ArticleSocial psychiatry and psychiatric epidemiology2023
Toward a typology of driving under the influence of alcohol and drugs.
Article in Social psychiatry and psychiatric epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- Understanding the Cause and Diversity of Women's Drink and Drug Driving-A Qualitative Exploration.Drug and alcohol review · 2026Article
- Article
- Driving under the influence of cannabis and alcohol: Evidence from a national sample of young drivers.Addictive behaviors · 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
3 authors at 3 institutions in 1 country.
Funding
Abstract
purposeMost research on driving under the influence (DUI) has relied upon variable-centered methods that examine predictors/correlates of DUI. In the present study, we utilize a person-level approach-latent class analysis (LCA)-to model a typology of individuals reporting DUI. This allows us to understand the degree to which individuals drive under the influence of a particular substance or do so across multiple substance types.
methodsWe use public-use data collected between 2016 and 2019 from the National Survey on Drug Use and Health. The analytic sample was 189,472 participants with a focus on those reporting DUI of psychoactive substances in the past-year (n = 24,619). LCA was conducted using self-reported DUI of past-year alcohol, cannabis, cocaine, heroin, hallucinogens, and methamphetamine as indicator variables.
resultsMore than 1 in 10 Americans reported a DUI within the past-year. One in five people who reported DUI of one substance also reported DUI of at least one additional substance. Using LCA to model heterogeneity among individuals reporting DUI, four classes emerged: "Alcohol Only" (55%), "Cannabis and Alcohol" (36%), "Polydrug" (5%), and "Methamphetamine" (3%). Rates of risk propensity, drug involvement, illicit drug use disorders, and criminal justice system involvement were highest among members of the "Polydrug" and "Methamphetamine" classes.
conclusionDrug treatment centers should take care to include discussions of the dangers and decision-making processes related to DUI of the full spectrum of illicit substances. Greater investment in drug treatment across the service continuum, including the justice system, could prevent/reduce future DUI episodes.
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Registered trials
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