Skip to main content
PMC home page
Preventive Medicine Reports logoLink to Preventive Medicine Reports
. 2022 Jun 13;28:101862. doi: 10.1016/j.pmedr.2022.101862

Associations between perceived source credibility, e-cigarettes, and e-cigarette ad perceptions

Donghee N Lee a,⁎, Jessica Liu b, Brittney Keller-Hamilton c, Joanne G Patterson d, Amelia V Wedel e, Coralia Vázquez-Otero f, Elise M Stevens a
PMCID: PMC9207267  PMID: 35733610

Abstract

The use of e-cigarettes among U.S. adults remains high, and aggressive industry advertising is a contributor. Consumer opinions of the e-cigarette industry’s credibility can influence e-cigarette product and ad perceptions. The purpose of this study was to examine the association of perceived source credibility of e-cigarette ads and consumer attitudes toward e-cigarette ads and product use. In October 2021, we conducted a survey using an online convenience sample (N = 497, Mage = 31.9). Participants viewed two randomly selected e-cigarette ads and were asked questions regarding source credibility, perceptions of the ads, and e-cigarette use. Linear mixed effects models with random intercepts were used to estimate associations between perceived source credibility with perceived ad relevance, effectiveness, liking, product use interest, and e-cigarette harms perceptions. We also tested whether associations between perceived source credibility and ad and e-cigarette perceptions were moderated by e-cigarette use. Models controlled for cigarette smoking status, age, sex, race, ethnicity, sexual orientation, and income. Perceived source credibility was positively associated with increased perceived ad relevance, effectiveness, liking, and product use interest (ps < 0.001). E-cigarette use moderated associations of perceived source credibility and perceived ad relevance, perceived ad effectiveness, and interest in using e-cigarettes, with associations being strongest among never users. Findings suggest that tobacco control messaging aiming to reduce the credibility of the e-cigarette industry might be most effective among adults who have never used e-cigarettes.

Keywords: Electronic cigarettes, Advertising, Mass media, Source credibility, Tobacco control communication

1. Introduction

In the United States, electronic cigarettes (e-cigarettes) are the most commonly used non-cigarette tobacco products among adults (Cornelius et al., 2020). While e-cigarettes demonstrate lower health harm compared to cigarettes (National Academies of Sciences, 2018), e-cigarette use is associated with adverse health effects (Overbeek et al., 2020, Skotsimara et al., 2019) and may increase uptake of combustible tobacco use among nonsmokers (Hair et al., 2021, Khouja et al., 2021, Soneji et al., 2017). Aggressive e-cigarette marketing is a contributor to e-cigarette use prevalence (Noel et al., 2011, Huang et al., 2014, Banerjee et al., 2015, Mantey et al., 2016). E-cigarette advertisements (ads) emphasizing product appeal (i.e., glamor, social desirability, flavor) (Londerée et al., 2018, Pokhrel et al., 2019) and lower health harms (Wang et al., 2021) of e-cigarettes (vs. cigarettes) have been found to influence positive attitudes toward e-cigarette ads and increase e-cigarette use among younger and older adults.

According to source credibility theory (Hovland et al., 1953), expert and relatable sources are the main types of sources that guide individuals’ health message processing. Specifically, individuals’ perceived credibility of a source can influence their perceptions, attitudes, and beliefs about health topics (Case et al., 2018). Perceived source credibility increases the persuasiveness of ads (Pornpitakpan, 2004) by influencing positive attitudes toward the ads and their advertised products (Hovland and Weiss, 1951). The tobacco industry takes advantage of this tactic by designing messaging to increase source credibility (Freeman and Chapman, 2009, Grana and Ling, 2014, Watts et al., 2021). Historically, e-cigarette companies have used credible (e.g., experts) and trusted sources (e.g., young models, social influencers) in their advertising to increase appeal (Grana and Ling, 2014, Padon et al., 2017). These advertising strategies are concerning because perceived credibility of a source influences e-cigarette use and risk perceptions (Alcalá and Shimoga, 2020, Erku et al., 2021, Vereen et al., 2020). For example, individuals who trust e-cigarette companies more than health professionals have 87% greater odds of using e-cigarettes (Vereen et al., 2020) and they report lower e-cigarette harm perceptions (Case et al., 2018, Alcalá and Shimoga, 2020). In response, tobacco control communication campaigns have focused on countering tobacco-industry credibility by exposing the industry’s deceptive advertising tactics (Malone et al., 2012). Evidence from several counter-industry campaigns inferred that instilling distrust in the tobacco industry can reduce smoking prevalence, initiation, and use intentions, while increasing support toward tobacco industry regulations among young adults (Malone et al., 2012). However, most research on counter-industry campaigns targeting the tobacco industry’s credibility has focused on combusted tobacco (Farrelly et al., 2002, Niederdeppe et al., 2004, Hershey et al., 2005).

