Issues with using police citations to assign responsibility in quasi-induced exposure

Accident Analysis & Prevention

Pfeiffer

Myers

et al. 2014

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.

Section: 0 Discussionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

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

Accident Analysis & Prevention

Pfeiffer

Myers

et al. 2014

“…A driver was determined to be responsible if he/she committed one or more driver actions (e.g., inattention, unsafe speed, failure to obey traffic control device, failure to yield to vehicle/pedestrian) that the officer determined to have contributed to the crash. We and others have documented the relative advantages of using this method rather than legal culpability methods such as issuance of a citation or moving violation when determining crash responsibility (Curry et al 2014; Jiang et al 2012). For each crash, any number of drivers—including none—could have been determined to be responsible for the crash.…”

Section: Methodsmentioning

confidence: 99%

Validation of quasi-induced exposure representativeness assumption among young drivers

Traffic Injury Prevention

Pfeiffer

Elliott

2015

Objective Young driver studies have applied quasi-induced exposure (QIE) methods to assess relationships between demographic and behavioral factors and at-fault crash involvement, but QIE’s primary assumption of representativeness has not yet been validated among young drivers. Determining whether non-responsible young drivers in clean (i.e., only one driver is responsible) two-vehicle crashes are reasonably representative of the general young driving population is an important step toward ensuring valid QIE use in young driver studies. We applied previously established validation methods to conduct the first study, to our knowledge, focused on validating the QIE representativeness assumption in a young driver population. Methods We utilized New Jersey’s (NJ) state crash and licensing databases (2008–2012) to examine the representativeness assumption among 17- to 20-year-old non-responsible drivers involved in clean multi-vehicle crashes. It has been hypothesized that if not-at-fault drivers in clean two-vehicle crashes are a true representation of the driving population, it would be expected that non-responsible drivers in clean three-or-more-vehicle crashes also represent this same driving population (Jiang and Lyles 2010). Thus, we compared distributions of age, gender, and vehicle type among: (1) non-responsible young drivers in clean two-vehicle crashes and (2) the first non-responsible young driver in clean crashes involving three or more vehicles to (3) all other non-responsible young drivers in clean crashes involving three or more vehicles. Distributions were compared using chi-square tests and conditional logistic regression; analyses were conducted for all young drivers and stratified by license status (intermediate vs. fully licensed drivers), crash location, and time of day of the crash. Results There were 41,323 non-responsible drivers in clean two-vehicle crashes and 6,464 non-responsible drivers in clean three-or-more-vehicle crashes. Overall, we found that the distributions of age, gender, and vehicle type were not statistically significantly different between the three groups; in each group, approximately one-fourth of drivers were of each year of age 17 through 20, half were males, and approximately 80% were driving a car/station wagon/minivan. In general, conclusions held when we evaluated the assumption within intermediate and fully licensed young drivers separately and by crash location and time. Conclusions It appears that the representativeness assumption holds among the population of NJ young drivers. We encourage young driver studies utilizing QIE methods to conduct internal validation studies to ensure appropriate application of these methods and we propose utilization of QIE methods to address broader foundational and applied questions in young driver safety.

“…Historically, crash responsibility has been based on citations or moving violations listed on the crash report (DeYoung et al 1997; Lardelli-Claret et al 2011; Rice et al 2003; Waller et al 2001). However, there are two important limitations with this method that have been identified and we recently confirmed: (1) Citation issuance varies substantially by factors that are independent of fault (e.g., age, gender); and (2) This method does not capture driving behaviors that are not illegal but still indicative of fault, such as inattention (Af Wåhlberg and Dorn 2007; Curry et al 2014; Jiang et al 2012). Instead, these studies have endorsed using the presence of a hazardous or crash-contributing driver action to determine fault.…”

Section: Application Of Quasi-induced Exposure Methods To Estimate Commentioning

confidence: 94%

Estimating young novice drivers' compliance with graduated driver licensing restrictions: A novel approach

Traffic Injury Prevention

2016

Objective Current methods of estimating compliance with Graduated Driver Licensing (GDL) restrictions among young drivers with intermediate driver’s licenses—which include surveys, direct observations, and naturalistic studies—cannot sufficiently answer many critical foundational questions: What is the extent of non-compliance among the population of young intermediate drivers? How does compliance change over the course of licensure? How does compliance differ by driver subgroup and in certain driving environments? This paper proposes an alternative and complementary approach to estimating population-level compliance with GDL nighttime and passenger restrictions via application of the quasi-induced exposure (QIE) method. Methods The paper summarizes the main limitations of previous methods employed to estimate compliance. It then introduces the proposed method of borrowing the fundamental assumption of the QIE method—that young intermediate drivers who are non-responsible in clean (i.e., one and only one responsible driver) multi-vehicle crashes are reasonably representative of young intermediate drivers on the road—to estimate population-based compliance. I describe formative work that has been done to ensure this method can be validly applied among young intermediate drivers and provide a practical application of this method: an estimate of compliance with New Jersey’s passenger restrictions among 8,006 non-responsible 17- to 20-year-old intermediate drivers involved in clean two-vehicle crashes from July 2010 through June 2012. Results Over the study period, an estimated 8.4% (95% CI: 7.8%, 9.0%) of intermediate drivers’ trips were not in compliance with NJ’s GDL passenger restriction. These findings were remarkably similar to previous estimates from more resource-intensive naturalistic studies (Goodwin et al., 2006; Klauer et al., 2011). Conclusion Studies can practically apply proposed methods to estimate population-level compliance with GDL passenger and night restrictions; examine how compliance varies by relevant driver, vehicle, and environmental factors; and evaluate the implementation of a GDL provision or other intervention aimed at increasing compliance with these restrictions. Important considerations and potential limitations and challenges are discussed.