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1.
Traffic Inj Prev ; 23(7): 385-389, 2022.
Article in English | MEDLINE | ID: mdl-35878005

ABSTRACT

OBJECTIVE: The aim of the current study was to compare the traffic histories of drivers fatally injured in a road traffic crash, to alive drivers of the same age and gender in order to determine if key markers of increased fatality-risk could be identified. METHODS: The case sample comprised 1,139 (82% male) deceased drivers, while the control sample consisted of 1,139 registered Queensland drivers (who were individually matched to the case sample on age and gender). RESULTS: Using a logistic regression model, and adjusting for age and gender, it was found that a greater number of offenses predicted greater odds of fatal crash involvement, with each increase in offense frequency category increasing ones' odds by 1.98 (95% CI: 1.8, 2.18). When each offense type was considered individually, dangerous driving offenses were most influential, predicting a 3.44 (95% CI: 2, 5.93) increased odds of being in the case group, followed by the following offense types: learner/provisional (2.88, 95% CI: 1.75, 4.74), drink and drug driving (2.82, 95% CI: 1.97, 4.04), not wearing a seatbelt/helmet (2.63, 95% CI: 1.53, 4.51), licensing offenses (1.87, 95% CI: 1.41, 2.49), and speeding (1.48, 95% CI: 1.33, 1.66). In contrast, mobile phone and road rules offenses were not identified as significant predictors. CONCLUSION: The findings indicate that engagement in a range of aberrant driving behaviors may result in an increased odds of future fatal crash involvement, which has multiple implications for the sanctioning and management of apprehended offenders.


Subject(s)
Accidents, Traffic , Automobile Driving , Dangerous Behavior , Female , Humans , Licensure , Male , Seat Belts
2.
J Safety Res ; 81: 143-152, 2022 06.
Article in English | MEDLINE | ID: mdl-35589285

ABSTRACT

INTRODUCTION: The aim of this study was to determine whether drivers who had received more traffic infringements were more likely to be at fault for the crash in which they were killed. METHOD: The current dataset was derived from the crash and traffic history records provided by the Queensland Department of Transport and Main Roads and Coroner's Court for every driver, with available records, who was killed in a crash in Queensland, Australia, between 2011 and 2019 (N = 1,136). The most common traffic offenses in the current sample were speeding, disobeying road rules, driving under the influence of drugs and alcohol, and unlicensed driving. Logistic regression models were used to compute odds ratios for the number of overall offenses, the number of specific offense types, and for specific offending profiles that were derived from the literature. Age, gender, and crash type were each controlled for by entering them into the initial blocks of the regression models. RESULTS: After accounting for the variance associated with age, gender, and crash type, only the overall number of offenses and the number of unlicensed driving offenses predicted a significant change in a drivers' likelihood of being at fault for the crash that killed them. Furthermore, drivers who were identified as having versatile (i.e., multiple offenses from different categories) or criminal-type offense profiles (i.e., offenses that were considered to approximate criminal offenses) were each significantly more likely to be at fault for a fatal crash. PRACTICAL APPLICATIONS: This study provided an important contribution by demonstrating how a more nuanced approach to understanding how a driver's traffic history might be used to identify drivers who are more at risk of being involved in a crash (i.e., for which they were at fault). The implications of these findings are discussed with recommendations and consideration for future research.


Subject(s)
Automobile Driving , Criminals , Accidents, Traffic , Humans , Logistic Models , Odds Ratio
3.
Accid Anal Prev ; 159: 106231, 2021 Sep.
Article in English | MEDLINE | ID: mdl-34130055

ABSTRACT

Roadside Drug Testing (RDT) is the primary strategy utilised in Australia to detect and deter drug driving. RDT operations have been expanding and evolving in Queensland since their introduction in 2007, with the number of tests increasing by 5.63 times between 2009 and 2019. The objective of this paper was to explore trends and characteristics of the 60,551 positive results detected in Queensland's RDT program (from January 2015 to June 2020), which focuses on the detection of Delta-9-tetrahydrocannabinol (THC), Methylenedioxymethylamphetamine (MDMA) and methamphetamine (MA). The analysis indicated that (over the entire testing period) MA was the most common drug detected in isolation (39.4%), followed by THC (34%) and the combination of MA and THC (21.9%). When considering detections with two or more drugs, MA was present in 64% of detections, THC in 59% and MDMA in 1.8%. THC was most commonly detected among younger drivers (e.g., aged 16 to 24), while MA was most commonly detected with drivers aged 25 and 59 years. Analysis of sociodemographic and contextual factors revealed that positive roadside tests were most commonly associated with males who had consumed methamphetamines, aged between 30 and 39 who were driving a car on a Friday or Saturday between 2:00 pm and 6:00 pm. The findings provide some indication as to the extent of drug driving within Queensland (and growing use of MA) and have clear implications for enforcement activities, not least, directing sufficient resources to address the burgeoning problem.


Subject(s)
Automobile Driving , Pharmaceutical Preparations , Accidents, Traffic , Adult , Dronabinol , Humans , Male , Queensland , Substance Abuse Detection
4.
Rev Sci Instrum ; 89(2): 023902, 2018 Feb.
Article in English | MEDLINE | ID: mdl-29495876

ABSTRACT

Spin-echo instruments are typically used to measure diffusive processes and the dynamics and motion in samples on ps and ns time scales. A key aspect of the spin-echo technique is to determine the polarisation of a particle beam. We present two methods for measuring the spin polarisation in spin-echo experiments. The current method in use is based on taking a number of discrete readings. The implementation of a new method involves continuously rotating the spin and measuring its polarisation after being scattered from the sample. A control system running on a microcontroller is used to perform the spin rotation and to calculate the polarisation of the scattered beam based on a lock-in amplifier. First experimental tests of the method on a helium spin-echo spectrometer show that it is clearly working and that it has advantages over the discrete approach, i.e., it can track changes of the beam properties throughout the experiment. Moreover, we show that real-time numerical simulations can perfectly describe a complex experiment and can be easily used to develop improved experimental methods prior to a first hardware implementation.

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