Micro-Randomized Trials (MRTs)

In micro-randomized trials, individuals are randomized hundreds or thousands of times over the course of the study. The goal of these trials is to optimize mobile health interventions by assessing the effect of intervention components and assessing whether the intervention component effects vary with time or the individuals current context. Through MRTs we can gather data to build optimized JITAIs.

JITAIs can include either or both engagement treatments and therapeutic treatments. The Heartsteps MRT is designed to promote physical activity among sedentary people. Heartsteps includes phone notifications that encourage physical activity; these are therapeutic in focus. The SARA MRT is designed to promote engagement by young adults in substance abuse research. SARA includes rewards for participants who complete assessments; these are engagement in focus. The design of both of these projects can be seen in the “Projects Using MRTs” section, below.

Over the course of the intervention, each participant may be randomized hundreds or thousands of times.

In the Heartsteps project, Methodology Center researchers are developing an app that encourages physical activity among people with a heart condition. The app displays messages on participants’ smartphones, and the messages encourage participants to engage in activity. The researchers identified five times throughout the day when people are mostly likely to be available to exercise, and one goal of the study is to determine which prompts work best at which times and under what circumstances. At each of the five time points, the application randomly decides to prompt or not prompt each participant to become active; over the course of the intervention, each participant is randomized hundreds or thousands of times. This sequence of both within-participant and between-participant randomizations comprises the MRT.

The resulting data is used to assess the effectiveness of the prompts and to build rules for when to prompt participants to become active.

The application also records outcomes. In this case, the app tracks whether or not the participant’s activity-tracking wristband detects physical activity by the participant in hour following randomization, the participant’s overall level of physical activity, and the participant’s context during each randomization (using GPS to determine the person’s location and the local weather). The resulting data is used by researchers to assess the effectiveness of the prompts and to build rules for when to prompt and not to prompt participants to become active. In other MRTs, the randomization could apply to what type of intervention to provide, rather than whether or not to provide a prompt. The ultimate goal of Heartsteps is the development of a JITAI that will successfully encourage higher levels of physical activity among this at-risk population. The study design of the MRT used in Heartsteps is shown below.

MRTs are an emergent innovation in behavioral science. Below are designs of MRTs that are being used to build JITAIs that address a range of health problems from obesity to opioid use.

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Boruvka, A., Almirall, D., Witkiewitz, K., Murphy, S. A. Assessing time-varying causal effect moderation in mobile health, to appear in the Journal of the American Statistical Association. Accepted author version posted online: 31 Mar 2017 http://dx.doi.org/10.1080/01621459.2017.1305274. NIHMS id: 909258.

Klasnja, P., Hekler, E.B., Shiffman, S., Boruvka, A., Almirall, D., Tewari, A. and Murphy, S. A. (2015). Micro-randomized trials: An experimental design for developing just-in-time adaptive interventions, Health Psychology. Vol 34(Suppl):1220-1228. doi: 10.1037/hea0000305. PubMed PMID: 26651463; PubMed Central PMCID: PMC4732571

Nahum-Shani, I., Smith, S. N. Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (in press). Just-in-time adaptive interventions (JITAIs) in mobile health: Key components and design principles for ongoing health behavior support. To appear in Annals of Behavioral Medicine. doi:10.1007/s12160-016-9830-8, PMCID: PMC5364076

Smith, S. S., Lee, A.J., Hall, K., Seewald, N.J., Boruvka, A., Murphy, S. A. and Klasnja, P., Design lessons from a micro-randomized pilot study in mobile health, (2017) Mobile Health Sensors, Analytic Methods, and Applications, Springer International Publishing AG 2017, J.M. Rehg et al. (eds.), DOI 10.1007/978-3-319-51394-2_4, pgs. 59-82.



Projects Using MRTs

Below are several examples of MRTs that illustrate the different design possibilities and questions that an MRT can answer.


This project tests the feasibility and effectiveness of providing, via a smartphone, just-in-time tailored physical activity suggestions as well as evening prompts to plan the following day’s physical activity so as to help sedentary individuals increase their activity. The resulting data will be used to inform the development of a JITAI for increasing physical activity.


This project tests the feasibility of conducting an MRT aiming to investigate whether real-time sensor-based assessments of stress are useful in optimizing the provision of just-in-time prompts to support stress-management in chronic smokers attempting to quit. The resulting data will be used to inform the development of a JITAI for smoking cessation.

  • PI: Santosh Kumar, Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K, https://md2k.org)
  • Location: Northwestern University, Bonnie Spring, (site P.I.)
  • Funding: NIBIB through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative (www.bd2k.nih.gov). U54EB020404


Substance Abuse Research Assistance (SARA)

The Substance Abuse Research Assistance (SARA) is an app for gathering data about substance use in high-risk populations. App developers are using an MRT to improve engagement with completion of the self-report data collection measures. At the time this summary was written, this MRT is unique in that it has an engagement component, but not a treatment one.

  • PIs: Maureen Walton, Susan Murphy, and Mashfiqui Rabbi Shuvo
  • Location: Harvard University and University of Michigan
  • Funding: Michigan Institute for Data Science (PI S. Murphy), the University of Michigan Injury Center (PI M. Walton), NIDA P50 DA039838 (PI Linda Collins), NIAAA R01 AA023187 (PI S. Murphy), CDC R49 CE002099 (PI: M. Walton)


BariFit MRT

Researchers are conducting this quality-improvement MRT aiming to promote weight maintenance through increased activity and improved diet among people who received bariatric surgery. At the time it was developed, this project was novel in that it implemented separate randomizations at the start of the study, on a daily basis, and five times throughout the day.

  • PI: Pedja Klasna
  • Location & Funding: Kaiser Permanente


MRT to Optimize mHealth Messaging for Weight-Loss Support

The current study seeks to investigate whether, what type, and under what conditions prompts should be provided in the context of a weight-loss program that uses a mobile app as minimal support for obese/overweight adults.

  • PIs: Bonnie Spring and Inbal “Billie” Nahum-Shani
  • Location: Northwestern University
  • Funding: R01 DK108678​


MRT to Promote Engagement with Purpose-Driven Well-Being App

JOOL is a behavioral health and well‐being app that is designed to help people monitor and improve their sleep, presence, activity, creativity, and eating, with the ultimate goal of helping people move closer to fulfilling their life’s purpose. This MRT aims to understand whether push notifications of tailored health messages are useful in promoting engagement with the JOOL app; and, if so, when and under what circumstances they are most effective.

Smartphone Addiction Recovery Coach (SARC) MRT

The smartphone addiction recovery coach (SARC) project tests the feasibility and effectiveness of providing, via smartphone, messages designed to encourage use of the ecological momentary interventions (EMIs) to support young adults enrolled in an outpatient substance-use program as they recover from disordered substance use.

  • PI: Michael Dennis
  • Location: Chestnut Health Systems
  • Funding: NIDA award DA011323