Reducing Commercial Tobacco Sales to Youth On and Around California Tribal Reservations with a Reward and Reminder Retail Intervention.

INTRODUCTION: High prevalence of commercial tobacco product (CTP) use among American Indian and Alaska Native (AI/AN) youth is a public health crisis. A multi-level Tribal-community-based participatory research project under Tribal public health authority implemented a retailer-focused intervention to reduce AI/AN youth CTP use. METHODS: We sought resolutions in support of a retailer-focused CTP intervention from Tribal Nations organized by a tribally-directed research program. We identified tobacco retail outlets operating on and within 5 miles of 9 Tribal reservations, and CTP products sold at these outlets. We conducted a four-wave Reward and Reminder intervention with apparent minor buyers. Clerks who complied with the law received a modest reward and commendation in social media posts to the local Tribal communities, while clerks who sold without age verification were reminded of the laws. RESULTS: Of 18 retail outlets selling CTP, 8 sold e-cigarettes, and all sold combustible cigarettes. The Reward and Reminder intervention showed an approximate 25% reduction in sales of CTP to apparent minors, with a 33% baseline CTP sales rate without age verification and an 8% intervention CTP sales rate without age verification. CONCLUSIONS: The intervention increased awareness of laws prohibiting CTP sales to minors and mandating age verification for young adults seeking to buy CTP. The intervention, which had support from all governing Tribal Nations, builds the evidence base of effective practices which Tribal public health authorities may utilize to reduce youth access to CTP on and around Tribal reservations. IMPLICATIONS: Sovereign Tribes have authority over commercial businesses operating on their lands. Tobacco 21 laws aiming to restrict commercial tobacco availability to youth are supported by Tribes. A retailer intervention in which apparent minors attempt commercial tobacco purchases can offer accountability feedback to retailers both on and near Tribal reservations. Obtaining Tribal support and publicizing the interventions helps mobilize Tribal communities to support commercial tobacco prevention and promote healthy youth.

Identification and Characterization of Synthetic Nicotine Product Promotion and Sales on Instagram Using Natural Language Processing.

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 (e.g., "#tobaccofreenicotine) related to synthetic nicotine. Using BERT, 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 (e.g., cost discussion, contact information for offline sales). RESULTS: A total of 7,425 unique posts were collected with 2,219 posts identified as related to promotion and selling of synthetic nicotine products. Nicotine pouches (52.9%, n=1174), ENDS (30.6%, n=679), and flavored e-liquids (14.1%, n=313) were most commonly promoted. 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 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 nicotine's 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 is 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.

Estimating County-Level Overdose Rates Using Opioid-Related Twitter Data: Interdisciplinary Infodemiology Study.

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.

Understanding the Experiences of American Indian and Alaska Native Students Enrolled in Allopathic and Osteopathic Medical Degree Programs.

PURPOSE: Despite a growing population, American Indian and Alaska Native (AI/AN) students have seen no meaningful increase in representation in allopathic and osteopathic medical degree programs. While AI/AN medical students are more likely to practice in underserved areas, they face financial and sociocultural obstacles towards doing so. This underscores the need to understand the experiences of these trainees, and identify barriers and facilitators to the successful recruitment, retention, and advancement of AI/AN trainees. METHODS: A survey was administered to members of the Association of Native American Medical Students (ANAMS), an organization representing self-identified Native medical students. This survey elicited demographic information, opinions of institutional climate, and aspects of academic and social experiences during medical school. RESULTS: There were n = 39 complete responses. Over fifty percent of respondents (n = 21) identified as AI/AN alone and not in combination with another racial or ethnic group. Overall, respondents were: Generally, not satisfied with their school's engagement with Native communities and AI/AN health curricula. Likely to report barriers towards their timely advancement in training, namely being a first-generation or low income student, and feelings of imposter syndrome. Likely to report an interest to work in primary care fields and serve AI/AN communities in the future. CONCLUSIONS: This survey identified several barriers to successful AI/AN medical trainee advancement, highlighting opportunities for institutions to foster inclusion of AI/AN trainees and grow the number of Native physicians.

