Frequency of social media use and exposure to tobacco or nicotine-related content in association with E-cigarette use among youth: A cross-sectional and longitudinal survey analysis

Vassey, Julia; Galimov, Arthur; Kennedy, Chris; Vogel, Erin A.; Unger, Jennifer B.

doi:10.1016/j.pmedr.2022.102055

Cited by 21 publications

(14 citation statements)

References 27 publications

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“…14 , 15 Short video clips on social media (eg, Instagram and TikTok) often have higher attentional engagement compared to still images 14 and are also more popular among adolescents than longer videos, (eg, on YouTube). 16 Research 12 shows that adolescents had higher odds of e-cigarette lifetime and current (past 30-day) use and initiation if they frequently (several times a day) used TikTok compared to adolescents who used TikTok less frequently or not at all. Adolescents 12 also had higher odds of e-cigarette lifetime use if they were frequently exposed (at least weekly) to tobacco-related content on TikTok compared to adolescents who were exposed to tobacco-related content on TikTok monthly or less frequently.…”

Section: Introductionmentioning

confidence: 99%

“…16 Research 12 shows that adolescents had higher odds of e-cigarette lifetime and current (past 30-day) use and initiation if they frequently (several times a day) used TikTok compared to adolescents who used TikTok less frequently or not at all. Adolescents 12 also had higher odds of e-cigarette lifetime use if they were frequently exposed (at least weekly) to tobacco-related content on TikTok compared to adolescents who were exposed to tobacco-related content on TikTok monthly or less frequently. E-cigarette use in TikTok and Instagram videos is often shown by general users or influencers in the context of a positive experience, humor, and jokes, and as a socially acceptable behavior.…”

Section: Introductionmentioning

confidence: 99%

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Scalable Surveillance of E-Cigarette Products on Instagram and TikTok Using Computer Vision

Vassey,

Kennedy,

Herbert Chang

et al. 2023

Nicotine and Tobacco Research

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Introduction Instagram and TikTok, video-based social media platforms popular among adolescents, contain tobacco-related content despite the platforms’ policies prohibiting substance-related posts. Prior research identified themes in e-cigarette-related social media posts using qualitative or text-based machine learning methods. We developed an image-based computer vision model to identify e-cigarette products in social media images and videos. Methods We created a dataset of 6,999 Instagram images labeled for 8 object classes: mod or pod devices, e-juice containers, packaging boxes, nicotine warning labels, e-juice flavors, e-cigarette brand names, and smoke clouds. We trained a DyHead object detection model using a Swin-Large backbone, evaluated the model’s performance on 20 Instagram and TikTok videos, and applied the model to 14,072 e-cigarette-related promotional TikTok videos (2019-2022; 10,276,485 frames). Results The model achieved the following mean average precision scores on the image test set: e-juice container: 0.89; pod device: 0.67; mod device: 0.54; packaging box: 0.84; nicotine warning label: 0.86; e-cigarette brand name: 0.71; e-juice flavor name: 0.89; and smoke cloud: 0.46. The largest number of TikTok videos – 9,091 (65%) - contained smoke clouds, followed by mod and pod devices detected in 6,667 (47%) and 5,949 (42%) videos respectively. Prevalence of nicotine warning labels was the lowest, detected in 980 videos (7%). Conclusions Deep learning-based object detection technology enables automated analysis of visual posts on social media. Our computer vision model can detect the presence of e-cigarettes products in images and videos, providing valuable surveillance data for tobacco regulatory science. Implications Prior research identified themes in e-cigarette-related social media posts using qualitative or text-based machine learning methods. We developed an image-based computer vision model to identify e-cigarette products in social media images and videos. We trained a DyHead object detection model using a Swin-Large backbone, evaluated the model’s performance on 20 Instagram and TikTok videos featuring at least two e-cigarette objects, and applied the model to 14,072 e-cigarette-related promotional TikTok videos (2019-2022; 10,276,485 frames). The deep learning model can be used for automated, scalable surveillance of image- and video-based e-cigarette-related promotional content on social media, providing valuable data for tobacco regulatory science. Social media platforms could use computer vision to identify tobacco-related imagery and remove it promptly, which could reduce adolescents’ exposure to tobacco content online.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Scalable Surveillance of E-Cigarette Products on Instagram and TikTok Using Computer Vision

Vassey,

Kennedy,

Herbert Chang

et al. 2023

Nicotine and Tobacco Research

Self Cite

View full text Add to dashboard Cite

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“…Recent data indicate a surge in content related to vaping use on these platforms. Notably, the majority of messages are positive and favorable towards vaping [24]. Content in these messages ranges from personal testimonials about the benefits of vaping over traditional smoking to endorsements by influencers of specific e-cigarette brands and flavors [25].…”

