Identifying e-cigarette content on TikTok: Using a BERTopic Modeling approach.

INTRODUCTION: The use of hashtags is a common way to promote e-cigarette content on social media. Analysis of hashtags may provide insight into e-cigarette promotion on social media. However, the examination of text data is complicated by the voluminous amount of social media data. This study used machine learning approaches (i.e., Bidirectional Encoder Representations from Transformers [BERT] topic modeling) to identify e-cigarette content on TikTok. METHODS: We used 13 unique hashtags related to e-cigarettes (e.g., #vape) for data collection. The final analytic sample included 12,573 TikTok posts. To identify the best fitting number of topic clusters, we used both quantitative (i.e., coherence test) and qualitative approaches (i.e., researchers checked the relevance of text from each topic). We, then, grouped and characterized clustered text to each theme. RESULTS: We evaluated that N=18 was the ideal number of topic clusters. The 9 overarching themes were identified: Social media and TikTok-related features (N=4; "duet", "viral"), Vape shops and brands (N=3; "store"), Vape tricks (N=3; "ripsaw"), Modified use of e-cigarettes (N=1; "coil", "wire"), Vaping and girls (N=1; "girl"), Vape flavors (N=1; "flavors"), Vape and cigarettes (N=1; "smoke"), Vape identities and communities (N=1; "community"), and Non-English language (N=3; Romanian and Spanish). CONCLUSIONS: This study used a machine learning method, BERTopic modeling, to successfully identify relevant themes on TikTok. This method can inform future social media research examining other tobacco products, and tobacco regulatory policies such as monitoring of e-cigarette marketing on social media. IMPLICATIONS: This study can inform future social media research examining other tobacco products, and tobacco regulatory policies such as monitoring of e-cigarette marketing on social media.

Psychometric evaluation of the Self-Report Habit Index for assessing habitual e-cigarette use behavior in high school adolescents.

Background: E-cigarettes are the most-used nicotine product among adolescents, but limited psychometrically-sound, e-cigarette-relevant measures exist for adolescents. We examined psychometric properties of the Self-Report Habit Index (SRHI) for assessing adolescents' habitual e-cigarette use. Methods: During Fall 2022, 4855 students from eight Connecticut high schools completed an anonymous survey. The analytic sample comprised 491 students who reported past-month e-cigarette use and completed the SRHI (Age M=15.94, SD=1.24 years, 56 % female, 37.1 % Hispanic, 57.6 % White). We examined the SRHI's latent factor structure; internal reliability; measurement invariance and between-groups differences (e.g., nicotine vs. nicotine-free vaping); and associations with total e-cigarette flavors used in the past month, past-30-day vaping frequency, and e-cigarette dependence. Results: The SRHI's 6-item, 1-factor structure was confirmed. Internal reliability was excellent. The SRHI was scalar invariant for all subgroups tested. Nicotine (vs. nicotine-free) and daily (vs. non-daily) e-cigarette use were associated with greater habitual e-cigarette use behavior. In adjusted models, habitual e-cigarette use was associated with using more e-cigarette flavors, vaping more frequently, and greater e-cigarette dependence. Habitual e-cigarette use incrementally accounted for variance in past-month flavors used and vaping frequency beyond dependence. Conclusions: The SRHI evidenced solid psychometric properties for assessing habitual e-cigarette use behavior among high school students. Relationships between habitual use and frequency of use, e-cigarette flavors, and dependence might be expected as these constructs are associated with the three characterizing features of habitual behaviors: frequent repetition, cue-driven elicitation, and automaticity. Future prospective research can clarify the temporal ordering of habitual e-cigarette use and dependence in adolescents.

Use of ENDS devices and modifications to vape cannabis among adolescents and young adults who also vape nicotine.

