Twitter Sentiment About the US Federal Tobacco 21 Law: Mixed Methods Analysis.

BACKGROUND: On December 20, 2019, the US "Tobacco 21" law raised the minimum legal sales age of tobacco products to 21 years. Initial research suggests that misinformation about Tobacco 21 circulated via news sources on Twitter and that sentiment about the law was associated with particular types of tobacco products and included discussions about other age-related behaviors. However, underlying themes about this sentiment as well as temporal trends leading up to enactment of the law have not been explored. OBJECTIVE: This study sought to examine (1) sentiment (pro-, anti-, and neutral policy) about Tobacco 21 on Twitter and (2) volume patterns (number of tweets) of Twitter discussions leading up to the enactment of the federal law. METHODS: We collected tweets related to Tobacco 21 posted between September 4, 2019, and December 31, 2019. A 2% subsample of tweets (4628/231,447) was annotated by 2 experienced, trained coders for policy-related information and sentiment. To do this, a codebook was developed using an inductive procedure that outlined the operational definitions and examples for the human coders to annotate sentiment (pro-, anti-, and neutral policy). Following the annotation of the data, the researchers used a thematic analysis to determine emergent themes per sentiment category. The data were then annotated again to capture frequencies of emergent themes. Concurrently, we examined trends in the volume of Tobacco 21-related tweets (weekly rhythms and total number of tweets over the time data were collected) and analyzed the qualitative discussions occurring at those peak times. RESULTS: The most prevalent category of tweets related to Tobacco 21 was neutral policy (514/1113, 46.2%), followed by antipolicy (432/1113, 38.8%); 167 of 1113 (15%) were propolicy or supportive of the law. Key themes identified among neutral tweets were news reports and discussion of political figures, parties, or government involvement in general. Most discussions were generated from news sources and surfaced in the final days before enactment. Tweets opposing Tobacco 21 mentioned that the law was unfair to young audiences who were addicted to nicotine and were skeptical of the law's efficacy and importance. Methods used to evade the law were found to be represented in both neutral and antipolicy tweets. Propolicy tweets focused on the protection of youth and described the law as a sensible regulatory approach rather than a complete ban of all products or flavored products. Four spikes in daily volume were noted, 2 of which corresponded with political speeches and 2 with the preparation and passage of the legislation. CONCLUSIONS: Understanding themes of public sentiment-as well as when Twitter activity is most active-will help public health professionals to optimize health promotion activities to increase community readiness and respond to enforcement needs including education for retailers and the general public.

A longitudinal study of SARS-CoV-2 antibody seroprevalence and mitigation behaviors among college students at an Arkansas University.

Objective: Assess university students' SARS-CoV-2 antibody seroprevalence and mitigation behaviors over time. Participants: Randomly selected college students (N = 344) in a predominantly rural Southern state. Methods: Participants provided blood samples and completed self-administered questionnaires at three timepoints over the academic year. Adjusted odds ratios and 95% confidence intervals were estimated from logistic regression analyses. Results: SARS-CoV-2 antibody seroprevalence was 18.2% in September 2020, 13.1% in December, and 45.5% in March 2021 (21% for those with no vaccination history). SARS-CoV-2 antibody seroprevalence was associated with large social gatherings, staying local during the summer break, symptoms of fatigue or rhinitis, Greek affiliation, attending Greek events, employment, and using social media as the primary COVID-19 information source. In March 2021, seroprevalence was associated with receiving at least one dose of a COVID-19 vaccination. Conclusion: SARS-CoV-2 seroprevalence was higher in this population of college students than previous studies. Results can assist leaders in making informed decisions as new variants threaten college campuses.

Viewer Reactions to EVALI Storylines on Popular Medical Dramas: A Thematic Analysis of Twitter Messages.

