Survey app aiding study into alcohol-impaired driving

Yi Shang has worked for years on perfecting a customizable mobile survey app to allow researchers to pair specific survey questions with data collected from wearable technology to unlock new methods of data collection. Now, his work will help break new ground in alcohol-impaired driving research.

Shang, a professor of Electrical Engineering and Computer Science at Mizzou, and frequent collaborator Tim Trull, professor of Psychological Sciences, are working with a team led by fellow Psychology Professor Denis McCarthy study in real time the decision-making process individuals make when deciding whether or not to drive after drinking. The study is funded by the National Institutes of Health.

Yi Shang Headshot.

MU Professor Yi Shang and his team are constantly improving their mobile survey platform platform to make it easy to use for a wide variety of research and data collection needs.

McCarthy has spent his career studying all manner of aspects of alcohol-impaired driving, and after years of controlled laboratory studies, he wanted to dig deeper into an individual’s decision-making process.

“Two things that weren’t there in [my previous] research. One was when you’re in the lab, you’re not actually deciding whether to drink or drive. You’re not allowed to do that … Two was that I was still looking at just one assessment for each person,” he said.

“I also want to look within people. Say this person might be a greater risk to drive drunk than other people, but what days does he drive drunk and what days does he not? Or this person might be low risk for drunk driving compared to other people, but they still do it every once in a while. What makes that event more likely?”

McCarthy wanted to gather real-time data from willing participants, and he reached out to Shang to see if his system could be modified to fit the project. The answer was yes.

“In addition to basic survey questions and answers on a smart phone, we also will be collecting sensor data and GPS data and also using a breathalyzer that will connect to the phone,” Shang explained.

The app also will alert participants when their blood-alcohol content gets to a point where driving would be dangerous in order to ensure safety. McCarthy set up the study to account for the possibility that the data collection process could affect participants’ behavior. The goal is to get robust, in-the-moment data on decision making that can help determine ways to cut down on alcohol-impaired driving.

“Another reason we got the funding is that either this doesn’t affect behavior, in which case we get data that nobody else has, or … the focus of the study changes to how can we use this kind of monitoring to develop easy-to-implement, cheap intervention that reduces drunk driving,” he explained.

Shang’s platform provided the customizability necessary for the study and had the added bonus of a partnership contained within a single campus. Shang and his team are constantly improving the platform to make it easy to use for a wide variety of research and data collection needs.

“It’s a generic, customizable survey taking platform,” he said. “You enter questions just like Survey Monkey, but it has this additional component of a question bank of psychological emotion question batteries together with a hook to sensors and GPS data.”

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