Fragility and crash over-representation among older drivers in Western Australia

This study assessed age-related and gender differences in the relative contribution of fragility and crash over-representation to serious injuries per crash-involved driver in Western Australia. Police-reported crashes for the period 1998-2003 were extracted from the Western Australian Road Injury Database. For each passenger vehicle driver age and gender group, serious injuries per crash-involved driver and driver involvements in crashes per 100 million vehicle-kilometre travelled (VKT) were calculated as the respective measure of fragility and crash over-representation. Results from the decomposition method of analysis showed that older drivers over the age of 70 sustained serious injury rates more than twice as high as those of the 30-59-year-old drivers. Fragility increased with age, contributing between 47% and 95% for drivers above 65 years, but crash over-representation was the dominant factor for male drivers above 80 years. In contrast, fragility contributed little to the excess injury risk of younger drivers under the age of 30. The importance of fragility as a contributing factor to the inflated serious injury risk per vehicle-kilometre travelled for older drivers suggested that road safety initiatives should be directed towards the protection of vehicle occupants as well as screening for their driving ability.     

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.     

Are child occupants a significant source of driving distraction?

Driver distraction represents a well-documented and growing contribution to the road safety problem. This study used a naturalistic, observational approach to examine if children in vehicles are a significant source of driving distraction. Families with children aged between 1 and 8 years drove an instrumented “study vehicle” on their regular trips for 3 weeks. A discrete video recording system in the vehicle provided images of the driver and front seat passenger, the rear seat child passengers and the traffic ahead. The video-recordings inside and outside the vehicle were analysed to identify potential distracting activities, where ‘distraction’ was broadly defined as any activity that distracted the driver or competed for their attention while driving. In addition, all potentially distracting activities that involved the driver looking away from the forward roadway for more than 2 s while the vehicle was in motion were also coded. Video-recordings were analysed for 92 driving journeys undertaken by 12 families including 25 children and 19 drivers. The mean journey duration was approximately 16 min (range: 2 min–3 h 34 min). Most journeys were undertaken during the day (89%), with the mother driving (65%) and without a front seat passenger (64%). Driving journeys were predominantly undertaken in urban areas (97%), on suburban roads/streets (94%), and under low complexity traffic conditions (91%). Most journeys involved some source of potential driver distraction (98%), with drivers distracted for 18% of the driving journey. The most frequent types of distracting activities that drivers engaged in included: touching their head or their face (35%), interacting with child passengers in the rear seat (12%), and engaging with the front seat passenger (9%). Almost three-quarters of these potentially distracting activities were engaged in by the driver while the study vehicle was in motion (72%) and 14% of all potentially distracting activities involved the driver's eyes off the roadway for greater than 2 s while the vehicle was in motion, thereby potentially doubling their crash risk. The most frequent child-related activities that drivers engaged in included: turning to look at the rear seated occupants or viewing the children using the rear-view mirror (76.4%), engaging in conversation with their children (16%), assisting their children (e.g., passing food and drink [7%]) and playing with their children (1%). Drivers spent significantly longer periods of time engaged in non-child occupant-related activities compared with child occupant-related activities and were significantly more likely to have their eyes off the forward roadway for greater than 2 s while engaged in non-child occupant-related activities (14%) compared to child occupant-related activities (10%). The results suggest that drivers need to be educated about the potential crash and injury risks associated with both child occupant-related and non-child occupant-related activities while driving their vehicle.     

An examination of the environmental,driver and vehicle factors associated with the serious and fatal crashes of older rural drivers

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004–2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100 km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances.     

The effects of age,gender, and crash types on drivers’ injury-related health care costs

There are many studies that evaluate the effects of age, gender, and crash types on crash related injury severity. However, few studies investigate the effects of those crash factors on the crash related health care costs for drivers that are transported to hospital. The purpose of this study is to examine the relationships between drivers’ age, gender, and the crash types, as well as other crash characteristics (e.g., not wearing a seatbelt, weather condition, and fatigued driving), on the crash related health care costs. The South Carolina Crash Outcome Data Evaluation System (SC CODES) from 2005 to 2007 was used to construct six separate hierarchical linear regression models based on drivers’ age and gender. The results suggest that older drivers have higher health care costs than younger drivers and male drivers tend to have higher health care costs than female drivers in the same age group. Overall, single vehicle crashes had the highest health care costs for all drivers. For males older than 64-years old sideswipe crashes are as costly as single vehicle crashes. In general, not wearing a seatbelt, airbag deployment, and speeding were found to be associated with higher health care costs. Distraction-related crashes are more likely to be associated with lower health care costs in most cases. Furthermore this study highlights the value of considering drivers in subgroups, as some factors have different effects on health care costs in different driver groups. Developing an understanding of longer term outcomes of crashes and their characteristics can lead to improvements in vehicle technology, educational materials, and interventions to reduce crash-related health care costs.     