BACKGROUND: Electronic nicotine delivery systems (ENDS) are the most used tobacco product among adolescents and young adults (AYAs) and are increasingly used to vape cannabis. It is unclear what vaping devices and ENDS modifications are used most frequently by AYAs who vape both nicotine and cannabis. METHODS: AYAs (aged 14-29) reporting ENDS use in the past 30 days were recruited via Qualtrics (N = 1,011). We conducted three multivariable logistic regression models examining differences in likelihood of: 1) vaping cannabis in the past 30 days; 2) mixing cannabis and nicotine liquids; and 3) using nicotine devices to vape cannabis; based on type of vaping device used most often, controlling for age, socio-economic status, gender, race, frequency of ENDS use, and other cannabis use. RESULTS: 40 % (n = 405) of AYAs reported vaping both nicotine and cannabis in the past 30 days. AYAs who used vape pens most often were more likely to have vaped cannabis concentrates in the past 30 days compared to individuals using disposable vapes (aOR = 2.72, 95 %CI = 1.75-4.21, p < 0.001). AYAs who used open systems most often (i.e., vape pens, mods, or e-hookah) were more likely than individuals using closed systems (i.e., disposable vapes, rechargeable pods or cigalikes) to combine nicotine and cannabis e-liquids (aOR = 2.03, 95 %CI = 1.43-2.89, p < 0.001) or use a nicotine device to vape cannabis (aOR = 1.66, 95 %CI = 1.17-2.34, p = 0.005). IMPLICATIONS: Co-use of cannabis and nicotine via similar devices, particularly vape pens and other open-systems, warrants collaborative regulatory efforts to mitigate co-use of both substances, with a particular need for increased regulation of cannabis vaping products.

Modification of Electronic Nicotine Delivery Systems Among Adolescents and Young Adults.

OBJECTIVES: We assessed awareness and perceptions of, information sources about, and engagement in modifying electronic nicotine delivery systems (ENDS) among adolescents and young adults (AYAs). METHODS: AYAs (N = 1018) endorsing past-month ENDS use completed a survey on awareness and use of the following modifications: (1) refilling rechargeable cartridges/pods or (2) disposable pods, (3) rewicking or (4) recharging disposable pods, (5) modifying nicotine e-liquids (eg, changing propylene glycol/vegetable glycerin, nicotine), (6) combining nicotine and cannabis for simultaneous vaping, and (7) putting cannabis in ENDS designed for nicotine vaping. Logistic regression assessed how sources of information (eg, friends, social media, nonsocial media Web sites, vape shops) about and perceptions of ENDS modifications associated with ENDS modifications. RESULTS: Refilling (69.0% heard, 40.1% tried) and recharging the battery (66.4% heard, 35.8% tried) of disposable pods were most common. Friends (64.4%) and social media (46.7%) were the most common sources of information. Notable significant associations between information sources and modifications were: 1. nonsocial media Web sites and vape shops with rewicking and recharging disposable devices and modifying nicotine e-liquid; 2. nonsocial media Web sites with refilling rechargeable cartridges/pods and disposable pods; and 3. social media with recharging disposable devices and mixing nicotine and cannabis liquids. Perceptions of reduced harm and "coolness" were associated with various modifications. DISCUSSION: AYAs are aware of and modify ENDS for purposes unintended by manufacturers. ENDS policies should consider unintended ENDS use to safeguard public health. Prevention efforts should communicate about the potential harms of ENDS modifications.

Role of neoadjuvant peptide receptor radionuclide therapy in unresectable and metastatic gastro-entero-pancreatic neuroendocrine neoplasms: A scoping review.

