Workshop: "Introduction to Adaptive and Just-In-Time Adaptive Interventions in Mobile Health: Theoretical, Practical and Methodological Considerations"

December 5-6, 2018

Workshop leaders

Prof. Dr. Billie (Inbal) Nahum-Shani, d3lab (www.d3lab-isr.com), University of Michigan  Prof. Dr. Shawna Smith, d3lab (www.d3lab-isr.com), University of Michigan.

 

Organization

Prof. Dr. Mathias Allemand, Department of Psychology & URPP “Dynamics of Healthy Aging” Dr. Marion Landis, Management Doctorates, Department of Psychology URPP “Dynamics of Healthy Aging”

 

Content

An adaptive intervention (AI) is an intervention design that seeks to address not only the unique, but also the changing needs of individuals as they progress through an intervention. AIs are intended to guide the efforts by therapists, teachers, and other clinical and/or academic staff to provide individualized intervention to individuals in practice. A Just-in-time Adaptive Intervention (JITAI) is a special form of an adaptive intervention that often capitalizes on advances in wireless and mobile devices to address the rapidly changing needs of individuals. In recent years there has been increased interest in developing empirically-informed AIs and JITAIs to address a wide range of behavioral health issues, including depression, anxiety, alcohol use, substence use and sedentary lifestyles. These intervention approaches play an important role in various domains of psychology, including clinical, educational, organizational and health psychology. The goal of this workshop is to provide an introduction to AIs and JITAIs, and discuss novel experimental approaches for optimizing these interventions.
 
Day 1.  Adaptive Interventions (AIs)

1. Introduction to AIs: Scholars will gain understanding of the nature and utility of AIs 

2. Experimental Designs for Evaluating and Optimizing AIs:  Scholars will become familiar with various experimental designs for evaluating and optimizing AIs, including the sequential multiple assignment randomized trial (SMART) design

3. Case Studies: Scholars will learn about the various ways in which a SMART can be used to optimize AIs in various fields

4. Data Analytics: Scholars will learn how to apply data analytic strategies for common primary and secondary aims in a SMART
 
Day 2. Just-in-Time Adaptive Interventions (JITAIs)

1. Introduction to JITAIs: Scholars will gain understanding of the nature and utility of JITAIs

2. Experimental Designs for Evaluating and Optimizing JITAIs:  Scholars will become familiar with Micro-Randomized Trial (MRT) designs for optimizing JITAIs. 

3. Data Analytics: Scholars will learn how to apply data analytic strategies for common primary and secondary aims in a MRT

4. Case Studies: Scholars will learn about the various ways in which a MRT can be used to optimize JITAIs in various fields