Vaping and Instagram: A Content Analysis of e-Cigarette Posts Using the Content Appealing to Youth (CAY) Index

Effects of a Social Media Intervention on Vaping Intentions: Randomized Dose-Response Experiment

BACKGROUND

e-Cigarette use, especially by young adults, is at unacceptably high levels and represents a public health risk factor. Digital media are increasingly being used to deliver antivaping campaigns, but little is known about their effectiveness or the dose-response effects of content delivery.

OBJECTIVE

The objectives of this study were to evaluate (1) the effectiveness of a 60-day antivaping social media intervention in changing vaping use intentions and beliefs related to the stimulus content and (2) the dose-response effects of varying levels of exposure to the intervention on vaping outcomes, including anti-industry beliefs, vaping intentions, and other attitudes and beliefs related to vaping.

METHODS

Participants were adults aged 18 to 24 years in the United States. They were recruited into the study through Facebook (Meta Platforms) and Instagram (Meta Platforms), completed a baseline survey, and then randomized to 1 of the 5 conditions: 0 (control), 4, 8, 16, and 32 exposures over a 15-day period between each survey wave. Follow-up data were collected 30 and 60 days after randomization. We conducted stratified analyses of the full sample and in subsamples defined by the baseline vaping status (never, former, and current). Stimulus was delivered through Facebook and Instagram in four 15-second social media videos focused on anti-industry beliefs about vaping. The main outcome measures reported in this study were self-reported exposure to social media intervention content, attitudes and beliefs about vaping, and vaping intentions. We estimated a series of multivariate linear regressions in Stata 17 (StataCorp). To capture the dose-response effect, we assigned each study arm a numerical value corresponding to the number of advertisements (exposures) delivered to participants in each arm and used this number as our focal independent variable. In each model, the predictor was the treatment arm to which each participant was assigned.

RESULTS

The baseline sample consisted of 1491 participants, and the final analysis sample consisted of 57.28% (854/1491) of the participants retained at the 60-day follow-up. We compared the retained participants with those lost to follow-up and found no statistically significant differences across demographic variables. We found a significant effect of the social media treatment on vaping intentions (β=-0.138, 95% CI -0.266 to -0.010; P=.04) and anti-industry beliefs (β=-0.122, 95% CI 0.008-0.237; P=.04) targeted by the intervention content among current vapers but not among the full sample or other strata. We found no significant effects of self-reported exposure to the stimulus.

CONCLUSIONS

Social media interventions are a promising approach to preventing vaping among young adults. More research is needed on how to optimize the dosage of such interventions and the extent to which long-term exposure may affect vaping use over time.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04867668; https://clinicaltrials.gov/study/NCT04867668.

Objective Characteristics and Subjective Responses of 18-24-Year-Olds to U.S. nationally Televised Tobacco Advertisements

Background: Restrictions on televised tobacco ads do not apply to vaping and oral nicotine products. Several campaigns are currently active on U.S. national television. This research examines the extent to which objective ad features are associated with ad, brand, and product appeal and use intentions among 18-24-year-olds. Methods: We identified seven unique campaigns for Vuse, Velo, and JUUL from the Mintel Comperemedia database, coded for youth-appealing content, and then randomly assigned among N = 1450 18-24-year-olds. Following exposure to one 15-second ad, participants completed a survey assessing their subjective responses. Results: Youth-appealing content was prevalent across these ads to varying degrees. Mixed effects regression analyses showed a positive association between features from the Content Appealing to Youth (CAY) index and pro-social brand perceptions, positive attitudes, reactions, and perceived effectiveness of the ad, and positive use perceptions. Moreover, themes related to customization of the device and environmental sustainability were associated with similar positive perceptions, including that using the product would be cool, as well as behavioral intentions to try, use occasionally, and use daily. Conclusions: Regulators need to update tobacco advertising restrictions to accurately reflect the current tobacco product landscape. This study contributes to the research on tobacco promotion strategies by examining the current marketing landscape for newer tobacco products and their appeal to youth. Findings from this study inform comprehensive tobacco marketing regulations, recommending the FDA update its guidelines and apply current marketing restrictions to e-cigarettes and oral nicotine products.

Characterizing Anti-Vaping Posts for Effective Communication on Instagram Using Multimodal Deep Learning

INTRODUCTION

Instagram is a popular social networking platform for sharing photos with a large proportion of youth and young adult users. We aim to identify key features in anti-vaping Instagram image posts associated with high social media user engagement by artificial intelligence.

