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Guest Lecture by Shawna N. Smith on August 23


We are happy to announce that Shawna N. Smith, Research Assistant Professor at Medical School (Psychiatry and Internal Medicine), University of Michigan, will give a guest lecture entitled How to Design and Evaluate Just-in-Time Adaptive Interventions (JITAIs) using Microrandomized Trials at ETH Zürich on August 23, 2017.

  • Location: ETH Zurich, WEV Building, Weinbergstrasse 56/58, 8092 Zürich, Room F109-111
  • Date: Wednesday, August 23, 2017
  • Time: 15:00 – 16:30

About Shawna N. Smith
Shawna N. Smith, PhD, is a sociologist and methodologist interested in improving population health through optimizing and expanding delivery of behavioral healthcare services and interventions. Much of her work focuses on improving access to behavioral health evidence-based practices in community-based settings and physical healthcare spaces. As Research Assistant Professor at the University of Michigan Medical School (Departments of Psychiatry & Internal Medicine), she currently works on four NIH funded projects aimed at improving population health by increasing access to physical activity, collaborative care and cognitive behavioral therapy interventions through new delivery modalities and implementation strategies. Methodologically, her work employs microrandomized trials (MRT) and cluster-randomized sequential multiple-assignment randomized trial (SMART) designs to evaluate contextual moderation, comparative effectiveness, and optimal treatment delivery and intervention support.
About the Guest Lecture
Mobile technologies are increasingly being used to deliver health and behavior change-related (mHealth) interventions. By combining opportunities for real-time, in situ intervention delivery with (frequently passive) streams of intensive data collection, researchers are now able to develop and optimize just-in-time adaptive interventions (JITAIs). JITAIs are mHealth interventions that use decision rules to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors over the long-term.
This talk will describe the key elements of a JITAI, and also present one experimental design method for optimizing JITAIs, the microrandomized trial (MRT). In MRTs, participants are sequentially randomized to receive intervention components at multiple decision points throughout study conduct, with the result that each participant may be randomized hundreds or thousands of times over the course of a study. As such, MRTs enable modeling of causal treatment effects and time-varying effect moderation for individual intervention components on proximal outcomes of interest within a JITAI. Examples and results from the six-week HeartSteps study, an MRT designed to inform a JITAI for increasing physical activity, will be used to illustrate MRT design, analyses and potential further work relevant to JITAI optimization.