Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 30, 2023
Date Accepted: Oct 11, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Transformer-Based Topic Modeling to Examine Discussions of Delta-8 THC
ABSTRACT
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, or CBD. Most states permit the sale of hemp and hemp-derived CBD 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.
Objective:
The goal of this study is to implement a novel topic modeling approach based on transformers, a state-of-the art natural language processing architecture, to identify and describe emerging trends and topics of discussion about delta-8 THC from social media discourse, including potential symptoms and adverse health outcomes experienced by people using delta-8 THC products.
Methods:
Posts from January 2008 to December 2021 discussing delta-8 THC were isolated from cannabis-related drug forums on Reddit, a social media platform which hosts the largest online drug forums worldwide. Using Python, unsupervised topic modeling leveraging state-of-the-art transformer-based models was employed. The models cluster posts into topics and assign labels describing the kinds of issues being discussed with respect to delta-8 THC. Results were then validated by human subject matter experts.
Results:
There were 41,191 delta-8 THC posts identified and 81 topics isolated, the most prevalent being 1) discussion of specific brands/products, 2) comparison of delta-8 THC to other hemp-derived cannabinoids, 3) and safety warnings. About 5% of the resulting topics included posts discussing health-related symptoms such as anxiety, sleep disturbance, and breathing problems. Until 2020, Reddit posts contained less than 10 mentions of delta-8-THC for every 100,000 cannabis posts annually. However, in 2020 these rates increased by 13 times the 2019 rate (to 99.2 mentions per 100,000 cannabis posts) and continued to increase into 2021 (349.5 mentions per 100,000 cannabis posts).
Conclusions:
Our study provides insights into emerging public health concerns around delta-8 THC, a novel substance about which little is known. Furthermore, we demonstrate the utility of transformer-based unsupervised learning approaches to derive intelligible topics from highly unstructured discussions of delta-8 THC, which may help improve the timeliness of identification of emerging health concerns related to new substances. Clinical Trial: N/A
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.