Previous research has found an association between awareness of e-cigarette, or vaping, product-use associated lung injury (EVALI) and lower intention to use e-cigarettes among young people. This study utilized Twitter data to evaluate if the January 2020 depiction of EVALI on New Amsterdam, Chicago Med, and Grey's Anatomy-three popular primetime medical dramas-could be a potential innovative avenue to raise awareness of EVALI. We obtained tweets containing e-cigarette-related search strings from 1/21/2020 to 02/18/2020 and filtered these with storyline-specific keywords, resulting in 1,493 tweets for qualitative coding by two trained human coders. Content codes were informed by prior research, theories of narrative influence, and e-cigarette related outcomes. Of 641 (42.9%) relevant tweets, the most frequent content codes were perceived realism (n = 292, 45.6%) and negative response (n = 264, 41.2%). A common theme among these tweets was that storylines were unrealistic because none of the characters with EVALI used THC-containing products. Approximately 12% of tweets (n = 78) mentioned e-cigarette knowledge and 28 (4.4%) mentioned behavior, including quitting e-cigarettes because of viewing the storylines. Implications for health communication research utilizing social media data and maximizing the achievement of positive health-related outcomes for storylines depicting current health topics are discussed.

The Influence of Social Media Interactions and Behaviors on Depressive Symptoms Among Sexual and Gender Minority Young Adults in the United States: Protocol for a Mixed Methods Longitudinal Study.

BACKGROUND: Sexual and gender minority (SGM; ie, lesbian, gay, bisexual, transgender, and otherwise queer) young adults experience disparities in depression and other internalizing psychopathology. Although social media use is widespread and SGM people have more social media accounts and are more socially active on them than non-SGM individuals, few studies have examined the impact of social media on depression in this group. OBJECTIVE: The PRIDE iM study will be the first longitudinal, mixed methods research conducted to determine the impact of social media interactions and behaviors as pathways to depressive symptoms among SGM young adults living in the United States. METHODS: PRIDE iM uses a bookends variation of the longitudinal sequential mixed methods design. Participants will be recruited nationally from social media. First, between July 2019 and February 2020, we conducted a qualitative phase (T1) comprising web-based individual interviews (N=58) to inform the building and content of the quantitative survey. Second, from February 2022 to September 2022, we will conduct a series of web-based surveys (N=1000 at baseline) with 4 data points (T2-T5), each one collected every 6 to 8 weeks. Third, from October 2022 to December 2022, we will conduct a second qualitative phase (T6) of web-based interviews using outcome trajectories found in the longitudinal survey analyses to purposively sample survey participants and conduct web-based interviews to contextualize and explain survey findings. Qualitative data from T1 and T6 will be analyzed using a reflexive thematic analysis approach. As we sought to capture change over time in the association between the main predictors (ie, social media interactions and behaviors) and depressive symptoms, we propose analyzing T2 to T5 data using latent growth models with a structural equation modeling framework. Data integration at the method, interpretation, and reporting levels will be achieved through building and connecting and the use of a staged approach and joint displays, respectively. At all stages, we will assess the fit of data integration as recommended by the principles of best practice for mixed methods research in psychology. RESULTS: Data collection will be completed by December 2022. Qualitative data analyses will be completed by March 2023, and quantitative analyses of the primary outcome of interest will be completed by June 2023. CONCLUSIONS: PRIDE iM will confirm, reject, or uncover the presence of potential relationships between social media interactions and behaviors and depressive symptoms among SGM people. This study represents fundamental groundwork to develop social media-based interventions that target modifiable interactions and behaviors that are most likely to influence mental health outcomes, thus seizing the opportunity to merge the popularity of this medium among SGM people with evidence-based approaches. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/43627.

Miscommunication about the US federal Tobacco 21 law: a content analysis of Twitter discussions.