To date, limited research has examined the role of perceived source credibility on consumer perceptions of e-cigarette ads and health harms. Some past research has tangentially touched on the topic, however. For instance, an experimental study about the effect of e-cigarette ads on social media found that ads with celebrity endorsements increased positive attitudes and use intentions more effectively than ads with non-celebrity endorsements (Phua et al., 2018). Another social media ad study found that adolescents reported greater attention, perceived norms, and favorable attitudes toward e-cigarettes when viewing an industry-promoted ad compared to peer-generated posts (Vogel et al., 2020). However, e-cigarette harm perceptions did not differ between adolescents who viewed industry-promoted or peer-generated posts (Vogel et al., 2020). This contrasts survey findings that adults who trust the e-cigarette industry are less likely to believe that e-cigarettes are harmful to one’s health (Case et al., 2018, Alcalá and Shimoga, 2020). Together, these studies suggest that source credibility may be associated with e-cigarette ad and harm perceptions. However, more research is needed that examines how perceived source credibility is related to e-cigarette ad perceptions (perceived ad relevance, effectiveness, and liking) and product perceptions (use interest and harm perceptions). Because these ad and product perceptions are antecedents to product use intentions and actual use behaviors, understanding the role of perceived e-cigarette industry credibility on consumers’ e-cigarette ad and product perceptions provides a target for e-cigarette prevention interventions (Iles et al., Lienemann et al., 2018, Moran et al., 2017, Noar et al., 2020, Pavlou and Stewart, 2000, Pechmann and Stewart, 1990, Moran et al., 2021). Furthermore, as e-cigarettes may be used as a harm reduction tool for adults who smoke (Wang et al., 2021, Zhu et al., 2017, Levy et al., 2018, Biener and Hargraves, 2015), it is important to understand how this population perceives e-cigarettes (Owusu et al., 2019) and the source of health information related to e-cigarettes (i.e., source credibility) (Wackowski et al., 2020). The goal of this study was to examine how perceived source credibility is associated with individuals’ perceptions of e-cigarette ads and interest in using the advertised product. Based on prior research from the cigarette literature, we hypothesized that greater perceived source credibility would be associated with greater perceived e-cigarette ad relevance, effectiveness, liking, interest in using e-cigarettes, and lower e-cigarette harm perceptions (Moran et al., 2021, Schmidt et al., 2016, Guttman and Peleg, 2003, Zagona and Harter, 1966). We also hypothesized that these associations would be strongest among e-cigarette users as past research has shown that use of the product decreases product harm perceptions (Choi and Forster, 2014, Villanti et al., 2015, Wackowski and Delnevo, 2016, Leavens et al., 2019). Finally, given the growing evidence that e-cigarettes may be a potential harm reduction tool for smokers (Wang et al., 2021, Zhu et al., 2017, Levy et al., 2018, Biener and Hargraves, 2015), we examined whether cigarette smoking status moderated the association between perceived source credibility of e-cigarette ads and outcome variables.

2. Methods

2.1. Sample

This study was part of a larger study examining e-cigarette advertising and e-cigarette use among adults living in the United States. In October 2021, we used Prolific (prolific.co), an international crowdsourcing platform for behavioral research studies, to recruit a convenience sample of participants. Participants were eligible to participate in the study if they were 18 years or older and resided in the United States. Sexual minority adults (i.e., lesbian, gay, bisexual, or other non-heterosexual people) were oversampled for the parent study.

2.2. Study design

Participants were prescreened for the eligibility criteria via Prolific. Potential participants meeting eligibility criteria reviewed a brief study description on Prolific, which included information about viewing e-cigarette product ads. During the consent process, participants were also informed that they would view e-cigarette ads currently on the market. After providing consent, participants were asked to complete several measures related to tobacco product use. Then, they were randomized to view two e-cigarette ads, selected from a pool of 173 real-world ads (from 2019 and 2020) coded for containing e-cigarette ad features (Liu et al., 2018). Full information on the ads has been published elsewhere (Liu et al., 2018). After viewing each ad, participants completed measures on perceived source credibility, perceptions of the ads, interest in using the product, and e-cigarette harm perceptions. After study completion, participants were compensated via Prolific’s policies. All procedures were approved by the host institution’s Institutional Review Board.

2.3. Measures

Demographics. Participants reported their age (treated as continuous), gender (collapsed to female, male, non-binary), race and ethnicity (collapsed to Non-Hispanic White, Non-Hispanic Black, other/multiple, Hispanic), sexual orientation (defined as self-reported sexual identity, collapsed to straight, gay/lesbian, bisexual, other), and individual income (coded in $10,000 increments from $0 to >$100,000 and treated as continuous).

E-cigarette use. Participants were asked to report their e-cigarette use. Participants were categorized as current users if they used e-cigarettes in the past 30 days, ever users if they had ever used e-cigarettes but not in the past 30 days, and never users if they had never used e-cigarettes (not even a puff).

Cigarette Smoking. Participants were asked to report their cigarette smoking status. Participants were categorized as current smokers if they smoked cigarettes in the past 30 days and non-smokers if they did not smoke cigarettes in the past 30 days.

Perceived source credibility. Perceived source credibility was assessed by using an adapted semantic differential scale (McCroskey and Teven, 1999). We included seven items measuring participant perceptions of the e-cigarette company viewed in each ad (e.g., cares about me – doesn’t care about me; dishonest – honest; untrustworthy – trustworthy). Scores were on a scale from 1 to 5, and one item was reverse coded. Items were summed and averaged (Cronbach’s alphas > 0.91). Higher scores indicated higher perceived source credibility.

Perceived ad relevance. Perceived ad relevance was assessed using two items: “The ad seemed to be written personally for me” and “The ad was very relevant to my situation.” (Jensen et al., 2012) Scores ranged from 1 (Strongly disagree) to 5 (Strongly agree). Items were summed and were averaged (Cronbach's alphas > 0.90) with higher scores indicating greater perceived ad relevance.

Perceived ad effectiveness. Perceived effectiveness of the ad was assessed using five items about whether participants thought the ad was worth remembering, grabbed their attention, was powerful, convincing, meaningful, and informative (Davis et al., 2013). Scores ranged from 1 (Strongly disagree) to 5 (Strongly agree). Items were summed and averaged (Cronbach's alphas > 0.93).

Ad liking. Liking of the ad was assessed using a single item: “I liked this ad” on a scale of 1 (Strongly disagree) to 5 (Strongly agree) (Moran et al., 2021).

Product use interest. Product use interest was assessed using a single item: “This ad made me want to use the product” on a scale of 1 (Strongly disagree) to 5 (Strongly agree) (Moran et al., 2021).

Perceived e-cigarette harm. Absolute perceived health harm of e-cigarettes was assessed using a single item measure on a scale of 0 (not at all harmful) to 10 (extremely harmful) (Tackett et al., 2015).

