INTRODUCTION: In 2019, the state of Massachusetts signed into law the first statewide sales restrictions of flavored ENDS/tobacco products for both physical and online shops in response to a previous executive order to curb E-Cigarette, or Vaping Product, Use Associated Lung Injury (EVALI) cases that were surging throughout the nation. METHODOLOGY: This study obtained licensure data from the Massachusetts Department of Revenue, to observe the changes in retail licensure comparing the pre ban (October 2018-August 2019) and post ban periods (October 2020- August 2021). A series of linear regression tests were conducted on both periods using census tract data to explore potential associations with sociodemographic covariates, including median age, median household income, and population proportion by gender, age, and race/ethnicity groups. RESULTS: Analysis of the Massachusetts post-ban period (October 2020-August 2021) found that new tobacco retail licenses issued decreased by 52.9% (n = 968) when compared to the pre-ban period (October 2018-August 2019) of 1831. A significant positive association was discovered between change in new retailer count and proportion male population (2.48 ± 1.05, P = .018) as well as proportion Hispanic population (1.19 ± .25, P < .001) at the census tract level. CONCLUSION/DISCUSSION: Our analysis indicates that, following the temporary MA flavor sales ban, the total number of licenses decreased, though decreases were more pronounced for new licenses when compared to continuing licenses. Higher increases in new tobacco retailer density were significantly associated with concentration of male and Hispanic populations.

BACKGROUND: Despite pediatric populations representing a smaller proportion of COVID-19 cases and having a less severe prognosis, those belonging to racial and ethnic minority groups are at an increased risk of developing more severe COVID-19-related outcomes. Vaccine coverage is crucial to pandemic mitigation efforts, yet since the start of the COVID-19 pandemic, vaccine hesitancy has increased and routine pediatric immunizations have decreased. Limited research exists on how vaccine hesitancy may contribute to low pediatric COVID-19 vaccine uptake among racial and ethnic minority populations. OBJECTIVE: This study aimed to characterize COVID-19 vaccine-related discussion and sentiment among Twitter users, particularly among racial and ethnic minority users. METHODS: We used the Twitter application programming interface to collect tweets and replies. Tweets were selected by filtering for keywords associated with COVID-19 vaccines and pediatric-related terms. From this corpus of tweets, we used the Biterm Topic Model to output topics and examined the top 200 retweeted tweets that were coded for pediatric COVID-19 vaccine relevance. Relevant tweets were analyzed using an inductive coding approach to characterize pediatric COVID-19 vaccine-related themes. Replies to relevant tweets were collected and coded. User metadata were assessed for self-reporting of race or ethnic group affiliation and verified account status. RESULTS: A total of 863,007 tweets were collected from October 2020 to October 2021. After outputting Biterm Topic Model topics and reviewing the 200 most retweeted tweets, 208,666 tweets and 3905 replies were identified as being pediatric COVID-19 vaccine related. The majority (150,262/208,666, 72.01%) of tweets expressed vaccine-related concerns. Among tweets discussing vaccine confidence, user replies expressing agreement were significantly outweighed by those expressing disagreement (1016/3106, 32.71% vs 2090/3106, 67.29%; P<.001). The main themes identified in the Twitter interactions were conversations regarding vaccine-related concerns including adverse side effects, concerns that the vaccine is experimental or needs more testing and should not be tested on pediatric populations, the perception that the vaccine is unnecessary given the perceived low risk of pediatric infection, and conversations associated with vaccine-related confidence (ie, the vaccine is protective). Among signal tweets and replies, we identified 418 users who self-identified as a racial minority individual and 40 who self-identified as an ethnic minority individual. Among the subcodes identified in this study, the vaccine being protective was the most discussed topic by racial and ethnic minority groups (305/444, 68.7%). CONCLUSIONS: Vaccine-related concerns can have negative consequences on vaccine uptake and participation in vaccine-related clinical trials. This can impact the uptake and development of safe and effective vaccines, especially among racial and ethnic minority populations.

Background

TikTok is a microvideo social media platform currently experiencing rapid growth and with 60% of its monthly users between the ages of 16 and 24 years. Increased exposure to e-cigarette content on social media may influence patterns of use, including the risk of overconsumption and possible nicotine poisoning, when users engage in trending challenges online. However, there is limited research assessing the characteristics of nicotine poisoning-related content posted on social media.

Objective

We aimed to assess the characteristics of content on TikTok that is associated with a popular nicotine poisoning-related hashtag.

Methods

We collected TikTok posts associated with the hashtag #nicsick, using a Python programming package (Selenium) and used an inductive coding approach to analyze video content and characteristics of interest. Videos were manually annotated to generate a codebook of the nicotine sickness-related themes. Statistical analysis was used to compare user engagement characteristics and video length in content with and without active nicotine sickness TikTok topics.

Results

A total of 132 TikTok videos associated with the hashtag #nicsick were manually coded, with 52.3% (69/132) identified as discussing firsthand and secondhand reports of suspected nicotine poisoning symptoms and experiences. More than one-third of nicotine poisoning-related content (26/69, 37.68%) portrayed active vaping by users, which included content with vaping behavior such as vaping tricks and overconsumption, and 43% (30/69) of recorded users self-reported experiencing nicotine sickness, poisoning, or adverse events such as vomiting following nicotine consumption. The average follower count of users posting content related to nicotine sickness was significantly higher than that for users posting content unrelated to nicotine sickness (W=2350.5, P=.03).

