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.
August 13, 2018
Join our next 1 & 1 workshop, when Methodology Center Investigator Susan Murphy will present "Analyzing data from a micro-randomized trial (MRT)." 1 & 1 workshops consist of a one-hour live video presentation on a method followed by a one-hour question-and-answer session with the presenter. The workshop will be held on Thursday, September 6, from 3:00 to 5:00 p.m. Eastern Time. This webinar is a follow up to the webinar that Susan presented on June 14, 2018. For anyone who did not attend Susan's first MRT workshop, we suggest watching the video of that webinar before joining us on September 6.
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.
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.
April 10, 2018
For our next 1 & 1 workshop, Methodology Center Investigator Susan Murphy will present an introduction to the micro-randomized trial (MRT). 1 & 1 workshops consist of a one-hour live video presentation on a method followed by a one-hour question-and-answer session with the presenter. After the presentation, Susan will accept questions via instant message and answer them live. The workshop will be held on Thursday, June 14, from 3:00 to 5:00 p.m. Eastern Time.
March 14, 2018
Congratulations to Methodology Center Investigator Susan Murphy, recipient of the 2018 Luminary Award from the Precision Medicine World Conference (PMWC). The PMWC Luminary Award recognizes researchers "who have accelerated personalized medicine into the clinical marketplace." Susan is being recognized for "innovative data science methods to improve patient care through mobile health in chronic disease," specifically her work on micro-randomized trials and just-in-time adaptive interventions.
February 27, 2018
Are you planning to attend the Society for Behavioral Medicine’s 39th Annual Meeting & Scientific Sessions in New Orleans on April 11-14, 2018? If so, schedule some time for some of our many talks, posters, workshops, and more.
August 11, 2017
Methodology Center Principal Investigator Susan Murphy has coedited a new textbook, Mobile Health: Sensors, Analytic Methods and Applications. It contains chapters written by Susan, Methodology Center Investigator Inbal “Billie” Nahum-Shani, and several Methodology Center collaborators. The book introduces mHealth technology, specifically wearable sensors that provide data for mHealth interventions, analytic methods for data from mobile sensors, and the development of mHealth interventions. The book provides a comprehensive reference on mHealth for technology-oriented researchers with backgrounds in computer science, engineering, statistics, and applied mathematics.
The Methodology Center is pleased to announce the availability of a new web applet for calculating the minimum sample size for a pilot SMART. The sequential, multiple assignment, randomized trial (SMART) is a novel experimental design that can be used to build high quality adaptive interventions that adapt to patient need. Pilot SMARTs can be used to examine feasibility and acceptability issues of adaptive interventions embedded in a full-scale SMART study.
April 6, 2017
Response to substance abuse treatment can look very different between individuals and even within individuals at different points in time. Sequential, multiple assignment, randomized trials (SMARTs) are being used to develop interventions that adapt based on individual needs and circumstances. New methods for data analysis show promise for improving intervention developers’ ability to tailor an intervention even more specifically to an in individual's needs for a broad range of health issues, including substance use. In a recent article in the journal Addiction, Methodology Center researchers Inbal (Billie) Nahum-Shani, Daniel Almirall, and their collaborators demonstrate the utility of Q-learning, a method developed in computer science, for the analysis of data from a SMART to prevent relapse among individuals with alcohol use disorders. Q-learning helped the authors identify a subset of individuals who appeared to be responding to treatment, but who needed additional treatment to maintain progress.
March 13, 2017
In our latest video releases, Methodology Center Investigator Susan Murphy introduces some innovative tools for building adaptive health interventions that can be delivered through a smartphone or other mobile device. In the first video, she introduces the just-in-time adaptive intervention (JITAI), a type of intervention that uses real-time data to deliver interventions as needed via mobile devices. In the second video, she introduces the microrandomized trial, an innovative trial design for building JITAIs. In the third video, Susan discusses data analysis to inform the development of a JITAI.