AIMS AND METHODS

We collected 8972 anti-vaping Instagram image posts and hand-coded 2200 Instagram images to identify nine image features such as warning signs and person-shown vaping. We utilized a deep-learning model, the OpenAI: contrastive language-image pre-training with ViT-B/32 as the backbone and a 5-fold cross-validation model evaluation, to extract similar features from the Instagram image and further trained logistic regression models for multilabel classification. Latent Dirichlet Allocation model and Valence Aware Dictionary and sEntiment Reasoner were used to extract the topics and sentiment from the captions. Negative binomial regression models were applied to identify features associated with the likes and comments count of posts.

RESULTS

Several features identified in anti-vaping Instagram image posts were significantly associated with high social media user engagement (likes or comments), such as educational warnings and warning signs. Instagram posts with captions about health risks associated with vaping received significantly more likes or comments than those about help quitting smoking or vaping. Compared to the model based on 2200 hand-coded Instagram image posts, more significant features have been identified from 8972 AI-labeled Instagram image posts.

CONCLUSION

Features identified from anti-vaping Instagram image posts will provide a potentially effective way to communicate with the public about the health effects of e-cigarette use.

IMPLICATIONS

Considering the increasing popularity of social media and the current vaping epidemic, especially among youth and young adults, it becomes necessary to understand e-cigarette-related content on social media. Although pro-vaping messages dominate social media, anti-vaping messages are limited and often have low user engagement. Using advanced deep-learning and statistical models, we identified several features in anti-vaping Instagram image posts significantly associated with high user engagement. Our findings provide a potential approach to effectively communicate with the public about the health risks of vaping to protect public health.

Understanding e-cigarette content and promotion on YouTube through machine learning

INTRODUCTION

YouTube is a popular social media used by youth and has electronic cigarette (e-cigarette) content. We used machine learning to identify the content of e-cigarette videos, featured e-cigarette products, video uploaders, and marketing and sales of e-cigarette products.

METHODS

We identified e-cigarette content using 18 search terms (eg, e-cig) using fictitious youth viewer profiles and predicted four models using the metadata as the input to supervised machine learning: (1) video themes, (2) featured e-cigarette products, (3) channel type (ie, video uploaders) and (4) discount/sales. We assessed the association between engagement data and the four models.

RESULTS

3830 English videos were included in the supervised machine learning. The most common video theme was 'product review' (48.9%), followed by 'instruction' (eg, 'how to' use/modify e-cigarettes; 17.3%); diverse e-cigarette products were featured; 'vape enthusiasts' most frequently posted e-cigarette videos (54.0%), followed by retailers (20.3%); 43.2% of videos had discount/sales of e-cigarettes; and the most common sales strategy was external links for purchasing (34.1%). 'Vape trick' was the least common theme but had the highest engagement (eg, >2 million views). 'Cannabis' (53.9%) and 'instruction' (49.9%) themes were more likely to have external links for purchasing (p<0.001). The four models achieved an F1 score (a measure of model accuracy) of up to 0.87.

DISCUSSION

Our findings indicate that on YouTube videos accessible to youth, a variety of e-cigarette products are featured through diverse videos themes, with discount/sales. The findings highlight the need to regulate the promotion of e-cigarettes on social media platforms.

Quantifying PG : VG ratio and nicotine content in commercially available e-liquids using handheld Raman spectroscopy

Electronic cigarettes are a popular nicotine consumption product that have risen in popularity as an alternative to cigarettes. However, their recent meteoric rise in market size and various controversies have resulted in the analyses of e-liquid ingredients to be focused on powerful laboratory-based slow methods such as chromatography and mass spectrometry. Here we present a complementary technology based on Raman spectroscopy combined with chemometrics as a fast, inexpensive, and highly portable screening tool to detect and quantify the propylene glycol : glycerol (PG : VG) ratio and nicotine content of e-cigarette liquids. Through this, the PG : VG ratio of 20 out of 23 commercial samples was quantified to within 3% of their stated value, while nicotine was successfully quantified to within 1 mg g-1 for 16 out of 23 samples without the need for accurate knowledge of flavonoid composition. High linearity was also achieved when flavours were kept constant. Finally, the limitations of Raman spectroscopy are discussed, and potential solutions are suggested.

