March 13, 2024, 1:30-3:30 p.m.

Society of Behavioral Medicine 2024 Annual Meeting

Description

Pre-Conference Course 13: Adaptive Interventions: Innovations in Intervention and Experimental Design

Among the challenges faced by scientists is how to design and implement interventions to achieve the greatest societal benefit. Adaptive interventions are intervention delivery frameworks that guide how dynamic information about a person should be used in practice to decide whether and how to intervene. The goal is to deliver the right type of intervention, at the right time, while minimizing the delivery of unnecessary treatment. For example, an adaptive intervention for promoting physical activity might start with a minimal intervention including a wearable device to monitor and provide feedback about physical activity. Then, physical activity adherence data from the wearable device are used monthly to decide whether to continue or step up with coaching calls. A mobile intervention to support smoking cessation, might collect data about the person’s stress every minute via wearable devices and use this data to decide whether or not to deliver a mobile-based message to promote tobacco abstinence. Advances in digital technologies, such as electronic health records, mobile devices, and wearable sensors, have created unprecedented opportunities to adapt interventions on different timescales (e.g., slow—every few months or weeks; and fast—every day, every few hours, or at the scale of minutes) and at multiple levels (e.g., at the patient level, the clinic level, and the health system level). Recent years have seen explosive growth in research to develop adaptive interventions across various domains of health. This growth was powered by the rapid development of experimental designs that enable investigators to answer important scientific questions about how to optimize (i.e., systematically develop effective and resource-efficient) various types of adaptive interventions. These novel designs, which were developed by our team, include the sequential multiple assignment randomized trial (SMART), the micro-randomized trial (MRT), the hybrid experimental design (HED) and the multilevel SMART. This course will provide an introduction to recent methodological advances for optimizing adaptive interventions. Specifically, we will introduce novel types of adaptive interventions that vary in terms of the timescale and level at which data is used to decide whether and how to intervene. We will also discuss new experimental designs for optimizing each type of adaptive intervention, including the SMART, MRT, HED and the multilevel SMART.

SBM student and transitional member attendees of this course may be reimbursed 100% of the course fee and other attendees may be reimbursed 75% of the course fee, pending grant underwriting from the National Institutes of Health Office of Disease Prevention.

Learn more at SBM.org

Presenters

Inbal Billie Nahum-Shani, PhD
Director, d3center
Professor, Institute for Social Research

Daniel Almirall, PhD
Co-director, d3center
Associate Professor
U-M Department of Statistics
Institute for Social Research

Kate Guastaferro, PhD
Associate Director, cadio
Assistant Professor,
Department of Social and Behavioral Sciences
School of Global Public Health
New York University