Exploring substance use disorder discussions in Native American communities: a retrospective Twitter infodemiology study.

BACKGROUND: The opioid epidemic has had a devastating impact on youth from American Indian and Alaska Native (AI/AN) Tribes and Villages, which also experience disparate suicide rates. The use of publicly available social media data originating from AI/AN communities may enhance public health response time to substance use disorder (SUD)-related overdose and augment Tribal public health surveillance systems, but these concepts have yet to be adequately explored. The goal of this exploratory analysis was to identify primary and secondary accounts of overdose and characterize relevant contextual factors in the AI/AN population on social media. METHODS: The Twitter application programming interface was queried for all Tweets containing geocoded data between March 2014 and June 2020 and filtered for the keyword ['overdose']. This sample of Tweets (n = 146,236) was then restricted to those geolocated from US Tribal lands (n = 619). Tweets were manually annotated for primary or secondary accounts of overdose as well as suicidal ideation, substance(s) used, stigma of drug use, and community-wide incidents. RESULTS: We collected a total of 146,235 tweets that were geocoded and contained the word 'overdose,' of which 9.5% were posted on Tribal lands (n = 619). 9.4% of these tweets (n = 58) met our study inclusion criteria and were mainly posted from Oklahoma (n = 26, 45%) and North Carolina (n = 13, 22.4%). Most Tweets (n = 41, 71%) described a primary account of an overdose and were mostly posted from 2014 to 2015. Less than half of the Tweets (n = 27, 46.5%) referenced a specific substance. Those substances mentioned included alcohol, marijuana, methamphetamine, heroin, laundry softener, cocaine, K2-Spice (synthetic cannabinoid), codeine, morphine, Nyquil, and Xanax. DISCUSSION: Though exploratory, our study identified SUD-related content self-reported by AI/AN communities on Twitter, especially in Oklahoma and North Carolina. These results may assist in the future design and detection of infodemiology trends and early warning signs that can better facilitate intervention specific to the ongoing Tribal opioid epidemic. While all data were collected from the public domain, additional care should be given to individual and community privacy.

Establishing a blockchain-enabled Indigenous data sovereignty framework for genomic data.

Technological advances have enabled the rapid generation of health and genomic data, though rarely do these technologies account for the values and priorities of marginalized communities. In this commentary, we conceptualize a blockchain genomics data framework built out of the concept of Indigenous Data Sovereignty.

Spread of COVID-19 Vaccine Misinformation in the Ninth Inning: Retrospective Observational Infodemic Study.

Background: Shortly after Pfizer and Moderna received emergency use authorizations from the Food and Drug Administration, there were increased reports of COVID-19 vaccine-related deaths in the Vaccine Adverse Event Reporting System (VAERS). In January 2021, Major League Baseball legend and Hall of Famer, Hank Aaron, passed away at the age of 86 years from natural causes, just 2 weeks after he received the COVID-19 vaccine. Antivaccination groups attempted to link his death to the Moderna vaccine, similar to other attempts misrepresenting data from the VAERS to spread COVID-19 misinformation. Objective: This study assessed the spread of misinformation linked to erroneous claims about Hank Aaron's death on Twitter and then characterized different vaccine misinformation and hesitancy themes generated from users who interacted with this misinformation discourse. Methods: An initial sample of tweets from January 31, 2021, to February 6, 2021, was queried from the Twitter Search Application Programming Interface using the keywords "Hank Aaron" and "vaccine." The sample was manually annotated for misinformation, reporting or news media, and public reaction. Nonmedia user accounts were also classified if they were verified by Twitter. A second sample of tweets, representing direct comments or retweets to misinformation-labeled content, was also collected. User sentiment toward misinformation, positive (agree) or negative (disagree), was recorded. The Strategic Advisory Group of Experts Vaccine Hesitancy Matrix from the World Health Organization was used to code the second sample of tweets for factors influencing vaccine confidence. Results: A total of 436 tweets were initially sampled from the Twitter Search Application Programming Interface. Misinformation was the most prominent content type (n=244, 56%) detected, followed by public reaction (n=122, 28%) and media reporting (n=69, 16%). No misinformation-related content reviewed was labeled as misleading by Twitter at the time of the study. An additional 1243 comments on misinformation-labeled tweets from 973 unique users were also collected, with 779 comments deemed relevant to study aims. Most of these comments expressed positive sentiment (n=612, 78.6%) to misinformation and did not refute it. Based on the World Health Organization Strategic Advisory Group of Experts framework, the most common vaccine hesitancy theme was individual or group influences (n=508, 65%), followed by vaccine or vaccination-specific influences (n=110, 14%) and contextual influences (n=93, 12%). Common misinformation themes observed included linking the death of Hank Aaron to "suspicious" elderly deaths following vaccination, claims about vaccines being used for depopulation, death panels, federal officials targeting Black Americans, and misinterpretation of VAERS reports. Four users engaging with or posting misinformation were verified on Twitter at the time of data collection. Conclusions: Our study found that the death of a high-profile ethnic minority celebrity led to the spread of misinformation on Twitter. This misinformation directly challenged the safety and effectiveness of COVID-19 vaccines at a time when ensuring vaccine coverage among minority populations was paramount. Misinformation targeted at minority groups and echoed by other verified Twitter users has the potential to generate unwarranted vaccine hesitancy at the expense of people such as Hank Aaron who sought to promote public health and community immunity.

