COVID-19 pediatric vaccine Hesitancy: Themes and interactions with verified twitter accounts.

Background: Though vaccine hesitancy and misinformation has been pervasive online, via platforms such as Twitter, little is known about the characteristics of pediatric-specific vaccine hesitancy and how online users interact with verified user accounts that may hold larger influence. Identifying specific COVID-19 pediatric vaccine hesitancy themes and online user interaction and sentiment may help inform health promotion that addresses vaccine hesitancy more effectively among parents and caregivers of pediatric populations.

Methods: Keywords were used to query the public streaming twitter application programming interface to collect tweets associated with COVID-19 pediatric vaccines.

Identification of Cannabis Product Characteristics and Pricing on Dark Web Markets.

Growing cannabis use has made it the most widely cultivated and trafficked illicit drug globally according to the World Health Organization, with 147 million people consuming cannabis-derived products (CDPs) in various product forms and constituency. Despite restrictions in certain countries, unregulated access can still be found on the dark web which specializes in trafficking of illicit goods. The objective was to systematically collect data from multiple marketplaces to identify types of cannabis products offered for sale.

Multifactor Quality and Safety Analysis of Semaglutide Products Sold by Online Sellers Without a Prescription: Market Surveillance, Content Analysis, and Product Purchase Evaluation Study.

Background: Over the past 4 decades, obesity has escalated into a global epidemic, with its worldwide prevalence nearly tripling. Pharmacological treatments have evolved with the recent development of glucagon-like peptide 1 agonists, such as semaglutide. However, off-label use of drugs such as Ozempic for cosmetic weight loss has surged in popularity, raising concerns about potential misuse and the emergence of substandard and falsified products in the unregulated supply chain.

Cannabis-Derived Product Types, Flavors, and Compound Types From an E-Commerce Website.

Importance: Cannabis-derived products (CDPs) are widely available and diverse. A classification of product and flavor types is necessary to establish a foundation for comparative research, although research aiming to classify cannabis in its variety of products, flavors, and cannabinoid compounds based on public online e-commerce data is lacking.

Objective: To analyze data from a large cannabis e-commerce marketplace to identify and characterize cannabis product types, flavors, and compound types.

Detection and Characterization of Online Substance Use Discussions Among Gamers: Qualitative Retrospective Analysis of Reddit r/StopGaming Data.

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.

Evaluating the Influence of Role-Playing Prompts on ChatGPT's Misinformation Detection Accuracy: Quantitative Study.

Background: During the COVID-19 pandemic, the rapid spread of misinformation on social media created significant public health challenges. Large language models (LLMs), pretrained on extensive textual data, have shown potential in detecting misinformation, but their performance can be influenced by factors such as prompt engineering (ie, modifying LLM requests to assess changes in output). One form of prompt engineering is role-playing, where, upon request, OpenAI's ChatGPT imitates specific social roles or identities.

Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study.

Background: Manually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes.

Abortion pill marketing and sourcing on twitter following Dobbs v. Jackson supreme court ruling.

Objective: This study examines abortion-related discourse on Twitter (X) pre-and post-Dobbs v. Jackson ruling, which eliminated the constitutional right to abortion.

Study Design: We used a custom data collection tool to collect tweets directly from Twitter using abortion-related keywords.

Digital technologies used in clinical trial recruitment and enrollment including application to trial diversity and inclusion: A systematic review.

Background: Many clinical trials fail because of poor recruitment and enrollment which can directly impact the success of biomedical and clinical research outcomes. Options to leverage digital technology for improving clinical trial management are expansive, with potential benefits for improving access to clinical trials, encouraging trial diversity and inclusion, and potential cost-savings through enhanced efficiency.

Objectives: This systematic review has two key aims: (1) identify and describe the digital technologies applied in clinical trial recruitment and enrollment and (2) evaluate evidence of these technologies addressing the recruitment and enrollment of racial and ethnic minority groups.

Search Engines and Generative Artificial Intelligence Integration: Public Health Risks and Recommendations to Safeguard Consumers Online.

