Frequently Asked Questions about Micro-Randomized Trials (MRTs)

blank sample MRT schematicJanuary 17, 2019:

In micro-randomized trials (MRTs), individuals are randomized hundreds or thousands of times over the course of the study. The goal of these trials is to optimize mobile health interventions by assessing the effect of intervention components and assessing whether the intervention component effects vary with time or an individual’s current context. In an effort to help researchers understand MRTs, we have developed a list of answers to frequently asked questions about these trials. This webpage can be used to answer your specific questions, or you can read the entire page to understand the use and design of MRTs. ​

Open the FAQ.

Video: Webinar on Analysis of Data From an MRT

September 20, 2018:

Thanks to all who participated in our 1 & 1 workshop on analysis of data from a micro-randomized trial (MRT). This is a video of the webinar that Methodology Center Principal Investigator Susan Murphy presented on Thursday, September 6, 2018. The video includes both the presentation and the question-and-answer session that followed. This is the second of two webinars on the MRT. Watch the first video before watching this one. These recordings are a great way to learn the basics of the MRT.

In an MRT, individuals are randomized hundreds or thousands of times over the course of the study. The goal of these trials is to assess the proximal, in-the-moment, impact of interventions (e.g., interventions that are intended to impact behavior over small time intervals). Through MRTs we can gather data to build optimized mHealth interventions.

Watch our website and eNews for information about upcoming 1 & 1 webinars.

Download the presentation slides.

Watch the video on YouTube.

Video: Webinar on Micro-Randomized Trials (MRTs)

July 25, 2018:

Thanks to all who participated in our 1 & 1 workshop on the micro-randomized trial (MRT). This is a video of the webinar that Methodology Center Principal Investigator Susan Murphy presented on Thursday, June 14, 2018. The video includes both the presentation and the question-and-answer session that followed. This recording is a great way to learn the basics of the MRT.

In an MRT, individuals are randomized hundreds or thousands of times over the course of the study. The goal of these trials is to assess the proximal, in-the-moment, impact of interventions (e.g., interventions that are intended to impact behavior over small time intervals). Through MRTs we can gather data to build optimized mHealth interventions.

Our next 1 & 1 workshop will be on Thursday, September 6, from 3:00 to 5:00 p.m. Eastern Time. Susan Murphy will present “Analyzing Data From an MRT.” For anyone who did not attend Susan’s first MRT workshop, we suggest watching the video before attending the webinar on September 6.

Watch the video on YouTube.

Grant: Expanding the Methodological Toolbox for Sequential, Multiple Assignment, Randomized Trials (SMARTs)

smartWORDLESSOctober 31, 2016:

Over the course of treatment, a clinician often alters treatment based on patient characteristics or response to earlier treatment. Sequential, multiple assignment, randomized trial (SMART) designs provide the data needed to construct high-quality adaptive interventions. Interventions that adapt at the right times (e.g., intensifying for people who do not respond to the initial treatment) can improve participant outcomes while decreasing the cost and burden of the intervention (e.g., stepping down treatment for responsive participants). SMART designs are currently being used around the world in dozens of trials to build adaptive interventions for drug use, HIV, ADHD, autism, obesity, and more.

Last year, a team of Methodology Center researchers was awarded a grant from the National Institute on Drug Abuse (R01 DA039901) to expand the methodological toolbox available for intervention designers seeking to analyze data and plan future SMART studies.

This research will develop multilevel models to allow intervention scientists to answer new questions using longitudinal data from a SMART—for example, to compare the effect of two adaptive interventions on changes in craving or substance use over time. The research will also develop sample size calculators to facilitate the planning of SMARTs studies with longitudinal outcomes. Co-principal investigators Inbal (Billie) Nahum Shani and Daniel Almirall are excited about the potential of this research to further expand the usefulness of SMART designs. Billie said, “Right now, the methods that we have for analyzing and planning sample size for SMART studies are relatively limited.  For example, they allow us to compare adaptive interventions only in terms of end-of-study outcome. However, many scientists are interested in taking advantage of longitudinal data they often collect in the course of a SMART study, and using it to compare adaptive interventions in terms of trajectories of change. For example, scientists may want to study change in HIV-risk behavior during the course of the intervention program. This is because modeling change, rather than end-of-study outcome, provides greater statistical power and a more nuanced picture of how the adaptive intervention works. In this project we will develop the tools to allow intervention designers conduct these analyses and plan future SMARTs with longitudinal outcomes.”

Other researchers on the team that include Linda Collins, John Dziak, and Susan Murphy. Billie, Danny, and Susan are based at University of Michigan, and Linda and John are at Penn State. This grant will add five more years of methodological research to the development of SMART, allowing this valuable method to be applied even more broadly.

