Big Data methods in biobehavioral health goal of training grant

By A'ndrea Elyse Messer
October 09, 2014

UNIVERSITY PARK, Pa. -- A National Institutes of Health Big Data to Knowledge Program grant to Donna Coffman, research associate professor in Penn State's College of Health and Human Development and principal investigator at the Methodology Center, targets the development of big data methods for biobehavioral change and maintenance. This training grant is for more than $500,000 over three years.

"Physical inactivity, poor stress management, poor diet and smoking are responsible for about 80 percent of coronary heart disease and cerebrovascular disease," said Coffman. "They are also partly responsible for other negative health outcomes including high lipids, high blood pressure, cancer, diabetes and obesity. By developing, extending and applying big data methods to biobehavioral health data, we can help individuals develop and maintain healthy behavior regarding physical activity, diet and stress management.

"This grant will allow me to develop the methods needed to make this possible. Thanks to smartphones and wearable devices, we are living in an age where rich data are commonplace. Amazon, Facebook and Google all use new forms of big data to sell us things. As a society, we can use other new forms of big data to improve public health, once we build the right tools."

Coffman's primary mentor will be Runze Li, Distinguished Professor of Statistics. Her co-mentors will be Vasant Honavar, Professor and holder of the Edward Frymoyer Chair of Information Science and Technology and Joshua Smyth, professor of biobehavioral health and medicine, all at Penn State.

The overall goal of the project is to develop and distribute methods for dealing with the vast amounts of data available in real time. This will be particularly valuable for the development of adaptive, individualized health-behavior interventions.

"This exciting, new type of intervention is capable of delivering a specific intervention at the specific moment when it is needed, increasing efficiency and effectiveness while decreasing participant burden," said Coffman.

(Media Contacts)

Last Updated October 29, 2014