Peptide receptor radionuclide therapy (PRRT) is an established therapy for metastatic neuroendocrine neoplasms (NEN). The role of PRRT as a neoadjuvant treatment prior to surgery or other local therapies is uncertain. This scoping review aimed to define the landscape of evidence available detailing the utility of PRRT in the neo-adjuvant setting, including the clinical contexts, efficacy, and levels of evidence. A comprehensive literature search of PUBMED, SCOPUS, and EMBASE through to December 2022 was performed to identify reports of PRRT use as neoadjuvant therapy prior to local therapies. Observational studies and clinical trials were included. A total of 369 records were identified by the initial search, and 17 were included in the final analysis, comprising 179 patients treated with neoadjuvant PRRT. Publications included case reports, retrospective cohort series and a phase 2 trial. Definitions of unresectable disease were variable. Radioisotopes used included 177Lu (n = 142) and 90Y (n = 36), used separately (n = 178) or in combination (n = 1). A combination of PRRT with chemotherapy was also explored (n = 2). Toxicity data was reported in 11/17 studies. Survival analysis was reported in 3/17 studies. Surgical resection following PRRT was reported for both the primary tumor (n = 71) and metastases (n = 12). Resection rates could not be calculated as not all publications reported whether resection was completed. Published literature exploring the use of PRRT in the neoadjuvant setting is mostly limited to case reports and retrospective cohort studies. From these limited data there is reported to be a role of PRRT in neoadjuvant setting in the literature. However, the low quality of evidence precludes any definite conclusion on the grade of disease, site of primary, isotope used or use of concomitant chemotherapy that can benefit from this application. Further prospective studies will require collaboration between multiple centers to gain sufficient high-quality evidence.

E-cigarette dependence and cooling flavor use are linked among youth.

BACKGROUND: E-cigarette flavors that produce cooling sensations may reduce nicotine harshness and enhance appeal among youth. While previous research has shown that use of cooling flavors is associated with more frequent vaping among youth, it is unknown whether the same holds true for e-cigarette dependence. This study examines the relationship between cooling flavor use and e-cigarette dependence among youth accounting for vaping frequency. METHODS: In Fall 2022, a survey was conducted among Connecticut high school students to assess past-month nicotine e-cigarette use, ever use of cooling flavors, cooling flavor types (e.g., fruit-cooling), and e-cigarette dependence. Analyses were restricted to those with past-month nicotine and nicotine-free e-cigarette use and complete data (n=204). Multivariable linear regressions were run to examine the association between cooling flavor use and e-cigarette dependence, adjusting for demographics, e-cigarette use characteristics, and other tobacco product use. RESULTS: 78.4% of the sample used cooling e-cigarette flavors, with 55.0% using mint-cooling flavors and 52.5% using fruit-cooling flavors. Regression results observed that cooling flavor use was associated with higher e-cigarette dependence (ꞵ=1.53, SE=0.63, p=0.017), with those who used cooling flavors having higher e-cigarette dependence than those who did not (M=5.78 [SD=5.33] vs. 2.84 [3.19]). CONCLUSIONS: Our results suggest that cooling flavor use is significantly associated with e-cigarette dependence among youth. While regulations often target menthol flavor, tobacco control agencies should consider restricting any flavor that can produce cooling sensations, even if they are not traditional menthol products, as cooling flavors is associated with youth e-cigarette dependence.

Sources of exposure to non-tobacco nicotine electronic nicotine delivery systems and associations with susceptibility to use and use behaviors among young adults in the United States.

INTRODUCTION: The Electronic Nicotine Delivery Systems (ENDS) industry recently introduced non-tobacco nicotine (NTN), which is not tobacco-derived and is often marketed as "tobacco-free nicotine." Given its novelty, it is important to understand where young adults learn about NTN ENDS. This study examined sources of exposure to NTN ENDS and relationships with NTN ENDS use and susceptibility. METHODS: We analyzed online survey data collected in Fall 2021 from 642 young adults (18-25 years) who had heard of NTN ENDS. We assessed 9 sources of NTN ENDS exposure (e.g., retail stores, social media) and examined associations between sources of exposure and NTN current (past-month) use, lifetime (non-current) use, and susceptibility to use, adjusting for demographics and other tobacco product use. RESULTS: Participants reported current NTN ENDS use (37.4%), lifetime use (12.0%), susceptibility (18.5%), or no susceptibility to use (32.1%). The most common sources of NTN ENDS exposure were retail stores (87.7%) and social media (81.0%). Exposure to NTN ENDS via social media was associated with greater odds of current NTN ENDS use (vs. no susceptibility) (aOR = 1.83, 95%CI: 1.02-3.28). Exposure via online streaming platforms was associated with greater odds of current (aOR = 1.75, 95%CI: 1.08-2.82) and lifetime NTN ENDS use (aOR = 2.42, 95%CI: 1.25-4.68). CONCLUSIONS: Young adults were exposed to and learned about NTN ENDS from diverse sources, primarily retail shops and social media. Further, exposure via social media and streaming platforms were associated with NTN ENDS use. Future studies should explore the content of NTN information from various sources to inform prevention efforts.

Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. We created an algorithm to predict cMRI-quantified PRF from echocardiography using machine learning (ML). We retrospectively performed echocardiographic measurements paired to cMRI within 3 months in patients with ≥ mild PR from 2009 to 2022. Model inputs were vena contracta ratio, PR index, PR pressure half-time, main and branch pulmonary artery diastolic flow reversal (BPAFR), and transannular patch repair. A gradient boosted trees ML algorithm was trained using k-fold cross-validation to predict cMRI PRF by phase contrast imaging as a continuous number and at > mild (PRF ≥ 20%) and severe (PRF ≥ 40%) thresholds. Regression performance was evaluated with mean absolute error (MAE), and at clinical thresholds with area-under-the-receiver-operating-characteristic curve (AUROC). Prediction accuracy was compared to historical clinician accuracy. We externally validated prior reported studies for comparison. We included 243 subjects (median age 21 years, 58% repaired tetralogy of Fallot). The regression MAE = 7.0%. For prediction of > mild PR, AUROC = 0.96, but BPAFR alone outperformed the ML model (sensitivity 94%, specificity 97%). The ML model detection of severe PR had AUROC = 0.86, but in the subgroup with BPAFR, performance dropped (AUROC = 0.73). Accuracy between clinicians and the ML model was similar (70% vs. 69%). There was decrement in performance of prior reported algorithms on external validation in our dataset. A novel ML model for echocardiographic quantification of PRF outperforms prior studies and has comparable overall accuracy to clinicians. BPAFR is an excellent marker for > mild PRF, and has moderate capacity to detect severe PR, but more work is required to distinguish moderate from severe PR. Poor external validation of prior works highlights reproducibility challenges.

Adolescents and Young Adults Use of Social Media and Following of e-Cigarette Influencers.

BACKGROUND: With high rates of both e-cigarette and social media use among adolescents and young adults (AYAs), social media influencers who promote e-cigarettes are particularly concerning but are understudied. We examined the association between AYAs' use of 11 different social media platforms (e.g. Facebook, Twitter, Instagram, TikTok, and YouTube) and exposure to social media e-cigarette influencers. OBJECTIVES: From November 2022 to February 2023, we conducted an online, US national survey of AYAs (14-29 years) who endorsed past-30-day e-cigarette use. We used binomial logistic regression to examine associations between the frequency of use of each social media platform and following e-cigarette influencers, controlling for age, sex, race, ethnicity, e-cigarette use frequency, and other tobacco and substance use (i.e., alcohol and cannabis). The model was stratified by adolescents (14-17 years; n = 293) and young adults (18-29 years; n = 654). RESULTS: The most frequently used social media platforms were Snapchat, TikTok and Instagram among adolescents, and YouTube, Instagram and TikTok among young adults. In adjusted models, following e-cigarette influencers was associated with more frequent use of TikTok (adjusted odds ratio [95% CI]; 1.33 [1.05, 1.68]) and Pinterest (1.18 [1.02, 1.38]) among adolescents, and more frequent use of Twitter (1.17 [1.06, 1.29]) among young adults. CONCLUSIONS: The use of different platforms was associated with exposure to e-cigarette influencers: TikTok and Pinterest among adolescents and Twitter among young adults. These findings can inform tobacco regulatory policy and social media platform restrictions of e-cigarette influencers on the platforms that are popular among AYAs.

