The mHealthHub is a virtual forum where technologists, researchers and clinicians connect, learn, share, and innovate on mHealth tools to transform healthcare.

Tools & Datasets

Reach out or find us on Social Media.

365 Innovation Drive, Suite 335, Memphis, TN 38152

mHealthHUB@MD2K.org

Join our Community.

Stay up-to-date on the latest mHealth news and training.

Invalid email address
We promise not to spam you. You can unsubscribe at any time.

Harnessing the Just-in-Time-Adaptive Intervention (JITAI) Framework to Optimize Behavioral Obesity Treatments and Better Understand Weight-related Behaviors

Monday, October 28, 2024 – 1:00 pm CT

 

Stephanie Goldstein, PhD
Associate Professor (Research)
Brown University

About the Webinar:

Behavioral obesity treatments are frontline, non-surgical interventions for weight management that involve gradual change to lifestyle behaviors (primarily eating and exercise, but can also include other health behaviors and psychological well-being). Critically, these interventions remain highly recommended in conjunction with anti-obesity medications. Just-in-time adaptive interventions (JITAIs) can enhance the power and sustainability of behavioral obesity treatments by adapting the provision of support to an individual's changing needs and contexts, and also provide a means to begin conceptualizing the moment-to-moment dynamics influencing weight-related behaviors. The rigorous development of JITAIs are largely supported by a framework, proposed by Nahum-Shani and colleagues, that outlines the key components of a JITAI (e.g., decision points, tailoring variables, intervention options and decision rules) and how each component relates to one another.

This talk will illustrate how this broader framework can inform a research agenda to better understand weight and weight-related behaviors, as well as create innovative digital tools, like JITAIs, to improve behavioral obesity treatments. Projects highlighted will include: (1) using a micro-randomized trial to optimize a smartphone-based JITAI that uses machine learning to deliver preventative support when an individual is at risk for ‘slipping' from their dietary goals; (2) behavioral phenotyping of dietary non-adherence behaviors using data from digital health tools; and (3) conducting a large-scale validation of watch and ring sensors to detect and characterize eating.

 

About the Presenter:

Stephanie Goldstein, PhD, is an Assistant Professor (Research) at the Weight Control and Diabetes Research Center (WCDRC) of The Miriam Hospital and Alpert Medical School of Brown University.  She specializes in using EMA administered via mobile phone to study dietary lapses (i.e., discrete instances of dietary non-adherence) and using JITAI to intervene on them. More about Stephanie Goldstein.