2.4. Statistical analysis

All analyses were conducted using R [version 1.1.456]. Descriptive statistics were used to describe the distributions of perceived source credibility, ad relevance, ad effectiveness, liking, product use interest, and perceived e-cigarette harm. Next, we estimated unadjusted associations between covariates and perceived source credibility. We used linear mixed models with random intercepts, fit using restricted maximum likelihood, to estimate unadjusted associations between each covariate and perceived source credibility. In separate models, we also examined whether (1) e-cigarette use status and (2) cigarette smoking status moderated the effect of perceived source credibility on e-cigarette ad and product perceptions using interaction terms. Models controlled for covariates (age, sex, race and ethnicity, sexual orientation, and income), as well as cigarette smoking (in the e-cigarette interaction model) and e-cigarette use (in the cigarette interaction model. When statistically significant interactions were detected using partial F-tests, we reported stratified results. An alpha of 0.05 was used to assess statistical significance. We adjusted the alpha for multiple comparisons using Tukey’s test following detection of a statistically significant interaction.

3. Results

3.1. Participants

On average, participants (N = 497) were 31.9 years old (SD = 10.6) and self-identified as female (45.1%) or male (47.9%), straight or heterosexual (54.3%), Non-Hispanic White (71.2%), and reported individual incomes below $100,000 (76.5%; Table 1).

Table 1.

Characteristics of participants enrolled in an online experiment, 2021 (N = 497).a

N = 497
Age; mean (sd) 31.9 (10.6)
Gender; n (%)
 Female 224 (45.1)
 Male 238 (47.9)
 Non-binary 35 (7.0)
Sexual Orientation; n (%)
 Straight or heterosexual 270 (54.3)
 Lesbian or gay 57 (11.5)
 Bisexual 142 (28.6)
 Other non-heterosexual 28 (5.6)
Race/ethnicityb; n (%)
 Non-Hispanic White 353 (71.2)
 Non-Hispanic Black 56 (11.3)
 Hispanic 54 (10.9)
 Other/multiple 33 (6.6)
Income; n (%)
 $0–9,999 88 (17.7)
 $10,000–19,999 51 (10.3)
 $20,000–29,999 45 (9.1)
 $30,000–39,999 41 (8.2)
 $40,000–49,999 45 (9.1)
 $50,000–59,999 27 (5.4)
 $60,000–69,999 17 (3.4)
 $70,000–79,999 25 (5.0)
 $80,000–89,999 19 (3.8)
 $90,000–99,999 22 (4.4)
 > $100,000 117 (23.5)
Open in a new tab
a

Participants were recruited from the online survey platform, Prolific.

b

One participant did not provide their race/ethnicity.

We detected several statistically significant associations between perceived source credibility and participant characteristics (Table 2). Participants who were older (b = 0.02, 95% CI: [0.01, 0.03], p < 0.001), male (b = 0.91, 95% CI: [0.68, 1.13], p < 0.001), current e-cigarette users (b = 0.70, 95% CI: [0.44, 0.96], p < 0.001), current smokers (b = 0.89, 95% CI: [0.66, 1.12], p < 0.001), Non-Hispanic Black (b = 0.44, 95% CI: [0.07, 0.81], p < 0.02), and had higher incomes (b = 0.12, 95% CI: [0.09, 0.15], p < 0.001) rated the e-cigarette advertising source as more credible on average.

Table 2.

Unadjusted associations between perceived source credibility and covariates (N = 497).

Variable b 95% CI P-value
Age 0.02 0.01, 0.03 <0.001
Gender
Female (ref)
Male 0.91 0.68, 1.13 <0.001
Other −0.25 −0.69, 0.20 0.276
E-cigarette usea
Never (ref)
Ever −0.16 −0.46, 0.14 0.294
Current 0.70 0.44, 0.96 <0.001
Cigarette smokingb
Non-smoking (ref)
Currently smoking 0.89 0.66, 1.12 <0.001
Sexual orientation
Straight (ref)
Gay/lesbian −0.98 −1.33, −0.62 <0.001
Bisexual −0.82 −1.07, −0.56 <0.001
Other −1.07 −1.55, −0.58 <0.001
Race/ethnicity
Non-Hispanic White (ref)
Non-Hispanic Black 0.44 0.07, 0.81 0.02
Other/multiple −0.29 −0.75, 0.18 0.228
Hispanic −0.46 −0.84, −0.09 0.016
Incomec 0.12 0.09, 0.15 <0.001
Open in a new tab
a

Participants were “never” users of e-cigarettes if they reported never using the product, even once; “former” users of e-cigarettes or other tobacco if they reported using the product at least once, but not in the past 30 days; and “current” users of e-cigarettes or other tobacco if they reported using the product at least once in the past 30 days.

b

Participants were non-smokers if they reported not smoking in the past 30 days and current smokers if they smoked in the past 30 days.

c

Income was treated as a continuous variable consisting of 11 levels ($0–9,999 to >$100,000 in increments of $10,000).

3.2. Associations of perceived source credibility with ad responses

Participants with greater perceived source credibility reported greater perceived relevance (b = 0.22, 95% CI: [0.16, 0.28], p < 0.001), effectiveness (b = 0.33, 95% CI: [0.26, 0.41], p < 0.001), and liking of the ad (b = 0.41, 95% CI: [0.34, 0.49], p < 0.001; Table 3).

Table 3.