Characteristics of Adolescents' and Young Adults' Exposure to and Engagement with Nicotine and Tobacco Product Content on Social Media.

To inform policy and messaging, this study examined characteristics of adolescents' and young adults' (AYAs') exposure to and engagement with nicotine and tobacco product (NTP) social media (SM) content. In this cross-sectional survey study, AYAs aged 13-26 (N=1,163) reported current NTP use, SM use frequency, and exposure to and engagement with SM content promoting and opposing NTP use (i.e. frequency, source[s], format[s], platform[s]). Participants who used NTPs (vs. did not use) were more likely to report having seen NTP content (p-values<.001). Prevalent sources were companies/brands (46.6%) and influencers (44.4%); prevalent formats were video (65.4%) and image (50.7%). Exposure to content promoting NTP use was prevalent on several popular platforms (e.g. TikTok, Instagram, Snapchat); exposure to content opposing NTP use was most prevalent on YouTube (75.8%). Among those reporting content engagement (i.e. liking, commenting on, or sharing NTP content; 34.6%), 57.2% engaged with influencer content. Participants reported engaging with content promoting and opposing NTP use on popular platforms (e.g. TikTok, Instagram, YouTube). Participants with (versus without) current NTP use were significantly more likely to use most SM platforms and to report NTP content exposure and engagement (p-values<.05). Results suggest that NTP education messaging and enforcement of platforms' content restrictions are needed.

Non-tobacco nicotine E-cigarette use and flavored E-cigarette use among young adults in the United States.

BACKGROUND: E-cigarette flavors can create sensations of sweetness and coolness while masking the aversiveness of nicotine. Recently, non-tobacco nicotine (NTN) products were introduced to the market, but little is known about flavors in NTN e-cigarette use. We examined associations between flavors (i.e., sweet, mint/menthol) and susceptibility to and use of NTN e-cigarettes. METHODS: 1239 US young adults (18-25 years) completed an anonymous, online survey in Fall 2021. The analytic sample included 520 participants who had used e-cigarettes and heard of NTN. Multinomial logistic regression models analyzed associations of flavored e-cigarette use (sweet and mint/menthol) with NTN e-cigarette use status (i.e., current [past-month] use, past [ever but not current] use, susceptible to use, and non-susceptible to use [reference]). RESULTS: Overall, 46.2% of participants reported current NTN use, 14.8% reported past use, 16.7% were susceptible to use, and 22.3% reported no susceptibility. Participants reported dual-use of sweet and mint/menthol NTN e-cigarette flavors (56.5%), sweet flavors use (24.8%), and mint/menthol flavor use (1.7%). Ever dual use of sweet and mint/menthol flavors was associated with current (OR = 9.64, 95%CI: 3.21-28.98) and past NTN e-cigarette use (8.30, [2.10-32.80]). Ever sweet flavor use was associated with current NTN use (3.80, 95%CI: 1.44-10.03) and susceptibility to future use (4.25, [1.53-11.81]). Similar findings were observed for mint/menthol flavors (current: 5.03, [1.41-17.99]; susceptible: 5.65, [1.64-19.51]). CONCLUSION: The use of sweet and mint/menthol flavors was significantly associated with NTN e-cigarette use among US young adults, highlighting the need for ongoing surveillance of flavored NTN e-cigarettes and appropriate regulations to discourage use.

The Scientific Basis for the Regulation of Flavors in Tobacco Products.

Effective tobacco policies are important for reducing the harm of tobacco use and can have a broad impact at the population level. This review provides an overview of how clinical science can inform tobacco policies with a focus on policies related to flavored tobacco products, using menthol cigarettes as an illustrative example. Specifically, this review summarizes the role of flavors in tobacco use and the history of regulation of flavored tobacco products by the US Food and Drug Administration (FDA), provides an overview of clinical research methods used to contribute to the scientific evidence to inform FDA tobacco policies, discusses key findings related to menthol tobacco products using these methods, and proposes future directions for clinical research. As the tobacco marketplace continues to evolve with new products and flavor chemicals, ongoing clinical science will be essential for establishing evidence-based policies to protect public health and reduce tobacco-related health disparities.

