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Patterns of Drug and Polydrug Detection in Drivers Suspected of Driving Under the Influence of an Intoxicant in Ireland 2019-2020: A Latent Class Analysis #MMPMID41391009
Drug Alcohol Rev 2026[Jan]; 45 (1): e70087 PMID41391009show ga
INTRODUCTION: Driving under the influence of drugs is a major risk factor for road traffic collisions. While increasing harms are observed in relation to polydrug use, evidence is needed about this issue in the context of road safety. We examined polydrug use patterns in drivers providing samples for toxicological analysis in Ireland between 2019 and 2020. METHODS: A cross-sectional study using LC-MS toxicology results from the Medical Bureau of Road Safety, which is responsible for the chemical testing of intoxicants in all drivers arrested under the Road Traffic Acts 1968-2024 in Ireland. Latent class analysis was performed on all samples with at least one drug detected (N = 4856). Descriptive statistics for age, gender and number of drug groups detected were calculated for each class identified. RESULTS: We identified six latent classes based on drug detection patterns. The cannabis only class (46.5%) is characterised by the detection of cannabis with no other drug involved, a high proportion of men and young age. The cocaine class (31.1%), which combines cocaine and cannabis use, and the stimulant class (2.5%), characterised by amphetamine/methamphetamine detection, have a similar demographic profile to the cannabis class. The polydrug non-opioid (11.8%), polydrug opioid (5.5%) and heroin (2.6%) classes are older, with lower male:female ratios. DISCUSSION AND CONCLUSIONS: By identifying profiles of people driving under the influence of drugs, this study contributes to enhancing knowledge of drug and polydrug use in motor vehicle drivers in Ireland. Further work is needed to examine risks and develop interventions to address polydrug driving.
|*Automobile Driving[MESH]
|*Driving Under the Influence/statistics & numerical data[MESH]
Drug+Alcohol+Rev 2026 ; 45 (1): e70087
