Interventions to Address Reward-seeking Behaviors Among Young Adults

Our current work involves a National Institutes of Health-funded, 5-year cluster-randomized trial designed to test the effects of administering a behavioral activation intervention in a semester-long freshman orientation seminar on multiple clinical outcomes.

In the lab, we also study the impact of reinforcement-seeking behaviors, primarily alcohol use and reward-driven eating, and health outcomes among young adults and underlying motivational mechanisms that drive multiple reward-seeking behaviors.


Defining Hyper-Palatable Foods Using a Standardized Definition and Examining Associations with Eating and Obesity-related Outcomes

Our recent work has focused on developing a data-driven, quantitative definition of hyper-palatable foods, and applying this definition to the USDA food system database.

Our work won an award for top paper at the Obesity Society Annual Meeting in 2019, was featured in Obesity (November 2019 issue), and has been covered by various media including Newsweek, Forbes, and NPR's Central Standard out of Kansas City.

Our next steps for this work include testing the predictive validity of the definition for relevant eating constructs (overeating, binge eating), and obesity-related outcomes. We are also working to quantify the prevalence of hyper-palatable foods internationally, to compare with our findings from the US food system.

alt="burger, fries, and a drink"

Assessing Alcohol Use and Eating Behavior Using Mobile App Technology

Smartphone applications have widespread utility for collecting real-time information about eating and drinking behavior.

We are developing new methods for assessing alcohol use in real-time using a mobile-photography app, in collaboration with researchers at Pennington Biomedical Research Center. This technology has the ability to quantify caloric and nutrition contents of alcoholic beverages, and relies on photos to report the details, removing the need for participants to self-report their intake, which can be prone to biases.

alt="Taking a picture of food using an iPhone"