition, or a control ad condition and viewed four randomly selected ads within condition. After watching each ad, participants reported ad recall and evaluated its effectiveness. After watching all four ads, participants selected their favorite of the four, performed a time-pressured product choice task and were then randomized to complete a modified version of the single-target implicit association task (stIAT) for either e-cigarettes or tobacco cigarettes. They then reported product beliefs and completed the susceptibility index before being debriefed. Debriefing included an explanation of the effects of persuasive advertising and a link to antivaping materials.

Study Sample

In February 2016, a total of 2420 youth (age 13–17) were invited to participate in an online study by Toluna (www.toluna-group.com). Invited respondents were participants in the online survey panel or were living in the households of adults in the survey panel. Subjects in the Toluna panel are compensated in the form of points that they can accumulate and turn in for gift cards. Parental permission was obtained prior to requesting youth assent; the University of Pennsylvania Institutional Review Board approved the study. Participants were eligible if they were between the ages of 13 and 17, were aware of e-cigarettes and had not used a tobacco product (eg, cigarettes, cigars/little cigars and cigarillos, smokeless, hookah or e-cigarettes) more than “once or twice.” This filter was selected for two main reasons. First, advertisement approaches for a new product category often focus on promoting trial for new users,17 and adolescents who have done more than experiment with e-cigarettes have been shown to be less influenced by e-cigarette ad exposure.18 While experimenters have some additional product knowledge than never users, they are still inexperienced, and may still be receptive to advertisements focused on trial. Second, inexperienced youth are arguably the most vulnerable group, as research is finding strong associations between use of e-cigarettes and subsequent initiation of tobacco use among youth with no baseline intention of tobacco use.19 These are youth who may not have gone on to smoke without first using e-cigarettes, a behavior which exposure to advertising may influence.

Advertisement Sample

The source for the e-cigarette advertisements was a dataset of 154 video-based e-cigarette advertisements that had been collected and coded in a previous study using a modified Content Appealing to Youth (CAY) Index,8 a tool which measures 38 content features identified in the research literature as appealing to adolescents. CAY features fall under five broad dimensions: (1) production value (stylistic features of an ad that stimulate involuntary cognitive engagement among youth), (2) character appeals (triggers for modeling and aspiration), (3) youth-oriented genres (ie, magic and humor, associated with youth entertainment), (4) product appeals (rated poorly by youth; reverse-coded), and (5) reward appeals (claims or depictions of positive, experiential outcomes from product use; correlated with positive youth expectations of product use). Ads are coded so that the higher the CAY score, the greater the presence of youth appealing features.12

For this study, some ads were excluded due to having low quality, a primary focus on a retail shop rather than on an e-cigarette product, explicit sexual content, or duration exceeding 30 seconds. The decision to filter by duration was made for multiple reasons: (1) high duration could inflate the CAY score due to having more time for multiple appeals, (2) a qualitative evaluation showed no significant differences in type of content featured in <30 versus >30 second ads, and (3) it was more ecologically valid as TV ads rarely exceed 30 seconds. The final sample was 50 unique ads, made up of 30 different brands. Of these, the 10 ads with highest CAY scores (M = 15.6, SD = 1.3) were selected for the high youth appeal condition, and the 10 ads with the lowest CAY scores (M = 7.9, SD = 1.1) were selected for the low youth appeal condition. The high youth appeal ads used more character (M = 1, SD = 0.47) and reward appeals (M = 6.3, SD = 2.4), compared to the low youth appeal ads’ character (M = 0.4, SD = 0.70, p = .04) and reward appeals (M = 2.6, SD = 2.1, p < .01). The low youth appeal ads used more product appeals such as e-cigarette use instructions and health claims (M = 3.2, SD = 1.0) compared to the high youth appeal ads (M = 1.6, SD = 0.70, p < .001). High and low youth ads were not significantly different in their use of production value features or use of youth-oriented genres.

The set of control ads were selected from among all the non e-cigarette ads nationally aired during the same time period during which the sample of televised e-cigarette ads was aired. This amounted to 9359 unique control ads. We limited the sample to food and beverage items as these are convenience products which appeal to very large market segments.20 We excluded food items with purported health benefits, such as vitamins. The final sample was 799 ads, from which we randomly selected 10. Examples include soft drinks, fast food restaurants, snacks and candy, and all ads were less than 30 seconds.

