Micro-Randomized Trials

In micro-randomized trials (MRTs), 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 relative effect of different intervention options and assessing whether the intervention effects vary with time or the individual's current context. With MRTs we can gather data to construct optimized just-in-time adaptive interventions (JITAIs).

Intervention options can include either or both engagement strategies and therapeutic treatments. Consider the Heartsteps MRT (described below) that is designed to promote physical activity among sedentary people. Heartsteps includes phone notifications with tailored activity suggestions to encourage physical activity; these are therapeutic in focus. On the other hand the SARA MRT (also described below) is designed to promote engagement by young adults in substance abuse research. SARA includes rewards for participants who complete assessments; these are engagement strategies. The design of both of these projects can be seen in the “Projects Using MRTs” section, below.

In an MRT, each participant can be randomized many times. For example in the Heartsteps project, the researchers identified five times throughout the day when people are mostly likely to be available to take a brief walk. At each of the five time points, the application randomizes between delivering a phone notification containing a tailored activity suggesion or to not deliver anything; as a result over the course of the 42 days, each participant is randomized 210 times. This sequence of both within-participant and between-participant randomizations comprises the MRT.

The MRT data can then be used to assess the effectiveness of the tailored activity suggestions and to build rules for when to deliver the suggestions in order to help individuals be more active. To do this the application records a variety of outcomes. In this case, the app collects the minute-by-minute step count from the participant’s activity-tracking wristband throughout the day, the participant’s overall level of physical activity, and the participant’s context at each of the 5 times per day (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 activity suggestions and to build rules for when and where to deliver the suggestions. In other MRTs, the randomization could apply to what type of intervention to provide, rather than whether or not to provide an intervention. The ultimate goal of Heartsteps is the development of a JITAI that will successfully encourage higher levels of physical activity. 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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MRT Sample Size Calculators can be found here.

Portions of this content and the related scientific research were funded by National Institute on Drug Abuse awards P50 DA039838 and P50 DA010075

MRT Webinars

Micro-randomized Trials, 1 & 1 Webinar sponsored by the Methodology Center, PSU, 2018

Analyzing Data from a Micro-randomized Trial, 1 & 1 Webinar sponsored by the Methodology Center, PSU, 2018

References

Boruvka, A., Almirall, D., Witkiewitz, K., Murphy, S. A. (2018). Assessing time-varying causal effect moderation in mobile health, Journal of the American Statistical Association. Accepted author version posted online: 31 Mar 2017 http://dx.doi.org/10.1080/01621459.2017.1305274. PMCID: PMC6241330.

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. (2018). Just-in-time adaptive interventions (JITAIs) in mobile health: Key components and design principles for ongoing health behavior support. Annals of Behavioral Medicine. May 18;52(6):446-462. 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.

Heartsteps

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.

Sense2Stop

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.

 

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.

 

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.

 

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.

 

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.

MRT to Improve EMA Engagement in Oral Chemotherapy Adherence for Adolescents and Young Adults

This study seeks to examine the time-varying, contextual factors that influence daily oral chemotherapy adherence in adolescents and young adults with leukemia.

MRT to Improve Oral Chemotherapy Adherence for Adolescents and Young Adults

This study employs an MRT to test different strategies for promoting adherence to oral chemotherapy in adolescents and young adults with leukemia. It delivers individually-tailored content, including messages targeting disease self-management and preferred app engagement strategies.