Quantitative calibration of Tb-161 SPECT/CT in view of personalised dosimetry assessment studies.

BACKGROUND: Terbium-161 (161Tb)-based radionuclide therapy poses an alternative to current Lutetium-177 (177Lu) approaches with the additional benefit of secondary Auger and conversion electron emissions capable of delivering high doses of localised damage to micro-metastases including single cells. Quantitative single-photon emission computed tomography, paired with computed tomography (SPECT/CT), enables quantitative measurement from post-therapy imaging. In view of dosimetry extrapolations, a Tb-161 sensitivity SPECT/CT camera calibration was performed using a method previously validated for 177Lu. METHODS: Serial imaging of a NEMA/IEC body phantom with Tb-161 was performed on SPECT/CT with low-energy high-resolution collimators employing a photopeak of 75 keV with a 20% width. Quantitative stability and recovery coefficients were investigated over a sequence of 19 scans with buffered 161Tb solution at total phantom activity ranging from 70 to 4990 MBq. RESULTS: Sphere recovery coefficients were 0.60 ± 0.05, 0.52 ± 0.07, 0.45 ± 0.07, 0.39 ± 0.07, 0.28 ± 0.08, and 0.20 ± 0.08 for spheres 37, 28, 22, 17, 13, and 10mm, respectively, when considered across all activity and scan durations with dual-energy window scatter correction. Whole-field reconstructed sensitivity was calculated as 1.42E-5 counts per decay. Qualitatively, images exhibited no visual artefacts and were comparable to 177Lu SPECT/CT. CONCLUSIONS: Quantitative SPECT/CT of 161Tb is feasible over a range of activities enabling dosimetry analogous to 177Lu whilst also producing suitable imaging for clinical review. This has been incorporated into a prospective trial of 161Tb-PSMA for men with metastatic prostate cancer.

Using Computer Vision to Detect E-cigarette Content in TikTok Videos.

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.

Why young adults use tobacco-free nicotine E-cigarettes: An analysis of qualitative data.

BACKGROUND: Tobacco-free nicotine (TFN) is often marketed as being better tasting and healthier than tobacco-derived nicotine (TDN). Studies have yet to systematically characterize subjective experiences using TFN e-cigarettes. This qualitative study explored young adults' reasons for using TFN e-cigarettes and perceptions of differences between using TFN and TDN e-cigarettes. METHOD: We conducted a national online Qualtrics survey of U.S. young adults aged 18-25 years in October 2021. Respondents who reported lifetime TFN e-cigarette use (n = 317, mean age: 20.8 (SD:2.2), 53.9 % female) provided write-in responses to open-ended questions assessing reasons for using TFN e-cigarettes and perceptions of differences between TFN and TDN e-cigarettes. Responses from participants were thematically analyzed by independent raters. RESULTS: Reasons for using TFN e-cigarettes included product taste/flavor, health reasons (e.g. believing TFN was healthy), and product accessibility. Perceptions of differences between TFN and TDN e-cigarettes included differences in taste/ flavor and acute psychoactive and physical effects (e.g., nicotine buzz, throat hit), with TFN e-cigarettes being described as generally stronger and superior relative to TDN e-cigarettes. CONCLUSION: These qualitative data suggest that taste and perceived health benefits are primary reasons that young adults try TFN e-cigarettes. Compared to TDN, young adults perceive TFN as better tasting with different psychoactive and less aversive effects. Determining if these perceived reasons for use and differences occur in blinded human experimental studies is a necessary next step to understanding TFN e-cigarette use. Additionally, understanding why young adults use TFN e-cigarettes is important in the development of prevention communication about these products.