Crash involvement of drivers with multiple crashes

A goal for any licensing agency is the ability to identify high-risk drivers. Kentucky data show that a significant number of drivers are repeatedly involved in crashes. The objective of this study is the development of a crash prediction model that can be used to estimate the likelihood of a driver being at fault for a near future crash occurrence. Multiple logistic regression techniques were employed using the available data for the Kentucky licensed drivers. This study considers as crash predictors the driver's total number of previous crashes, citations accumulated, the time gap between the latest two crashes, crash type, and demographic factors. The driver's total number of previous crashes was further disaggregated into the drivers' total number of previous at-fault and not-at-fault crashes. The model can be used to correctly classify at-fault drivers up to 74.56% with an overall efficiency of 63.34%. The total number of previous at-fault crash involvements, and having previous driver license suspensions and traffic school referrals are strongly associated with a driver being responsible for a subsequent crash. In addition, a driver's likelihood to be at fault in a crash is higher for very young or very old, males, drivers with both speeding and non-speeding citations, and drivers that had a recent crash involvement. Thus, the model presented here enables agencies to more actively monitor the likelihood of a driver to be at fault in a crash.     

Prevalence of teen driver errors leading to serious motor vehicle crashes

Objectives

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors.

Methods

The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15–18 year old drivers.

Results

822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors.

Conclusions

Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training.     

Statistical implications of using moving violations to determine crash responsibility in young driver crashes

Traditional methods for determining crash responsibility – most commonly moving violation citations – may not accurately characterize at-fault status among crash-involved drivers given that: (1) issuance may vary by factors that are independent of fault (e.g., driver age, gender), and (2) these methods do not capture driver behaviors that are not illegal but still indicative of fault. We examined the statistical implications of using moving violations to determine crash responsibility in young driver crashes by comparing it with a method based on crash-contributing driver actions. We selected all drivers in police-reported passenger-vehicle crashes (2010–2011) that involved a New Jersey driver <21 years old (79,485 drivers < age 21, 61,355 drivers ≥ age 21). For each driver, crash responsibility was determined from the crash report using two alternative methods: (1) issuance of a moving violation citation; and (2) presence of a driver action (e.g., failure to yield, inattention). Overall, 18% of crash-involved drivers were issued a moving violation while 50% had a driver action. Only 32.2% of drivers with a driver action were cited for a moving violation. Further, the likelihood of being cited given the presence of a driver action was higher among certain driver subgroups—younger drivers, male drivers, and drivers in single-vehicle and more severe crashes. Specifically among young drivers, those driving at night, carrying peer passengers, and having a suspended or no license were more often cited. Conversely, fatally-injured drivers were almost never cited. We also demonstrated that using citation data may lead to statistical bias in the characterization of at-fault drivers and of quasi-induced exposure measures. Studies seeking to accurately determine crash responsibility should thoughtfully consider the potential sources of bias that may result from using legal culpability methods. For many studies, determining driver responsibility via the identification of driver actions may yield more accurate characterizations of at-fault drivers.     

A linkage study of Western Australian drink driving arrests and road crash records

Records of drivers in all reported road crashes occurring in Western Australia between 1987 and 1995 were linked with records of all drink driving arrests in the same period. About 7% of all drink driving arrests occurred because of a road crash. Differences were observed between these drink-driving crashes and other types of road crashes. Drink driving crashes tended to be more severe than those not involving alcohol. Serious crashes (involving fatalities or hospitalisations) accounted for 20% of alcohol-related crashes, but only 6% of all crashes reported over the study period. From another perspective, crash-related drink-driving arrests were more likely than routine enforcement arrests to involve younger (18-35 years) and older (65 years and over) drink drivers. Routine enforcement arrests, on the other hand, were likely to involve a greater proportion of Aboriginal drivers.     