Measures

Demographics and Tobacco-related Measures

The baseline survey measured age, gender, race, education, parent education, tobacco product (ie, tobacco cigarettes, cigar, smokeless, hookah, and e-cigarette) trial (response options included never, 1–2 times ever, or 3+ times), tobacco product advertising exposure (past 30 days recall and frequency), peer and family smoking, e-cigarette brand recognition of 41 different e-cigarette brands, sensation seeking,21 and an abbreviated Barratt Impulsiveness Scale.22,23

Ad Evaluation

Following each ad, participants reported whether they had ever seen the ad before (yes or no), ad liking on a 10-point scale from not at all (0) to very much (9), and perceived ad effectiveness as agreement with 3 items: (1) “This was an effective ad,” (2) “This ad would make me want to buy the product,” and (3) “This ad would make others want to buy the product” (response options: strongly disagree—strongly agree). An average of these three items was taken to generate an overall ad effectiveness score. Perceived target audience for each ad was measured with one item: “Who would you think this ad was trying to target/appeal to most: (1) children (under age 10), (2) teenagers (age 10–17), (3) young adults (age 18–25), or (4) adults (age 26+)?” After viewing all four ads participants reported which was their favorite ad and provided a brief explanation.

Time-Pressured Product Choice Task

Respondents were shown nine products and asked “If you were to get a coupon to purchase one of these products, which one would you choose?” Products included pictures of the actual packages of the four products they viewed ads for, either e-cigarettes or control products, as well as four randomly selected e-cigarette products (if assigned to the control group) or control products (if assigned to an e-cigarette group) and a single generic tobacco cigarette pack. While they made their selection, a timer at the top of the screen counted down from 10 and began flashing in red with 3 seconds remaining. Previous studies have found similar product choice measures without the time pressure to be associated with tobacco product ad exposure, harm perceptions,24 and intention to try tobacco products in the future.25 Adding time pressure puts limits on the amount of information that can be processed during consumer decision making,26 and when processing resources are limited, affective reactions and implicit associations have been found to contribute more heavily to consumer decisions.27–29

Implicit Association Test

Two stIAT (D. H. J. Wigboldus, R. W. Holland, A. van Knippenberg, Unpublished Data) were used to assess implicit associations toward smoking and vaping, respectively. This computerized reaction time task was chosen given its previous use in samples of adolescents, in assessing implicit associations toward smoking, and due to its psychometric properties.30–34 Participants performed a stIAT online using the Inquisit web software version 4 (www.millisecond.com), which measures positive and negative attitudes toward a single item (e-cigarettes or tobacco cigarettes) post-ad exposure. Five pictures that showed a scene related to vaping/smoking were used. In both tasks, five adjectives with a positive meaning (good, happy, pleasant, friendly, sincere) and five adjectives with a negative meaning (cruel, unpleasant, fake, angry, annoying) were used. The relative response time for classifying e- and tobacco cigarettes as either positive or negative was the measure of automatic attitude toward e-cigarettes/tobacco cigarettes.35,36

Product Beliefs

Participants reported their agreement on 5-point Likert scales ranging from strongly disagree to strongly agree with the following items, “E-cigarettes are…cool, enjoyable, healthy, helpful in social situations, visually appealing, fun, and high tech” (α = 0.94).

Susceptibility to Trying Tobacco Cigarettes and E-cigarettes

Susceptibility to trying e-cigarettes and tobacco cigarettes was measured using the following three items: “How likely is it that: you will try a tobacco/e-cigarette, even one or two puffs, any time soon?” “…any time during the next year?” and “If one of your best friends were to offer you a tobacco/e-cigarette, you would use it?” reported on 5-point Likert scales ranging from “Very unlikely” to “Very likely.”37 Participants reporting “very unlikely” to all three questions were categorized as committed never users, with all other participants classified as susceptible to use.38

Data Analysis

Data were analyzed using STATA 13.1 LP. We conducted bivariate tests (ie, t test and Analysis of Variance) and multivariate regression analyses (logistic regression, ordered logistic regression, and linear regression, according to outcome variable). Standardized coefficients or odds radios (ORs) and 95% confidence intervals were used to predict the effect of condition on outcome, controlling for any tobacco use.

