Characteristics and engagement among English-language online forums for addiction recovery available in the US.

In developing public resources for the Networks Enhancing Addiction Recovery - Forum Activity Roadmap (NEAR-FAR), we completed a systematic observational study of English-language online forums related to recovery from alcohol or other drug addiction in late 2021. Among 207 identified forums, the majority were classified as "general addiction" or alcohol-focused, though classifications related to other substances were common on websites hosting multiple forums. Commonly used social media platforms such as Reddit, Facebook, or Quora offered easily accessible venues for individuals seeking online support related to a variety of substances.

Characterizing online social support for alcohol use disorder: A mixed-methods approach.

Background: Online social media communities are increasingly popular venues for discussing alcohol use disorder (AUD) and recovery. Little is known about distinct contexts of social support that are exchanged in this milieu, which are critical to understanding the social dynamics of online recovery support.

Methods: We randomly selected one post per day over the span of a year from the StopDrinking recovery forum.

Stakeholder-Driven Intervention Development for Dialysis Trials Using a Design Sprint Methodology.

Rationale & Objective: Stigma contributes to ineffective treatment for pain among individuals with kidney failure on dialysis, particularly with buprenorphine pain treatment. To address stigma, we adapted a Design Sprint, an industry-developed structured exercise where an interdisciplinary group works over 5 days to clarify the problem, identify and choose a solution, and build and test a prototype.

Study Design: Adapted Design Sprint which clarified the problem to be solved, proposed solutions, and created a blueprint for the selected solution.

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.

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.

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.

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.

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.

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.

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.

E-Cigarette-Related Nicotine Misinformation on Social Media.

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. A total of 10.

Using TikTok in recovery from substance use disorder.

Background: There are many effective treatment options for substance use disorder (SUD), yet most individuals with SUD do not seek formal treatment services. Given the rising popularity of TikTok and need to foster innovative means through which to attract and engage individuals with SUD with treatment, we sought to characterize how TikTok users in SUD recovery are using this platform to bolster their recovery support and/or give hope to others who are struggling with substance use.

Methods: Our sample consisted of 82 of the most liked TikTok videos related to attempts to cut down on or abstain from substances and/or strengthen SUD recovery.

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.

#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.

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.

#DoctorsSpeakUp: Lessons learned from a pro-vaccine Twitter event.

Background: In response to growing anti-vaccine activism on social media, the #DoctorsSpeakUp event was designed to promote pro-vaccine advocacy. This study aimed to analyze Twitter content related to the event to determine (1) characteristics of the Twitter users who authored these tweets, (2) the proportion of tweets expressing pro-vaccine compared to anti-vaccine sentiment, and (3) the content of these tweets.

Methods: Data were collected using Twitter's Filtered Streams Interface, and included all publicly available tweets with the "#DoctorsSpeakUp" hashtag on March 5, 2020, the day of the event.

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.

COVID-19 Social Distancing and Online Mutual Help Engagement for Alcohol Use Recovery.

Introduction: COVID-19 and associated social distancing has presented challenges for individuals engaging in face-to-face mutual help groups (MHGs) such as Alcoholics Anonymous for alcohol use recovery. Online MHGs may be particularly appealing to individuals with limited access or inclination to attend in-person MHGs. We examined engagement within the popular "StopDrinking" online MHG, hypothesizing that engagement would increase due to demand for virtual peer support as COVID-19 social distancing progressed.

Measures of Organizational Culture and Climate in Primary Care: a Systematic Review.

Background: Primary care is increasingly contributing to improving the quality of patient care. This has imposed significant demands on clinicians with rising needs and limited resources. Organizational culture and climate have been found to be crucial in improving workforce well-being and hence quality of care.

Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.

Background: Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tweets and characterize sentiments in them can underpin a Twitter-based vaping surveillance system. Compared with traditional machine learning classifiers that are reliant on annotations that are expensive to obtain, deep learning classifiers offer the advantage of requiring fewer annotated tweets by leveraging the large numbers of readily available unannotated tweets.

Integrating Social Dynamics Into Modeling Cigarette and E-Cigarette Use.

. The use of electronic cigarettes (e-cigarette) offers potential to facilitate cigarette smoking cessation, yet potentially increases risk of cigarette smoking initiation. This relationship has been primarily modeled in mathematical ways that often do not represent real-world complexities, which could inform decisions regarding local prevention programs or policies.

JUUL on Twitter: Analyzing Tweets About Use of a New Nicotine Delivery System.

Background: Initial reports suggest that JUUL, a popular e-cigarette, is being used in schools and other locations in which cigarette smoking is illegal or discouraged. However, there is little scholarly research documenting this. We aimed to make a systematic analysis of JUUL use themes and sentiment on Twitter.

I wake up and hit the JUUL: Analyzing Twitter for JUUL nicotine effects and dependence.

Background: JUUL-a novel electronic nicotine delivery system (ENDS)-comprises most of the ENDS market share. Additionally, JUUL has a high nicotine content and utilizes a patented nicotine salt formulation aimed to speed absorption. Many JUUL users are not aware of the nicotine content and therefore may not be expecting acute nicotine effects or potential for dependence.