Synthetic Cannabinoids in Prisons: Content Analysis of TikToks.

Background: Synthetic cannabinoids are a significant public health concern, especially among incarcerated populations due to increased reports of abuse. Recent news reports have highlighted the severe consequences of K2/Spice, a synthetic cannabinoid, among the prison population in the United States. Despite regulations against cell phone use, inmates use TikTok to post K2/Spice-related content. Objective: This study aimed to examine TikTok posts for use and illicit distribution of psychoactive substances (eg, K2/Spice) among incarcerated populations. Methods: The study collected TikTok videos associated with the #k2spice hashtag and used a data collection approach similar to snowball sampling. Inductive coding was used to conduct content analysis of video characteristics. Videos were manually annotated to generate binary classifications related to the use of K2/Spice as well as selling and buying activities associated with it. Statistical analysis was used to determine associations between a video's user engagement and an intent to buy or sell K2/Spice. Results: A total of 89 TikTok videos with the hashtag #k2spice were manually coded, with 40% (n=36) identified as displaying the use, solicitation, or adverse effects of K2/Spice among the prison population. Of them, 44.44% (n=16) were in a prison-based setting documenting adverse effects including possible overdose. Videos with higher user engagement were positively correlated with comments indicating an intent to buy or sell K2/Spice. Conclusions: K2/Spice is a drug subject to abuse among prison inmates in the United States, including depictions of its harmful effects being recorded and shared on TikTok. Lack of policy enforcement on TikTok and the need for better access to treatment services within the prison system may be exacerbating substance use among this highly vulnerable population. Minimizing the potential individual harm of this content on the incarcerated population should be a priority for social media platforms and the criminal justice system alike.

Neural precursor cells form integrated brain-like tissue when implanted into rat cerebrospinal fluid.

There is tremendous interest in transplanting neural precursor cells for brain tissue regeneration. However, it remains unclear whether a vascularized and integrated complex neural tissue can be generated within the brain through transplantation of cells. Here, we report that early stage neural precursor cells recapitulate their seminal properties and develop into large brain-like tissue when implanted into the rat brain ventricle. Whereas the implanted cells predominantly differentiated into glutamatergic neurons and astrocytes, the host brain supplied the intact vasculature, oligodendrocytes, GABAergic interneurons, and microglia that seamlessly integrated into the new tissue. Furthermore, local and long-range axonal connections formed mature synapses between the host brain and the graft. Implantation of precursor cells into the CSF-filled cavity also led to a formation of brain-like tissue that integrated into the host cortex. These results may constitute the basis of future brain tissue replacement strategies.