OBJECTIVE: Tobacco 21 is a law that sets the minimum legal sales age of tobacco products to 21. On 20 December 2019, the USA passed a federal Tobacco 21 law. The objective of this study is to explore Twitter discussions about the federal Tobacco 21 law in the USA leading up to enacted. METHODS: Twitter messages about Tobacco 21 posted between September and December 2019 were collected via RITHM software. A 2% sample of all collected tweets were double coded by independent coders using a content analysis approach. RESULTS: Findings included three content categories of tweets (news, youth and young adults and methods of avoiding the law) with eight subcodes. Most news tweets incorrectly described the law as a purchase law (54.7%). However, Tobacco 21 is in fact a sales law-it only includes penalties for tobacco retailers who sell to under-age purchasers. About one-fourth (27%) of the tweets involved youth and young adults, with some claiming the law would reduce youth smoking and others doubting its ability to limit youth access to tobacco products. Few tweets (2.5%) mentioned methods of circumventing the policy, such as having an older peer purchase tobacco. CONCLUSIONS: As several countries explore raising their age of sale of tobacco laws to 21, they should couple policy enactment with clear and accurate communication about the law. Compliance agencies at all levels (eg, local, regional, national) can use social media to identify policy loopholes and support vulnerable populations throughout the policy implementation process.

Classification of Twitter Vaping Discourse Using BERTweet: Comparative Deep Learning Study.

BACKGROUND: Twitter provides a valuable platform for the surveillance and monitoring of public health topics; however, manually categorizing large quantities of Twitter data is labor intensive and presents barriers to identify major trends and sentiments. Additionally, while machine and deep learning approaches have been proposed with high accuracy, they require large, annotated data sets. Public pretrained deep learning classification models, such as BERTweet, produce higher-quality models while using smaller annotated training sets. OBJECTIVE: This study aims to derive and evaluate a pretrained deep learning model based on BERTweet that can identify tweets relevant to vaping, tweets (related to vaping) of commercial nature, and tweets with provape sentiment. Additionally, the performance of the BERTweet classifier will be compared against a long short-term memory (LSTM) model to show the improvements a pretrained model has over traditional deep learning approaches. METHODS: Twitter data were collected from August to October 2019 using vaping-related search terms. From this set, a random subsample of 2401 English tweets was manually annotated for relevance (vaping related or not), commercial nature (commercial or not), and sentiment (positive, negative, or neutral). Using the annotated data, 3 separate classifiers were built using BERTweet with the default parameters defined by the Simple Transformer application programming interface (API). Each model was trained for 20 iterations and evaluated with a random split of the annotated tweets, reserving 10% (n=165) of tweets for evaluations. RESULTS: The relevance, commercial, and sentiment classifiers achieved an area under the receiver operating characteristic curve (AUROC) of 94.5%, 99.3%, and 81.7%, respectively. Additionally, the weighted F1 scores of each were 97.6%, 99.0%, and 86.1%, respectively. We found that BERTweet outperformed the LSTM model in the classification of all categories. CONCLUSIONS: Large, open-source deep learning classifiers, such as BERTweet, can provide researchers the ability to reliably determine if tweets are relevant to vaping; include commercial content; and include positive, negative, or neutral content about vaping with a higher accuracy than traditional natural language processing deep learning models. Such enhancement to the utilization of Twitter data can allow for faster exploration and dissemination of time-sensitive data than traditional methodologies (eg, surveys, polling research).

A Genome-Wide Association Study of Prediabetes Status Change.

We conducted the first genome-wide association study of prediabetes status change (to diabetes or normal glycaemia) among 900 White participants of the Atherosclerosis Risk in Communities (ARIC) study. Single nucleotide polymorphism (SNP)-based analysis was performed by logistic regression models, controlling for age, gender, body mass index, and the first 3 genetic principal components. Gene-based analysis was conducted by combining SNP-based p values using effective Chi-square test method. Promising SNPs (p < 1×10-5) and genes (p < 1×10-4) were further evaluated for replication among 514 White participants of the Framingham Heart Study (FHS). To accommodate familial correlations, generalized estimation equation models were applied for SNP-based analyses in the FHS. Analysis results across ARIC and FHS were combined using inverse-variance-weighted meta-analysis method for SNPs and Fisher's method for genes. We robustly identified 5 novel genes that are associated with prediabetes status change using gene-based analyses, including SGCZ (ARIC p = 9.93×10-6, FHS p = 2.00×10-3, Meta p = 3.72×10-7) at 8p22, HPSE2 (ARIC p = 8.26×10-19, FHS p = 5.85×10-3, Meta p < 8.26×10-19) at 10q24.2, ADGRA1 (ARIC p = 1.34×10-5, FHS p = 1.13×10-3, Meta p = 2.88×10-7) at 10q26.3, GLB1L3 (ARIC p = 3.71×10-6, FHS p = 4.51×10-3, Meta p = 3.16×10-7) at 11q25, and PCSK6 (ARIC p = 6.51×10-6, FHS p = 1.10×10-2, Meta p = 1.25×10-6) at 15q26.3. eQTL analysis indicated that these genes were highly expressed in tissues related to diabetes development. However, we were not able to identify any novel locus in single SNP-based analysis. Future large scale genomic studies of prediabetes status change are warranted.

