Back

Derived Intoxicating Cannabis Vape Product Attributes and Marketing in an Online Retail Environment

Chen-Sankey, J.; LoParco, C. R.; La Capria, K.; Meng, S.; Mazzeo, R.; Vijayakumar, N.; Kong, A. Y.; Tillett, K. K.; Berg, C.; Rossheim, M. E.

2025-01-23 public and global health
10.1101/2025.01.22.25320970 medRxiv
Show abstract

IntroductionThe 2018 Farm Bill unintentionally allowed the proliferation of derived intoxicating cannabis vape products (DICVPs), raising concerns about associated health risks. To inform public health prevention efforts, this study analyzed the product attributes and marketing features of DICVPs in an online retail environment. MethodsIn 2023, we extracted information on product attributes and descriptions of 490 DICVPs from two online retail websites with high web traffic. In 2024, two trained coders thematically coded product descriptions for their product characteristics and marketing features. ResultsOverall, 95 unique brands and 26 unique intoxicating cannabinoids were identified. The most frequent marketing features were overall vape product design and use (99.0%), including vaping satisfaction, discreetness, convenience, and use instructions. Regulation and compliance messages (91.6%) were also prevalent, including lab testing for additives and/or chemicals, health warnings, hemp-derived labels, references to the 2018 Farm Bill, and FDA approval statements. Other prominent themes included: flavor and sensation claims (79.6%, i.e., flavor variety, fruit flavors); psychoactive effect claims (43.3%, e.g., potency or expected user experience); product quality claims (38.4%, e.g., "quality," "natural," "purity"); and other positive effect claims (33.9%, e.g., mood enhancement, relaxation). DiscussionThe DICVP online marketplace is highly fragmented with a variety of brands and intoxicating compounds. Common marketing strategies promoting appealing flavors and positive vaping experiences may increase product use interest among young people. Features related to product legality and quality may reduce perceived barriers and risks of using products. Continuous monitoring of the DICVP marketplace is needed to inform policymaking.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.