Adjusted models estimating main effect of source credibility and interaction effects of source credibility and e-cigarette use on ad and e-cigarette perceptions (N = 497).a

Variable b 95% CI P-value
Perceived ad relevance
Source credibility (stratified by e-cigarette use) Never 0.22 0.16, 0.28 <0.001
Ever −0.02a −0.31, 0.27 0.91
Current 0.11b −0.20, 0.42 0.491
Perceived ad effectiveness
Source credibility (stratified by e-cigarette use) Never 0.33 0.27, 0.40 <0.001
Ever −0.03a −0.33, 0.28 0.868
Current −0.34a −0.66, −0.02 0.038
Ad liking
Source credibility 0.41 0.36, 0.46 <0.001
Use interest
Source credibility (stratified by e-cigarette use) Never 0.16 0.08,0.23 <0.001
Ever 0.17a −0.18, 0.52 0.335
Current 0.18b −0.18, 0.55 0.329
Harm perceptions
Source credibility −0.04 −0.10, 0.03 0.278
Open in a new tab
a

Linear mixed effects models with random intercepts were used to estimate associations. We report significant main effects and interaction effects for perceived source credibility and e-cigarette use status on outcome variables. Covariates included age, gender, sexual orientation, race, ethnicity, and cigarette use. P-values were calculated using partial F-tests. Tukey’s tests were used to assess statistical significance of pairwise comparisons. P-values that meet the criteria for statistical significance are bolded. Means without a common superscript letter differ (p < 0.001). Models analyzed the interaction between e-cigarette use status and age group, but results are only stratified by age group status when the interaction was statistically significant. Stratified results are presented from models with statistically significant (p < 0.05) interactions between age group and e-cigarette use status.

E-cigarette use moderated the effect of perceived source credibility on perceived ad relevance (p < 0.001; Table 3). A one-unit increase in perceived source credibility was associated with increased perceived ad relevance among participants who had never used an e-cigarette (b = 0.22, 95% CI: [0.16, 0.28], p < 0.001), but perceived source credibility was not associated with perceived ad relevance among current and ever e-cigarette users. Cigarette smoking status also moderated the effect of perceived source credibility on perceived ad relevance (p < 0.001; Table 4). A one-unit increase in perceived source credibility was associated with increased perceived ad relevance among participants who had never smoked a cigarette (b = 0.22, 95% CI: [0.17, 0.27], p < 0.001), but perceived source credibility was not associated with perceived ad relevance among current cigarette smokers.

Table 4.

Adjusted models estimating main effect of source credibility and interaction effects of source credibility and cigarette use on ad and e-cigarette perceptions (N = 497).a

Variable b 95% CI P-value
Perceived ad relevance
Source credibility (stratified by cigarette smoking) Non-smokers 0.22 0.17, 0.27 <0.001
Current smokers 0.04 −0.26, 0.34 0.781
Perceived ad effectiveness
Source credibility (main effect) 0.39 0.34, 0.43 <0.001
Ad liking
Source credibility (main effect) 0.41 0.36, 0.46 <0.001
Use interest
Source credibility (stratified by cigarette smoking) Non-smokers 0.17 0.12,0.23 <0.001
Current smokers 0.08 −0.27, 0.43 0.656
Harm perceptions
Source credibility (main effect) −0.04 −0.10, 0.03 0.278
Open in a new tab
a

Linear mixed effects models with random intercepts were used to estimate associations. We report significant main effects and interaction effects for perceived source credibility and cigarette smoking status on outcome variables. Covariates included age, gender, sexual orientation, race, ethnicity, and e-cigarette use.

E-cigarette use moderated the effect of perceived source credibility on perceived ad effectiveness (p < 0.001; Table 3). Among participants who had never used an e-cigarette, a one-unit increase in perceived source credibility was associated with increased perceived ad effectiveness (b = 0.33, 95% CI: [0.27, 0.40], p < 0.001). Among current e-cigarette users, a one-unit increase in perceived source credibility was associated with decreased perceived ad effectiveness (b = -0.34, 95% CI: [-0.66, −0.02], p = 0.038). Perceived source credibility was not associated with perceived ad effectiveness among ever e-cigarette users. Cigarette smoking status did not moderate the association between perceived source credibility and perceived ad effectiveness (Table 4).

Neither e-cigarette use nor cigarette smoking status moderated the effect of perceived source credibility on ad liking (Table 3, Table 4, respectively).

3.3. Associations of perceived source credibility with e-cigarette product responses

Participants with greater perceived source credibility had greater interest in using the advertised products (b = 0.16, 95% CI: [0.08, 0.23], p < 0.001; Table 3). Perceived source credibility was not associated with e-cigarette harm perceptions.

E-cigarette use status moderated the effect of perceived source credibility on interest in using the advertised products (p < 0.001, Table 3). A one-unit increase in perceived source credibility was associated with increased interest in using e-cigarettes among participants who had never used e-cigarettes (b = 0.16, 95% CI: [0.08, 0.23], p < 0.001), but perceived source credibility was not associated with use interest among current and ever e-cigarette users. Cigarette smoking status also moderated the effect of perceived source credibility and interest in using the advertised product (p < 0.001; Table 4). Among nonsmokers, a one-unit increase in perceived source credibility was associated with increased interest in using e-cigarettes (b = 0.17, 95% CI: [0.12, 0.23], p < 0.001), but the association was nonsignificant among current smokers.

Neither e-cigarette use nor cigarette smoking status moderated the association between source credibility and e-cigarette harm perceptions (Table 3, Table 4, respectively).

4. Discussion

Using real-world ads by popular e-cigarette companies (Liu et al., 2018), our study found that perceived source credibility of e-cigarette ads was associated with increased perceived ad relevance, effectiveness, liking, and interest in using the advertised e-cigarette products. Furthermore, these associations were strongest for never e-cigarette users. In other words, we identified that perceiving e-cigarette companies as credible when viewing real-world ads increases favorable perceptions toward the ads and interest in using the advertised e-cigarette products—particularly among adults who have never used an e-cigarette. Results suggest that public health messaging that challenges the credibility of e-cigarette companies may be an effective method to reduce the influence of e-cigarette ads on e-cigarette related attitudes among adults who have never used e-cigarettes.