Policy and Behavior: Comparisons between Twitter Discussions about the US Tobacco 21 Law and Other Age-Related Behaviors.

To combat the e-cigarette epidemic among young audiences, a federal law was passed in the US that raised the minimum legal sales age of tobacco to 21 years (commonly known as Tobacco 21). Little is known about sentiment toward this law. Thus, the purpose of our study was to systematically explore trends about Tobacco 21 discussions and comparisons to other age-restriction behaviors on Twitter. Twitter data (n = 4628) were collected from September to December of 2019 that were related to Tobacco 21. A random subsample of identified tweets was used to develop a codebook. Two trained coders independently coded all data, with strong inter-rater reliability (κ = 0.71 to 0.93) found for all content categories. Associations between sentiment and content categories were calculated using χ2 analyses. Among relevant tweets (n = 955), the most common theme­the disjunction between ages for military enlistment and tobacco use­was found in 17.8% of all tweets. Anti-policy sentiment was strongly associated with the age of military enlistment, alcohol, voting, and adulthood (p < 0.001 for all). Opposition to Tobacco 21 propagates on social media because the US federal law does not exempt military members. However, the e-cigarette epidemic may have fueled some support for this law.

Discussions and Misinformation About Electronic Nicotine Delivery Systems and COVID-19: Qualitative Analysis of Twitter Content.

BACKGROUND: Misinformation and conspiracy theories related to COVID-19 and electronic nicotine delivery systems (ENDS) are increasing. Some of this may stem from early reports suggesting a lower risk of severe COVID-19 in nicotine users. Additionally, a common conspiracy is that the e-cigarette or vaping product use-associated lung injury (EVALI) outbreak of 2019 was actually an early presentation of COVID-19. This may have important public health ramifications for both COVID-19 control and ENDS use. OBJECTIVE: Twitter is an ideal tool for analyzing real-time public discussions related to both ENDS and COVID-19. This study seeks to collect and classify Twitter messages ("tweets") related to ENDS and COVID-19 to inform public health messaging. METHODS: Approximately 2.1 million tweets matching ENDS-related keywords were collected from March 1, 2020, through June 30, 2020, and were then filtered for COVID-19-related keywords, resulting in 67,321 original tweets. A 5% (n=3366) subsample was obtained for human coding using a systematically developed codebook. Tweets were coded for relevance to the topic and four overarching categories. RESULTS: A total of 1930 (57.3%) tweets were coded as relevant to the research topic. Half (n=1008, 52.2%) of these discussed a perceived association between ENDS use and COVID-19 susceptibility or severity, with 42.4% (n=818) suggesting that ENDS use is associated with worse COVID-19 symptoms. One-quarter (n=479, 24.8%) of tweets discussed the perceived similarity/dissimilarity of COVID-19 and EVALI, and 13.8% (n=266) discussed ENDS use behavior. Misinformation and conspiracy theories were present throughout all coding categories. CONCLUSIONS: Discussions about ENDS use and COVID-19 on Twitter frequently highlight concerns about the susceptibility and severity of COVID-19 for ENDS users; however, many contain misinformation and conspiracy theories. Public health messaging should capitalize on these concerns and amplify accurate Twitter messaging.

