Trial reportAddictive behaviors2022
Communicating the risks of tobacco and alcohol co-use.
Trial report in Addictive behaviors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Rates and correlates of simultaneous use and mixing of alcohol, tobacco, and cannabis among adults who currently use alcohol and tobacco.Addictive behaviors · 2025Article
- Perceptions of cannabis warnings and recommendations for improvement: a qualitative study with people who use cannabis from the United States.BMC public health · 2025Article
- Risk factors for non-vertebral fractures in community-dwelling elderly: a 10-year follow-up study in New Zealand.Archives of osteoporosis · 2025Article
- Exploring the association of time-inconsistent preferences with smoking behavior: A cross-sectional survey study from Sichuan, China.Tobacco induced diseases · 2025Article
- Article
- Socioeconomic Inequalities in Alcohol and Tobacco Consumption: A National Ecological Study in Mexican Adolescents.TheScientificWorldJournal · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundWhile tobacco and alcohol co-use is highly prevalent across the United States, little experimental research has examined ways to counter such dual use. We developed and tested messages about the risks of co-using tobacco and alcohol among adults who used a combustible tobacco product and drank alcohol within the 30 days.
methodsIn an online experiment, 1,300 participants were randomly assigned to read different messages about tobacco and alcohol co-use (e.g., Alcohol and tobacco cause throat cancer). Three between-subjects experiments manipulated the presence of: 1) a marker word (e.g., Warning), 2) text describing the symptoms of health effects and a quitting self-efficacy cue, and 3) an image depicting the health effect. Participants rated each message using a validated Perceived Message Effectiveness (PME) scale. We used independent samples t-tests to examine differences between experimental conditions. Results include effect sizes (Cohen's d) to compare standardized mean differences.
resultsOur sample was 64% male, 70% white, 23% Black, and 17% Hispanic/Latino with a mean age of 42.4 (SD = 16.4) years. Messages that described the symptoms of the health effect (d = 0.17, p = 0.002) and included an image (d = 0.11, p = 0.04) were rated significantly higher in PME compared with messages that did not describe symptoms and were text-only. We found no significant effects of a marker word or self-efficacy cue on PME.
conclusionsMessages that describe the symptoms of health effects and include text and images may be particularly effective for communicating the risks of tobacco and alcohol co-use and decreasing adverse health effects from co-use.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.