Blame attribution analysis of police motor vehicle collision reports involving child bicyclists.

BACKGROUND: Injuries resulting from collisions between a bicyclist and driver are preventable and have high economic, personal and societal costs. Studying the language choices used by police officers to describe factors responsible for child bicyclist-motor vehicle collisions may help shift prevention efforts away from vulnerable road users to motorists and the environment. The overall aim was to investigate how police officers attribute blame in child (≤18 years) bicycle-motor vehicle collision scenarios. METHODS: A document analysis approach was used to analyse Alberta Transportation police collision reports from Calgary and Edmonton (2016-2017). Collision reports were categorised by the research team according to perceived blame (child, driver, both, neither, unsure). Content analysis was then used to examine police officer language choices. A narrative thematic analysis of the individual, behavioural, structural and environmental factors leading to collision blame was then conducted. RESULTS: Of 171 police collision reports included, child bicyclists were perceived to be at fault in 78 reports (45.6%) and adult drivers were perceived at fault in 85 reports (49.7%). Child bicyclists were portrayed through language choices as being irresponsible and irrational, leading to interactions with drivers and collisions. Risk perception issues were also mentioned frequently in relation to poor decisions made by child bicyclists. Most police officer reports discussed road user behaviours, and children were frequently blamed for collisions. CONCLUSIONS: This work provides an opportunity to re-examine perceptions of factors related to motor vehicle and child bicyclist collisions with a view to prevention.

The Relationship of Urban Form on Children and Adolescent Health Outcomes: A Scoping Review of Canadian Evidence.

Urban form can have an impact on health outcomes in children, and the synthesis of findings can identify gaps in the literature and regional reviews may help guide policymakers. This study aims to complete a scoping review of the research relating urban form to health outcomes in children and adolescents from urban Canadian settings. Thirteen online databases were searched to identify studies that had objective measures of urban form and health outcomes. Two research assistants independently reviewed 27,444 titles and abstracts, and 176 full-text articles, returning 32 unique studies with youth-specific data. The majority of the included studies were cross-sectional or ecological (n = 26). Six studies used Canada-wide data and the rest were from Ontario (n = 11), Alberta (n = 6), and Quebec (n = 6). Urban form characteristics included neighbourhood food environment (n = 11), parks/natural space/greenness (n = 10), road or intersection characteristics (n = 7), and aggregated urban form measures (n = 7). Studies examined a variety of health outcomes: the majority considered weight status (n = 16) and injury (n = 10). Although there is over-reliance on mainly cross-sectional study designs, there is evidence suggesting that urban form is associated with health outcomes in Canadian youth, with parks/greenspace, road connectivity, and road characteristics most consistently associated with health outcomes in youth.

Adaptation of a Canadian culpability scoring tool to Alberta police traffic collision report data.

Objective: The objective of this study was to adapt a previously validated Canadian Culpability Scoring Tool (CCST) to Alberta police report data. Methods: Police traffic collision reports from motor vehicle (MV) collisions in Calgary and Edmonton (Alberta, Canada) from 2010 to 2014 were used. Adaptation of the CCST was completed with input from personnel within Alberta Transportation, contributing to face and content validity. Two research assistants, given only the information necessary for scoring, evaluated 175 randomly selected MV-MV collisions. Interrater agreement was estimated using kappa (k) and reported with 95% confidence intervals (CIs). Discussion of disagreements between the research assistants and consultation from Alberta Transportation informed the algorithm used in the Alberta Motor Vehicle Collision Culpability Tool (AMVCCT). The AMVCCT was automated and applied to all motorists involved in collisions. Binary logistic regression was used to examine characteristics of the culpable and nonculpable drivers and their effects were reported using odds ratios (ORs) with 95% CIs. Results: Interrater agreement for the random sample was excellent (k = 0.95; 95% CI, 0.92-0.99). Of those drivers hospitalized, 1,130 (37.54%) were rated not culpable and 1,880 (62.46%) were rated culpable. The odds of being culpable were higher for males than for females (OR = 1.43; 95% CI, 1.23-1.66). The odds of being culpable were higher in those impaired by alcohol than those considered "apparently normal" (OR = 61.10; 95% CI, 22.66-164.75). The odds of being deemed culpable, when compared with drivers >54 years old, were higher for those <25 years old (OR = 1.72; 95% CI, 1.35-2.20) and lower for those in the 40- to 54-year-old age group (OR = 0.78; 95% CI, 0.63-0.96). Driving between 12 a.m. and 6 a.m. resulted in higher odds of being culpable compare with all other 6-h time blocks. Direction and statistical significance remained consistent when applying the tool to all MV collisions. Sensitivity analysis including the removal of single vehicle collisions did not affect the direction or statistical significance of the main results. Conclusions: The AMVCCT identified a culpable group that exhibited characteristics expected in drivers who are at fault in collisions. The age groups 25-39 and 40-54 demonstrated different results than the CCST. However, this is the only difference that exists in the findings of the AMVCCT compared to the CCST and could exist due to differences between the driving populations in Alberta and British Columbia. It is possible to adapt the CCST to provinces outside British Columbia and, in doing so, we can identify risk factors for collision contribution and not-at-fault drivers who represent the driving population.