Understanding nonuse of mandatory e-scooter helmets.

OBJECTIVES: Head injuries resulting from e-scooter use have led to calls for helmet use to be promoted or mandatory. Helmet use is mandatory for e-scooters in Australia but observational studies have reported significant levels of nonuse, particularly by riders of shared e-scooters. The aim of this study is to understand whether nonuse in the mandatory context is a consistent behavior for an individual or is situationally-influenced, and what are the factors associated with nonuse. METHODS: An online survey was completed between 2022 and 2023 by 360 adult e-scooter riders in Canberra, Australia. Riders were asked whether they had worn a helmet on their last ride and how often they had not worn a helmet when riding in the last 30 days. The survey also asked about rider characteristics (demographics, frequency of e-scooter and bicycle use, perceived risk of e-scooter use, e-scooter ownership, and risky behaviors while riding), trip duration and perceptions of the helmet requirement (knowledge of and support for the law). RESULTS: Respondents were mostly male, young, highly educated, and full-time workers. Of the 29.1% of riders who reported riding without a helmet in the last 30 days, 24.4% had worn a helmet at least once during that period and 4.8% had consistently not worn a helmet. Younger age, shared e-scooter use and more frequent riding frequency (shared e-scooters only) were associated with helmet nonuse in the bivariate analyses but not in the logistic regression. Logistic regression showed that the independent predictors of helmet nonuse were the number of risky riding behaviors, lack of knowledge, and lack of support for the law. CONCLUSIONS: Most nonuse of helmets in a mandatory context seems to be situational, rather than consistent. Many of the factors associated with nonuse of helmets for e-scooters are similar to those reported for bicycles. Nonuse of helmets appears to be one of a number of risky behaviors performed by riders, rather than being primarily an outcome that is specific to factors associated with helmets (e.g., concerns about hygiene, discomfort or availability).

Changes in shared and private e-scooter use in Brisbane, Australia and their safety implications.

Shared electric scooter (e-scooter) schemes debuted in US cities in 2017 and have spread to many cities worldwide. Rider inexperience and the inexperience of other road users in interacting with e-scooters may be contributing to injuries. Shared e-scooters came to Brisbane, Australia, in November 2018 and our observational study in February 2019 found a high level of non-compliance with regulations by riders of shared, but not private, e-scooters. This paper examines whether e-scooter safety improved over time by comparing the numbers and behaviors of shared and private e-scooter riders with a follow-up observational study conducted in October 2019. Riders of e-scooters (and bicycles) were counted at six sites in inner-city Brisbane by trained observers over four weekdays. Type of e-scooter (private, Lime, Neuron), helmet use, gender, age group, riding location, time of day and presence of passengers were recorded. The number of shared e-scooters observed dropped from 711 in February to 495 in October but the number of private e-scooters increased from 90 to 269, resulting in a slight reduction in the total number of e-scooters. The correct helmet wearing rate increased non-significantly from 61.4% to 66.8% for shared e-scooters and remained high for riders of private e-scooters (95.5% in February and 94.3% in October). The percentage of e-scooters ridden on the road (which is illegal in central Brisbane) remained roughly the same (shared: 6.6% in February, 4.2% in October; private: 4.5% in February, 4.9% in October). The percentage of children and adolescents (illegally) riding shared e-scooters fell from 10.3% to 6.7%. The prevalence of any of these illegal behaviors among shared e-scooter riders fell significantly for shared e-scooter riders from 49.6% to 39.1% while the prevalence of illegal behaviors by other riders remained lower and did not change. The reduction in illegal behavior among shared e-scooter riders accompanied by the tripling of usage of private e-scooters suggests that e-scooter safety is likely to have improved.

Comparing the risky behaviours of shared and private e-scooter and bicycle riders in downtown Brisbane, Australia.

