Research-informed evidence and support for road safety legislation: Findings from a national survey

Public opinion is influential in the policymaking process, making it important to understand the factors that influence popular support or opposition to public health policies. Researchers and policymakers tend to agree that scientific evidence can inform decision-making, but this influence has not been explored sufficiently, especially in the area of injury prevention. This paper considers the potential for the communication of evidence-based research and public health data to influence opinion about legislation that could reduce road-related injury. We conducted a nationally-representative online survey to assess public attitudes toward four road-safety laws; ignition interlock, school zone red-light cameras, restrictions on infotainment systems, and children's bicycle helmets. For each law, we assessed initial support and then provided a research-informed statistic on either the injury risk posed or the law's efficacy reducing risk and re-examined the law's support or opposition. The survey was completed by 2397 U.S. adults. Each law was initially supported by a majority of respondents, with greatest support for ignition interlock (74.4%) and children's bicycle helmets (74.8%). Exposure to research-informed statements increased legislative support for 20–30% of respondents. Paired analyses demonstrate significant increases toward supportive opinions when comparing responses to the initial and research-informed statements. The study demonstrates considerable public support for evidence-based road-related laws. Overall support was augmented by exposure to research data. Injury prevention practitioners can capitalize on this support in efforts to build support for legislation that would prevent injury. Researchers should be encouraged to expand their efforts to share research results with both the public and policymakers.     

Estimating safety performance trends over time for treatments at intersections in Florida

Researchers have put great efforts in quantifying Crash Modification Factors (CMFs) for diversified treatment types. In the Highway Safety Manual (HSM), CMFs have been identified to predict safety effectiveness of converting a stop-controlled to a signal-controlled intersection (signalization) and installing Red Light Running Cameras (RLCs). Previous studies showed that both signalization and adding RLCs reduced angle crashes but increased rear-end crashes. However, some studies showed that CMFs varied over time after the treatment was implemented. Thus, the objective of this study is to investigate trends of CMFs for the signalization and adding RLCs over time. CMFs for the two treatments were measured in each month and 90-day moving windows respectively. The ARMA time series model was applied to predict trends of CMFs over time based on monthly variations in CMFs. The results of the signalization show that the CMFs for rear-end crashes were lower at the early phase after the signalization but gradually increased from the 9th month. On the other hand, the CMFs for angle crashes were higher at the early phase after adding RLCs but decreased after the 9th month and then became stable. It was also found that the CMFs for total and fatal/injury crashes after adding RLCs in the first 18 months were significantly greater than the CMFs in the following 18 months. This indicates that there was a lag effect of the treatments on safety performance. The results of the ARMA model show that the model can better predict trends of the CMFs for the signalization and adding RLCs when the CMFs are calculated in 90-day moving windows compared to the CMFs calculated in each month. In particular, the ARMA model predicted a significant safety effect of the signalization on reducing angle and left-turn crashes in the long term. Thus, it is recommended that the safety effects of the treatment be assessed using the ARMA model based on trends of CMFs in the long term after the implementation of the treatment.