20 citations · 39 across the 6 of their papers we have counts for
12 papers
IntelligentPooling: Practical Thompson Sampling for mHealth
Sabina Tomkins, Peng Liao, Predrag Klasnja +1
In mobile health (mHealth) smart devices deliver behavioral treatments repeatedly over time to a user with the goal of helping the user adopt and maintain healthy behaviors. Reinfo…
The Micro-Randomized Trial for Developing Digital Interventions: Experimental Design Considerations
Ashley E. Walton, Linda M. Collins, Predrag Klasnja +4
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 ev…
The Micro-Randomized Trial for Developing Digital Interventions: Data Analysis Methods
Tianchen Qian, Michael A. Russell, Linda M. Collins +4
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, da…
Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data
Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Li +11
Mobile health (mHealth) applications are a powerful medium for providing behavioral interventions, and systematic reviews suggest that theory-based interventions are more effective…
Rapidly Personalizing Mobile Health Treatment Policies with Limited Data
Sabina Tomkins, Peng Liao, Predrag Klasnja +2
In mobile health (mHealth), reinforcement learning algorithms that adapt to one's context without learning personalized policies might fail to distinguish between the needs of indi…
Off-Policy Estimation of Long-Term Average Outcomes with Applications to Mobile Health
Peng Liao, Predrag Klasnja, Susan Murphy
Due to the recent advancements in wearables and sensing technology, health scientists are increasingly developing mobile health (mHealth) interventions. In mHealth interventions, m…