Our findings that positive associations between perceived source credibility and e-cigarette ad and product perceptions were generally strongest among adults who had never used e-cigarettes and were nonsmokers suggests that perceived source credibility is one mechanism by which e-cigarette advertisements might persuade nonusers to use e-cigarettes (Pokhrel et al., 2019, Lienemann et al., 2018, Pierce et al., 2017). We also identified that perceived source credibility was negatively associated with perceived ad effectiveness among current e-cigarette users. These findings align with existing research that demonstrates differences in the trusted sources of tobacco-related health information between tobacco users and non-users (Guttman and Peleg, 2003, Rutten et al., 2009). It is also possible that the current e-cigarette users in our study held pre-existing positive attitudes toward their preferred e-cigarette brand, and that they were shown a randomly-selected ad from an e-cigarette brand that they did not prefer and thus found less credible (Falomir and Invernizzi, 1999). Altogether, results suggest that e-cigarette public health education campaign messages targeting people who have never used e-cigarettes could capitalize on counter-industry strategies (i.e., e-cigarette denormalization messages). Such counter-industry messaging might be less effective among current e-cigarette users, thus requiring additional strategies that restrict appealing ad features (e.g., social benefits and flavor (Villanti et al., 2021)).

Perceived source credibility was not associated with perceptions of e-cigarette harm in our sample, which contrasts prior research (Vogel et al., 2020). Furthermore, neither e-cigarette use status nor cigarette smoking status moderated these associations. Because increased harm perceptions are associated with reduced e-cigarette use among adults (Wang et al., 2021, Zhu et al., 2017, Levy et al., 2018, Biener and Hargraves, 2015), more research is needed to understand factors that influence harm perceptions of e-cigarettes to effectively communicate about the health harms of e-cigarettes to tobacco non-users. Future research into e-cigarette harm perceptions might also consider how to communicate harms of e-cigarettes to nonusers while still positioning e-cigarettes as a potential harm reduction tool for smokers (Wackowski et al., 2020).

Finally, we found several sociodemographic correlates of perceived source credibility. Individuals who self-identified as Non-Hispanic Black perceived e-cigarette ad companies as more credible than those who self-identified as Non-Hispanic White. These racial differences may reflect historical and targeted marketing by the tobacco industry toward marginalized social groups (Primack et al., 2007). This finding suggest that specific social groups might benefit from targeted interventions that aim to reduce the credibility of e-cigarette companies.

5. Limitations and future directions

Our study has limitations related to sampling and data collection methods. Because we used convenience sampling, our findings are not generalizable to the US population. However, tobacco research studies using online convenience sampling have found comparable results to studies using probability sampling (Jeong et al., 2018). Additionally, we used self-reported measures to collect data, which raises the potential for social desirability bias in reporting tobacco-related behaviors (Rozin and Singh, 1999). Despite these limitations, the results from our study present opportunities for future research to examine the effects of counter-industry marketing on e-cigarette ad perceptions, product perceptions, and use behaviors. From a harm reduction perspective, public health messaging may also capitalize on perceived source credibility to convey the potential health benefits of using e-cigarettes for adults who smoke.

6. Conclusions

This study provides some of the first evidence that source credibility influences consumer perceptions of e-cigarette advertising and the advertised e-cigarette products. Our findings showed that perceived source credibility of real-world advertisements was associated with positive consumer perceptions of ad relevance, effectiveness, liking, and increased interest in using the advertised e-cigarette products. Additionally, we found that e-cigarette use and cigarette smoking moderated these associations, with effects of perceived source credibility on e-cigarette ad and product perceptions generally being the strongest among adults who had never used e-cigarettes and nonsmokers. These findings indicate a need for targeted health messaging based on e-cigarette use and cigarette smoking status. Findings from our study underscore that counter-industry tactics that reduce the credibility of e-cigarette companies might be particularly effective among people who do not use e-cigarettes and nonsmokers.

Funding

This work was funded by the National Institute on Drug Abuse of the National Institutes of Health (NIH) under award R00DA046563 (EMS, PI) and supported by the NIH National Cancer Institute (NCI) under award numbers T32CA172009 (DNL), T32CA057711-27 (JL) and T32CA229114 (JGP) Research reported in this publication was supported by NCI and FDA Center for Tobacco Products (CTP) (K99CA260718; PI: JGP). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH or the Food and Drug Administration.

CRediT authorship contribution statement

Donghee N. Lee: Conceptualization, Methodology, Investigation, Writing – original draft. Jessica Liu: Formal analysis, Methodology, Data curation, Writing – review & editing. Brittney Keller-Hamilton: Data curation, Investigation, Writing – review & editing. Joanne G. Patterson: Data curation, Writing – review & editing. Amelia V. Wedel: Writing – review & editing. Coralia Vázquez-Otero: Writing – review & editing, Data curation. Elise M. Stevens: Funding acquisition, Data curation, Investigation, Methodology, Writing – review & editing, Supervision.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