Results

Participant Characteristics

Of the 2420 invited to participate, 460 did not meet the eligibility criteria, 296 declined to participate, 397 were excluded for other reasons, and some experienced technical difficulties (see Figure 1). Table 1 presents the participant characteristics of the final, randomized sample (N = 417). Of those randomized, 73% had never used any tobacco product, and there were no significant differences in never use by condition (p = .41).

Figure 1.

Figure 1.

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Study sample disposition diagram. IAT = Implicit association task.

Table 1.

Descriptive Statistics and Outcomes by Condition Assignment (n = 417)

Category Control n (%) High n (%) Low n (%) p value
Overall 145 (34.8) 138 (33.1) 134 (32.1)
Gender Female 88 (60.7) 84 (60.9) 74 (55.2) .56
Age 13 19 (13.1) 14 (10.1) 18 (13.4) .69
14 26 (17.9) 24 (17.4) 24 (17.9)
15 31 (21.4) 34 (24.6) 28 (20.9)
16 30 (20.7) 30 (21.7) 38 (28.4)
17 39 (26.9) 36 (26.1) 26 (19.4)
Education Junior High 36 (24.8) 36 (26.1) 39 (29.1) .83
Some High School 99 (68.3) 87 (63.0) 84 (62.7)
High School or more 10 (6.9) 15 (10.9) 11 (8.2)
Parent education Some High School 48 (33.0) 32 (23.2) 35 (26.1) .42
High School 13 (9.0) 16 (11.6) 15 (11.2)
Some college 21 (14.5) 24 (17.4) 22 (16.4)
College or more 59 (40.7) 64 (46.3) 57 (42.6)
Don’t know 4 (2.8) 2 (1.5) 5 (3.7)
Race White, non-Hispanic 76 (52.4) 89 (64.5) 85 (63.4) .06
Black, non-Hispanic 17 (11.7) 20 (14.5) 11 (8.2)
Hispanic 28 (19.3) 16 (11.6) 15 (11.2)
Other, non-Hispanic 24 (16.6) 13 (9.4) 23 (17.2)
Tobacco product use Never cigarette 127 (87.6) 106 (76.8) 106 (79.1) .05
Never cigar 137 (94.5) 124 (89.9) 112 (83.6) .01
Never smokeless 140 (96.6) 130 (94.2) 122 (91.0) .15
Never hookah 137 (94.5) 125 (90.6) 121 (90.3) .36
Never e-cigarette 116 (80.0) 108 (78.3) 107 (79.9) .92
Never any tobacco product 110 (75.9) 91 (65.9) 99 (73.9) .15
Tobacco product advertising exposure No tobacco exposure 61 (42.1) 71 (51.5) 65 (48.5) .26
No e-cigarette exposure 61 (42.1) 52 (37.7) 56 (41.8) .94
Peer tobacco use M (SD) 0.56 (0.85) 0.58 (0.85) 0.76 (1.1) .15
Parent tobacco use M (SD) 0.39 (0.49) 0.33 (0.47) 0.40 (0.49) .48
E-cigarette brand recognition M (SD) 2.7 (3.6) 1.9 (2.3) 2.6 (3.2) .05
Sensation seeking M (SD) 13.5 (3.0) 13.8 (3.2) 13.9 (2.9) .44
Barratt impulsiveness subscales M (SD) Attention subscale 2.12 (0.54) 2.18 (0.56) 2.21 (0.53) .36
Motor subscale 2.18 (0.63) 2.20 (0.64) 2.30 (0.64) .22
Nonplanning subscale 2.35 (0.64) 2.36 (0.70) 2.38 (0.68) .92
Outcome measures
E-cigarette item selected n (%) 3 (2.1) 19 (13.8) 22 (16.4) <.001
Susceptibility to trial N (%) Smoking 43 (29.7) 46 (33.3) 55 (41.0) .07
Vaping 67 (46.2) 78 (56.5) 79 (59.0) .13
Ad evaluation M (SD) Recall 1.34 (1.2) 0.33 (0.82) 0.33 (0.86) <.001
Liking 6.55 (1.5) 4.4 (2.2) 5.0 (2.4) <.001
Effectiveness 3.63 (0.7) 2.8 (0.9) 3.0 (0.9) <.001
Target audience 2.5 (0.5) 3.2 (0.4) 3.2 (0.5) <.001
Positive e-cigarette beliefs M (SD) 15.2 (7.6) 17.5 (7.7) 19.2 (8.2) <.001
stIATaM (SD) Smoking 0.10 (0.4) 0.11 (0.45) −0.03 (0.42) .15
Vaping −0.05 (0.4) −0.18 (0.47) −0.15 (0.41) .21
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stIAT = Single-target implicit association task.

