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Introduction Previous research has identified abundant e-cigarette content on social media using primarily text-based approaches. However, frequently used social media platforms among youth, such as TikTok, contain primarily visual content, requiring the ability to detect e-cigarette-related content across large sets of videos and images. This study aims to use a computer vision technique to detect e-cigarette-related objects in TikTok videos. Aims and Methods We searched 13 hashtags related to vaping on TikTok (eg, #vape) in November 2022 and obtained 826 still images extracted from a random selection of 254 posts. We annotated images for the presence of vaping devices, hands, and/or vapor clouds. We developed a YOLOv7-based computer vision model to detect these objects using 85% of extracted images (N  = 705) for training and 15% (N  = 121) for testing. Results Our model's recall value was 0.77 for all three classes: vape devices, hands, and vapor. Our model correctly classified vape devices 92.9% of the time, with an average F1 score of 0.81. Conclusions The findings highlight the importance of having accurate and efficient methods to identify e-cigarette content on popular video-based social media platforms like TikTok. Our findings indicate that automated computer vision methods can successfully detect a range of e-cigarette-related content, including devices and vapor clouds, across images from TikTok posts. These approaches can be used to guide research and regulatory efforts. Implications Object detection, a computer vision machine learning model, can accurately and efficiently identify e-cigarette content on a primarily visual-based social media platform by identifying the presence of vaping devices and evidence of e-cigarette use (eg, hands and vapor clouds). The methods used in this study can inform computational surveillance systems for detecting e-cigarette content on video- and image-based social media platforms to inform and enforce regulations of e-cigarette content on social media. [ABSTRACT FROM AUTHOR]

Introduction: We examined the effect of visual optimizations on warning text recall.Methods: We used Amazon's Mechanical Turk to recruit 1854 young adult (18-34 years) electronic cigarette (e-cigarette) users or susceptible nonusers. We conducted a between-subjects 3 × 2 × 2 experiment to examine the influence of color (black text on white background [BW] vs. black on yellow [BY] vs. yellow on black [YB]), shape (rectangle vs. novel), and signal word (presence vs. absence of the word "warning"). We randomized participants to view one of 12 warnings on a fictional e-cigarette advertisement. We coded open-ended recall responses into three categories: (1) recalled nothing, (2) recalled something, (3) recalled the concept. We examined main effects on warning text recall using multinomial regression. We examined differences in attention, perceived message effectiveness, and appeal.Results: Those exposed to BW or BY warnings were more likely than those exposed to YB to recall something (AOR = 1.6, AOR = 1.5, respectively) or the concept (OR = 1.4, BW). Those exposed to novel shape (44.7% novel vs. 37.9% rectangle; p = .003) or color (44.5% BY vs. 41.9% YB vs. 37.5% BW; p = .04) warnings were more likely to report attention to the warning. In aided recall, those exposed to the signal word were more likely than those not exposed to select the correct response (64.0% vs. 31.3%; p < .0001). We did not find differences for message effectiveness or appeal.Conclusions: Visual optimizations such as color may influence warning text recall and should be considered for new warnings. Research should continue exploring variations for advertisement warnings to maximize attention to warning text.Implications: This study examines the impact of visual optimizations on recall of the US Food and Drug Administration-mandated e-cigarette advertisement warning text. We found that color might influence warning text recall, but we did not find effects for shape or signal word. It is possible the newly mandated e-cigarette advertisement warnings, which are required to occupy at least 20% of the advertisement, are currently novel enough to attract attention. Future research should examine optimizations following implementation of the new advertisement warnings. [ABSTRACT FROM AUTHOR]

Introduction It is unclear whether warnings on electronic cigarette (e-cigarette) advertisements required by the US Food and Drug Administration (FDA) will apply to social media. Given the key role of social media in marketing e-cigarettes, we seek to inform FDA decision making by exploring how warnings on various tweet content influence perceived healthiness, nicotine harm, likelihood to try e-cigarettes, and warning recall. Methods In this 2 × 4 between-subjects experiment participants viewed a tweet from a fictitious e-cigarette brand. Four tweet content versions (e-cigarette product, e-cigarette use, e-cigarette in social context, unrelated content) were crossed with two warning versions (absent, present). Adult e-cigarette users (N = 994) were recruited via social media ads to complete a survey and randomized to view one of eight tweets. Multivariable regressions explored effects of tweet content and warning on perceived healthiness, perceived harm, and likelihood to try e-cigarettes, and tweet content on warning recall. Covariates were tobacco and social media use and demographics. Results Tweets with warnings elicited more negative health perceptions of the e-cigarette brand than tweets without warnings (p <.05). Tweets featuring e-cigarette products (p <.05) or use (p <.001) elicited higher warning recall than tweets featuring unrelated content. Conclusions This is the first study to examine warning effects on perceptions of e-cigarette social media marketing. Warnings led to more negative e-cigarette health perceptions, but no effect on perceived nicotine harm or likelihood to try e-cigarettes. There were differences in warning recall by tweet content. Research should explore how varying warning content (text, size, placement) on tweets from e-cigarette brands influences health risk perceptions. Implications FDA's 2016 ruling requires warnings on advertisements for nicotine-containing e-cigarettes, but does not specify whether this applies to social media. This study is the first to examine how e-cigarette warnings in tweets influence perceived healthiness and harm of e-cigarettes, which is important because e-cigarette brands are voluntarily including warnings on Twitter and Instagram. Warnings influenced perceived healthiness of the e-cigarette brand, but not perceived nicotine harm or likelihood to try e-cigarettes. We also saw higher recall of warning statements for tweets featuring e-cigarettes. Findings suggest that expanding warning requirements to e-cigarette social media marketing warrants further exploration and FDA consideration. [ABSTRACT FROM AUTHOR]