References

  1. Cornelius M.E., Wang T.W., Jamal A., Loretan C.G., Neff L.J. Tobacco product use among adults — United States, 2019. MMWR Morb. Mortal. Wkly. Rep. 2020;69(46):1736–1742. doi: 10.15585/mmwr.mm6946a4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. National Academies of Sciences, Engineering, and Medicine. Public Health Consequences of E-Cigarettes. National Academies Press; 2018. http://www.ncbi.nlm.nih.gov/books/NBK507171/. [PubMed]
  3. Overbeek D.L., Kass A.P., Chiel L.E., Boyer E.W., Casey A.M.H. A review of toxic effects of electronic cigarettes/vaping in adolescents and young adults. Crit. Rev. Toxicol. 2020;50(6):531–538. doi: 10.1080/10408444.2020.1794443. [DOI] [PubMed] [Google Scholar]
  4. Skotsimara G., Antonopoulos A.S., Oikonomou E., Siasos G., Ioakeimidis N., Tsalamandris S., Charalambous G., Galiatsatos N., Vlachopoulos C., Tousoulis D. Cardiovascular effects of electronic cigarettes: a systematic review and meta-analysis. Eur. J. Prev. Cardiol. 2019;26(11):1219–1228. doi: 10.1177/2047487319832975. [DOI] [PubMed] [Google Scholar]
  5. Hair, E.C., Barton, A.A., Perks, S.N., et al. Association between e-cigarette use and future combustible cigarette use: Evidence from a prospective cohort of youth and young adults, 2017-2019. Addict. Behav. 2021;112:106593. doi:10.1016/j.addbeh.2020.106593. [DOI] [PubMed]
  6. Khouja J.N., Suddell S.F., Peters S.E., Taylor A.E., Munafò M.R. Is e-cigarette use in non-smoking young adults associated with later smoking? A systematic review and meta-analysis. Tob Control. 2021;30(1):8–15. doi: 10.1136/tobaccocontrol-2019-055433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Soneji S., Barrington-Trimis J.L., Wills T.A., Leventhal A.M., Unger J.B., Gibson L.A., Yang J.W., Primack B.A., Andrews J.A., Miech R.A., Spindle T.R., Dick D.M., Eissenberg T., Hornik R.C., Dang R., Sargent J.D. Association between initial use of e-cigarettes and subsequent cigarette smoking among adolescents and young adults: a systematic review and meta-analysis. JAMA Pediatr. 2017;171(8):788. doi: 10.1001/jamapediatrics.2017.1488. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Noel JK, Rees VW, Connolly GN. Electronic cigarettes: a new ‘tobacco’ industry? Tob Control. 2011;20(1):81-81. doi:10.1136/tc.2010.038562. [DOI] [PubMed]
  9. Huang J., Kornfield R., Szczypka G., Emery S.L. A cross-sectional examination of marketing of electronic cigarettes on Twitter. Tob Control. 2014;23(suppl 3):iii26–iii30. doi: 10.1136/tobaccocontrol-2014-051551. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Banerjee S., Shuk E., Greene K., Ostroff J. Content analysis of trends in print magazine tobacco advertisements. Tob Regul Sci. 2015;1(2):103–120. doi: 10.18001/TRS.1.2.1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Mantey D.S., Cooper M.R., Clendennen S.L., Pasch K.E., Perry C.L. E-Cigarette marketing exposure is associated with e-cigarette use among US Youth. J. Adolesc. Health Off. Publ. Soc. Adolesc. Med. 2016;58(6):686–690. doi: 10.1016/j.jadohealth.2016.03.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Londerée A.M., Roberts M.E., Wewers M.E., Peters E., Ferketich A.K., Wagner D.D. Adolescent attentional bias toward real-world flavored e-cigarette marketing. Tob. Regul. Sci. 2018;4(6):57–65. doi: 10.18001/TRS.4.6.6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Pokhrel P., Herzog T.A., Fagan P., Unger J.B., Stacy A.W. E-cigarette advertising exposure, explicit and implicit harm perceptions, and e-cigarette use susceptibility among nonsmoking young adults. Nicotine Tob. Res. Off. J. Soc. Res. Nicotine Tob. 2019;21(1):127–131. doi: 10.1093/ntr/nty030. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Wang R.J., Bhadriraju S., Glantz S.A. E-Cigarette use and adult cigarette smoking cessation: a meta-analysis. Am J Public Health. 2021;111(2):230–246. doi: 10.2105/AJPH.2020.305999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Hovland C.I., Janis I.L., Kelley H.H. Yale University Press; 1953. Communication and Persuasion. [Google Scholar]
  16. Case K.R., Lazard A.J., Mackert M.S., Perry C.L. Source Credibility and E-Cigarette Attitudes: Implications for Tobacco Communication. Health Commun. 2018;33(9):1059–1067. doi: 10.1080/10410236.2017.1331190. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Pornpitakpan C. The persuasiveness of source credibility: a critical review of five decades’ evidence. J Appl Soc Psychol. 2004;34(2):243–281. doi: 10.1111/j.1559-1816.2004.tb02547.x. [DOI] [Google Scholar]
  18. Hovland C.I., Weiss W. The influence of source credibility on communication effectiveness. Public Opin. Q. 1951;15(4):635–650. doi: 10.1086/266350. [DOI] [Google Scholar]
  19. Freeman B., Chapman S. Open source marketing: Camel cigarette brand marketing in the “Web 2.0” world. Tob. Control. 2009;18(3):212–217. doi: 10.1136/tc.2008.027375. [DOI] [PubMed] [Google Scholar]
  20. Grana R.A., Ling P.M. “Smoking revolution”: a content analysis of electronic cigarette retail websites. Am. J. Prev. Med. 2014;46(4):395–403. doi: 10.1016/j.amepre.2013.12.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Watts C., Burton S., Freeman B. ‘The last line of marketing’: Covert tobacco marketing tactics as revealed by former tobacco industry employees. Glob. Public Health. 2021;16(7):1000–1013. doi: 10.1080/17441692.2020.1824005. [DOI] [PubMed] [Google Scholar]
  22. Padon A.A., Maloney E.K., Cappella J.N. Youth-targeted e-cigarette marketing in the US. Tob. Regul. Sci. 2017;3(1):95–101. doi: 10.18001/TRS.3.1.9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Alcalá H.E., Shimoga S.V. It is about trust: trust in sources of tobacco health information, perceptions of harm, and use of e-cigarettes. Nicotine Tob Res. 2020;22(5):822–826. doi: 10.1093/ntr/ntz004. [DOI] [PubMed] [Google Scholar]
