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Big Data Boosts Obesity Research Results

From study design to patient engagement, Gary Bennett, PhD, shares his insight on what is and is not effective in applying technology to obesity research.

Published August 09, 2016

Big Data Boosts Obesity Research Results

The need for interventions to prevent and treat obesity is extremely urgent, as over one-third of adults and 17% of children in the United States are considered to be obese based on body mass index (BMI). From wearable devices to smartphone applications for tracking diet and exercise, consumer technologies are aiming to make a positive impact on changing lifestyle behaviors and potentially decreasing obesity rates. Gary Bennett, PhD, of the Duke Global Digital Health Science Center, is bringing digital health to obesity interventions to measure and evaluate the effectiveness of technology in increasing patient engagement and improving long-term health outcomes, such as weight maintenance. Recently Dr. Bennett spoke with us about best practices when designing studies applying technology to obesity interventions, surprising study results on weight and co-existing conditions, and the most promising element for obesity tech research (that is also commonly ignored).

According to Dr. Bennett, one of the most significant mistakes made in research on health technology and patient engagement is not taking into consideration the user experience. "We as researchers can easily get hyper-focused on theory, evidence, and innovative new functionality. However, apps are only useful if they're actually used by patients," he stated. User engagement is the best predictor of positive outcomes, which is why it is so important to manufacturers of consumer technology. "Commercial smartphone application developers are constantly testing and iterating through design and functionality changes to optimize user engagement. The (research) field far too frequently adopts the 'someone-can-make-it-pretty-later' approach, which results in outcomes that underestimate their true effect." Dr. Bennett also noted that creating more consumer technologies isn't necessarily the solution to increasing patient engagement and improving health outcomes. "The existing suite of apps do a fine job of collecting data, but they're less useful for changing behavior. What we need are creative, theory- and evidence-based tools that integrate with existing apps and leverage their data to improve patient outcomes and make clinical care (whether that's from a primary care provider or other clinician) more efficient and effective."

Dr. Bennett's research on technology and obesity has led to some surprising results with long-term outcomes. "Our Shape trial was a test of weight gain prevention app for medically vulnerable patients in primary care. Many in this group have exceedingly high obesity risk, but very little interest in weight loss. We predicted that the app would help patients avoid weight gain during the 18-month trial. However, we were surprised to find that they kept the weight off for up to four years." A second unexpected outcome was a nearly 70% decrease in depression among patients with high rates of depression at the start of the study, he added. The relationship between depression and obesity has been suggested to be a reciprocal one, as obesity has been shown to increase the risk of depression and depression to be predictive for developing obesity.

When it comes to a promising consumer technology for obesity research, for Dr. Bennett the most encouraging one is one we take for granted-human beings. "Nearly all of our apps work better when combined with human coaching, counseling, or care. Although most thought that digital health technologies would render us humans irrelevant, we're now finding that they're most useful-particularly with complex conditions like obesity-in making clinical care more efficient and effective. Ultimately, we should be focused on the data, using it to better deliver real-time personalized feedback, reminders, and notifications to patients, while identifying the ways that it can best inform clinical care."

Hear more about technology and obesity from Gary Bennett, PhD, and others at "Big Data, Consumer Technology, and the Obesity Epidemic: Emerging Science and Ethical Considerations" on September 16, 2016 at the New York Academy of Sciences.