ArticleAnnals of behavioral medicine : a publication of the Society of Behavioral Medicine2015
The potential impact of intelligent systems for mobile health self-management support: Monte Carlo simulations of text message support for medication adherence.
Article in Annals of behavioral medicine : a publication of the Society of Behavioral Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Reinforcement learning for proposing smoking cessation activities that build competencies: Combining two worldviews in a virtual coach.BMC medical informatics and decision making · 2025Trial
- Artificial Intelligence for Clinical Decision Support in Rural Spine Care: A Narrative Review.Healthcare (Basel, Switzerland) · 2026Review
- Artificial intelligence and machine learning in spine care: Advancing precision diagnosis, treatment, and rehabilitation.World journal of orthopedics · 2025Review
- The impact of using reinforcement learning to personalize communication on medication adherence: findings from the REINFORCE trial.NPJ digital medicine · 2024Article
- An Automatically Adaptive Digital Health Intervention to Decrease Opioid-Related Risk While Conserving Counselor Time: Quantitative Analysis of Treatment Decisions Based on Artificial Intelligence and Patient-Reported Risk Measures.Journal of medical Internet research · 2023Article
- Adaptive learning algorithms to optimize mobile applications for behavioral health: guidelines for design decisions.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Preferences for mHealth Technology and Text Messaging Communication in Patients With Type 2 Diabetes: Qualitative Interview Study.Journal of medical Internet research · 2021Article
- Can the artificial intelligence technique of reinforcement learning use continuously-monitored digital data to optimize treatment for weight loss?Journal of behavioral medicine · 2019Article
- The Impact of the mKidney mHealth System on Live Donor Follow-Up Compliance: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2019Article
- Beyond Adherence Thresholds: A Simulation Study of the Optimal Classification of Longitudinal Adherence Trajectories From Medication Refill Histories.Frontiers in pharmacology · 2019Article
- Assessing the Attitudes and Perceptions Regarding the Use of Mobile Health Technologies for Living Kidney Donor Follow-Up: Survey Study.JMIR mHealth and uHealth · 2018Article
- Mobile Phone Support for Diabetes Self-Care Among Diverse Adults: Protocol for a Three-Arm Randomized Controlled Trial.JMIR research protocols · 2018Article
- Mobile Health Devices as Tools for Worldwide Cardiovascular Risk Reduction and Disease Management.Circulation · 2015Article
- Personal health technology: A new era in cardiovascular disease prevention.Postgraduate medicine · 2015Review
- Understanding patients' health and technology attitudes for tailoring self-management interventions.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2015Article
- Confirming the theoretical structure of expert-developed text messages to improve adherence to anti-hypertensive medications.Research in social & administrative pharmacy : RSAPArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundMobile health (mHealth) services cannot easily adapt to users' unique needs. PURPOSE: We used simulations of text messaging (SMS) for improving medication adherence to demonstrate benefits of interventions using reinforcement learning (RL).
methodsWe used Monte Carlo simulations to estimate the relative impact of an intervention using RL to adapt SMS adherence support messages in order to more effectively address each non-adherent patient's adherence barriers, e.g., forgetfulness versus side effect concerns. SMS messages were assumed to improve adherence only when they matched the barriers for that patient. Baseline adherence and the impact of matching messages were estimated from literature review. RL-SMS was compared in common scenarios to simple reminders, random messages, and standard tailoring.
resultsRL could produce a 5-14% absolute improvement in adherence compared to current approaches. When adherence barriers are not accurately reported, RL can recognize which barriers are relevant for which patients. When barriers change, RL can adjust message targeting. RL can detect when messages are sent too frequently causing burnout.
conclusionsRL systems could make mHealth services more effective.
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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.