Team members

Susan Murphy (Harvard)
James M. Rehg (Georgia Tech)
Inbal Nahum-Shani (Michigan)
Mustafa al'Absi (Minnesota)
Santosh Kumar (Memphis)
Gregory Abowd (Georgia Tech)
Ida Sim (UC-San Francisco)
Bonnie Spring (Northwestern)

Peng Liao (Michigan)
Walter Dempsey (Harvard)

Just-in-Time-Adaptive Interventions


Just-in-Time Adaptive Interventions (JITAIs) are mHealth technologies that aim to deliver the right intervention components at the right times and locations to optimally support individuals’ health behaviors.

These interventions are adapted to the dynamics of a person’s “emotional, social, physical and contextual state, so as to prevent negative outcomes and promote the adoption and maintenance of healthy behaviors.” [1]

JITAIs are designed to help people make the right decision “in the moment” so that they have an impact in the near future. Because the development of mHealth technologies is progressing at a faster pace than the science to evaluate their efficacy and validity, new methods need to be developed to test these technologies. mHealth researchers have been using a micro-randomized trial design to test the effects of JITAIs. [2]

MD2K software uses three apps for interventions: Mood Surfing and Thought Shakeup, developed internally, and Head Space, which is commercially available. Mood Surfing is to guide one's mind away from negative thoughts; Thought Shakeup is designed to help the user reframe negative thoughts that may contribute to stress, and Head Space offers modules that help regulate stress.


[1] Nahum-Shani, S., Smith, S. N., Tewari, A., Witkiewitz, K., Collins, L. M., Spring, B., & Murphy, S. A. (2014). Just-in-Time adaptive interventions (JITAIs): An organizing framework for ongoing health behavior support. (Technical Report No. 14-126). University Park, PA: The Methodology Center, Penn State.

[2] P. Liao; P. Klasnja; A. Tewari; S.A. Murphy: Micro-Randomized Trials in mHealth. In: Statistics in Medicine, 2015.





Copyright © 2018 MD2K. MD2K is supported by the National Institutes of Health Big Data to Knowledge Initiative (Grant #1U54EB020404)
Team: Cornell Tech, GA Tech, Harvard, U. Memphis, Northwestern, Ohio State, Open mHealth, UCLA, UCSD, UCSF, UMass, U. Michigan, Utah, WVU