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Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted such as weekly, daily, or even many times a day. This high intensity of adaptation is…

Human-Computer Interaction · Computer Science 2020-05-13 Ashley E. Walton , Linda M. Collins , Predrag Klasnja , Inbal Nahum-Shani , Mashfiqui Rabbi , Maureen A. Walton , Susan A. Murphy

Although there is much excitement surrounding the use of mobile and wearable technology for the purposes of delivering interventions as people go through their day-to-day lives, data analysis methods for constructing and optimizing digital…

There is a growing interest in leveraging the prevalence of mobile technology to improve health by delivering momentary, contextualized interventions to individuals' smartphones. A just-in-time adaptive intervention (JITAI) adjusts to an…

Other Statistics · Statistics 2018-12-31 Nicholas J. Seewald , Shawna N. Smith , Andy Jinseok Lee , Predrag Klasnja , Susan A. Murphy

Technological advancements in mobile devices have made it possible to deliver mobile health interventions to individuals. A novel intervention framework that emerges from such advancements is the just-in-time adaptive intervention (JITAI),…

Methodology · Statistics 2020-07-29 Jing Xu , Xiaoxi Yan , Caroline Figueroa , Joseph Jay Williams , Bibhas Chakraborty

Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention (JITAI), which aims to suggest the…

Methodology · Statistics 2023-07-10 Jing Xu , Xiaoxi Yan , Caroline Figueroa , Joseph Jay Williams , Bibhas Chakraborty

With the recent evolution of mobile health technologies, health scientists are increasingly interested in developing just-in-time adaptive interventions (JITAIs), typically delivered via notification on mobile device and designed to help…

Machine Learning · Computer Science 2019-09-10 Peng Liao , Kristjan Greenewald , Predrag Klasnja , Susan Murphy

Micro-randomized trials (MRTs) play a crucial role in optimizing digital interventions. In an MRT, each participant is sequentially randomized among treatment options hundreds of times. While the interventions tested in MRTs target…

Methodology · Statistics 2025-09-04 Tianchen Qian

Advances in wearables and digital technology now make it possible to deliver behavioral mobile health interventions to individuals in their everyday life. The micro-randomized trial (MRT) is increasingly used to provide data to inform the…

Methodology · Statistics 2020-07-30 Tianchen Qian , Hyesun Yoo , Predrag Klasnja , Daniel Almirall , Susan A. Murphy

Micro-randomized trials (MRTs) are widely used to assess the marginal and moderated effect of mobile health (mHealth) treatments delivered via mobile devices. In many applications, the mHealth treatments are categorical with multiple levels…

Methodology · Statistics 2025-04-23 Jeremy Lin , Tianchen Qian

We evaluated the viability of using Large Language Models (LLMs) to trigger and personalize content in Just-in-Time Adaptive Interventions (JITAIs) in digital health. As an interaction pattern representative of context-aware computing,…

The use of reinforcement learning (RL) to learn policies for just-in-time adaptive interventions (JITAIs) is of significant interest in many behavioral intervention domains including improving levels of physical activity. In a…

Machine Learning · Computer Science 2024-11-04 Karine Karine , Benjamin M. Marlin

Existing statistical methods for the analysis of micro-randomized trials (MRTs) are designed to estimate causal excursion effects using data from a single MRT. In practice, however, researchers can often find previous MRTs that employ…

Methodology · Statistics 2025-05-13 Easton Huch , Inbal Nahum-Shani , Lindsey Potter , Cho Lam , David W. Wetter , Walter Dempsey

Humans can play a more active role in improving their comfort in the built environment if given the right information at the right place and time. This paper outlines the use of Just-in-Time Adaptive Interventions (JITAI) implemented in the…

Human-Computer Interaction · Computer Science 2025-08-13 Clayton Miller , Yun Xuan Chua , Matias Quintana , Binyu Lei , Filip Biljecki , Mario Frei

Increasing technological sophistication and widespread use of smartphones and wearable devices provide opportunities for innovative and highly personalized health interventions. A Just-In-Time Adaptive Intervention (JITAI) uses real-time…

Machine Learning · Statistics 2022-04-26 Huitian Lei , Yangyi Lu , Ambuj Tewari , Susan A. Murphy

The micro-randomized trial (MRT) is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health (mHealth) intervention components that may be delivered at hundreds or thousands of decision points.…

Methodology · Statistics 2021-12-14 Jieru Shi , Zhenke Wu , Walter Dempsey

Construction of just-in-time adaptive interventions, such as prompts delivered by mobile apps to promote and maintain behavioral change, requires knowledge about time-varying moderated effects to inform when and how we deliver intervention…

Methodology · Statistics 2022-12-06 Jieru Shi , Zhenke Wu , Walter Dempsey

To optimize mobile health interventions and advance domain knowledge on intervention design, it is critical to understand how the intervention effect varies over time and with contextual information. This study aims to assess how a push…

Applications · Statistics 2024-10-22 Jiaxin Yu , Tianchen Qian

The micro-randomized trial (MRT) is a new experimental design which allows for the investigation of the proximal effects of a "just-in-time" treatment, often provided via a mobile device as part of a mobile health intervention. As with a…

Methodology · Statistics 2020-08-07 Nicholas J. Seewald , Ji Sun , Peng Liao

Micro-randomized trials (MRTs), which sequentially randomize participants at multiple decision times, have gained prominence in digital intervention development. These sequential randomizations are often subject to certain constraints. In…

Applications · Statistics 2025-01-07 Xiang Meng , Walter Dempsey , Peng Liao , Nick Reid , Pedja Klasnja , Susan Murphy

The use and development of mobile interventions are experiencing rapid growth. In "just-in-time" mobile interventions, treatments are provided via a mobile device and they are intended to help an individual make healthy decisions "in the…

Methodology · Statistics 2020-07-23 Peng Liao , Predrag Klasnja , Ambuj Tewari , Susan A. Murphy
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