Assessing Responses to Cannabis Health Warnings Among Adults in U.S. Recreational States

Guided by the Extended Parallel Process Model, this study used BERTopic modeling and manual coding to analyze reactions to cannabis health warnings and to assess how those responses were associated with message reactions, health beliefs, and intentions.

In 2022, adults (aged ≥21 years; N=1,078) living in recreational cannabis-use-approved U.S. states who reported using cannabis in the past year were randomly assigned to view text-only or pictorial cannabis health warnings. Participants wrote free-response reactions to the warnings, which were analyzed in 2025 using BERTopic, a clustering approach of topical modeling. Participant responses were manually coded into Extended Parallel Process Model response categories (maladaptive or adaptive). Three linear regression models were conducted, with the main outcome measures (i.e., reactance, health beliefs, and intentions to prevent harms from using cannabis) as the dependent variables; frequency of cannabis use (e.g., past 30-day use and problematic cannabis-use risk), cannabis risk perceptions, and Extended Parallel Process Model responses as predictors; and condition as a control variable.

BERTopic identified 11 thematic subtopics that were coded for Extended Parallel Process Model responses. Responses were more maladaptive (624; 57.9%) than adaptive (454; 42.1%). Multiple linear regression results showed that maladaptive Extended Parallel Process Model response was significantly associated with higher levels of reactance (β=0.38), less accurate health beliefs about cannabis harms (β= -0.32), and lower intentions to prevent harms from using cannabis (β= -0.31).

Results provide data-driven evidence on how U.S. cannabis consumers evaluate health warnings from established cannabis control systems. Participant responses reveal areas of resistance and acceptance to warnings, identifying potential ways to improve future messaging.