Archived Content

The Office of Disease Prevention (ODP) archives materials that are more than 3 years old and no longer being updated. Over time, links and other information may have changed. We cannot guarantee that all of the links in these materials will be current or accurate.

Methods: Mind the Gap

Webinar Series

Using Control Systems Engineering To Optimize Adaptive Mobile Health Interventions

June 4, 2019
Dr. Heckler
Eric B. Hekler, Ph.D.

University of California, San Diego

View the Webinar

About the Webinar

Dr. Linda Collins et al. have advanced a new framework for the creation and optimization of behavioral interventions called the multiphase optimization strategy (MOST). MOST is an engineering-inspired approach to intervention development, which emphasizes the use of optimization trials prior to conducting randomized controlled trials to produce empirically optimized interventions. The first type of optimization trial that was advanced in MOST is the factorial/fractional factorial trial, which can be used to optimize static interventions to eliminate underperforming components. Adaptive behavioral interventions are more complex than static interventions as there are a variety of additional elements that can feasibly be optimized, such as the timing on when to deliver an intervention or the tailoring variables used to individualize the intervention. Thus, additional optimization trial designs are needed to enable empirical optimization of them, with two optimization trials being the sequential multiple assignment randomized trial (SMART) and the micro-randomized trial (MRT). Drs. Eric Hekler and Daniel Rivera have been advancing an approach via the use of methods from control systems engineering—in particular, the use of system identification and a new optimization trial called the control optimization trial (COT)—as a third type of optimization trial for adaptive interventions.

In this presentation, Dr. Hekler first reviews the need for optimization of adaptive interventions, building on MOST, followed by an overview of control systems engineering and attributes of problems that are well matched to control engineering. He then summarizes key steps in the development and optimization of an adaptive intervention using this approach, leading to a COT. Dr. Rivera is also available on the call to answer any questions that arise. 

About Eric Hekler

Dr. Eric Hekler is an Associate Professor in the Department of Family Medicine and Public Health at University of California, San Diego (UCSD). He is also Director of the Center for Wireless and Population Health Systems and a faculty member of the Design Lab at UCSD. His research focuses on facilitating individualized behavior change for fostering long-term health and well-being via digital health tools. Along with Dr. Daniel Rivera and colleagues, Dr. Hekler has helped develop Just Walk, arguably the first idiographic (i.e., n of 1) behavioral intervention based on control engineering principles.

Dr. Hekler’s research has been funded by the National Library of Medicine; National Cancer Institute; National Heart, Lung, and Blood Institute; National Science Foundation’s Smart and Connected Health program, Robert Wood Johnson Foundation, and other groups, such as Google’s Faculty Research Awards program. Prior to UCSD, Dr. Hekler was a faculty member at Arizona State University. He completed his postdoctoral training at Stanford University and received his Ph.D. in clinical health psychology from Rutgers University.

Last updated on