  24. Erku D.A., Bauld L., Dawkins L., Gartner C.E., Steadman K.J., Noar S.M., Shrestha S., Morphett K. Does the content and source credibility of health and risk messages related to nicotine vaping products have an impact on harm perception and behavioural intentions? A systematic review. Addiction. 2021;116(12):3290–3303. doi: 10.1111/add.15473. [DOI] [PubMed] [Google Scholar]
  25. Vereen R.N., Westmaas J.L., Bontemps-Jones J., Jackson K., Alcaraz K.I. Trust of information about tobacco and e-cigarettes from health professionals versus tobacco or electronic cigarette companies: differences by subgroups and implications for tobacco messaging. Health Commun. 2020;35(1):89–95. doi: 10.1080/10410236.2018.1544875. [DOI] [PubMed] [Google Scholar]
  26. Malone R.E., Grundy Q., Bero L.A. Tobacco industry denormalisation as a tobacco control intervention: a review. Tob Control. 2012;21(2):162–170. doi: 10.1136/tobaccocontrol-2011-050200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Farrelly M.C., Healton C.G., Davis K.C., Messeri P., Hersey J.C., Haviland M.L. Getting to the truth: evaluating national tobacco countermarketing campaigns. Am J Public Health. 2002;92(6):901–907. doi: 10.2105/ajph.92.6.901. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Niederdeppe J., Farrelly M.C., Haviland M.L. Confirming “truth”: more evidence of a successful tobacco countermarketing campaign in Florida. Am J Public Health. 2004;94(2):255–257. doi: 10.2105/ajph.94.2.255. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Hershey J.C., Niederdeppe J., Evans W.D., Nonnemaker J., Blahut S., Holden D., Messeri P., Haviland M.L. The theory of “truth”: how counterindustry campaigns affect smoking behavior among teens. Health Psychol. Off. J. Div. Health Psychol. Am. Psychol. Assoc. 2005;24(1):22–31. doi: 10.1037/0278-6133.24.1.22. [DOI] [PubMed] [Google Scholar]
  30. Phua J., Jin S.V., Hahm J.M. Celebrity-endorsed e-cigarette brand Instagram advertisements: Effects on young adults’ attitudes towards e-cigarettes and smoking intentions. J. Health Psychol. 2018;23(4):550–560. doi: 10.1177/1359105317693912. [DOI] [PubMed] [Google Scholar]
  31. Vogel, E.A., Ramo, D.E., Rubinstein, M.L., et al., Effects of Social Media on Adolescents’ Willingness and Intention to Use E-Cigarettes: An Experimental Investigation. Nicotine Tob Res. 2020;23(4):694-701. doi:10.1093/ntr/ntaa003. [DOI] [PMC free article] [PubMed]
  32. Iles, I.A., Gillman, A.S., Klein, W.M.P., Ferrer, R.A., Kaufman, A., Associations between absolute and relative electronic cigarette harm perceptions and information-seeking behaviours among US adult current, former and never smokers. Drug Alcohol Rev. n/a(n/a). doi:10.1111/dar.13368. [DOI] [PubMed]
  33. Lienemann, B.A., Rose, S.W., Unger, J.B., et al. Tobacco advertisement liking, vulnerability factors, and tobacco use among young adults. Nicotine Tob. Res. 2018;21(3):300-308. doi: 10.1093/ntr/nty220. [DOI] [PMC free article] [PubMed]
  34. Moran, M.B., Pierce, J.P., Weiger, C., Cunningham, M.C., Sargent, J.D., The use of imagery and text that could convey reduced harm in american spirit advertisements. Tob Control. 2017;26(E1):e68-e70. doi:10.1136/tobaccocontrol-2016-053251. [DOI] [PMC free article] [PubMed]
  35. Noar S.M., Barker J., Bell T., Yzer M. Does perceived message effectiveness predict the actual effectiveness of tobacco education messages? A systematic review and meta-analysis. Health Commun. 2020;35(2):148–157. doi: 10.1080/10410236.2018.1547675. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Pavlou P.A., Stewart D.W. Measuring the effects and effectiveness of interactive advertising: a research agenda. J. Interact. Advert. 2000;1(1):61–77. doi: 10.1080/15252019.2000.10722044. [DOI] [Google Scholar]
  37. Pechmann C., Stewart D.W. The effects of comparative advertising on attention, memory, and purchase intentions. J Consum. Res. 1990;17(2):180–191. doi: 10.1086/208548. [DOI] [Google Scholar]
  38. Moran M.B., Heley K., Czaplicki L., Weiger C., Strong D., Pierce J. Tobacco advertising features that may contribute to product appeal among US adolescents and young adults. Nicotine Tob. Res. Off. J. Soc. Res. Nicotine Tob. 2021;23(8):1373–1381. doi: 10.1093/ntr/ntaa275. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Zhu S.H., Zhuang Y.L., Wong S., Cummins S.E., Tedeschi G.J. E-cigarette use and associated changes in population smoking cessation: evidence from US current population surveys. BMJ. 2017;358 doi: 10.1136/bmj.j3262. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Levy D.T., Yuan Z., Luo Y., Abrams D.B. The Relationship of E-Cigarette Use to Cigarette Quit Attempts and Cessation: Insights From a Large, Nationally Representative U.S. Survey. Nicotine Tob. Res. 2018;20(8):931–939. doi: 10.1093/ntr/ntx166. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Biener L., Hargraves J.L. A longitudinal study of electronic cigarette use among a population-based sample of adult smokers: association with smoking cessation and motivation to quit. Nicotine Tob. Res. 2015;17(2):127–133. doi: 10.1093/ntr/ntu200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Owusu, D., Lawley, R., Yang, B., et al., ‘The lesser devil you don’t know’: a qualitative study of smokers’ responses to messages communicating comparative risk of electronic and combusted cigarettes. Tob. Control. Published online April 30, 2019:tobaccocontrol-2018-054883. doi:10.1136/tobaccocontrol-2018-054883. [DOI] [PMC free article] [PubMed]