Conclusions

TikTok users openly discuss experiences, both firsthand and secondhand, with nicotine adverse events via the #nicsick hashtag including reports of overconsumption resulting in sickness. These study results suggest that there is a need to assess the utility of digital surveillance on emerging social media platforms for vaping adverse events, particularly on sites popular among youth and young adults. As vaping product use-patterns continue to evolve, digital adverse event detection likely represents an important tool to supplement traditional methods of public health surveillance (such as poison control center prevalence numbers).

Introduction

Exposure to pro-tobacco and electronic nicotine delivery system (ENDS) social media content can lead to overconsumption, increasing the likelihood of nicotine poisoning. This study aims to examine trends and characteristics of nicotine sickness content on Twitter between 2018-2020.

Methods

Tweets were collected retrospectively from the Twitter Academic Research Application Programming Interface (API) stream filtered for keywords: 'nic sick', 'nicsick', 'vape sick', 'vapesick' between 2018-2020. Collected tweets were manually annotated to identify suspected user-generated reports of nicotine sickness and related themes using an inductive coding approach. The Augmented Dickey-Fuller (ADF) test was used to assess stationarity in the monthly variation of the volume of tweets between 2018-2020.

Results

A total of 5651 tweets contained nicotine sickness-related keywords and 18.29% (n=1034) tweets reported one or more suspected nicotine sickness symptoms of varied severity. These tweets were also grouped into five related categories including firsthand and secondhand reports of symptoms, intentional overconsumption of nicotine products, users expressing intention to quit after 'nic sick' symptoms, mention of nicotine product type/brand name that they consumed while 'nic sick', and users discussing symptoms associated with nicotine withdrawal following cessation attempts. The volume of tweets reporting suspected nicotine sickness appeared to increase throughout the study period, except between February and April 2020. Stationarity in the volume of 'nicsick' tweets between 2018-2020 was not statistically significant (ADF= -0.32, p=0.98) indicating a change in the volume of tweets.

Conclusions

Results point to the need for alternative forms of adverse event surveillance and reporting, to appropriately capture the growing health burden of vaping. Infoveillance approaches on social media platforms can help to assess the volume and characteristics of user-generated content discussing suspected nicotine poisoning, which may not be reported to poison control centers. Increasing volume of user-reported nicotine sickness and intentional overconsumption of nicotine in twitter posts represent a concerning trend associated with ENDS-related adverse events and poisoning.

Background

There were an estimated 100,306 drug overdose deaths between April 2020 and April 2021, a three-quarter increase from the prior 12-month period. There is an approximate 6-month reporting lag for provisional counts of drug overdose deaths from the National Vital Statistics System, and the highest level of geospatial resolution is at the state level. By contrast, public social media data are available close to real-time and are often accessible with precise coordinates.

Objective

The purpose of this study is to assess whether county-level overdose mortality burden could be estimated using opioid-related Twitter data.

Methods

International Classification of Diseases (ICD) codes for poisoning or exposure to overdose at the county level were obtained from CDC WONDER. Demographics were collected from the American Community Survey. The Twitter Application Programming Interface was used to obtain tweets that contained any of the 36 terms with drug names. An unsupervised classification approach was used for clustering tweets. Population-normalized variables and polynomial population-normalized variables were produced. Furthermore, z scores of the Getis Ord Gi clustering statistic were produced, and both these scores and their polynomial counterparts were explored in regression modeling of county-level overdose mortality burden. A series of linear regression models were used for predictive modeling to explore the interpretability of the analytical output.

Results

Modeling overdose mortality with normalized demographic variables alone explained only 7.4% of the variability in county-level overdose mortality, whereas this was approximately doubled by the use of specific demographic and Twitter data covariates based on a backward selection approach. The highest adjusted R² and lowest AIC (Akaike Info Criterion) were obtained for the model with normalized demographic variables, normalized z scores from geospatial analyses, and normalized topic counts (adjusted R²=0.133, AIC=8546.8). The z scores of the Getis Ord Gi statistic appeared to have improved utility over population-normalization alone. In this model, median age, female population, and tweets about web-based drug sales were positively associated with opioid mortality. Asian race and Hispanic ethnicity were significantly negatively associated with county-level burdens of overdose mortality.

Conclusions

Social media data, when transformed using certain statistical approaches, may add utility to the goal of producing closer to real-time county-level estimates of overdose mortality. Prediction of opioid-related outcomes can be advanced to inform prevention and treatment decisions. This interdisciplinary approach can facilitate evidence-based funding decisions for various substance use disorder prevention and treatment programs.

A case-control study was conducted between 1 December 2021 and 31 January 2022 to identify factors, which increase risk for coronavirus disease 2019 (COVID-19) among athletes in the National Basketball Association (NBA). Behavioral factors and stadium attendance significantly decreased time to COVID-19 infection, but local COVID-19 rates were not associated in a multivariable model.