Section: Social Media Marketing Strategies and Normalization Of Vapingmentioning

confidence: 99%

“…Individuals who are exposed to promotional or user-generated e-cigarette content have a lower perception of harm, have more positive attitudes toward vaping, and have a higher risk of initiating e-cigarette use [26,27]. For example, a recent longitudinal study found that adolescents who reported seeing e-cigarette posts at least one time a week on TikTok had a higher risk of lifetime and current e-cigarette use [24]. Findings also indicated that the frequency of TikTok use was a significant predictor of initiating e-cigarette use [24].…”

Section: Social Media Marketing Strategies and Normalization Of Vapingmentioning

confidence: 99%

“…For example, a recent longitudinal study found that adolescents who reported seeing e-cigarette posts at least one time a week on TikTok had a higher risk of lifetime and current e-cigarette use [24]. Findings also indicated that the frequency of TikTok use was a significant predictor of initiating e-cigarette use [24]. Findings from another study indicated that when young people on social media (friends, influencers, etc.)…”

Section: Social Media Marketing Strategies and Normalization Of Vapingmentioning

confidence: 99%

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Normalization of Vaping on TikTok: A Mixed-Methods Approach Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis (Preprint)

Jung,

Murthy,

Bateineh

et al. 2023

Journal of Medical Internet Research

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Background: Posts on social media that depict vaping in positive social situations serve to shape expectations about vaping, suggesting it is socially acceptable. TikTok, a social media platform popular among adolescents, has such content, despite restrictions on uploading depictions or promotions of controlled substances. There is a need to understand strategies employed in promoting vaping on TikTok, especially among susceptible youth audiences. JMIR PreprintsJung et al success rate in classifying 'vaping cessation.'Our study provides valuable insights for regulatory policies and public health initiatives aimed at tackling the normalization of vaping on social media platforms.

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Health Warnings on Instagram Advertisements for Synthetic Nicotine E-Cigarettes and Engagement

Wu,

Trifiro,

Ranker

et al. 2024

JAMA Netw Open

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ImportanceSynthetic nicotine is increasingly used in e-cigarette liquids along with flavors to appeal to youths. Regulatory loopholes have allowed tobacco manufacturers to use social media to target youths.ObjectiveTo analyze the extent to which synthetic nicotine e-cigarette brands have implemented US Food and Drug Administration (FDA) health warning requirements and to evaluate the association between health warnings and user engagement on Instagram.Design, Setting, and ParticipantsIn this cross-sectional study, posts from 25 brands were analyzed across a 14-month period (August 2021 to October 2022). A content analysis was paired with Warning Label Multi-Layer Image Identification, a computer vision algorithm designed to detect the presence of health warnings and whether the detected health warning complied with FDA guidelines by (1) appearing on the upper portion of the advertisement and (2) occupying at least 20% of the advertisement’s area. Data analysis was performed from March to June 2024.ExposureSynthetic nicotine e-cigarette advertisement on Instagram.Main Outcomes and MeasuresThe outcome variables were user engagement (number of likes and comments). Negative binomial regression analyses were used to evaluate the association between the presence and characteristics of health warnings and user engagement.ResultsOf a total of 2071 posts, only 263 (13%) complied with both FDA health warning requirements. Among 924 posts with health warnings, 732 (79%) displayed warnings in the upper image portion, and 270 (29%) had a warning covering at least 20% of the pixel area. Posts with warnings received fewer comments than posts without warnings (mean [SD], 1.8 [2.5] vs 5.4 [11.7] comments; adjusted incident rate ratio [aIRR], 0.70; 95% CI, 0.57-0.86; P &lt; .001). For posts containing warnings, a larger percentage of the warning label’s pixel area was associated with fewer comments (aIRR, 0.96; 95% CI, 0.93-0.99; P = .003). Flavored posts with health warnings placed in the upper image portion received more likes than posts with warnings in the lower portion (mean [SD], 34.6 [35.2] vs 19.9 [19.2] likes; aIRR, 1.48; 95% CI, 1.07-2.06; P = .02).Conclusions and RelevanceIn this cross-sectional study of synthetic nicotine brand Instagram accounts, 87% of sampled posts did not adhere to FDA health warning requirements in tobacco promotions. Enforcement of FDA compliant health warnings on social media may reduce youth engagement with tobacco marketing.

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Frequency of social media use and exposure to tobacco or nicotine-related content in association with E-cigarette use among youth: A cross-sectional and longitudinal survey analysis

Cited by 21 publications

References 27 publications

Scalable Surveillance of E-Cigarette Products on Instagram and TikTok Using Computer Vision

Scalable Surveillance of E-Cigarette Products on Instagram and TikTok Using Computer Vision

Normalization of Vaping on TikTok: A Mixed-Methods Approach Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis (Preprint)

Health Warnings on Instagram Advertisements for Synthetic Nicotine E-Cigarettes and Engagement

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