Evidence map›Paper›PMID 40716688›Full record

Trial reportAmerican journal of preventive medicine2025

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

Zachary B Massey, Chau Tong, Tianting Zhang, Kate H Wexell, Yachao Li, Junru Zhao

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in American journal of preventive medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Zachary B MasseyTSET Health Promotion Research Center, Stephenson Cancer Center, The University of Oklahoma Health Sciences, Oklahoma City, Oklahoma; Department of Health Promotion Sciences, Hudson College of Public Health, University of Oklahoma Health Sciences, Oklahoma City, Oklahoma. Electronic address: zachary-massey@ou.edu.
Chau TongSchool of Journalism, University of Missouri, Columbia, Missouri; Institute for Data Science and Informatics, University of Missouri, Columbia, Missouri.
Tianting ZhangSchool of Journalism, University of Missouri, Columbia, Missouri.
Kate H WexellTruman School of Government and Public Affairs, University of Missouri, Columbia, Missouri.
Yachao LiDepartment of Communication, Journalism, and Film, School of the Arts and Communication, The College of New Jersey, Ewing Township, New Jersey; Department of Public Health, School of Nursing and Health Sciences, The College of New Jersey, Ewing Township, New Jersey.
Junru ZhaoTSET Health Promotion Research Center, Stephenson Cancer Center, The University of Oklahoma Health Sciences, Oklahoma City, Oklahoma; Department of Pediatrics, College of Medicine, The University of Oklahoma Health Sciences, Oklahoma City, Oklahoma.

Funding

Tissue Pathology Shared ResourceP30CA225520 · NCI · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI ROBERT S. MANNEL · 2018 to 2026
$27.1M
Developing and Testing Warning Labels for Retail Cannabis ProductsK01DA057395 · NIDA · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · PI Zachary Massey · 2023 to 2026
$717k
NCI NIH HHS P30 CA225520NIDA NIH HHS K01 DA057395
6 · The paper itself

Abstract

introductionGuided 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.

methodsIn 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.

resultsBERTopic 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).

conclusionsResults 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.

Indexed as

CannabisHealth Knowledge, Attitudes, PracticeMarijuana SmokingMarijuana UseAdultFemaleHumansIntentionLinear ModelsMaleMiddle AgedUnited StatesYoung Adult

Identifiers

PMID40716688
PMCPMC13258294

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.