Older driver population and crash involvement trends, 1974-1988.

North Carolina motor vehicle crash data for even-numbered years 1974-1988, inclusive, are analyzed in conjunction with North Carolina population, licensed driver, and mileage data to examine trends in motor vehicle crash involvement by driver age, sex, and race. Crash rates per licensed driver are presented along with crash rates per estimated vehicle miles travelled calculated on the basis of induced exposure. Results focus particularly on older drivers. They show that older drivers' representation in the licensed driver population has increased at a greater rate than their representation in either the census or crash involvement populations. These trends are particularly strong for females and for nonwhites. Furthermore, crash rates have declined more for drivers aged 55 and older than for younger drivers. The greatest declines, both in terms of crashes per licensed driver and crashes per estimated miles travelled, have been experienced by drivers age 65 and older, particularly nonwhites. Males show higher overall crash rates per miles travelled than females, but this effect decreases with age and disappears entirely in the oldest age categories. Results are discussed in light of the changing nature of the overall driving population and the cohort of older drivers in particular.     

Relationship of parent driving records to the driving records of their children

Many studies have shown that young driver crash rates can be influenced by such factors as lifestyle characteristics and licensing systems. However, the influence of parents on their teenage children's crash and violation rates has not received much attention. The present study used data from the North Carolina driver history file to match the crash and violation records of young drivers between the ages of 18 and 21 with those of their parents. Results indicate that children's driving records in the first few years of licensure are related to the driving records of their parents. Children whose parents had three or more crashes on their record were 22% more likely to have had at least one crash compared with children whose parents had no crashes. Likewise, children whose parents had three or more violations were 38% more likely to have had a violation compared with children whose parents had none. Logistic regression models showed that these relationships held when controlling for household type and child gender.     

Driver risk factors for sleep-related crashes

A population-based case-control study was carried out to examine driver risk factors for sleep-related motor vehicle crashes. Cases included 312 drivers involved in recent North Carolina crashes and identified on police reports as asleep at the time of the crash and 155 drivers identified as fatigued. Controls were 529 drivers also involved in recent crashes but not identified as asleep or fatigued, and 407 drivers not involved in recent crashes. All drivers were contacted for brief telephone interviews. Results showed that drivers in sleep-related crashes were more likely to work multiple jobs, night shifts, or other unusual work schedules. They averaged fewer hours sleep per night, reported poorer quality sleep, were less likely to feel they got enough sleep, were sleepier during the day, drove more often late at night, and had more prior instances of drowsy driving. Compared to drivers in non-sleep-related crashes, they had been driving for longer times, been awake more hours, slept fewer hours the night before, and were more likely to have used soporific medications. Knowledge of specific risk factors for sleep-related crashes is an important first step in reducing the thousands of deaths and injuries each year in the US attributed to drowsy driving.     

Prevalence and factors associated with road traffic crash among taxi drivers in Hanoi,Vietnam

Injury due to road traffic crash is a major cause of ill health and premature deaths in developing countries. Taxis provide a main mode of public transport in Vietnam but there has been little research on the risk of crash for taxi drivers. This retrospective study collected information on taxi crashes for the period 2006–2009 by interviewing drivers from five taxi companies in Hanoi, Vietnam, using a structured questionnaire. Of the total 1214 participants recruited, 276 drivers reported at least one crash, giving an overall crash prevalence of 22.7%. Among the crashed group, 50 drivers (18.1%) were involved in two to four crashes. Logistic regression analysis further identified age of driver, type of driving licence, employment status, perceived sufficiency of income, seat-belt usage, and traffic infringement history to be significantly associated with the crash risk. Further prospective and qualitative studies are recommended to provide detailed crash characteristics as well as behaviour and perception of taxi drivers, so that an effective intervention can be developed to improve road safety and to prevent injury of these commercial drivers.     