Introduction: Recent developments in smoking cessation support systems and interventions have highlighted the requirement for unobtrusive, passive ways to measure smoking behavior. A number of systems have been developed for this that either use bespoke sensing technology, or expensive combinations of wearables and smartphones. Here, we present StopWatch, a system for passive detection of cigarette smoking that runs on a low-cost smartwatch and does not require additional sensing or a connected smartphone.Methods: Our system uses motion data from the accelerometer and gyroscope in an Android smartwatch to detect the signature hand movements of cigarette smoking. It uses machine learning techniques to transform raw motion data into motion features, and in turn into individual drags and instances of smoking. These processes run on the smartwatch, and do not require a smartphone.Results: We conducted preliminary validations of the system in daily smokers (n = 13) in laboratory and free-living conditions running on an Android LG G-Watch. In free-living conditions, over a 24-h period, the system achieved precision of 86% and recall of 71%.Conclusions: StopWatch is a system for passive measurement of cigarette smoking that runs entirely on a commercially available Android smartwatch. It requires no smartphone so the cost is low, and needs no bespoke sensing equipment so participant burden is also low. Performance is currently lower than other more expensive and complex systems, though adequate for some applications. Future developments will focus on enhancing performance, validation on a range of smartwatches, and detection of electronic cigarette use.Implications: We present a low-cost, smartwatch-based system for passive detection of cigarette smoking. It uses data from the motion sensors in the watch to identify the signature hand movements of cigarette smoking. The system will provide the detailed measures of individual smoking behavior needed for context-triggered just-in-time smoking cessation support systems, and to enable just-in-time adaptive interventions. More broadly, the system will enable researchers to obtain detailed measures of individual smoking behavior in free-living conditions that are free from the recall errors and reporting biases associated with self-report of smoking. [ABSTRACT FROM AUTHOR]

Introduction: While research has documented associations between recall of point-of-sale (POS) tobacco marketing and youth tobacco use, much of the research is cross-sectional and focused on cigarettes. The present longitudinal study examined recall of tobacco marketing at the POS and multiple types of tobacco use 6 months later.Methods: The Texas Adolescent Tobacco Advertising and Marketing Surveillance System (TATAMS) is a large-scale, representative study of 6th, 8th, and 10th graders in 79 middle and high schools in five counties in Texas. Weighted logistic regression examined associations between recall of tobacco advertisements and products on display at baseline and ever use, current use, and susceptibility to use for cigarette, e-cigarette, cigar, and smokeless products 6 months later.Results: Students' recall of signs marketing e-cigarettes at baseline predicted ever e-cigarette use and increased susceptibility to use e-cigarettes at follow-up, across all store types. Recall of e-cigarette displays only predicted susceptibility to use e-cigarettes at follow-up, across all store types. Both recall of signs marketing cigars and cigar product displays predicted current and ever cigar smoking and increased susceptibility to smoking cigars at follow-up, across all store types. Recall of cigarette and smokeless product marketing and displays was not associated with tobacco use measures.Conclusion: The POS environment continues to be an important influence on youth tobacco use. Restrictions on POS marketing, particularly around schools, are warranted.Implications: Cross-sectional studies have shown that exposure to POS cigarette marketing is associated with use of cigarettes among youth, though longitudinal evidence of the same is sparse and mixed. Cross-sectional studies have found that recall of cigars, smokeless product, and e-cigarette tobacco marketing at POS is associated with curiosity about tobacco use or intentions to use tobacco among youth, but limited longitudinal research has been conducted. Findings from the present longitudinal study suggest that recall of tobacco marketing at retail POS predicts ever use of e-cigarettes and cigars, current use of cigars, and susceptibility to cigar and e-cigarette use among youth. [ABSTRACT FROM AUTHOR]

Introduction: This study assesses the relationship between tobacco/e-cigarette marketing exposure and single, dual, and polytobacco product use, among adolescents. Given the increased use of noncigarette tobacco products (eg, cigars, e-cigarettes, hookah) among youth, it is imperative to understand if marketing exposure is associated with dual and polytobacco product use.Methods: Data were obtained from the 2014 National Youth Tobacco Survey and weighted to be representative of US middle and high school students. Multivariable multinomial logistic regression models were used to assess the relationships between product marketing (via internet, print, retail, and TV/movies) and past 30-day single, dual, and poly (three or more) tobacco product use. Three analyses were conducted using different categories as referent groups to allow for comprehensive examination of the relationships between all groups.Results: Marketing exposure was significantly correlated with a greater risk of single, dual, and polytobacco product use relative to nonusers. Relative to single product users, product marketing exposure was significantly correlated with a greater relative risk of dual and polytobacco use. There was no statistical difference in the association of marketing exposure between dual and polytobacco use, in any model.Conclusion: A positive relationship between tobacco product marketing exposure and number of tobacco products used was observed. The magnitude of the relationship grew from single product to dual/poly use. Restrictions of marketing of all tobacco products, similar to cigarettes, particularly in the retail setting, should be considered.Implications: This study has two primary public health implications. First, self-reported exposure to tobacco/e-cigarette marketing is widespread among adolescents of all tobacco product categories. Second, this widespread exposure to tobacco/e-cigarette marketing appears to not only be correlated with use of a single tobacco product (eg, cigarettes, e-cigarettes), but also multiple tobacco products. While longitudinal studies are needed to further investigate the relationships observed in this study, findings justify further study given the known relationship between tobacco marketing exposure and subsequent cigarette use. [ABSTRACT FROM AUTHOR]