Electric scooter (e-scooter) use has increased internationally, with concerns about injuries to riders and pedestrians, and reports of non-use of helmets, excessive speed, drink-riding and underage riding. E-scooter regulations vary widely among jurisdictions, with likely effects on the extent and nature of safety issues. This study was conducted in downtown Brisbane, Australia, where e-scooters must be ridden on the footpath, bicycles are allowed on the road and the footpath, and helmet use is mandatory for bicycle and e-scooter riders of all ages. It examined involvement in illegal and risky behaviours, and interactions with pedestrians. Shared and private e-scooters, and shared and private bicycles were compared to assess the relative influences of type of vehicle and shared use. Observations at six sites in downtown Brisbane in February 2019 recorded 711 shared e-scooters, 90 private e-scooters, 274 shared bicycles and 2788 private bicycles. Illegal riding (not wearing a helmet, riding on the road, or carrying a passenger) was more prevalent among shared than private e-scooters (49.6 % vs. 12.2 %). Non-use of helmets was more common among riders of shared e-scooters (38.6 %, OR = 20.995, p < .001) and shared bicycles (18.8 %, OR = 10.994, p < .001) than private bicycles (1.5 %); occurred more often on the footpath than the road (20.1 % vs. 1.8 %, OR = 3.004, p < .001); and occurred more between 2 and 4 pm than between 7 and 9a.m. (21.3 % vs. 5.5 %, OR = 1.711, p < .01). More than 90 % of e-scooters, about half of shared bicycles and about a quarter of private bicycles were ridden on the footpath, with about 40 % within 1 m of at least one pedestrian. When there were pedestrians within 1 m, conflict rates ranged from zero to 1.5 % and no collisions were observed. At least for helmet non-use, the results suggest that risky behaviours are more prevalent among users of shared schemes, and that this difference is accentuated for e-scooters. Interactions with pedestrians are common but conflicts rarely occur in footpath riding. Further observational and survey studies are recommended to better understand the factors influencing the perceptions and behaviours of shared and private e-scooters and pedestrians. The knowledge gained from these studies needs to be integrated with injury outcome data to determine the appropriateness of rules for maximum speeds and locations of riding in terms of both rider and pedestrian safety.

Drivers who don't comply with a minimum passing distance rule when passing bicycle riders.

INTRODUCTION: Drivers' passing cyclists closely can contribute to crashes, falls, and intimidation, which may discourage cycling. In response, minimum passing distance (MPD) rules have been introduced in many jurisdictions. This study examined the factors associated with non-compliance with a MPD rule. METHOD: An online survey of 3,769 drivers in Queensland, Australia was administered 1 year after a MPD rule began. It assessed compliance with and attitudes toward the rule. Linear regression modeling was used to examine which attitudinal and demographic factors were associated with non-compliance. RESULTS: The percentage of drivers who reported that they did not comply with the road rule "most of the time" or "almost always" was 35.5% in speed zones of ≤60 km/h and 31.8% in speed zones of >60 km/h. Associated with a greater likelihood of being non-compliant were: only infrequently observing motorists giving bicycle riders more distance when overtaking; greater awareness of bicycle riders when driving on the road; disagreeing that the rule had changed the person's driving; agreeing that the rule was making overtaking bicycle riders difficult; disagreeing that the rule had made it safer for bicycle riders; agreeing that it was difficult to judge 1 or 1.5 m when overtaking a bicycle rider; and agreeing that giving 1.5 m clearance in >60 km/h zones to bicycle riders was annoying (p < .05). In high speed zones, drivers aged 18-39 years were more likely than those aged 50+ years to be non-compliant (p < .05). Compliance was not associated with driver sex, amount of driving, or perceived level of enforcement. CONCLUSIONS: Reported non-compliance with the MPD rule is widespread and is related more to attitudinal than demographic factors. Practical applications: Strategies for helping drivers to judge passing distance and improve their understanding of the importance for cyclist safety of leaving an adequate distance are needed.

Factors influencing noncompliance with bicycle passing distance laws.

Many jurisdictions around the world have implemented laws to require a minimum distance when motor vehicles pass cyclists, but research into the factors influencing passing distances has produced inconsistent results, indicating the need for future research. This study examined the factors influencing motorists' compliance with a legislated bicycle passing distance rule in Queensland, Australia. Unlike the earlier studies, which used volunteer riders to record passing events, this study used a naturalistic study design to record passing events where none of the motorists or the cyclists were aware of being studied. As a result, this study captured the 'true' driving and riding behaviours during passing events. The likelihood of non-compliance was greater on higher (70-80 km/h speed limits) and lower (40 km/h) speed roads than 60 km/h roads, at curved road sections, and on roads with narrower traffic lanes. Rider characteristics (age, gender, helmet status, type of clothing, type of bicycle, and individual or group riding) had no statistically significant association with compliance status. The findings indicate that efforts to improve cyclist safety during overtaking events should focus on non-rider related factors, such as roadway infrastructure characteristics.

Cyclists' perceptions of motorist harassment pre- to post-trial of the minimum passing distance road rule amendment in Queensland, Australia.

