Trends in Firearm Injuries Treated in Emergency Departments by Individual- and County-Level Characteristics, 2019 to 2023.

Study Objective: To understand trends in nonfatal firearm injuries by examining rates of firearm injury emergency department (ED) visits stratified by individual- and county-level characteristics.

Methods: Data from participating EDs within 10 jurisdictions in the United States funded through the Centers for Disease Control and Prevention's Firearm Injury Surveillance Through Emergency Rooms program, including the District of Columbia, Florida, Georgia, New Mexico, North Carolina, Oregon, Utah, Virginia, Washington, and West Virginia, were analyzed. We examined trends in firearm injury ED visits by sex, age group, jurisdiction, county-level urbanicity, and county-level social vulnerability from January 2019 to August 2023.

Identification of Myths and Misinformation About Treatment for Opioid Use Disorder on Social Media: Infodemiology Study.

Background: Health misinformation and myths about treatment for opioid use disorder (OUD) are present on social media and contribute to challenges in preventing drug overdose deaths. However, no systematic, quantitative methodology exists to identify what types of misinformation are being shared and discussed.

Objective: We developed a multistage analytic pipeline to assess social media posts from Twitter (subsequently rebranded as X), YouTube, Reddit, and Drugs-Forum for the presence of health misinformation about treatment for OUD.

Using Transformer-Based Topic Modeling to Examine Discussions of Delta-8 Tetrahydrocannabinol: Content Analysis.

Background: Delta-8 tetrahydrocannabinol (THC) is a psychoactive cannabinoid found in small amounts naturally in the cannabis plant; it can also be synthetically produced in larger quantities from hemp-derived cannabidiol. Most states permit the sale of hemp and hemp-derived cannabidiol products; thus, hemp-derived delta-8 THC products have become widely available in many state hemp marketplaces, even where delta-9 THC, the most prominently occurring THC isomer in cannabis, is not currently legal. Health concerns related to the processing of delta-8 THC products and their psychoactive effects remain understudied.

Racial Concordance on Healthcare Use within Hispanic Population Subgroups.

Objective: To examine the association of patient-provider racial and ethnic concordance on healthcare use within Hispanic ethnic subgroups.

Methods: We estimate multivariate probit models using data from the Medical Expenditure Panel Survey, the only national data source measuring how patients use and pay for medical care, health insurance, and out-of-pocket spending. We collect and utilize data on preventive care visits, visits for new health problems, and visits for ongoing health problems from survey years 2007-2017 to measure health outcomes.

A Social-Ecological Approach to Modeling Sense of Virtual Community (SOVC) in Livestreaming Communities.

Participation in communities is essential to individual mental and physical health and can yield further benefits for members. With a growing amount of time spent participating in virtual communities, it's increasingly important that we understand how the community experience manifests in and varies across these online spaces. In this paper, we investigate Sense of Virtual Community (SOVC) in the context of live-streaming communities.

Development of a Machine Learning Model to Estimate US Firearm Homicides in Near Real Time.

Importance: Firearm homicides are a major public health concern; lack of timely mortality data presents considerable challenges to effective response. Near real-time data sources offer potential for more timely estimation of firearm homicides.

Objective: To estimate near real-time burden of weekly and annual firearm homicides in the US.

Trends in stigmatizing language about addiction: A longitudinal analysis of multiple public communication channels.

Introduction: Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data to assess progress made in reducing use of stigmatizing language about addiction.

Methods: Using language guidelines published by the federal National Institute on Drug Abuse (NIDA), we examined trends in use of stigmatizing terms about addiction across four popular public communication modalities: news articles, blogs, Twitter, and Reddit.

Evidence of the emergence of illicit benzodiazepines from online drug forums.

Illicit or 'designer' benzodiazepines are a growing contributor to overdose deaths. We employed natural language processing (NLP) to study benzodiazepine mentions over 10 years on 270 online drug forums (subreddits) on Reddit. Using NLP, we automatically detected mentions of illicit and prescription benzodiazepines, including their misspellings and non-standard names, grouping relative mentions by quarter.

Estimating Weekly National Opioid Overdose Deaths in Near Real Time Using Multiple Proxy Data Sources.

Importance: Opioid overdose is a leading public health problem in the United States; however, national data on overdose deaths are delayed by several months or more.

Objectives: To build and validate a statistical model for estimating national opioid overdose deaths in near real time.

Design, Setting, And Participants: In this cross-sectional study, signals from 5 overdose-related, proxy data sources encompassing health, law enforcement, and online data from 2014 to 2019 in the US were combined using a LASSO (least absolute shrinkage and selection operator) regression model, and weekly predictions of opioid overdose deaths were made for 2018 and 2019 to validate model performance.

Signals of increasing co-use of stimulants and opioids from online drug forum data.

Background: Despite recent rises in fatal overdoses involving multiple substances, there is a paucity of knowledge about stimulant co-use patterns among people who use opioids (PWUO) or people being treated with medications for opioid use disorder (PTMOUD). A better understanding of the timing and patterns in stimulant co-use among PWUO based on mentions of these substances on social media can help inform prevention programs, policy, and future research directions. This study examines stimulant co-mention trends among PWUO/PTMOUD on social media over multiple years.

Concerns among people who use opioids during the COVID-19 pandemic: a natural language processing analysis of social media posts.

Background: Timely data from official sources regarding the impact of the COVID-19 pandemic on people who use prescription and illegal opioids is lacking. We conducted a large-scale, natural language processing (NLP) analysis of conversations on opioid-related drug forums to better understand concerns among people who use opioids.

Methods: In this retrospective observational study, we analyzed posts from 14 opioid-related forums on the social network Reddit.

Characterizing and Identifying the Prevalence of Web-Based Misinformation Relating to Medication for Opioid Use Disorder: Machine Learning Approach.

Background: Expanding access to and use of medication for opioid use disorder (MOUD) is a key component of overdose prevention. An important barrier to the uptake of MOUD is exposure to inaccurate and potentially harmful health misinformation on social media or web-based forums where individuals commonly seek information. There is a significant need to devise computational techniques to describe the prevalence of web-based health misinformation related to MOUD to facilitate mitigation efforts.

Business and property types experiencing excess violent crime: a micro-spatial analysis.

Background: Beyond alcohol retail establishments, most business and property types receive limited attention in studies of violent crime. We sought to provide a comprehensive examination of which properties experience the most violent crime in a city and how that violence is distributed throughout a city.

Methods: For a large urban city, we merged violent incident data from police reports with municipal tax assessor data from 2012-2017 and tabulated patterns of violent crime for 15 commercial and public property types.