aSample sizes: Smoking control n = 62, low = 56, high = 59; Vaping control n = 75, low = 71, high = 72.

After viewing the ads, participants were asked to download a web player and complete the Implicit Association Test on a separate website (www.millisecond.com). Over 50% of participants withdrew at this point. Participants in the low youth appeal e-cigarette ad condition were more likely to withdraw at the IAT (65%) compared to control (57%, p = .02), and more likely than the high youth appeal condition (63%), though not significantly. Respondents who had never tried tobacco cigarettes and who were assigned to an e-cigarette ad condition were more likely to quit compared to respondents who had ever tried tobacco cigarettes (p = .03).

Prior to this point in the study, there were no group differences in demographics or tobacco use. However, this pattern of withdrawal meant respondents in the e-cigarette conditions were more likely to have ever (1–2 times) tried cigars/little cigars and cigarillos (p = .01) compared to control and were marginally more likely to have ever used tobacco cigarettes (p = .05). The same pattern was observed for smokeless, hookah, and e-cigarette use, though not significantly.

To account for any selection bias that dropout may have introduced, we controlled for past use of any tobacco product in all regression analyses. An index was used (any product use vs. never any product use) because of the small cell sizes of youth who had ever tried tobacco products.

Ad Evaluation

Ad evaluation was most positive for control ads compared to e-cigarette ads across items. Comparing low to high youth appeal e-cigarette ads, there was no difference in average recall, effectiveness, or target audience (both groups thought e-cigarette ads were targeting young adults), however respondents in the low youth appeal condition reported greater liking of the ads (M = 5.0, SD = 2.4) compared to respondents in the high youth appeal condition (M = 4.4, SD = 2.2), F(1, 270) = 4.93, p = .03. Higher ad liking was also predictive of greater susceptibility to trying e-cigarettes, OR = 2.1, p < .000, and tobacco cigarettes, OR = 2.7, p < .000, compared to control, controlling for past tobacco use and condition. In the open-ended favorite ad question, the most common reasons given for liking a low youth appeal e-cigarette ad were ad quality, brevity, visuals, humor, and information. The most common reasons given for liking a high youth appeal e-cigarette ad were the use of a celebrity, attractive actors, coolness, humor, and visuals.

Time-pressured Product Choice

Overall, 44 (11%) respondents were interested in a coupon for an e-cigarette product and 2 selected the generic tobacco cigarette pack. There was a significant difference across conditions in the proportion of people interested in an e-cigarette, F(2, 414) = 9.04, p < .001. Using a multivariate logistic regression controlling for any past tobacco use, the odds of selecting an e-cigarette were 6.9 times higher if assigned to the high youth appeal e-cigarette condition compared to control (p = .003) and 9.6 times higher if assigned to the low youth appeal e-cigarette condition compared to control (p < .001). The odds between e-cigarette groups were not significantly different.

Implicit Associations

All respondents showed negative associations with vaping in the e-cigarette single-target implicit association test, but no group differences were found (p = .21). Respondents assigned to control and high youth appeal e-cigarette conditions had more positive associations with smoking tobacco cigarettes compared to the low youth appeal e-cigarette condition, but the differences were not significant (p = .15).