Read more about SMART 

Eric Laber Receives Alumni Award

September 23, 2016:ELABER

Congratulations to Eric Laber, associate professor of statistics at North Carolina State University, recipient of The Methodology Center 2016 Distinguished Alumni Award. Eric develops methods for data-driven decision making. He applies his work in a broad variety of ways including precision medicine, artificial intelligence, adaptive conservation, and the management of infectious diseases.

Eric was a research assistant at The University of Michigan’s Institute for Social Research from 2008-2011 where he worked with Susan Murphy and was a Methodology Center trainee. During his time at Michigan, he worked on developing the sequential, multiple assignment, randomized trial (SMART), and assisted in the development of PROC Qlearn. Eric has published 34 peer-reviewed articles, nine first-authored. Eric is also the recipient of North Carolina State University’s 2015-16 Cavell Brownie Mentoring Award for his creative mentoring of graduate and undergraduate statistics students.

Visit Eric’s website.

Special Issue: Adaptive Interventions for Children’s Mental Health

September 8, 2016:boy sits in field

There are vast individual differences in youth presenting for mental health treatment. Youth vary in their initial clinical presentation; their contextual risk and protective factors; and their engagement, adherence and response to evidence-based treatments. For this reason, adaptive interventions, which are individually tailored to each person, are valuable tools in the treatment and prevention of child and adolescent mental health (CAMH) disorders. Methodology Center Investigator Daniel Almirall co-edited a recent special issue of the Journal of Clinical Child & Adolescent Psychology that showcases recent applications and innovations of adaptive interventions for addressing CAMH disorders.

To introduce the issue, Daniel and his co-editor Andrea Chronis-Tuscano wrote an article that introduces adaptive interventions and the use of the sequential, multiple assignment, randomized trial (SMART) for the development of evidence-based adaptive interventions. The article also gives an overview of research using adaptive interventions for CAMH disorders and describes future directions for this research.

The special issue includes articles on using adaptive interventions to treat ADHD, autism spectrum disorder, depression, conduct problems and more.

Read the article.

Open the special issue.

 

Reference

Almirall, D., & Chronis-Tuscano, A. (2016). Adaptive interventions in child and adolescent mental health. Journal of Clinical Child & Adolescent Psychology, 45(4), 383-395.

Susan Murphy Elected to Academy of Sciences

SMURPHY

Susan Murphy, 2013 MacArthur Fellow

May 13, 2016:

We are pleased to announce that Methodology Center Principal Investigator Susan Murphy has been elected to the National Academy of Sciences. Susan’s innovative research, particularly her development of the sequential, multiple assignment, randomized trial (SMART), and her recent work on just-in-time adaptive interventions (JITAIs) has garnered many honors and accolades, including membership in the National Academy of Medicine in 2014 and a MacArthur Foundation “genius” award in 2013.

The National Academy of Sciences was established by Congress in 1863 to provide independent advice to the government about science and technology. Susan was elected to another Academy, the National Academy of Medicine (previously known as the Institute of Medicine), in 2014. In both Academies, current members elect new members who have made distinguished research contributions.

Susan’s research focuses on developing innovative research approaches to improve the personalization of treatment. She developed SMART, an experimental design tool that allows scientists to build empirically based interventions that adapt to patient characteristics and response to treatment. Recently, Susan has begun investigating the construction of JITAIs, which use real-time data from mobile technologies to deliver personalized behavioral interventions exactly when they are needed.

Susan’s work has impacted the research of countless scientists and interventionists. SMARTs are being used to address a broad range of topics including cocaine abuse, depression, problem drinking, obesity, ADHD, and autism. Dozens of SMARTs have been funded by the National Institutes of Health, and multiple NIH program announcements specifically request SMART designs.

Susan is Herbert E. Robbins Distinguished University Professor of statistics, research professor at the Institute for Social Research, and professor of psychiatry at the University of Michigan. She is a fellow of the College of Problems of Drug Dependence, the MacArthur Foundation, the Center for Advanced Study in the Behavioral Sciences at Stanford University, the American Statistical Association, and the Institute of Mathematical Statistics. She is an elected member of the International Statistical Institute and from 2007-2009 served as co-editor of The Annals of Statistics. She has been a primary investigator in The Methodology Center since 1995.

Read more about Susan’s research.

Training on Optimizing Interventions

February 2, 2016:

Applications are no longer being accepted.

Applications are now being accepted for a five-day training, “Optimization of Behavioral and Biobehavioral Interventions” with instructors Linda M. Collins, Susan Murphy, and Daniel Almirall. The training will cover the multiphase optimization strategy (MOST); factorial and fractional factorial screening experiments; adaptive interventions; the sequential, multiple assignment, randomized trial (SMART); just-in-time adaptive interventions (JITAIs); and obtaining funds for optimization projects.  In addition, there will be a variety of presenters describing how they are optimizing behavioral and biobehavioral interventions. Join us May 16-20, 2016, in Bethesda, Maryland.