• Corpus ID: 74138410

Micro-randomized trials & mHealth

@inproceedings{Liao2015MicrorandomizedT,
  title={Micro-randomized trials \& mHealth},
  author={Peng Liao and Predrag V. Klasnja and Ambuj Tewari and Susan A. Murphy},
  year={2015}
}
The use and development of mobile interventions is experiencing rapid growth. [] Key Method In a micro-randomized trial, treatments are sequentially randomized throughout the conduct of the study, with the result that each participant may be randomized at the 100s or 1000s of occasions at which a treatment might be provided. Further, we develop a test statistic for assessing the proximal effect of a treatment as well as an associated sample size calculator.

THE STRATIFIED MICRO-RANDOMIZED TRIAL DESIGN: SAMPLE SIZE CONSIDERATIONS FOR TESTING NESTED CAUSAL EFFECTS OF TIME-VARYING TREATMENTS

  • A.
  • Psychology
  • 2018
Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and

Micro-Randomized Trials : An Experimental Design for Developing Just-inTime Adaptive Interventions

Objective—This paper presents an experimental design, the micro-randomized trial, developed to support optimization of just-in-time adaptive interventions (JITAIs). JITAIs are mHealth technologies

THE STRATIFIED MICRO-RANDOMIZED TRIAL DESIGN: SAMPLE SIZE CONSIDERATIONS FOR TESTING NESTED CAUSAL EFFECTS OF TIME-VARYING TREATMENTS

  • A.
  • Psychology
  • 2019
Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and

THE STRATIFIED MICRO-RANDOMIZED TRIAL DESIGN: SAMPLE SIZE CONSIDERATIONS FOR TESTING NESTED CAUSAL EFFECTS OF TIME-VARYING TREATMENTS.

Assessing whether reminders, delivered at times of stress, result in a reduction/prevention of stress in the near-term, and whether this effect changes with time in study is discussed.

Assessing Time-Varying Causal Effect Moderation in Mobile Health

A formal definition for moderated effects in terms of potential outcomes is introduced, a definition that is particularly suited to mobile interventions, where treatment occasions are numerous, individuals are not always available for treatment, and potential moderators might be influenced by past treatment.

Optimizing Digital Integrated Care via Micro‐Randomized Trials

A new randomized trial design, the Micro‐Randomized Trial (MRT), is described for informing the development of mHealth interventions, and examples of scientific questions important to theDevelopment of an mHealth intervention are provided.

Illustrating idiographic methods for translation research: moderation effects, natural clinical experiments, and complex treatment-by-subgroup interactions

A critical juncture in translation research involves the preliminary studies of intervention tools, provider training programs, policies, and other mechanisms used to leverage knowledge garnered at

Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework.

A pragmatic framework is established that can be used to organize existing evidence into a useful model for JITAI construction and will help to guide the next generation of empirical work to support the creation of effective JITAIs.

Off-Policy Estimation of Long-Term Average Outcomes With Applications to Mobile Health

The measure of performance is the average of proximal outcomes over a long time period should the particular mHealth policy be followed, and an estimator as well as confidence intervals are provided.

Assessing Time-Varying Causal Effect Moderation in the Presence of Cluster-Level Treatment Effect Heterogeneity and Interference

The micro-randomized trial is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health (mHealth) intervention components that may be delivered at

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