Puff Bars, Tobacco Policy Evasion, and Nicotine Dependence: Content Analysis of Tweets.

BACKGROUND: Puff Bars are e-cigarettes that continued marketing flavored products by exploiting the US Food and Drug Administration exemption for disposable devices. OBJECTIVE: This study aimed to examine discussions related to Puff Bar on Twitter to identify tobacco regulation and policy themes as well as unanticipated outcomes of regulatory loopholes. METHODS: Of 8519 original tweets related to Puff Bar collected from July 13, 2020, to August 13, 2020, a random 20% subsample (n=2661) was selected for qualitative coding of topics related to nicotine dependence and tobacco policy. RESULTS: Of the human-coded tweets, 2123 (80.2%) were coded as relevant to Puff Bar as the main topic. Of those tweets, 698 (32.9%) discussed tobacco policy, including flavors (n=320, 45.9%), regulations (n=124, 17.8%), purchases (n=117, 16.8%), and other products (n=110, 15.8%). Approximately 22% (n=480) of the tweets referenced dependence, including lack of access (n=273, 56.9%), appetite suppression (n=59, 12.3%), frequent use (n=47, 9.8%), and self-reported dependence (n=110, 22.9%). CONCLUSIONS: This study adds to the growing evidence base that the US Food and Drug Administration ban of e-cigarette flavors did not reduce interest, but rather shifted the discussion to brands utilizing a loophole that allowed flavored products to continue to be sold in disposable devices. Until comprehensive tobacco policy legislation is developed, new products or loopholes will continue to supply nicotine demand.

The Brain-Derived Neurotrophic Factor Functional Polymorphism and Hand Grip Strength Impact the Association between Brain-Derived Neurotrophic Factor Levels and Cognition in Older Adults in the United States.

INTRODUCTION: Aging is associated with subtle cognitive decline in attention, memory, executive function, processing speed, and reasoning. Although lower brain-derived neurotrophic factor (BDNF) has been linked to cognitive decline among older adults, it is not known if the association differs among individuals with various BDNF Val66Met (rs6265) genotypes. In addition, it is not clear whether these associations vary by hand grip strength or physical activity (PA). METHODS: A total of 2904 older adults were included in this study using data from the Health and Retirement Study. Associations between serum BDNF and measures of cognitive function were evaluated using multivariable linear regression models stratified by Met allele status. PA and hand grip strength were added to the model to evaluate whether including these variables altered associations between serum BDNF and cognition. RESULTS: Mean age was 71.4 years old, and mean body mass index was 28.3 kg/m2. Serum BDNF levels were positively associated with higher total cognitive score (beta = 0.34, p = .07), mental status (beta = 0.16, p = .07), and word recall (beta = 0.22, p =.04) among Met carriers, while serum BDNF levels were negatively associated with mental status (beta = -0.09, p = .07) among non-Met carriers. Furthermore, associations changed when hand grip strength was added to the model but not when PA was added to the model. CONCLUSIONS: The BDNF Val66Met variant may moderate the association between serum BDNF levels and cognitive function in older adults. Furthermore, such associations differ according to hand grip strength but not PA.

E-Cigarette-Related Nicotine Misinformation on Social Media.

Background. Twitter provides an opportunity to examine misperceptions about nicotine and addiction as they pertain to electronic nicotine delivery systems (ENDS). The purpose of this study was to systematically examine a sample of ENDS-related tweets that presented information about nicotine or addiction for the presence of potential misinformation.Methods. A total of 10.1 million ENDS-related tweets were obtained from April 2018 through March 2019 and were filtered for unique tweets containing keywords for nicotine and addiction. A subsample (n = 3,116) were human coded for type of account (individual, group, commercial, or news) and presence of potential misinformation.Results. Of tweets that presented ENDS-related nicotine or addiction information (n = 904), 41.7% (n = 377) contained potential misinformation coded as anti-vaping exaggeration, pro-vaping exaggeration, nicotine is not addictive or is never harmful, or unproven health benefits.Conclusions. Anti-vaping exaggeration tweets distorted or embellished claims about ENDS nicotine and addiction; pro-vaping exaggeration tweets misinterpreted results from scientific studies. Misinformation that nicotine is not addictive or is never harmful or has unproven health benefits appeared less but are potentially problematic. ENDS-related messaging should be designed to be easily understood by the public and monitored to detect the spread of misinterpretation or misinformation on social media.