Photo credit: John D. and Catherine T. MacArthur Foundation
January 18, 2017
Every year in the United States, 800,000 deaths are directly attributable to behavioral factors like smoking and alcohol use. Interventions that help people modify their risky behavior could save many lives. Because adaptive interventions (also called dynamic treatment regimens) adjust based on participant need or preference, they have the capacity to increase intervention effectiveness and/or decrease cost and patient burden.
November 30, 2016
Micro-randomized trials (MRTs) are a type of experiment for use in developing a mobile intervention. In order to understand MRTs, consider an intervention that promotes physical activity among cardiac patients.
A new web applet allows users to calculate the number of subjects needed for an MRT given the length of the study, the number of randomizations per day, and a few other criteria. The methodological foundation of the applet is explained in "Sample size calculations for micro-randomized trials in mHealth,"recently published in the journal Statistics in Medicine.
Open the article. (Journal access required.)
October 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.
September 23, 2016
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.
September 8, 2016
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.
September 7, 2016
The Methodology Center is declaring this the “Year of SMART” to raise awareness among researchers, reviewers, and program officers at various agencies about the potential value of the sequential, multiple-assignment, randomized trial (SMART). SMART is a type of multi-stage factorial experimental design that allows researchers to build or optimize high-quality adaptive interventions. An adaptive intervention is a sequence of individually tailored intervention decision rules that help guide how best to adapt and re-adapt an intervention over time based on the evolving condition of the individual.
November 23, 2015
Congratulations to the team of researchers from The Methodology Center and North Carolina State University on their recently awarded grant from the National Institute on Alcohol Abuse and Alcoholism, “Data-Based Methods for Just-in-Time Adaptive Interventions in Alcohol Use.” Despite the many problems associated with alcohol abuse, relatively few people in the United States receive treatment for alcohol use disorders. Using smartphones to deliver interventions will allow more people to be treated, and will reduce the cost of treatment. This project aims to develop the methods and algorithms needed to provide each individual with the proper intervention exactly when he or she needs it.
September 10, 2015
We are delighted to announce that the National Institute on Drug Abuse (NIDA) recently awarded The Methodology Center a $13 million grant to support both ongoing and new research for the next five years.
"This grant is the cornerstone of all our scientific funding," said Linda Collins, Director of The Methodology Center. "Importantly, it is enabling us to launch a new initiative in the area of analysis of complex behavioral data related to substance use and HIV."
August 19, 2014
We are pleased to announce that the University of Michigan has named Susan A. Murphy distinguished university professor for her research, leadership, and service. Susan is a Methodology Center principal investigator, Herbert E. Robbins Distinguished University Professor of statistics, research professor at the Institute for Social Research, and professor of psychiatry.
Susan's research focuses on development of innovative research approaches to improve the personalization of treatment. She developed the sequential, multiple assignment, randomized trial (SMART), which led to her being named a John D. and Catherine T. MacArthur Foundation fellow in 2013. SMART is an experimental design tool that allows scientists to build empirically based interventions that adapt according to patient characteristics and response to treatment. While development of SMART continues, Susan is also investigating the construction of just-in-time adaptive interventions (JITAIs), which use real-time data from mobile technologies to deliver personalized behavioral interventions exactly when interventions are needed.
January 27, 2015
Adaptive interventions help guide clinicians in their decisions concerning when and how treatments should be altered, but developing empirically based adaptations requires gathering the right kind of data. The sequential, multiple assignment, randomized trial is a recent innovation that can provide high-quality, experimental data for developing adaptive interventions. Recently, a group of autism researchers published the results of their SMART study in the article “Communication interventions for minimally verbal children with autism: A sequential, multiple assignment, randomized trial,” which appears in the Journal of the American Academy of Child and Adolescent Psychiatry, a top journal in child and adolescent mental health. The authors, led by Connie Kasari of UCLA, designed a project to improve spoken communication for children with autism who are minimally verbal. The study’s results show the benefit of integrating speech-generating devices (SGD) as a part of language development interventions and the potential of SMART designs for developing adaptive interventions.