E-cigarette Beliefs

Just under half of the respondents agreed or strongly agreed that e-cigarettes are high tech, a third thought e-cigarettes were visually appealing, over 25% thought they were socially helpful or cool, and 22% thought they were enjoyable or fun. A quarter of the respondents in the low youth appeal condition, 13% in the high youth appeal condition and 8% of control agreed e-cigarettes are healthy; correspondingly, the low youth appeal ads were more likely to include health related claims (M = 0.7, SD = 0.48) compared to high youth appeal ads (M = 0.1, SD = 0.32), F(1, 18) = 10.80, p < .01. Assignment to the low youth appeal condition predicted more positive beliefs about e-cigarettes than control, β = 0.22, p < .001, and high youth appeal condition predicted marginally more positive beliefs than control, β = 0.08, p = .09, but the difference between e-cigarette conditions was not significant.

Table 2.

Regression Equations Predicting the Effect of Condition on Outcomes Controlling for Past Tobacco Use (n = 417)

Outcomes High (n = 138) Low (n = 134) Past tobacco use R-squared
r a β or OR r a β or OR r a β or OR
Ad evaluation
 Liking −.48*** −0.47*** −.32*** −0.32*** .18*** 0.21*** .20***
 Effectiveness −.48*** −0.46*** −.38*** −0.35*** .21*** 0.23** .21***
 Target audience .59*** 0.56*** .58*** 0.56*** −.08 −0.12** .33***
E-cigarette selected .22** 6.86** .25*** 9.61*** .26*** 3.60*** .13***
stIATb
 Smoking (n = 177) .02 0.01 −.14 −0.14ƚ −.04 −0.01 .01
 Vaping (n = 218) −.15ƚ −0.12 −.07 −0.10 −.07 −0.07 .01
Positive e-cigarette beliefs .15* 0.08ƚ .25*** 0.22*** .43*** 0.44*** .23***
 High Tech .12* 1.32 .20*** 2.18** .29*** 3.42*** .04***
 Visual .10 1.27 .24*** 2.60*** .36*** 4.53*** .06***
 Social .17** 1.74* .27*** 2.89*** .36*** 4.55*** .06***
 Cool .10ƚ 1.29 .17** 1.95** .42*** 5.83*** .07***
 Enjoyable .16** 1.60* .24*** 2.59*** .43*** 6.33*** .08***
 Fun .09 1.24 .15* 1.85** .45*** 6.90*** .08***
 Healthy .10 1.28 .21*** 2.35*** .38*** 5.10*** .07***
Cigarette susceptible .04 0.95 .12* 1.76* .43*** 7.96*** .15***
E-cigarette susceptible .10ƚ 1.30 .13* 1.80* .46*** 0.58*** .18***
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All tests compare e-cigarette condition to control.

stIAT = Single-target implicit association task.

aSpearman correlation between variables with control = 0.

bSample sizes: Smoking control n = 62, low = 56, high = 59; Vaping control n = 75, low = 71, high = 72.

*p < .05, **p < .01, ***p < .001, ƚp < .10.

Susceptibility to Trying E-cigarettes and Tobacco Cigarettes

Overall, 224 youth (54%) were susceptible to trying an e-cigarette, measured as any response other than “very unlikely” to trying an e-cigarette soon, this year, and if offered by a best friend. By group, 59% of youth in the low youth appeal condition were susceptible to trying an e-cigarette compared with 46% in the control condition and 56% in the high youth appeal condition. Assignment to the low youth appeal condition predicted greater susceptibility to trying e-cigarettes compared to control, OR = 1.80, p = .03.

Over a third (N = 144) of respondents were susceptible to trying a tobacco cigarette; 30% in the control condition, 33% in the high youth appeal condition, and 41% in the low youth appeal condition, F(2, 414) = 3.11, p = .04. Assignment to the low youth appeal condition predicted greater susceptibility to trying tobacco cigarettes compared to control, OR = 1.76, p = .04.