Background: The online pharmacy market is growing, with legitimate online pharmacies offering advantages such as convenience and accessibility. However, this increased demand has attracted malicious actors into this space, leading to the proliferation of illegal vendors that use deceptive techniques to rank higher in search results and pose serious public health risks by dispensing substandard or falsified medicines. Search engine providers have started integrating generative artificial intelligence (AI) into search engine interfaces, which could revolutionize search by delivering more personalized results through a user-friendly experience.

Is This Safe? Examining Safety Assessments of Illicit Drug Purchasing on Social Media Using Conjoint Analysis.

: Illicit substance sales facilitated by social media platforms are a growing public health issue given recent increases in overdose deaths, including an alarming rise in cases of fentanyl poisoning. However, little is known about how online users evaluate what features of social media posts convey safety, which can influence their intent to source illicit substances. : This study adapts conjoint analysis which assessed how attributes of social media posts (i.

Rates of adverse events and related risk factors following e-cigarette use.

Background: E-cigarettes have emerged as popular products, especially for younger populations. However, concerns regarding health effects exist and there is a notable gap in understanding the prevalence and nature of adverse events. This study aims to examine the rate of adverse events in individuals who use e-cigarettes in a large sample.

Detecting nuance in conspiracy discourse: Advancing methods in infodemiology and communication science with machine learning and qualitative content coding.

The spread of misinformation and conspiracies has been an ongoing issue since the early stages of the internet era, resulting in the emergence of the field of infodemiology (i.e., information epidemiology), which investigates the transmission of health-related information.

Identification and Characterization of Illegal Sales of Cannabis and Nicotine Delivery Products on Telegram Messaging Platform.

Introduction: Unregulated and potentially illegal sales of tobacco, nicotine, and cannabis products have been detected on various social media platforms, e-commerce sites, online retailers, and the dark web. New end-to-end encrypted messaging services are popular among online users and present opportunities for marketing, trading, and selling of these products. The purpose of this study was to identify and characterize tobacco, nicotine, and cannabis selling activity on the messaging platform Telegram.

Characterization of COVID-19 vaccine clinical trial discussions on the social question-and-answer site Quora.

Introduction: Throughout the COVID-19 pandemic, underserved populations, such as racial and ethnic minorities, were disproportionately impacted by illness, hospitalization, and death. Equity in clinical trials means that the participants in clinical trials represent the people who are most likely to have the health condition and need the treatment that the trial is testing. Infodemiology approaches examining user conversations on social media platforms have the potential to elucidate specific barriers and challenges related to clinical trial participation, including among racial and ethnic minority populations.

Detection and Characterization of Web-Based Pediatric COVID-19 Vaccine Discussions and Racial and Ethnic Minority Topics: Retrospective Analysis of Twitter Data.

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.

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.

Inductive Characterization of ENDS-Associated Adverse Events Among California Young Adults.

Introduction: Previous studies have identified numerous adverse events experienced with the use of ENDS or E-cigarettes. However, much remains unknown about adverse event frequency, duration, and response experienced by users. The purpose of this study was to inductively characterize ENDS-attributed adverse events among young adults.

Assessing the Impact of the Massachusetts Temporary Flavor Ban on Licensed Tobacco Retailers.

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.

Tobacco/nicotine dependence as a risk factor for substance use disorders and related mental health conditions among cancer patients.

Background: Cancer patients often face multiple comorbidities and are at risk for various mental health conditions and substance use disorders. Tobacco/nicotine dependence (TND) is a known risk factor for poor health outcomes and has been associated with psychiatric disorders including substance use disorder. However, the specific relationship between TND and the risk of substance use disorder and mental health conditions among cancer patients remains underexplored.

The Influence of News Consumption Habits and Dispositional Traits on Trust in Medical Scientists.

Public trust in medical institutions is essential for ensuring compliance with medical directives. However, the politicization of public health issues and the polarized nature of major news outlets suggest that partisanship and news consumption habits can influence medical trust. This study employed a survey with 858 participants and used regression analysis to assesses how news consumption habits and information assessment traits (IATs) influence trust in medical scientists.