INTRODUCTION: There has been a rapid proliferation of synthetic nicotine products in recent years, despite newly established regulatory authority and limited research into its health risks. Previous research has implicated social media platforms as an avenue for nicotine product unregulated sales. Yet, little is known about synthetic nicotine product content on social media. We utilized natural language processing to characterize the sales of synthetic nicotine products on Instagram. METHODS: We collected Instagram posts by querying Instagram hashtags (eg, #tobaccofreenicotine) related to synthetic nicotine. Using Bidirectional Encoder Representations from Transformers, collected posts were categorized into thematically related topic clusters. Posts within topic clusters relevant to study aims were then manually annotated for variables related to promotion and selling (eg, cost discussion, contact information for offline sales). RESULTS: A total of 7425 unique posts were collected with 2219 posts identified as related to promotion and selling of synthetic nicotine products. Nicotine pouches (52.9%, n = 1174), electronic nicotine delivery systems (30.6%, n = 679), and flavored e-liquids (14.1%, n = 313) were most commonly promoted. About 16.1% (n = 345) of posts contained embedded hyperlinks and 5.8% (n = 129) provided contact information for purported offline transactions. Only 17.6% (n = 391) of posts contained synthetic nicotine-specific health warnings. CONCLUSIONS: In the United States, synthetic nicotine products can only be legally marketed if they have received premarket authorization from the Food and Drug Administration (FDA). Despite these prohibitions, Instagram appears to be a hub for potentially unregulated sales of synthetic and tobacco-free products. Efforts are needed by platforms and regulators to enhance content moderation and prevent unregulated online sales of existing and emerging synthetic nicotine products. IMPLICATIONS: There is limited clinical understanding of synthetic nicotines unique health risks and how these novel products are changing over time due to regulatory oversight. Despite synthetic nicotine-specific regulatory measures, such as the requirement for premarket authorization and FDA warning letters issued to unauthorized sellers, access to and promotion of synthetic nicotine is widely occurring on Instagram, a platform with over 2 billion users and one that is popular among youth and young adults. Activities include direct-to-consumer sales from questionable sources, inadequate health warning disclosure, and exposure with limited age restrictions, all conditions necessary for the sale of various tobacco products. Notably, the number of these Instagram posts increased in response to the announcement of new FDA regulations. In response, more robust online monitoring, content moderation, and proactive enforcement are needed from platforms who should work collaboratively with regulators to identify, report, and remove content in clear violation of platform policies and federal laws. Regulatory implementation and enforcement should prioritize digital platforms as conduits for unregulated access to synthetic nicotine products and other future novel and emerging tobacco products.

BACKGROUND: Video games have rapidly become mainstream in recent decades, with over half of the US population involved in some form of digital gaming. However, concerns regarding the potential harms of excessive, disordered gaming have also risen. Internet gaming disorder (IGD) has been proposed as a tentative psychiatric disorder that requires further study by the American Psychological Association (APA) and is recognized as a behavioral addiction by the World Health Organization. Substance use among gamers has also become a concern, with caffeinated or energy drinks and prescription stimulants commonly used for performance enhancement. OBJECTIVE: This study aimed to identify substance use patterns and health-related concerns among gamers among a population of Reddit users. METHODS: We used the public streaming Reddit application programming interface to collect and analyze all posts from the popular subreddit, r/StopGaming. From this corpus of posts, we filtered the dataset for keywords associated with common substances that may be used to enhance gaming performance. We then applied an inductive coding approach to characterize substance use behaviors, gaming genres, and physical and mental health concerns. Potential disordered gaming behavior was also identified using the tentative IGD guidelines proposed by the APA. A chi-square test of independence was used to assess the association between gaming disorder and substance use characteristics, and multivariable logistic regression was used to analyze whether mental health discussion or the mention of any substance with sufficient sample size was significantly associated with IGD. RESULTS: In total, 10,551 posts were collected from Reddit from June 2017 to December 2022. After filtering the dataset for substance-related keywords, 1057 were included for further analysis, of which 286 mentioned both gaming and the use of ≥1 substances. Among the 286 posts that discussed both gaming and substance use, the most mentioned substances were alcohol (n=132), cannabis (n=104), and nicotine (n=48), while the most mentioned genres were role-playing games (n=120), shooters (n=90), and multiplayer online battle arenas (n=43). Self-reported behavior that aligned with the tentative guidelines for IGD was identified in 66.8% (191/286) posts. More than half, 62.9% (180/286) of the posts, discussed a health issue, with the majority (n=144) cited mental health concerns. Common mental health concerns discussed were depression and anxiety. There was a significant association between IGD and substance use (P<.001; chi-square test), and there were significantly increased odds of IGD among those who self-reported substance use (odds ratio 2.29, P<.001) and those who discussed mental health (odds ratio 1.64, P<.03). CONCLUSIONS: As gaming increasingly becomes highly prevalent among various age groups and demographics, a better understanding of the interplay and convergence among disordered gaming, substance use, and negative health impacts can inform the development of interventions to mitigate risks and promote healthier gaming habits.