Conclusions

This study supports previous findings that an environment in which e-cigarette marketing is unregulated and available to adolescents2 is associated with susceptibility to future tobacco product use.19 We showed exposure to e-cigarette advertisements to be predictive of more positive e-cigarette beliefs and greater likelihood of selecting an e-cigarette item in a product choice task compared to control, adjusting for the influence of past tobacco product use. These findings add to the growing body of literature that e-cigarette ad exposure can kindle explicit interest in e-cigarettes,18,39,40 as well as implicit interest in e-cigarettes.16

Contrary to hypothesis, exposure to low youth appealing e-cigarette ads, and not high youth appealing e-cigarette ads, predicted greater susceptibility to trying e- and tobacco cigarettes compared to control. Youth also reported liking the “low appeal” ads more than the high appeal ads, and greater ad liking was predictive of e- and tobacco cigarette susceptibility. Product novelty may be an important consideration in assessing the youth appeal of marketing. The features most prevalent in the low youth appeal ads were educational, such as how to use e-cigarettes, and how they are different from tobacco cigarettes. While youth dislike such product appeals in the marketing for alcohol, which is a prevalent and familiar product,41–43 this may be valuable information to nonsmoking teenagers imagining they may one day be offered a vape in front of peers. This is borne out in that a common reason youth gave for liking a low appeal ad was the information it provided. The validation studies for the CAY index involved experienced underage drinkers,12 however this study sample consisted of youth who had never or only once or twice ever used any tobacco product. Farrelly et al. also found that never-smoking youth rated informational e-cigarette ads highly.18 In marketing where there is a high need for cognitive evaluation, rational appeals may be more effective than emotional appeals.44 This is an effect that would likely diminish as the product becomes more familiar, at which point reward appeals such as positive emotions, normative modeling, and lifestyle appeals may be more persuasive.

The study also showed exposure to e-cigarette advertisements to be predictive of susceptibility to trying tobacco cigarettes compared to control. This adds some credence to the concern that e-cigarette advertising may renormalize tobacco cigarette use in a generation for whom decades of declining rates of cigarette use has begun to plateau.45 More research is needed using both qualitative and quantitative designs to determine if there are specific features that contribute to this association, that is, vapor that simulates smoke,46 similarity in design of e-cigarettes with tobacco cigarettes, and health claims that could decrease the perception of risk of tobacco cigarettes.

We found no effect of condition on tobacco or e-cigarette implicit attitudes as measured by the single-target Implicit Association Test, contrary to the findings of Pokhrel et al.16 The most likely explanation is that Pokhrel et al.16 used a two-target IAT in which associations with e-cigarettes were measured relative to associations with tobacco cigarettes. In such a test, it is unclear which factor or combination of factors contribute to the overall score. A high IAT score could indicate high positive associations with e-cigarettes, high negative associations with tobacco cigarettes, a lack of negative associations with e-cigarettes or a lack of positive associations with tobacco cigarettes.47

The pattern of withdrawal after ad exposure may itself be informative. Never tobacco users assigned to an e-cigarette ad condition were most likely to withdraw, and more youth dropped out of the low youth appeal condition than any other condition, suggesting it may not have been as appealing to them as the high youth appeal condition compared to control. Yet, why those respondents who remained in the low youth appeal condition reported the most susceptibility to trying tobacco products is a question we cannot answer with this data, and perhaps points to a particularly vulnerable group.

The study faced some limitations. The use of active parent permission and youth assent limited our access to youth, and the sensitive nature of underage tobacco product use may have created some nonresponse bias. Further, though we controlled for tobacco use, the findings must be interpreted with some caution due to the postrandomization dropout that left fewer never tobacco product users in the e-cigarette ad conditions. Measuring susceptibility before ad exposure would have been informative in determining the reasons for dropout. Finally, future research using a computerized reaction time task which requires downloading an app, or something similar, may wish to increase the amount of compensation to better incentivize participants to continue.

Despite the limitations, this study moves the literature on e-cigarette advertising forward by suggesting that any e-cigarette advertising may be persuasive to youth, including advertising designed specifically for adult smokers. In an unregulated e-cigarette marketing environment, the presence of e-cigarette advertisements that are particularly persuasive to inexperienced youth, that create a social environment friendly to e-cigarettes, and that can be placed within programming targeted at this demographic may ultimately contribute to underage initiation of tobacco product use and all of the harms that accompany it.

Funding

Research reported in this publication was supported by the National Cancer Institute (NCI) of the National Institutes of Health (NIH) and U.S. Food and Drug Administration (FDA) Center for Tobacco Products (CTP) under Award Number P50CA179546. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the Food and Drug Administration (FDA).

Declaration of Interests

No authors have any conflicts of interest to declare.

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