Exploring Factors That Predict Marketing of e-Cigarette Products on Twitter: Infodemiology Approach Using Time Series.

Background: Electronic nicotine delivery systems (known as electronic cigarettes or e-cigarettes) increase risk for adverse health outcomes among naïve tobacco users, particularly youth and young adults. This vulnerable population is also at risk for exposed brand marketing and advertisement of e-cigarettes on social media. Understanding predictors of how e-cigarette manufacturers conduct social media advertising and marketing could benefit public health approaches to addressing e-cigarette use. Objective: This study documents factors that predict changes in daily frequency of commercial tweets about e-cigarettes using time series modeling techniques. Methods: We analyzed data on the daily frequency of commercial tweets about e-cigarettes collected between January 1, 2017, and December 31, 2020. We fit the data to an autoregressive integrated moving average (ARIMA) model and unobserved components model (UCM). Four measures assessed model prediction accuracy. Predictors in the UCM include days with events related to the US Food and Drug Administration (FDA), non-FDA-related events with significant importance such as academic or news announcements, weekday versus weekend, and the period when JUUL maintained an active Twitter account (ie, actively tweeting from their corporate Twitter account) versus when JUUL stopped tweeting. Results: When the 2 statistical models were fit to the data, the results indicate that the UCM was the best modeling technique for our data. All 4 predictors included in the UCM were significant predictors of the daily frequency of commercial tweets about e-cigarettes. On average, brand advertisement and marketing of e-cigarettes on Twitter was higher by more than 150 advertisements on days with FDA-related events compared to days without FDA events. Similarly, more than 40 commercial tweets about e-cigarettes were, on average, recorded on days with important non-FDA events compared to days without such events. We also found that there were more commercial tweets about e-cigarettes on weekdays than on weekends and more commercial tweets when JUUL maintained an active Twitter account. Conclusions: e-Cigarette companies promote their products on Twitter. Commercial tweets were significantly more likely to be posted on days with important FDA announcements, which may alter the narrative about information shared by the FDA. There remains a need for regulation of digital marketing of e-cigarette products in the United States.

Acceptability and Efficacy of the SMARxT Media Literacy Education Program to Counter Pharmaceutical Marketing Influences among Medical Trainees.

Background: Evidence-based prescribing (EBP) results in decreased morbidity and reduces medical costs. However, pharmaceutical marketing influences medication requests and prescribing habits, which can detract from EBP. Media literacy, which teaches critical thinking, is a promising approach for buffering marketing influences and encouraging EBP. The authors developed the "SMARxT" media literacy education program around marketing influences on EBP decision-making. The program consisted of six videos and knowledge assessments that were delivered as an online educational intervention through the Qualtrics platform. Methods: In 2017, we assessed program feasibility, acceptability, and efficacy of enhancing knowledge among resident physicians at the University of Pittsburgh. Resident physicians (n=73) responded to pre-test items assessing prior knowledge, viewed six SMARxT videos, and responded to post-test items. A 6-month follow-up test was completed to quantitatively assess sustained changes in knowledge and to qualitatively assess summative feedback about the program (n=54). Test scores were assessed from pre- to post-test and from pre-test to follow-up using paired-sample t-tests. Qualitative results were synthesized through content analysis. Results: Proportion of correct knowledge responses increased from pre-test to immediate post-test (31% to 64%, P<0.001) at baseline. Correct responses also increased from pre-test to 6-month follow-up (31% to 43%, P<0.001). Feasibility was demonstrated by 95% of enrolled participants completing all baseline procedures and 70% completing 6-month follow-up. Quantitative measures of acceptability yielded positive scores and qualitative responses indicated participants' increased confidence in understanding and countering marketing influences due to the intervention. However, participants stated they would prefer shorter videos, feedback about test scores, and additional resources to reinforce learning objectives. Conclusion: The SMARxT media literacy program was efficacious and acceptable to resident physicians. Participant suggestions could be incorporated into a subsequent version of SMARxT and inform similar clinical education programs. Future research should assess program impact on real-world prescribing practices.

