The guilty, the unlucky, or the unaware? Assessing self-reported behavioral contributors and attributions on pedestrian crashes through structural equation modeling and mixed methods.

INTRODUCTION: Recent literature suggests that the causation of pedestrians' crashes and the contribution of safety-related behaviors within them may substantially differ compared to other road users. This study aimed to test the effect of individual factors and safety-related road behaviors on the self-reported walking crashes suffered by pedestrians and, complementarily, to analyze the causes that pedestrians attributed to the crashes they suffered as pedestrians during the previous five years. METHOD: For this cross-sectional research performed in Spain, data from a nationwide sample of 2,499 pedestrians from the 17 regions of the country were collected. Participants had a mean age of 31 years. They responded to a questionnaire on demographics, safety-related walking behaviors, and self-reported pedestrian crashes and the causes attributed to them. RESULTS: Utilizing Structural Equation Models (SEM), it was found that self-reported walking crashes can be predicted through unintentional risky behaviors (errors). However, violations and positive behaviors remain non-significant predictors, allowing to hypothesize that they might, rather, play a key role in the pedestrian's involvement in pre-crash scenarios (critical situations preceding crashes). Also, categorical analyses allowed to determine that the causes that pedestrians attributed to the walking crashes they had suffered were principally their own errors (44.6%), rather than their own traffic violations (8.5%). Nevertheless, this trend is inverse when they believe the responsibility of the crash weighs on the driver. That is to say, they usually attribute the crash to their traffic violations rather than errors. However, many biases could help explain these attributional findings. PRACTICAL APPLICATIONS: The results of this study highlight key differences in behavioral features and crash predictors among pedestrians, with potentially relevant applications in the study and improvement of walking safety from behavioral-based approaches.

Not gendered but different from each other? A structural equation model for explaining risky road behaviors of female and male pedestrians.

As alternative transportation is getting more and more fashionable, and more people worldwide are "shifting" to walking trips, even for their daily commuting, traffic crashes suffered by pedestrians are still a great concern for road safety and public health researchers and practitioners. In this regard, risky or "aberrant" road behaviors have emerged, during the last few years, as a key issue to be considered for crash prevention. Nevertheless, the idea of a "generic pedestrian" is getting re-evaluated, and analyzing key features, such as gender, seems to be crucial for understanding pedestrians' performance and safety outcomes. OBJECTIVE: The objective of this study was to examine the effect of gender on pedestrians' both deliberate (traffic violations) and undeliberate (errors) risky walking behaviors, considering a set of theoretically based demographic and psychosocial variables as their potential predictors. METHOD: For this cross-sectional study, data from 1070 Spanish pedestrians (60 % females and 40 % males, aged between 16 and 79) from the 17 regions of Spain, responding to an electronic questionnaire, were analyzed through a multi-group structural equation modeling (MGSEM) approach. RESULTS: Although age, handheld device-interaction, and sensation-seeking seem to have a similar effect on the errors and violations reported by both genders (similarities), factors such as risk perception, educational level and the misbehaviors observed in other road users are significant predictors only in the case of male pedestrians. On the other hand, road distractions have been shown to play a significant role in females' errors and violations, while males' road distractions seem to only affect their involuntary risky behaviors. CONCLUSION: The findings of this study support the influence of gender in the statistical explanation of both deliberate and undeliberate walking risky road behaviors, also depicting the differential role of certain demographic and psychosocial factors when we compare male and female pedestrians.