Finding a New Safety Performance Function for Two-Way, Two-Lane Highways in Rural Areas

For over 30 years, crash prediction models (CPMs) have been created and analyzed, with the objective being to find the best way to predict where crashes will occur and how to prevent them in the future. This has recently become a popular discussion and reality since the release of the Highway Safety Manual (HSM) and its CPM in 2010. However, many are still hesitant to begin implementing these methods as the accuracy can vary. This is a study testing the original HSM's CPMs to state-specific calibrated CPMs, and new, independent CPMs to find the best model for rural, two-lane highways in Kansas. Almost 300 miles of highway geometric data were collected to create these new models using negative binomial regression. The most significant variables in each model were found to consistently be lane width and roadside hazard rating. These models were compared against CPMs calibrated to be used on the HSM using nine validation segments. A difficulty to overcome was the large amount of animal-related crashes, as they account for 58.9 percent of crashes on Kansas highways. Removing those from the equation showed a large improvement in accuracy compared to other models created

Suicide risk profiles and barriers to professional help-seeking among college students with elevated risk for suicide.

Suicide is the second leading cause of death among college students, yet many students with elevated suicide risk do not seek professional help. This study identified suicide risk profiles among college students and examined these in relation to students perceived barriers to professional help-seeking. Data were obtained from college students (n = 1689) identified to be at elevated risk for suicide based at four US universities. Latent class analysis was performed to determine risk profiles, followed by examinations of differences in help-seeking barriers by profile groupings. Results revealed three student groupings: (1) moderate internalizing and externalizing symptoms (with low alcohol misuse), (2) highest internalizing and externalizing symptoms (with highest social disconnection), and (3) lowest internalizing symptoms and low externalizing (with highest social connection and alcohol misuse). Group 1 included the youngest and most racially and sexually diverse students, Group 2 endorsed the most help-seeking barriers, and Group 3 endorsed the fewest barriers. Group 2 is especially concerning, considering the severe clinical characteristics, high number of barriers, and low connectedness to others for potential support. Understanding these differences across risk and barrier profiles is an important step towards developing tailored approaches to increase mental health care in college populations