Fatal intersection crashes in Norway: Patterns in contributing factors and data collection challenges

Fatal motor vehicle intersection crashes occurring in Norway in the years 2005–2007 were analyzed to identify causation patterns among their underlying contributing factors, and also to assess if the data collection and documentation procedures used by the Norwegian in-depth investigation teams produces the information necessary to do causation pattern analysis. 28 fatal accidents were analyzed. Causation charts of contributing factors were first coded for each driver in each crash using the Driving Reliability and Error Analysis Method (DREAM). Next, the charts were aggregated based on a combination of conflict types and whether the driver was going straight or turning. Analysis results indicate that drivers who were performing a turning maneuver in these crashes faced perception difficulties and unexpected behavior from the primary conflict vehicle, while at the same time trying to negotiate a demanding traffic situation. Drivers who were going straight on the other hand had less perception difficulties but largely expect any turning drivers to yield, which led to either slow reaction or no reaction at all. In terms of common contributing factors, those often pointed to in literature as contributing to fatal crashes, e.g. high speed, drugs and/or alcohol and inadequate driver training, contributed in 12 of 28 accidents. This confirms their prevalence, but also shows that most drivers end up in these situations due to combinations of less auspicious contributing factors. In terms of data collection and documentation, there was an asymmetry in terms of reported obstructions to view due to signposts and vegetation. These were frequently reported as contributing for turning drivers, but rarely reported as contributing for their counterparts in the same crashes. This probably reflects an involuntary focus of the analyst on identifying contributing factors for the driver held legally liable, while less attention is paid to the driver judged not at fault. Since who to blame often is irrelevant from a countermeasure development point of view, this underlying investigator approach needs to be addressed to avoid future bias in crash investigation reports.     

A logistic model of the effects of roadway, environmental, vehicle, crash and driver characteristics on hit-and-run crashes

Leaving the scene of a crash without reporting it is an offence in most countries and many studies have been devoted to improving ways to identify hit-and-run vehicles and the drivers involved. However, relatively few studies have been conducted on identifying factors that contribute to the decision to run after the crash. This study identifies the factors that are associated with the likelihood of hit-and-run crashes including driver characteristics, vehicle types, crash characteristics, roadway features and environmental characteristics. Using a logistic regression model to delineate hit-and-run crashes from nonhit-and-run crashes, this study found that drivers were more likely to run when crashes occurred at night, on a bridge and flyover, bend, straight road and near shop houses; involved two vehicles, two-wheel vehicles and vehicles from neighboring countries; and when the driver was a male, minority, and aged between 45 and 69. On the other hand, collisions involving right turn and U-turn maneuvers, and occurring on undivided roads were less likely to be hit-and-run crashes.     

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention.     

The effect of distractions on the crash types of teenage drivers

Teenage drivers are overrepresented in crashes when compared to middle-aged drivers. Driver distraction is becoming a greater concern among this group as in-vehicle devices, opportunities for distractions, and teenage drivers' willingness to engage in these activities increase. The objective of this study was to determine how different distraction factors impact the crash types that are common among teenage drivers. A multinomial logit model was developed to predict the likelihood that a driver will be involved in one of three common crash types: an angular collision with a moving vehicle, a rear-end collision with a moving lead vehicle, and a collision with a fixed object. These crashes were evaluated in terms of four driver distraction categories: cognitive, cell phone related, in-vehicle, and passenger-related distractions. Different driver distractions have varying effects on teenage drivers' crash involvement. Teenage drivers that were distracted at an intersection by passengers or cognitively were more likely to be involved in rear-end and angular collisions when compared to fixed-object collisions. In-vehicle distractions resulted in a greater likelihood of a collision with a fixed object when compared to angular collisions. Cell phone distractions resulted in a higher likelihood of rear-end collision. The results from this study need to be evaluated with caution due to the limited number of distraction related cases available in the U.S. GES crash database. Implications for identifying and improving the reporting of driver distraction related factors are therefore discussed.     

Pregnant driver-associated motor vehicle crashes in North Carolina, 2001–2008

Background

Motor vehicle crashes are the leading cause of maternal injury-related mortality during pregnancy in the United States, yet pregnant women remain an understudied population in motor vehicle safety research.

Methods

We estimated the risk of being a pregnant driver in a crash among 878,546 pregnant women, 16–46 years, who reached the 20th week of pregnancy in North Carolina (NC) from 2001 to 2008. We also examined the circumstances surrounding the crash events. Pregnant drivers in crashes were identified by probabilistic linkage of live birth and fetal death records and state motor vehicle crash reports.