Characteristics Associated with Young Adults' Intentions to Engage with Anti-Vaping Instagram Posts

The purpose of this study was to identify behavioral and sociodemographic factors associated with intentions to engage with anti-vaping Instagram posts among a young adult population. This study proposes the following research questions: (1) Does e-cigarette use status influence intentions to engage with anti-vaping Instagram posts?, and (2) How are e-cigarette use and social media use associated? We recruited a convenience sample of young adults (N = 459; aged 18-30 years) in July of 2022 into an online experimental study from Prolific. Participants saw five image-based Instagram posts about the health harms of using e-cigarettes. Participants were then asked about their intentions to engage ("Comment on", "Reshare", "DM/Send this to a friend", "Like", and/or "Take a screenshot of") with the posts. We used logistic regression to run adjusted models for each engagement outcome, which included fixed effects for sociodemographics, tobacco use, and social media/internet use. For the sum of the engagement outcome, we used Poisson regression. Total number of social media sites used was associated with intentions to "Like" the posts (p = 0.025) and the overall engagement score (p = 0.019), respectively. Daily internet use was associated with intentions to "Comment on" (p = 0.016) and "Like" (p = 0.019) the posts. Young adults who reported past 30-day e-cigarette use had higher odds of using Twitter (p = 0.013) and TikTok (p < 0.001), and a higher total number of social media sites used (p = 0.046), compared to young adults who reported never use e-cigarettes. The initial evidence from our exploratory research using a convenience sample suggests that social media campaigns about the harms of e-cigarette use may be an effective way to engage younger audiences, a generation that frequents social media. Efforts to disseminate social media campaigns should consider launching on multiple platforms, such as Twitter and TikTok, and consider e-cigarette use status when posting.

A Comparative Analysis of E-Cigarette and Cigarette Posts on Instagram

E-cigarette use has grown rapidly over the past decade and become a threat to public health. Marketing-especially through social media-has contributed significantly to this growth, which suggests that regulating content in social media will be critical in supporting efforts to reverse this trend. A content analysis was performed to compare 254 e-cigarette posts on Instagram with 228 cigarette posts on the same platform. The majority of e-cigarette posts were from e-cigarette companies (40.9%) and industry people (18.5%), whereas the majority of cigarette posts were from laypeople (76.8%). More e-cigarette posts than cigarette posts appeared to have a marketing intent (56.3% vs. 1.3%), and brand representation in photographs/videos was more frequent in the e-cigarette posts than in the cigarette posts (63.0% vs. 15.8%). Further, compared with the e-cigarette posts, the cigarette posts were more likely to portray daily life (73.2% vs. 41.3%) and humans (80.3% vs. 43.7%) in the photograph/video. The cigarette posts also portrayed smoking much more often than the e-cigarette posts portrayed vaping (67.1% vs. 21.3%). The study findings broaden the field's understanding of cigarette and e-cigarette content on Instagram and social media, and have implications for monitoring and regulating content for e-cigarettes and cigarettes.

E-Cigarette Retailers' Use of Instagram in New Zealand: A Content Analysis

E-cigarette companies claim their products are key to improving health outcomes by providing smokers with lower-risk alternatives. However, the rapid uptake of e-cigarettes among young people has prompted concern about company marketing practices. In 2019, there was no legislation to govern e-cigarette marketing in New Zealand. This period provides an ideal context for examining how e-cigarette companies promoted their products before the introduction of marketing regulations. We conducted a content analysis of the Instagram accounts of five prominent e-cigarette retailers based in New Zealand during 2019-2020. We assessed health- and risk-related claims and marketing techniques. Less than 10% of Instagram posts refer to smoking alternatives or risk of nicotine addiction. E-cigarette devices were more likely to be promoted for stylistic features such as colours and ease of use (29.7%). Music festival sponsorship (19.1%), social media influencers (9.2%), and lifestyle marketing (41.5%) were identified as youth-oriented promotional strategies. E-cigarette retailers claim to promote harm-reduction tools to smokers, yet this study finds few references to smoking alternatives in any content. Instead, retailers utilised strategies to engage with a young audience, including festival sponsorship and stylish influencers. This youth-oriented marketing, in combination with weak and delayed government action, may have contributed to the high use of e-cigarettes among young New Zealanders.

Examining influencer compliance with advertising regulations in branded vaping content on Instagram

Background

Youth and young adults are exposed to vaping advertisements on social media sites, despite regulations and guidelines intended to reduce the prevalence of such content on these platforms. This research uses replicable criteria to identify vaping influencers who have worked with vaping brands to promote vaping products on Instagram and documents the extent to which posts by these users comply with existing advertising regulations.

Methodology

We conducted three google searches collecting eight different vaping influencer lists, with a total of 575 unique influencers. We limited our sample to public accounts with 100,000 followers or more (n = 54). An initial sample of 360 Instagram posts was used to identify an analytic sample of 262 vape-related posts from 2021. We conducted a conceptual content analysis to first identify unambiguous vaping advertisements (branded content), and then code ads for compliance with existing regulations.

