Behavioral science and analytics for injury
reduction
Alcohol Impaired driving Research
Active Projects
A Pilot Randomized Control Trial using Loss vs. Gain Framed Text Messaging for Reducing Alcohol-Impaired Driving
PI: Kit Delgado, MD, MS, University of Pennsylvania
The aim of this project is to pilot test the feasibility of implementing a randomized control trial of a behavioral intervention that combines smartphone-paired breathalyzers and driving exposure data to reduce binge drinking and drinking and driving. Participants who report risky drinking behaviors will be provided a smartphone-paired personal breathalyzer and download a smartphone app that collects driving telematics data.
Effect of Smartphone Breathalyzer Blood Alcohol Content Feedback on Willingness to Drive: A Laboratory Randomized
Control Trial
PI: Kit Delgado, MD, MS, University of Pennsylvania
The objective of this pilot study is to evaluate the effect of blood alcohol content (BAC) feedback from a smartphone paired breath testing device on drinkers’ willingness to drive according to estimated BAC level. In a laboratory setting, we provide weight-based doses of alcohol to participants. Half are shown their BAC after testing, and half remain blind to their alcohol levels. After each reading, we ask participants to rate their willingness to drive.
Test Accuracy of Smartphone Paired Breath Testing Devices: A Validation Study
PI: Kit Delgado, MD, MS, University of Pennsylvania,
The goal of this pilot project is to assess the accuracy of commercially available mobile breathalyzer devices. In a laboratory setting, we provide participants with weight-based doses of alcohol and obtain their BAC using breath testing devices that pair with a smartphone app. These devices are tested against a police-grade breathalyzer.
Publications
Funded by the Penn Injury Science Center
This study validates the test accuracy of commercially available personal alcohol breath testing devices that pair with smartphones against measurements from a police grade breath testing device and a blood alcohol content tests.
Funded by the National Center for Injury Control and Prevention and Centers for Disease Control and Prevention
To understand the impact of crashes after big ridesharing companies, like Uber, were integrated into cities, we created a study using time-series analyses on 4 US cities. We assumed that Uber's presence would be associated with fewer alcohol-involved crashes. Though this is partially supported in the results, we found that there was no concomitant change in all injury crashes and relationships between ridesharing and motor vehicle crashes differ between cities over time and may depend on specific local characteristics.