Infodemiological Examination of Personal and Commercial Tweets About Cannabidiol: Term and Sentiment Analysis.

BACKGROUND: In the absence of official clinical trial information, data from social networks can be used by public health and medical researchers to assess public claims about loosely regulated substances such as cannabidiol (CBD). For example, this can be achieved by comparing the medical conditions targeted by those selling CBD against the medical conditions patients commonly treat with CBD. OBJECTIVE: The objective of this study was to provide a framework for public health and medical researchers to use for identifying and analyzing the consumption and marketing of unregulated substances. Specifically, we examined CBD, which is a substance that is often presented to the public as medication despite complete evidence of efficacy and safety. METHODS: We collected 567,850 tweets by searching Twitter with the Tweepy Python package using the terms "CBD" and "cannabidiol." We trained two binary text classifiers to create two corpora of 167,755 personal use and 143,322 commercial/sales tweets. Using medical, standard, and slang dictionaries, we identified and compared the most frequently occurring medical conditions, symptoms, side effects, body parts, and other substances referenced in both corpora. In addition, to assess popular claims about the efficacy of CBD as a medical treatment circulating on Twitter, we performed sentiment analysis via the VADER (Valence Aware Dictionary for Sentiment Reasoning) model on the personal CBD tweets. RESULTS: We found references to medically relevant terms that were unique to either personal or commercial CBD tweet classes, as well as medically relevant terms that were common to both classes. When we calculated the average sentiment scores for both personal and commercial CBD tweets referencing at least one of 17 medical conditions/symptoms terms, an overall positive sentiment was observed in both personal and commercial CBD tweets. We observed instances of negative sentiment conveyed in personal CBD tweets referencing autism, whereas CBD was also marketed multiple times as a treatment for autism within commercial tweets. CONCLUSIONS: Our proposed framework provides a tool for public health and medical researchers to analyze the consumption and marketing of unregulated substances on social networks. Our analysis showed that most users of CBD are satisfied with it in regard to the condition that it is being advertised for, with the exception of autism.

Randomised controlled trial of a brief, clinic-based intervention to promote safer sex among young Black men who have sex with men: implications for pre-exposure prophylaxis-related counselling.

Background The aim of this study was to determine the 3-month efficacy of a single-session, clinic-based intervention promoting condom use for anal and oral sex among HIV-uninfected Black young men who have sex with men (YBMSM). METHODS: A pre-post test randomised controlled trial (RCT) was conducted from 2012 to 2015 using a 3-month period of observation. Recruitment and assessment occurred in sexually transmissible infection (STI) clinics. Men were randomised to either the intervention condition (n=142) or a standard-of-care control condition (n=135). The experimental condition comprised a single session of a one-to-one program designed for use in STI clinics. YBMSM completed both baseline and 3-month follow-up assessments. Outcomes measures were condomless anal insertive sex, condomless anal receptive sex and condomless oral sex. RESULTS: Among men receiving the intervention, 11.2% (n=15) reported any condomless anal insertive sex at follow-up, compared with 20.6% (n=27) among controls (rate ratio=0.54, P=0.04). In addition, 12.0% (n=17) of men receiving the intervention reported any condomless anal receptive sex at follow-up, compared with 21.6% (n=29) among controls (rate ratio=0.55, P=0.03). When combining insertive and receptive anal sex, 18.3% (n=26) of men receiving the intervention reported any condomless sex, compared with 31.1% (n=42) among controls (rate ratio=0.59, P=0.01). Furthermore, 45.8% (n=33) of men receiving the intervention reported any condomless oral sex at follow-up, compared with 63.2% (n=48) among controls (rate ratio=0.72, P=0.03). CONCLUSIONS: This analysis of data from a Phase 3 RCT suggests that a single session of a clinic-based behavioural intervention may effectively promote the consistent use of condoms for anal and oral sex among HIV-uninfected YBMSM. The single-session program may be a valuable counselling tool for use in conjunction with recommended quarterly clinic appointments for YBMSM using pre-exposure prophylaxis.

Efficacy of a Clinic-Based Safer Sex Program for Human Immunodeficiency Virus-Uninfected and Human Immunodeficiency Virus-Infected Young Black Men Who Have Sex With Men: A Randomized Controlled Trial.

OBJECTIVE: To test the efficacy of a single-session, clinic-based intervention designed to promote condom use among young black men who have sex with men (YBMSM). METHODS: Six hundred YBMSM were enrolled in a randomized controlled trial, using a 12-month observation period. An intent-to-treat analysis was performed, with multiple imputation for missing data. RESULTS: Compared with the reference group, human immunodeficiency virus (HIV)-infected men in the intervention group had 64% greater odds of reporting consistent condom use for anal receptive sex over 12 months (estimated odds ratio, 1.64; 95% confidence interval, 1.23-2.17, P = 0.001). Also, compared with the reference group, HIV-uninfected men in the intervention group had more than twice the odds of reporting consistent condom use for anal receptive sex over 12 months (estimated odds ratio, 2.14; 95% confidence interval, 1.74-2.63, P < 0.001). Significant intervention effects relative to incident sexually transmitted diseases were not observed. CONCLUSIONS: A single-session, clinic-based, intervention may help protect HIV-uninfected YBMSM against HIV acquisition and HIV-infected YBMSM from transmitting the virus to insertive partners.