Results

On average, the 54 Instagram accounts had 265,851.9 followers (sd = 383,349.8) and 4,158 posts (sd = 7,302.1). Most posts featured vaping products 239 (91.2%), with 186 (76.2%) posts being unambiguously branded vape advertisements and 31 (14.3%) even including purchase links in the post itself. However, one post complied with FTC disclosure guidelines. Although 50 (20.9%) had warning labels, only 8 (15.1%) were fully compliant with FDA warning label guidelines.

Discussion

Findings demonstrate minimal compliance with existing regulations among influencers known to have financial relationships with vaping brands. Most influencer posts are unambiguous, branded, vaping advertisements. Implications for barriers to regulating influencer content and the need for greater enforcement resources are discussed.

Tech, Sex, and E-cigarettes: The Gendering of Vape Promotion on Instagram

The promotion of vape products on social media has been implicated in increasing rates of e-cigarette usage, particularly among youth and young adults. While research has examined overall trends in vape-related content across a number of platforms, the role that social media "influencers" play in promoting vaping and potentially augmenting this public health crisis has been insufficiently explored. The present study examined 44,052 Instagram posts by 60 male presenting and 60 female presenting vape influencers to understand how influencer gender mediates the performance of vape culture online. Our textual and visual analysis of these influencers' posts over one year revealed significant bifurcations based on gender. Independent sample t-tests showed statistically significant gender differences in word frequency. Male-presenting influencers tended to emphasize their expertise with vape devices as technologies, while female-presenting influencers tended to focus on their own appearance. Further, factor analysis indicated six major categories of textual features, and multiple linear regression tests showed varying levels of user engagement with the different categories across both genders. Chi-square tests indicated that female-presenting influencers highlighted their own bodies in the visual content of their posts, whereas male presenting influencers often posted images of vape devices or their component parts alone. These findings suggest that gender presentation plays an important role in shaping vape influencers' promotional tactics and vape-related content on Instagram, and also provides insights into what kinds of content receive the most user engagement. This study can therefore help inform interventions to mitigate the impact of social media vape promotion.

#NicotineAddictionCheck: Puff Bar Culture, Addiction Apathy, and Promotion of E-Cigarettes on TikTok

This study aimed to classify and delineate types of user-generated content about the disposable e-cigarette Puff Bar shared on the popular video-based social media platform TikTok. We qualitatively analyzed 148 popular TikTok videos collected in July 2020. During an iterative process of data reduction and thematic analysis, we categorized videos by overarching genres and identified emergent themes. Young adults were engaged at all stages of the research process. Together, videos were viewed over 137 million times on TikTok. Seven genres of Puff Bar content emerged: skits and stories, shared vaper experiences, videos to show off, product reviews, product unboxing, promotion of Puff Bar, and crafts. Videos depicted Puff Bar users’ apathy about addiction and a lack of concern of the health effects of e-cigarette use. Additionally, Puff Bar promotion content from underground retailers was extensive and some targeted underage persons. Qualitative analysis of social media content can richly describe emerging online culture and illuminate the motivations of adolescent and young adult e-cigarette use. Social media can facilitate new product adoption; comprehensive e-cigarette regulation and enforcement can counteract these effects by closing loopholes through which new products emerge.

Videos With the Hashtag #vaping on TikTok and Implications for Informed Decision-making by Adolescents: Descriptive Study

BACKGROUND

Despite the public health importance of vaping and the widespread use of TikTok by adolescents and young adults, research is lacking on the nature and scope of vaping content on this networking service.

OBJECTIVE

The purpose of this study is to describe the content of TikTok videos related to vaping.

METHODS

By searching the hashtag #vaping in the discover feature, ~478.4 million views were seen during the time of data collection. The first 100 relevant videos under that hashtag were used in this study. Relevance was determined by simply noting if the video was related in any way to vaping. Coding consisted of several categories directly related to vaping and additional categories, including the number of likes, comments, and views, and if the video involved music, humor, or dance.

RESULTS

The 100 videos included in the sample garnered 156,331,347 views; 20,335,800 likes; and 296,460 comments. The majority of the videos (n=59) used music and over one-third (n=37) used humor. The only content category observed in the majority of the videos sampled was the promotion of vaping, which was included in 57 videos that garnered over 74 million views (47.5% of cumulative views). A total of 42% (n=42) of the 100 videos sampled featured someone vaping or in the presence of vape pens, and these videos garnered over 22% (>35 million) of the total views.

CONCLUSIONS

It is necessary for public health agencies to improve understanding of the nature and content of videos that attract viewers' attention and harness the strength of this communication channel to promote informed decision-making about vaping.