Analyzing Twitter Chatter About Tobacco Use Within Intoxication-related Contexts of Alcohol Use: "Can Someone Tell Me Why Nicotine is So Fire When You're Drunk?"

INTRODUCTION: Alcohol and tobacco are commonly used together. Social influences within online social networking platforms contribute to youth and young adult substance use behaviors. This study used a sample of alcohol- and tobacco-related tweets to evaluate: (1) sentiment toward co-use of alcohol and tobacco, (2) increased susceptibility to tobacco use when consuming alcohol, and (3) the role of alcohol in contributing to a failed attempt to quit tobacco use. METHODS: Data were collected from the Twitter API from January 1, 2019 through December 31, 2019 using tobacco-related keywords (e.g., vape, ecig, smoking, juul*) and alcohol-related filters (e.g., drunk, blackout*). A total of 78,235 tweets were collected, from which a random subsample (n = 1,564) was drawn for coding. Cohen's Kappa values ranged from 0.66 to 0.99. RESULTS: Most tweets were pro co-use of alcohol and tobacco (75%). One of every ten tweets reported increased susceptibility to tobacco use when intoxicated. Non-regular tobacco users reported cravings for and tobacco use when consuming alcohol despite disliking tobacco use factors such as the taste, smell, and/or negative health effects. Regular tobacco users reported using markedly higher quantities of tobacco when intoxicated. Individuals discussed the role of alcohol undermining tobacco cessation attempts less often (2.0%), though some who had quit smoking for prolonged periods of time reported reinitiating tobacco use during acute intoxication episodes. CONCLUSIONS: Tobacco cessation interventions may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts. IMPLICATIONS: Sentiment toward co-use of alcohol and tobacco on Twitter is largely positive. Individuals reported regret about using tobacco, or using more than intended, when intoxicated. Those who had quit smoking or vaping for prolonged periods of time reported reinitiating tobacco use when consuming alcohol. While social media-based tobacco cessation interventions like the Truth Initiative's "Ditch the Juul" campaign demonstrate potential to change tobacco use behaviors, these campaigns may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts.

Social Media as It Interfaces with Psychosocial Development and Mental Illness in Transitional-Age Youth.

Social media (SM) can be defined as "a group of Internet-based applications that allow the creation and exchange of user-generated content." This includes formation of online communities and sharing of information, ideas, opinions, messages, images, and videos. Therefore, although all online video games would not necessarily count as SM, video games that allow for substantial sharing of information and development of online communities do fit this definition. SM has become an integral component of how people worldwide connect with friends and family, share personal content, and obtain news and entertainment. Use of SM is particularly prevalent among transitional-age youth, usually defined as individuals aged 16 to 24 years, who are at critical junctures around developmental tasks such as identity development and establishment of social norms.

Re-evaluating standards of human subjects protection for sensitive health data in social media networks.

This study addresses ethical questions about conducting health science research using network data from social media platforms. We provide examples of ethically problematic areas related to participant consent, expectation of privacy, and social media networks. Further, to illustrate how researchers can maintain ethical integrity while leveraging social media networks, we describe a study that demonstrates the ability to use social media to identify individuals affected by cancer. We discuss best practices and ethical guidelines for studying social media network data, including data collection, analysis, and reporting.

#Alcohol: Portrayals of Alcohol in Top Videos on TikTok.

