ArticleProceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies2020
Personalized HeartSteps: A Reinforcement Learning Algorithm for Optimizing Physical Activity.
Article in Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
74 citing papers in PubMed, 1 synthesis or guideline pooled it.
- AI-Driven Mental Health Support for Caregivers of Individuals With Alzheimer Disease: Systematic Literature Review and Development of a Conceptual Framework.JMIR mental health · 2026Pooled it
- Characteristics of Tailored Text Messages Associated With Increased Physical Activity Among Cardiac Rehabilitation Enrollees: Secondary Analysis of a Microrandomized Trial.JMIR mHealth and uHealth · 2026Trial
- Pilot microrandomized trial of a brief digital intervention for suicidal thoughts.Journal of consulting and clinical psychology · 2025Trial
- Text Messages to Promote Physical Activity in Patients With Cardiovascular Disease: A Micro-Randomized Trial of a Just-In-Time Adaptive Intervention.Circulation. Cardiovascular quality and outcomes · 2024Trial
- Just-in-Time Adaptive Intervention for Stabilizing Sleep Hours of Japanese Workers: Microrandomized Trial.Journal of medical Internet research · 2024Trial
- Acceptability of a Text Message-Based Mobile Health Intervention to Promote Physical Activity in Cardiac Rehabilitation Enrollees: A Qualitative Substudy of Participant Perspectives.Journal of the American Heart Association · 2024Trial
- How Notifications Affect Engagement With a Behavior Change App: Results From a Micro-Randomized Trial.JMIR mHealth and uHealth · 2023Trial
- A bibliometric analysis of research on the application of just-in-time adaptive interventions in mental health.Medicine · 2026Review
- Tailoring in eHealth lifestyle interventions targeting people with cardiometabolic conditions and lower socioeconomic position: A scoping review.PLOS digital health · 2026Article
- Offline Reinforcement Learning for Adaptive Support in AI-Assisted Decision-Making.ACM transactions on computer-human interaction : a publication of the Association for Computing Machinery · 2026Article
- Practical considerations when designing an online learning algorithm for an app-based mHealth intervention.Contemporary clinical trials · 2026Article
- Off by a beat: the effects of temporal misalignment in reinforcement learning for sepsis treatment.NPJ digital medicine · 2026Article
- Effective monitoring of online AI decision-making algorithms in just-in-time adaptive interventions.NPJ digital medicine · 2026Article
- Understanding the impact of perceived app usability on the efficacy of mobile health intervention for traumatic brain injury caregivers.Rehabilitation psychology · 2026Article
- Personalized Glucose Management With AI: Pilot Study Using a Multiarmed Bandit Approach.JMIR formative research · 2026Article
- Digital Twins for Just-in-Time Adaptive Interventions (JITAIs): Framework for Optimizing and Continually Improving JITAIs.Journal of medical Internet research · 2026Article
- A just-in-time adaptive mobile application intervention to reduce sodium intake and blood pressure in patients with hypertension: Rationale and design of the LowSalt4Life 2 trial.American heart journal · 2026Article
- Optimization of academic performance and mental health in college students through an AI-driven personalized physical exercise and mindfulness intervention system.Scientific reports · 2026Article
- WMRE2030: integrating wearable devices, multi-omics, and artificial intelligence-driven real-time feedback into a daily-scale closed-loop framework for a new era of precision exercise.Frontiers in physiology · 2026Review
- A digital twin-based comparative reinforcement learning framework for personalized behavioral recommendation.Frontiers in artificial intelligence · 2026Article
14 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
With the recent proliferation of mobile health technologies, health scientists are increasingly interested in developing just-in-time adaptive interventions (JITAIs), typically delivered via notifications on mobile devices and designed to help users prevent negative health outcomes and to promote the adoption and maintenance of healthy behaviors. A JITAI involves a sequence of decision rules (i.e., treatment policies) that take the user's current context as input and specify whether and what type of intervention should be provided at the moment. In this work, we describe a reinforcement learning (RL) algorithm that continuously learns and improves the treatment policy embedded in the JITAI as data is being collected from the user. This work is motivated by our collaboration on designing an RL algorithm for HeartSteps V2 based on data collected HeartSteps V1. HeartSteps is a physical activity mobile health application. The RL algorithm developed in this work is being used in HeartSteps V2 to decide, five times per day, whether to deliver a context-tailored activity suggestion.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.