Drink and drug driving countermeasures have several similarities, yet also have a number of differences. To improve the effectiveness of these countermeasures, it is important to delineate the perceptions of both legal and non-legal factors between drink driving and drug driving. This study aimed to understand these differences and how legal and non-legal factors uniquely contribute to future intentions to engage in these illegal behaviours. A total of 546 licensed drivers who have a history of using both alcohol and drugs (marijuana, MDMA, and/or ice/speed) responded to an online survey that included legal deterrence measures as well as established measures of non-legal factors for both drink driving and drug driving. The non-legal factors included the fear of physical loss (e.g., fear of injuring yourself or others), social loss (e.g., social disapproval) and internal loss (e.g., guilt). Participants were more likely to report drug driving compared to drink driving, with a higher perceived chance of being caught for drink driving and more experience avoiding punishment for drug driving. Physical loss to others and internal loss were higher for drink driving. For both models, punishment avoidance was a significant predictor. Certainty of apprehension and severity punishment were only significant deterrents for drug driving, not drink driving. The threat of physical loss to oneself was a significant deterrent for drink driving, not drug driving. The results show that legal and non-legal deterrents are rated as lower for drug driving compared to drink driving, yet legal sanctions are still a deterrent for drug driving. Further, non-legal countermeasures are needed for both drink and drug driving that increase drivers' perceived fear of physical loss to others, internal loss, and social sanctions associated with the behaviours.

Background/objectives With the increasing popularity and saliency of social media, there is a pressing need to identify whether exposure to such content can affect road rule compliance, especially given that social media has been found to influence other risky behaviours. This systematic review (conducted in accordance with the PRISMA guidelines) summarised existing evidence concerning: (a) the nature of driving-related content on social media and (b) whether such content can influence attitudes and subsequent driving behaviour. Methods Peer-reviewed articles written in English, that explored social media content in relation to road safety or driving behaviours (e.g., speeding, tailgating, distraction, impaired driving, and seatbelt use), were eligible for review. Searches were conducted via SCOPUS, PUBMED, ProQuest and TRID in June 2021. Results/discussion A total of 8 studies met the requirements for this study, resulting in three key findings. First, it was found that very few studies have explored the type and extent of driving-related content on social media, and the small collection of existing research has focused solely on YouTube and Twitter. Second, whilst the nature of driving-related content on social media varies substantially across studies, a body of content exists that promotes or encourages risky driving behaviour or road rule violations. Third, and despite the array of available online content, there is a paucity of research illuminating the impact of social media messages on attitudes towards, and behaviours linked to road safety. This review highlights the need for research to keep pace with the rapidly changing nature of social media (not least the impacts upon human behaviour) and outlines pathways to increase current scientific understanding.

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.(c) 2022 National Safety Council and Elsevier Ltd. All rights reserved.

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.

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.

Objective: This study represents phase one of a three-year research project aiming to investigate the impact of reflective practice groups for nurses. Background: Evidence indicates that increased job demands, and inadequate support contribute to nursing burnout, reduced capacity and workplace attrition. There is some evidence that group interventions may help address such issues. Study Design/Methods: This study utilised a cross sectional, quantitative research methodology. Overall, 251 nurses completed questionnaires incorporating 11 validated subscales. Levels of compassion satisfaction, intolerance to uncertainty, inhibitory anxiety, group cohesiveness, psychological distress, and psychosocial safety were evaluated in relation to number of groups attended, for both individual nurses and work groups. The data was then examined alongside existing personal and job resources. Results: Individual nurses who attended 6–18 reflective practice groups demonstrated increased tolerance to uncertainty and less inhibitory anxiety, whilst those who attended more than 18 groups demonstrated increased compassion satisfaction and group cohesiveness. There was, however, no evidence to indicate more pervasive, work group benefits. Whilst the second part of the study confirmed that reflective practice group attendance was significantly correlated with increased compassion satisfaction, it was not able to explain changes in levels of burnout, secondary traumatic stress or compassion satisfaction over and above personal factors, job factors and levels of psychological distress. Conclusion: Professional quality of life involves a complex set of variables. Reflective practice group attendance is correlated with a number of benefits for nurses however cause and effect were not clearly determined. A subsequent study will focus on the more subtle mechanisms and indirect effects of the groups on nurses' personal resources. Relevance: This research supports the role of person and job factors in explaining professional quality of life for nurses and provides evidence to support a number of positive outcomes for nurses attending reflective practice groups; establishing a foundation for future studies to explore impacts and mediators in greater detail. What is already known about the topic? Personal and job resources can buffer against job demands to improve Professional Quality of Life (ProQoL). Nurses who lack personal resources are more likely to report burnout. What this paper adds: Personal resources of autonomy, self-efficacy and optimism are particularly important for nursing ProQoL. Higher levels of RPG attendance are correlated with improved tolerance to uncertainty, reduced inhibitory anxiety, increased compassion satisfaction and improved group cohesion. An explanatory link between RPG and variations in ProQoL is still not clear as RPG attendance in itself was not found to account for changes in ProQoL over personal resources, job resources and job demands. The study identifies a direction for further research into the role RPG may play in the development of personal resources for nurses.