  43. Wackowski O.A., Rashid M., Greene K.L., Lewis M.J., O’Connor R.J. Smokers’ and young adult non-smokers’ perceptions and perceived impact of snus and e-cigarette modified risk messages. Int. J. Environ. Res. Public Health. 2020;17(18):6807. doi: 10.3390/ijerph17186807. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Schmidt A.M., Ranney L.M., Pepper J.K., Goldstein A.O. Source credibility in tobacco control messaging. Tob. Regul. Sci. 2016;2(1):31–37. doi: 10.18001/TRS.2.1.3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Guttman N., Peleg H. Public preferences for an attribution to government or to medical research versus unattributed messages in cigarette warning labels in Israel. Health Commun. 2003;15(1):1–25. doi: 10.1207/S15327027HC1501_1. [DOI] [PubMed] [Google Scholar]
  46. Zagona S.V., Harter M.R. Credibility of source and recipient’s attitude: factors in the perception and retention of information on smoking behavior. Percept. Mot. Skills. 1966;23(1):155–168. doi: 10.2466/pms.1966.23.1.155. [DOI] [PubMed] [Google Scholar]
  47. Choi K., Forster J.L. Beliefs and experimentation with electronic cigarettes: a prospective analysis among young adults. Am. J. Prev. Med. 2014;46(2):175–178. doi: 10.1016/j.amepre.2013.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Villanti A.C., Cobb C.O., Cohn A.M., Williams V.F., Rath J.M. Correlates of hookah use and predictors of hookah trial in U.S. young adults. Am. J. Prev. Med. 2015;48(6):742–746. doi: 10.1016/j.amepre.2015.01.010. [DOI] [PubMed] [Google Scholar]
  49. Wackowski O.A., Delnevo C.D. Young Adults’ Risk Perceptions of Various Tobacco Products Relative to Cigarettes: Results From the National Young Adult Health Survey. Health Educ. Behav. Off. Publ. Soc. Public Health Educ. 2016;43(3):328–336. doi: 10.1177/1090198115599988. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Leavens E.L.S., Meier E., Brett E.I., Stevens E.M., Tackett A.P., Villanti A.C., Wagener T.L. Polytobacco use and risk perceptions among young adults: The potential role of habituation to risk. Addict. Behav. 2019;90:278–284. doi: 10.1016/j.addbeh.2018.11.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Liu, J., Vázquez-Otero, C., Berman, M.L., Stevens, E.M., Youth-appealing features in popular e-cigarette brand advertising in the USA after heightened scrutiny in 2018. Tob Control. Published online October 21, 2021:tobaccocontrol-2021-056720. doi: 10.1136/tobaccocontrol-2021-056720. [DOI] [PMC free article] [PubMed]
  52. McCroskey J.C., Teven J.J. Goodwill: a reexamination of the construct and its measurement. Commun. Monogr. 1999;66(1):90–103. [Google Scholar]
  53. Jensen J.D., King A.J., Carcioppolo N., Davis L. Why are tailored messages more effective? A multiple mediation analysis of a breast cancer screening intervention. J Commun. 2012;62(5):851–868. doi: 10.1111/j.1460-2466.2012.01668.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Davis K.C., Nonnemaker J., Duke J., Farrelly M.C. Perceived effectiveness of cessation advertisements: The importance of audience reactions and practical implications for media campaign planning. Health Commun. 2013;28(5):461–472. doi: 10.1080/10410236.2012.696535. [DOI] [PubMed] [Google Scholar]
  55. Tackett A.P., Lechner W.V., Meier E., Grant D.M., Driskill L.M., Tahirkheli N.N., Wagener T.L. Biochemically verified smoking cessation and vaping beliefs among vape store customers. Addiction. 2015;110(5):868–874. doi: 10.1111/add.12878. [DOI] [PubMed] [Google Scholar]
  56. Pierce J.P., Sargent J.D., White M.M., Borek N., Portnoy D.B., Green V.R., Kaufman A.R., Stanton C.A., Bansal-Travers M., Strong D.R., Pearson J.L., Coleman B.N., Leas E., Noble M.L., Trinidad D.R., Moran M.B., Carusi C., Hyland A., Messer K. Receptivity to tobacco advertising and susceptibility to tobacco products. Pediatrics. 2017;139(6):e20163353. doi: 10.1542/peds.2016-3353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Rutten L.J.F., Augustson E.M., Doran K.A., Moser R.P., Hesse B.W. Health information seeking and media exposure among smokers: a comparison of light and intermittent tobacco users with heavy users. Nicotine Tob. Res. Off. J. Soc. Res. Nicotine Tob. 2009;11(2):190–196. doi: 10.1093/ntr/ntn019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Falomir J.M., Invernizzi F. The role of social influence and smoker identity in resistance to smoking cessation. Swiss J Psychol. 1999;58(2):73. doi: 10.1024/1421-0185.58.2.73. [DOI] [Google Scholar]
  59. Villanti, A.C., LePine, S.E., West, J.C., et al. Identifying message content to reduce vaping: results from online message testing trials in young adult tobacco users. Addict. Behav. 2021;115:106778. doi: 10.1016/j.addbeh.2020.106778. [DOI] [PMC free article] [PubMed]
  60. Primack B.A., Bost J.E., Land S.R., Fine M.J. Volume of tobacco advertising in african american markets: systematic review and meta-analysis. Public Health Rep. 2007;122(5):607–615. doi: 10.1177/003335490712200508. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Jeong, M., Zhang, D., Morgan, J.C., et al. Similarities and Differences in Tobacco Control Research Findings From Convenience and Probability Samples. Ann Behav Med Publ Soc Behav Med. 2018;53(5):476-485. doi: 10.1093/abm/kay059. [DOI] [PMC free article] [PubMed]
  62. Rozin, P., Singh, L., The moralization of cigarette smoking in the United States. J. Consum. Psychol. 1999;8(3):321-337.

Articles from Preventive Medicine Reports are provided here courtesy of Elsevier

RESOURCES