Effectiveness of an anger control program among veterans with PTSD and other mental health issues: A comparative study.

OBJECTIVE: This study examines the effectiveness of an anger management program among veterans with posttraumatic stress disorder (PTSD) and other mental health issues. METHOD: Veterans with (n = 76) and without (n = 58) PTSD completed anger management groups at the Crescenz Veterans Affairs Medical Center. Self-rated checklists of anger and PTSD symptoms (for those with PTSD) were completed before and after the group. RESULTS: Significant improvement in anger was observed in the overall sample (p < .001) but did not differ based on PTSD diagnosis. No significant PTSD symptom changes were observed. CONCLUSIONS: Veterans with broad mental health concerns benefited significantly from this anger management program, consistent with prior research. Implications for program improvement and future research are discussed.

Development and validation of a community-level social determinants of health index for drug overdose deaths in the HEALing Communities Study.

INTRODUCTION: Social determinants of health (SDoH), such as socioeconomic status, education level, and food insecurity, are believed to influence the opioid crisis. While global SDoH indices such as the CDC's Social Vulnerability Index (SVI) and Area Deprivation Index (ADI) combine the explanatory power of multiple social factors for understanding health outcomes, they may be less applicable to the specific challenges of opioid misuse and associated outcomes. This study develops a novel index tailored to opioid misuse outcomes, tests the efficacy of this index in predicting drug overdose deaths across contexts, and compares the explanatory power of this index to other SDoH indices. METHODS: Focusing on four HEALing Communities Study (HCS) states (Kentucky, Massachusetts, New York and Ohio; encompassing 4269 ZIP codes), we identified multilevel SDoH potentially associated with opioid misuse and aggregated publicly available data for each measure. We then leveraged a random forest model to develop a composite measure that predicts age-adjusted drug overdose mortality rates based on SDoH. We used this composite measure to understand HCS and non-HCS communities in terms of overdose risk across areas of varying racial composition. Finally, we compared variance in drug overdose deaths explained by this index to variance explained by the SVI and ADI. RESULTS: Our composite measure included 28 SDoH measures and explained approximately 89 % percent of variance in age-adjusted drug overdose mortality across HCS states. Health care measures, including emergency department visits and primary care provider availability, were top predictors within the index. Index accuracy was robust within and outside of HCS communities and states. This measure identified high levels of overdose mortality risk in segregated communities. CONCLUSIONS: Existing SDoH indices fail to explain much variation in area-level overdose mortality rates. Having tailored composite indices can help us to identify places in which residents are at highest risk based on their composite contexts. A comprehensive index can also help to develop effective community interventions for programs such as HCS by considering the context in which people live.

Detecting Tweets Containing Cannabidiol-Related COVID-19 Misinformation Using Transformer Language Models and Warning Letters From Food and Drug Administration: Content Analysis and Identification.

Background: COVID-19 has introduced yet another opportunity to web-based sellers of loosely regulated substances, such as cannabidiol (CBD), to promote sales under false pretenses of curing the disease. Therefore, it has become necessary to innovate ways to identify such instances of misinformation. Objective: We sought to identify COVID-19 misinformation as it relates to the sales or promotion of CBD and used transformer-based language models to identify tweets semantically similar to quotes taken from known instances of misinformation. In this case, the known misinformation was the publicly available Warning Letters from Food and Drug Administration (FDA). Methods: We collected tweets using CBD- and COVID-19-related terms. Using a previously trained model, we extracted the tweets indicating commercialization and sales of CBD and annotated those containing COVID-19 misinformation according to the FDA definitions. We encoded the collection of tweets and misinformation quotes into sentence vectors and then calculated the cosine similarity between each quote and each tweet. This allowed us to establish a threshold to identify tweets that were making false claims regarding CBD and COVID-19 while minimizing the instances of false positives. Results: We demonstrated that by using quotes taken from Warning Letters issued by FDA to perpetrators of similar misinformation, we can identify semantically similar tweets that also contain misinformation. This was accomplished by identifying a cosine distance threshold between the sentence vectors of the Warning Letters and tweets. Conclusions: This research shows that commercial CBD or COVID-19 misinformation can potentially be identified and curbed using transformer-based language models and known prior instances of misinformation. Our approach functions without the need for labeled data, potentially reducing the time at which misinformation can be identified. Our approach shows promise in that it is easily adapted to identify other forms of misinformation related to loosely regulated substances.