OBJECTIVE: The purpose of this study was to characterize the content and themes present in user-generated TikTok videos portraying alcohol. METHOD: We captured the 100 most popular videos including the #alcohol hashtag on the popular social networking site TikTok. We used an iterative process to codebook development, resulting in codes for user sentiment toward alcohol, type of alcohol depicted, brand references, degree of alcohol use, and positive/negative associations with alcohol use. Videos were independently double coded, evaluated for inter-rater agreement, and adjudicated if differences were present. RESULTS: The videos in our sample were collectively viewed 291,999,100 times. The vast majority (98%) of videos expressed pro-alcohol sentiment. Nearly half of videos (41%) were guide videos demonstrating drink recipes. The majority of videos (72%) included liquor. Consuming multiple drinks quickly was depicted in more than half of videos (61%), whereas intoxication (13%) was exhibited less frequently. Positive associations with alcohol were prevalent; 69% of videos conveyed positive experiences with alcohol, 55% of videos contained humor, and 45% included associations of alcohol with camaraderie. Negative associations with alcohol were rarely portrayed (4%). CONCLUSIONS: Top alcohol-related videos on TikTok are heavily viewed. Their contents demonstrate a propensity to promote rapid consumption of multiple drinks and to juxtapose alcohol use with positive associations such as humor and camaraderie, while rarely depicting negative outcomes associated with hazardous alcohol use.

Vape Shop Proliferation and Noncompliance in Pennsylvania: A Pre- and Post-tax Analysis.

BACKGROUND: The growing use of electronic nicotine delivery systems (ENDS) among adolescents is a public health concern. Taxation of these products is a viable approach to reduce ENDS use, particularly among adolescents. Opponents of taxation posit that it puts specialty retailers (ie, vape shops) out of business, thereby reducing availability of ENDS for adult smokers seeking harm reduction. Pennsylvania enacted substantial ENDS taxes in October 2016. This study sought to examine (1) the prevalence of Pennsylvania vape shops before and after ENDS taxes were enacted and (2) ENDS retail licensing compliance among vape shops. METHODS: We employed standardized searches for vape shops in Pennsylvania on the Yelp business-listing platform a month prior to and for 18 consecutive months following the imposition of ENDS taxes. We then compared listings to a public database of ENDS-related retail licenses to determine compliance status. RESULTS: The number of listed vape shops increased in a linear fashion by a magnitude of 23%. In addition, when we compared a final listing of retailers to data from the state tax authority, we found roughly a quarter (22%-29%) of vape shops to be noncompliant with maintaining a valid ENDS retail license. CONCLUSIONS: Overall, ENDS taxation in Pennsylvania has not appeared to reduce prevalence of vape shops as anticipated. However, stricter enforcement of the tax law is necessary to ensure compliance among retailers. These findings have implications for implementation and enforcement of ENDS tax policy nationwide, including states that currently lack such policies.

Temporal Associations Between Social Media Use and Depression.

INTRODUCTION: Previous studies have demonstrated cross-sectional associations between social media use and depression, but their temporal and directional associations have not been reported. METHODS: In 2018, participants aged 18-30 years were recruited in proportion to U.S. Census characteristics, including age, sex, race, education, household income, and geographic region. Participants self-reported social media use on the basis of a list of the top 10 social media networks, which represent >95% of social media use. Depression was assessed using the 9-Item Patient Health Questionnaire. A total of 9 relevant sociodemographic covariates were assessed. All measures were assessed at both baseline and 6-month follow-up. RESULTS: Among 990 participants who were not depressed at baseline, 95 (9.6%) developed depression by follow-up. In multivariable analyses conducted in 2020 that controlled for all covariates and included survey weights, there was a significant linear association (p<0.001) between baseline social media use and the development of depression for each level of social media use. Compared with those in the lowest quartile, participants in the highest quartile of baseline social media use had significantly increased odds of developing depression (AOR=2.77, 95% CI=1.38, 5.56). However, there was no association between the presence of baseline depression and increasing social media use at follow-up (OR=1.04, 95% CI=0.78, 1.38). Results were robust to all sensitivity analyses. CONCLUSIONS: In a national sample of young adults, baseline social media use was independently associated with the development of depression by follow-up, but baseline depression was not associated with an increase in social media use at follow-up. This pattern suggests temporal associations between social media use and depression, an important criterion for causality.