β Scribed by Kenneth W. Terhune
No coin nor oath required. For personal study only.
This paper evaluates judgments of driver crash responsibility to estimate alcohol and drug impairment effects when exposure data are unavailable to calculate crash risks. Previous studies using responsibility judgments provided some evidence that responsibility is related to BAC. Other studies. some inferring responsibility. indicated a relation between responsibility and relative crash risk. Data are presented showing that responsibilit! judgments with a rating scale have high interrater reliability, and systematic relations with BAC suggest some validity in the ratings. A method is demonstrated for estimating relative crash risk from responsibility judgments with accident data, and the limitations of responsibility analysis are discussed. While alcohol and drug impairment effects are best determined with relative crash risks determined from accident and exposure data. responsibility analysis may provide useful indications in the absence of exposure data.
Lack of exposure data presents a special challenge to determining whether drugs other than alcohol constitute a significant highway safety problem. In studying alcohol effects. pioneering investigators such as Holcomb[ 19381, Borkenstein, et a/.,[ 1964/1974], and Hurst [ 19701 had such data available. Central to their approaches were data on the blood alcohol concentrations (BAC's) of drivers in accidents and those not in accidents but on the road at times and places similar to the accident drivers. The BAC distributions in the accident and "exposure" samples were compared statistically to derive the relative risk of having an accident when a driver is within a certain BAC range. Large-scale studies in Grand Rapids, Michigan (Borkenstein er al.. 1964/1974] and in Huntsville, Alabama and San Diego [Farris, et al. I9771 were able to show that relative crash risk increases systematically with BAC, reaching extremely high levels in the intoxication range. For example, the Grand Rapids study indicated that the probability of a driver causing an accident when at 0.14% BAC is about twenty times that of a sober driver.
As discussed by Joscelyn and Donelson [I9801 and Benjamin (19801, obtaining needed exposure data is now more difficult, and it may be impossible in the case of drugs. One problem is the reluctance of government to intrude upon the driving public with roadside surveys. Another is that studies requiring bodily specimens taken from drivers at roadside may find few drivers willing to participate. The high costs of collecting such data constitute a third obstacle. For these reasons, a method that avoids the need for exposure samples may be essential to future research on the role of drugs in crashes. Already studies have found significant incidence rates of drugs in the bloodstreams of accident drivers: in one American city, 22% of crashinjured drivers were found to have drugs other than alcohol in their blood [Terhune and Fell, 19811; an Ontario study found drugs in 26% of driver fatalities [Warren, et al., 19801. Should drugs continue to be found in crash drivers at these high rates, their causal role in accidents is likely to become a central question.
A method for assessing the influence of drugs on crashes that does not require exposure data is responsibility analysis, where rater's judgements are combined statistically to estimate drug effects. Though the basic procedures have been around for some years, they are by no means widely used or accepted as a substitute for more precise estimates of relative crash risk based on accident and exposure data. Recently, however, the U.S. National Academy of Sciences [1982], noting the use of responsibility analysis by Warren and colleagues [ 1980], suggested possible further development of the method for studying marijuana effects. Because of its potential value, responsibility analysis is evaluated and its application is demonstrated in this paper. +This article is based on a paper presented at the annual meeting of the American Association for Automotive Medicine,
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