Results

During the 8-year study period, the estimated risk of being a driver in a crash was 12.6 per 1000 pregnant women. Pregnant women at highest risk of being drivers in serious crashes were 18–24 years old (4.5 per 1000; 95% confidence interval, CI,4.3, 4.7), non-Hispanic black (4.8 per 1000; 95% CI = 4.5, 5.1), had high school diplomas only (4.5 per 1000; 95% CI = 4.2, 4.7) or some college (4.1 per 1000; 95% CI = 3.9, 4.4), were unmarried (4.7 per 1000; 95% CI = 4.4, 4.9), or tobacco users (4.5 per 1000; 95% CI = 4.1, 5.0). A high proportion of crashes occurred between 20 and 27 weeks of pregnancy (45%) and a lower proportion of crashes involved unbelted pregnant drivers (1%) or airbag deployment (10%). Forty percent of crashes resulted in driver injuries.

Conclusions

NC has a relatively high pregnant driver crash risk among the four U.S. states that have linked vital records and crash reports to examine pregnancy-associated crashes. Crash risks were especially elevated among pregnant women who were young, non-Hispanic black, unmarried, or used tobacco. Additional research is needed to quantify pregnant women's driving frequency and patterns.     

Young driver crash rates by licensing age,driving experience,and license phase

Background

Few studies have concurrently assessed the influence of age and experience on young driver crashes, in particular in the post-Graduated Driver Licensing (GDL) era. Further, little attention is given to the transition from intermediate to full licensure. We examined the independent and joint contributions of licensing age, driving experience, and GDL license phase on crash rates among the population of young New Jersey (NJ) drivers.

Methods

From a unique linked database containing licensing and crash data, we selected all drivers who obtained their NJ intermediate license at 17–20 years old from 2006–2009 (n = 410,230). We determined the exact age at which each driver obtained an intermediate and full license and created distinct, fixed cohorts of drivers based on their age at intermediate licensure. For each cohort, we calculated and graphed observed monthly crash rates over the first 24 months of licensure. Further, we examined crash rates by age at licensure, driving experience (i.e., time since licensure), and license phase.

Results

First-month crash rates were higher among the youngest drivers (licensed at 17y0m). Drivers who were licensed later experienced a reduced “steepness” in the slope of their crash rates in the critical initial months of driving, but there did not appear to be any incremental benefit of later licensure once drivers had six months of driving experience. Further, at each age, those with more driving experience had lower crash rates; however, the benefit of increased experience was greatest for the substantial proportion of teens licensed immediately after becoming eligible (at 17y0m). Finally, independent of age and experience, teen drivers’ crash risk increased substantially at the point of transition to a full license, while drivers of a similar age who remained in the intermediate phase continued to experience a decline in crash rates.

Conclusion

Age and driving experience interact to influence crash rates. Further, independent of these two factors, there is an abrupt increase in crash risk at the point of transition from intermediate to full licensure. Future studies should investigate whether this increase is accounted for by a change in driving exposure, driving behaviors, and/or other factors.     

Differences in state drug testing and reporting by driver type in U.S. fatal traffic crashes

IntroductionDriving under the influence of drugs, including marijuana, has become more prevalent in recent years despite local, state, and federal efforts to prevent such increases. The Fatality Analysis Reporting System (FARS) is the primary source of drugged driving data for fatal crashes in the United States but lacks the completeness required to calculate unbiased estimates of drug use among drivers involved in fatal crashes.MethodsThis article uses the 2013 FARS dataset to present differences in state drug testing rates by driver type, driver fault type, and state-level factors; discusses limitations related to analysis and interpretation of drugged driving data; and offers suggestions for improvements that may enable appropriate use of FARS drug testing data in the future.ResultsResults showed that state drug testing rates were highest among drivers who died at the scene of the crash (median = 70.8%) and drivers who died and were at fault in the crash (median = 64.4%). The lowest testing rates were seen among surviving drivers who were not transported to a hospital (median = 14.0%) and surviving drivers who were not at fault in the crash (median = 10.0%). Drug testing rates differed by state blood alcohol content (BAC) testing rate across all driver types and driver fault types, and in general, states that tested a higher percentage of drivers for BAC had higher drug testing rates.DiscussionTesting rates might be increased through standardization and mandatory testing policies. FARS data users should continue to be cautious about the limitations of using currently available data to quantify drugged driving. More efforts are needed to improve drug testing and reporting practices, and more research is warranted to establish drug concentration levels at which driving skills become impaired.