By looking at different levels of crash-factors, this study allows for some separation of those factors and therefore achieves more detail in studying the role of gender on non-fatal motor vehicle crashes. One of the clearest results coming from this study is that females are less involved in alcohol-related crashes and speeding-related crashes than males. This result is not surprising, however, for it only confirms previous findings in the literature (Liu et al., 2005
; Romano et al., 2008
). Our lack of finding for gender differences associated to fatigue/inattention or maneuvering suggests that the occurrence of these factors is not circumscribed to a certain gender, but that their occurrence affects the general population. Further, the lack of significance for gender in their association with maneuvering suggests that the skill-levels of males and females may be equivalent.
This study also underscores the implicit complexity of the crash situations, as well as the potentiality of the hierarchical model when applied to crash data. For instance, this study found that female drivers are more prone to be involved in maneuver and weather/surface crash situations than male drivers when speeding, but female drivers were less likely to speed than males. Similar complexity was found by Romano and colleagues (2009)
applied a hierarchical model to study the role of gender on fatal crashes. In that study, like in this one, female drivers were less likely to speed or to be involved in alcohol-related crashes than males. Also found in both studies was some evidence suggesting that female drivers were not more prone to skill-related crashes (level-1 crash-factors) than their male counterparts were. Thus, both studies present additional evidence against the popular myth portraying female drivers as more prone to be involved in skill-related crashes than males, particularly when driving occurs under normal traffic conditions. As discussed, however, the evidence coming from this study is not conclusive. We also found that females were more involved in some weather/surface-related crashes (), and that females might be more prone to maneuver-related crashes when speeding is involved. Unfortunately, reasons for these findings are unclear.
Despite its interesting results, this study is not free of shortcomings. As mentioned, the inclusion of higher-level crash factors in the analytical model seems appropriate because it helped explain some of the variations observed at lower levels. Application of our hierarchical model is not free of problems, however. One such difficulty emanates from the required partition of the database, which resulted in small sample sizes for some categories and forced us to collapse variables into broader categories. Another limitation involves the modeling of crashes as a function of the hierarchically structured factor levels and covariables. An intuitively appealing approach to such modeling would have been the use of path analysis, modeling the role of factors at superior levels (e.g., alcohol) on intermediate levels (e.g., speeding), and lower levels (e.g., maneuvering). Unfortunately, the use of path analysis to the hierarchical model presents several limitations, such as dealing with categorical variables and some paths that are not well defined. Research aiming to find a valid implementation of path analysis to the problem and data under study is already underway by our research team. Unfortunately, this line of research has not yet yielded fruitful results. Finally, due to the unaccounted complexities, some of the results obtained by this study, although statistically significant, are of dubious implications or irrelevant. That is, for instance, the case of our finding that female drivers were more likely to be involved in maneuver and weather/surface crashes than their male counterparts when they were also speeding. While findings like this are statistically correct, their operational and policy implications are not.
In this study, we proposed an alternative strategy. To understand the role of gender at different crash-factor levels, we separated the analyses into two parts: independently examining the contribution of level-3 to the level-2 crash-factors and the level-2 crash-factors to the level-1 crash-factors. Although this approach did not allow for a full integration of the three-level crash-factors, by focusing on the gender-related interaction terms and going from level-1 crash-factors up to level-3, the model provided some meaningful results.
As mentioned, paths showing the influence of crash-factors as they triggered down from level 3 to level 1 could not be investigated. Also, to maximize the likelihood that drivers included in this study were responsible for the crash, we only included single-vehicle crashes. Not all crashes are reported to law enforcement agencies; therefore, crashes involving very little property damage and no injuries are likely to be underreported and therefore absent from the GES. Finally, another limitation of this study (perhaps the most relevant) involves the possibility of bias by those officers who coded the crashes. Police officers may have been more prone to assign different codes to females than males (e.g., giving a maneuver code to females more frequently than to males). Nevertheless, our study only found an association between female drivers and maneuver in situations in which speeding was involved. If there were gender-related bias in the way these types of crashes were registered, then such an association between speeding and maneuver should be revisited.
In summary, by applying a hierarchical model, this study disentangles some of the factors explaining the role of gender in nonfatal crashes. As such, this effort provides support to the application of these models. As a result, we found that many of the gender-based differences associated to skill-related crashes were either nonexistent, or largely explained by gender differences in alcohol consumption. However, our model was not free of problems and some of the findings seem either irrelevant or difficult to interpret for policy considerations. Thus, further research on the use of hierarchical models to investigate gender-differences in motor-vehicle crashes would be advisable.