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Introduction: Daily use of cannabis is increasing in Australia, yet there is limited understanding of the driving behaviours within this cohort, including how they perceive and manage the risks of being apprehended for drug driving and involved in a crash after consumption., Methods: An online survey was completed by 487 Australians who reported daily cannabis use (30% medically prescribed patients, 58% male)., Results: Current drug driving (i.e., driving within 4 h of consuming cannabis each week) was reported by 86% of participants. Future drug driving was anticipated by 92% of the sample. While most participants (93%) disagreed that their risk of crash increased following cannabis use, participants reported that they would drive more carefully (89%), leave greater headway (79%) and/or drive slower (51%) following cannabis consumption. Half of the sample (53%) perceived the risk of apprehension for drug driving to be likely to some extent. Strategies to reduce the likelihood of being detected were used by 25% of participants, and included using Facebook police location sites (16%), driving on back roads (6%) and/or consuming substances to mask the presence of drugs (13%). The regression analysis revealed that individuals who reported more occasions of cannabis use per day, and who perceived that cannabis does not reduce driving ability, reported a greater extent of current drug driving., Discussion and Conclusions: Interventions and education which aim to challenge this perception that 'cannabis does not reduce driving ability' may prove important for reducing drug driving among the most frequent consumers of cannabis., (© 2023 The Authors. Drug and Alcohol Review published by John Wiley & Sons Australia, Ltd on behalf of Australasian Professional Society on Alcohol and other Drugs.)

Introduction: While research has reported on overall prevalence rates of drug driving, the extent of recidivist offending has yet to be explored. The objective of this research was to examine recidivistic behaviors detected through Roadside Drug Testing (RDT) in Queensland (between December 2007 and June 2020), with a focus on: Delta-9-tetrahydrocannabinol (THC), 3,4-Methylenedioxymethylamphetamine (MDMA), and methamphetamine (MA)., Method: Data were provided by the Queensland Police Service, and contained information on positive drug detections that were confirmed via laboratory analysis., Results: The analyses revealed 50,442 unique offenders with a total of 67,727 offenses, as 25% (N = 12,490) of all offenders had been apprehended more than once (ranging from 2 to 11 offences). MA use was more common among recidivist offenders, whereas THC was more common for those with one offense. On average, the days between offenses decreased with increases in offense number., Conclusions: The findings provide evidence for the extent of drug driving recidivism on Queensland roads., Practical Applications: To deter recidivists and the greater motorist population from drug driving, there is need for greater resources dedicated to RDT to increase both the perceived and real likelihood of detection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 National Safety Council and Elsevier Ltd. All rights reserved.)

Unlicensed driving is a serious problem in many Australian states, with unlicensed driving-related crashes (UDC) costing up to $304 million per year in Queensland, and $176 million in Victoria. In this paper, we present a Benefit-Cost Ratio (BCR) analysis of a set of Intelligent Transportation Systems technologies aimed at preventing unlicensed driving by verifying the driver's identity through biometric technology, as well as the validity of their licence. Utilised together, the technology would essentially take the form of a licence interlock. The goal of this program of research (from which this paper stems) was to provide preliminary recommendations as to which technology is the most beneficial and should be implemented as part of a government-led program increasing the functionalities of electronic driving licences (EDL). The corresponding BCR analysis revealed that fingerprints and finger vascular patterns recognition technologies were found to systematically have the best BCRs. In regard to the most effective manner to implement the technology, a corresponding investigation with five scenarios revealed that the greatest benefits would be achieved with: (a) a mandatory system for all banned drivers (e.g., suspensions & disqualifications), and (b) a mandatory system for banned drivers under the age of 21 only. Scenario (b) performs extremely well, with returns of up to 16 times the investment with a simple fingerprint-based interlock. Although often more modest, all systems were found to have BCRs above 1 in all of the implementation scenarios except one. This paper further outlines the findings in regard to addressing the significant problem of unlicensed driving via emerging technologies., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Recent revisions of deterrence theory have highlighted the powerful effects of personal and vicarious punishment avoidance on criminal activity. The present paper reports on an application of Stafford and Warr's [Stafford, M.C., Warr, M., 1993. A reconceptualization of general and specific deterrence. J. Res. Crime Delinq. 30 (2), 123-135] reconceptualisation of deterrence theory to a group of recidivist drink drivers to explain their self-reported offending behaviours. The analysis indicated that punishment avoidance exerted the greatest influence on self-reported offending behaviours, although perceptions of arrest certainty and severity also appear associated with drink driving offences. In contrast, vicarious exposure to others who have been punished or avoided punishment was not associated with further drink driving behaviours. The results suggest that recidivist drink drivers are not heavily influenced by vicarious experiences, and that past behaviour is an efficient predictor of future behaviour. The findings have direct implications for the reconceptualisation and application of deterrence models to elucidate offending behaviours.