Issues addressed Cyclists' perceptions of harassment from motorists discourages cycling. This study examined changes in cyclists' reporting of harassment pre- to post-introduction of the Queensland trial of the minimum passing distance road rule amendment (MPD-RRA). Methods Cross-sectional online surveys of cyclists in Queensland, Australia were conducted in 2009 (pre-trial; n=1758) and 2015 (post-trial commencement; n=1997). Cyclists were asked about their experiences of harassment from motorists while cycling. Logistic regression modelling was used to examine differences in the reporting of harassment between these time periods, after adjustments for demographic characteristics and cycling behaviour. Results At both time periods, the most reported types of harassment were deliberately driving too close (causing fear or anxiety), shouting abuse and making obscene gestures or engaging in sexual harassment. The percentage of cyclists who reported tailgating by motorists increased between 2009 and 2015 (15.1% to 19.5%; P<0.001). The percentage of cyclists reporting other types of harassment did not change significantly. Conclusions Cyclists in Queensland continue to perceive harassment while cycling on the road. The amendment to the minimum passing distance rule in Queensland appears to be having a negative effect on one type of harassment but no significant effects on others. So what? Minimum passing distance rules may not be improving cyclists' perceptions of motorists' behaviours. Additional strategies are required to create a supportive environment for cycling.

Observational study of compliance with Queensland bicycle helmet laws.

Mandatory bicycle helmet laws have been found to increase helmet wearing rates in Australia and internationally. However, much of the research on factors influencing compliance with the Australian helmet laws is dated or focuses on commuters and city areas only. To address this gap, video recordings of bicycle riders were undertaken at 17 sites across Queensland, Australia, representing a mixture of on- and off-road locations, speed limits and regions. Helmet status was able to be determined for 98% of riders observed. The level of compliance with the laws was very high, with 98.3% of the more than 27,000 riders observed wearing helmets. Riders riding on roads were less compliant than those riding on bicycle paths, but no significant differences were observed between the school-holiday and school-term periods. Among the on-road riders, boys were less compliant than girls and overall children were less compliant than adults. Higher compliance levels were found for group riders, road bike riders, lycra-clad riders, during morning hours, and on 50km/h or lower speed limit roads. While the overall level of compliance was very high, certain subgroups were identified as a possible focus for interventions to further improve the compliance level, for example children (particularly boys) riding mountain bikes away from groups during the afternoon hours on 60km/h roads.

Older drivers' crashes in Queensland, Australia.

BACKGROUND: The growing proportion of older adults in Australia is predicted to comprise 23% of the population by 2030. Accordingly, an increasing number of older drivers and fatal crashes of these drivers could also be expected. While the cognitive and physiological limitations of ageing and their road safety implications have been widely documented, research has generally considered older drivers as a homogeneous group. Knowledge of age-related crash trends within the older driver group itself is currently limited. OBJECTIVE: The aim of this research was to identify age-related differences in serious road crashes of older drivers. This was achieved by comparing crash characteristics between older and younger drivers and between sub-groups of older drivers. Particular attention was paid to serious crashes (crashes resulting in hospitalisation and fatalities) as they place the greatest burden on the Australian health system. METHOD: Using Queensland Crash data, a total of 191,709 crashes of all-aged drivers (17-80+) over a 9-year period were analysed. Crash patterns of drivers' aged 17-24, 25-39, 40-49, 50-59, 60-69, 70-79 and 80+ were compared in terms of crash severity (e.g., fatal), at fault levels, traffic control measures (e.g., stop signs) and road features (e.g., intersections). Crashes of older driver sub-groups (60-69, 70-79, 80+) were also compared to those of middle-aged drivers (40-49 and 50-59 combined, who were identified as the safest driving cohort) with respect to crash-related traffic control features and other factors (e.g., speed). Confounding factors including speed and crash nature (e.g., sideswipe) were controlled for. RESULTS AND DISCUSSION: Results indicated that patterns of serious crashes, as a function of crash severity, at-fault levels, road conditions and traffic control measures, differed significantly between age groups. As a group, older drivers (60+) represented the greatest proportion of crashes resulting in fatalities and hospitalisation, as well as those involving uncontrolled intersections and failure to give way. The opposite was found for middle-aged drivers, although they had the highest proportion of alcohol and speed-related crashes when compared to older drivers. Among all older drivers, those aged 60-69 were least likely to be involved in or the cause of crashes, but most likely to crash at interchanges and as a result of driving while fatigued or after consuming alcohol. Drivers aged 70-79 represented a mid-range level of crash involvement and culpability, and were most likely to crash at stop and give way signs. Drivers aged 80 years and beyond were most likely to be seriously injured or killed in, and at-fault for, crashes, and had the greatest number of crashes at both conventional and circular intersections. Overall, our findings highlight the heterogeneity of older drivers' crash patterns and suggest that age-related differences must be considered in measures designed to improve older driver safety.