The Volume and Tone of Twitter Posts About Cannabis Use During Pregnancy: Protocol for a Scoping Review

Cresswell, Liam; Espín-Noboa, Lisette; Murphy, Malia S. Q.; Ramlawi, Serine; Walker, MC; Karsai, Márton; Corsi, Daniel J.

doi:10.2196/34421

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…There is a clear and pronounced advertising presence on Twitter of loosely regulated substances touted to treat COVID-19, although this type of self-treatment lacks evidentiary support. Twitter is a medium known for rapid spread of medical misinformation, perhaps especially concerning substances like CBD [54][55][56][57]. The COVID-19 pandemic has been yet another opportunity for CBD marketers and sellers to mislead the public about CBD's role in treating or preventing the disease.…”

Section: Discussionmentioning

confidence: 99%

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

Turner¹,

Kantardzic²,

Vickers‐Smith³

et al. 2023

JMIR Infodemiology

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Background The 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.

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Section: Discussionmentioning

confidence: 99%

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

Turner¹,

Kantardzic²,

Vickers‐Smith³

et al. 2023

JMIR Infodemiology

View full text Add to dashboard Cite

show abstract

“…A manual examination of these topics resulted in nine health categories. Some of these categories were also used in other cannabis-related Twitter studies [24][25][26][27]. Regarding our result on "concern over the effects of cannabis on children, teenagers, pregnant women, and individuals with illnesses," one study used a topic-modeling approach to investigate tweets related to cannabis use in pregnancy [24].…”

Section: Cannabis Addiction (T129)mentioning

confidence: 99%

“…Some of these categories were also used in other cannabis-related Twitter studies [24][25][26][27]. Regarding our result on "concern over the effects of cannabis on children, teenagers, pregnant women, and individuals with illnesses," one study used a topic-modeling approach to investigate tweets related to cannabis use in pregnancy [24]. The study identified nine topic clusters, including effects of cannabis during pregnancy, cannabis exposure on infants, and legalization and police.…”

Section: Cannabis Addiction (T129)mentioning

confidence: 99%

Sentiment and Topic Modeling Analysis on Twitter Reveals Concerns over Cannabis-Containing Food after Cannabis Legalization in Thailand

Lerksuthirat,

Srisuma,

Ongphiphadhanakul

et al. 2023

Healthc Inform Res

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Objectives: Twitter has been used to express a diverse range of public opinions about cannabis legalization in Thailand. The purpose of this study was to observe changes in sentiments after cannabis legalization and to investigate health-related topics discussed on Twitter.Methods: Tweets in Thai and English related to cannabis were scraped from Twitter between May 1 and June 13, 2022, during cannabis legalization in Thailand. Sentiment and topic-modeling analyses were used to compare the content of tweets before and after legalization. Health-related topics were manually grouped into categories by their content and rated according to the number of corresponding tweets.Results: We collected 21,242 and 6,493 tweets, respectively, for Thai and English search terms. A sharp increase in the number of tweets related to cannabis legalization was detected at the time of its public announcement. Sentiment analysis in the Thai search group showed a significant change (p < 0.0001) in sentiment distribution after legalization, with increased negative and decreased positive sentiments. A significant change was not found in the English search group (p = 0.4437). Regarding cannabis-containing food as a leading issue, topic-modeling analysis revealed public concerns after legalization in the Thai search group, but not the English one. Topics related to cannabis tourism surfaced only in the English search group.Conclusions: Since cannabis legalization, the primary health-related concern has been cannabis-containing food. Education and clear regulations on cannabis use are required to strengthen oversight of cannabis in the Thai population, as well as among medical tourists.

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“I don’t need my kid to be high”: prioritizing harm reduction when using cannabis during pregnancy

Gould,

Ganesh,

Ceasar

2024

Harm Reduct J

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BackgroundCannabis is the most common illicit substance used in pregnancy. As use continues to increase, understanding peoples’ behaviors surrounding cannabis use during pregnancy is needed to improve maternal and child health outcomes. The aim of this study was to better understand pregnant individuals' perceptions and knowledge of cannabis use and use patterns as well as the social and environmental factors that may influence their use.MethodsWe conducted interviews with 19 participants between December 2022 and March 2023. Individuals self-identified as BIPOC (Black, Indigenous, People of Color), were over 21 years of age, spoke English or Spanish, resided in California, and had used cannabis during pregnancy in the last 0–2 years. Using qualitative, constructivist grounded theory methods, we analyzed the contexts that contributed to participants’ lived experiences surrounding cannabis use behaviors during pregnancy.ResultsParticipants reported making conscious decisions to responsibly manage their cannabis use during pregnancy to minimize potential harm to the fetus. Participants prioritized making what they perceived to be safer adjustments to their use of cannabis: (1) changing the amount of cannabis used, (2) changing the types of cannabis products used, and (3) changing sources of cannabis procurement.DiscussionOur findings show that pregnant individuals are seeking information about safe cannabis use beyond medical supervision and are open to altering their cannabis consumption patterns. However, they are unable to find trustworthy and evidence-based harm reduction practices which can be implemented to mitigate harm to their unborn children. A harm reduction approach is needed in the field of maternal cannabis use to promote positive maternal and fetal health outcomes.ConclusionsMore data is needed on comprehensive harm reduction approaches to cannabis use during pregnancy. This requires implementation of education on these topics in healthcare settings presented by prenatal care clinicians.

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The Volume and Tone of Twitter Posts About Cannabis Use During Pregnancy: Protocol for a Scoping Review

Cited by 5 publications

References 35 publications

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

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

Sentiment and Topic Modeling Analysis on Twitter Reveals Concerns over Cannabis-Containing Food after Cannabis Legalization in Thailand

“I don’t need my kid to be high”: prioritizing harm reduction when using cannabis during pregnancy

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