ArticleJMIR cardio
The Atrial Fibrillation Health Literacy Information Technology System: Pilot Assessment.
Article in JMIR cardio. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03093558 (Pilot Atrial Fibrillation Information Technology Trial), which is not on this map. Cited by 26 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Pilot Atrial Fibrillation Information Technology Trial
Who cites it
26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 52 citations in OpenAlex.
- Engagement With Conversational Agent-Enabled Interventions in Cardiometabolic Disease Self-Management: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- Considering User Experience and Behavioral Approaches in the Design of mHealth Interventions for Atrial Fibrillation: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Computer-Controlled Virtual Humans in Patient-Facing Systems: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2020Pooled it
- The mobile health intervention for rural patients with atrial fibrillation a randomized controlled trial.International journal of cardiology · 2025Trial
- Patient Perspectives on Conversational Artificial Intelligence for Atrial Fibrillation Self-Management: Qualitative Analysis.Journal of medical Internet research · 2025Trial
- Mapping behavior change techniques and health data combinations in virtual agents for chronic condition management: A systematic scoping review.PLOS digital health · 2026Article
- Effectiveness of virtual nurse interventions in chronic disease self-management: a systematic review of randomized controlled trials.BMC nursing · 2026Article
- Future Patient-Telerehabilitation of Patients With Atrial Fibrillation: Protocol for a Multicenter, Mixed Methods, Randomized Controlled Trial.JMIR research protocols · 2025Article
- Engagement With Conversational Agent-Enabled Interventions in Cardiometabolic Disease Management: Protocol for a Systematic Review.JMIR research protocols · 2024Article
- Atrial fibrillation: epidemiology, screening and digital health.The Lancet regional health. Europe · 2024Review
- Embodied Conversational Agents for Chronic Diseases: Scoping Review.Journal of medical Internet research · 2024Article
- RACares: a conceptual design to guide mHealth relational agent development based on a systematic review.mHealth · 2024Review
- Factors Influencing the Acceptability, Acceptance, and Adoption of Conversational Agents in Health Care: Integrative Review.Journal of medical Internet research · 2023Review
- Conversational Agents in Health Care: Scoping Review of Their Behavior Change Techniques and Underpinning Theory.Journal of medical Internet research · 2022Article
- Design and rationale of the mobile health intervention for rural atrial fibrillation.American heart journal · 2022Article
- Article
- Web-Based Information Seeking Behaviors of Low-Literacy Hispanic Survivors of Breast Cancer: Observational Pilot Study.JMIR formative research · 2021Article
- Rurality and atrial fibrillation: a pathway to virtual engagement and clinical trial recruitment in response to COVID-19.American heart journal plus : cardiology research and practice · 2021Article
- The Combined Effects of Patient Activation and Relational Aspects on the Quality of Life in Atrial Fibrillation Patients.Frontiers in psychology · 2021Article
- Self-Reported Mobile Health-Based Risk Factor and CHAFrontiers in cardiovascular medicine · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundAtrial fibrillation (AF) is a highly prevalent heart rhythm condition that has significant associated morbidity and requires chronic treatment. Mobile health (mHealth) technologies have the potential to enhance multiple aspects of AF care, including education, monitoring of symptoms, and encouraging and tracking medication adherence. We have previously implemented and tested relational agents to improve outcomes in chronic disease and sought to develop a smartphone-based relational agent for improving patient-centered outcomes in AF.
objectiveThe objective of this study was to pilot a smartphone-based relational agent as preparation for a randomized clinical trial, the Atrial Fibrillation Health Literacy Information Technology Trial (AF-LITT).
methodsWe developed the relational agent for use by a smartphone consistent with our prior approaches. We programmed the relational agent as a computer-animated agent to simulate a face-to-face conversation and to serve as a health counselor or coach specific to AF. Relational agent's dialogue content, informed by a review of literature, focused on patient-centered domains and qualitative interviews with patients with AF, encompassed AF education, common symptoms, adherence challenges, and patient activation. We established that the content was accessible to individuals with limited health or computer literacy. Relational agent content coordinated with use of the smartphone AliveCor Kardia heart rate and rhythm monitor. Participants (N=31) were recruited as a convenience cohort from ambulatory clinical sites and instructed to use the relational agent and Kardia for 30 days. We collected demographic, social, and clinical characteristics and conducted baseline and 30-day assessments of health-related quality of life (HRQoL) with the Atrial Fibrillation Effect on Quality of life (AFEQT) measure; self-reported medication adherence with the Morisky 8-item Medication Adherence Scale (MMAS-8); and patient activation with the Patient Activation Measure (PAM).
resultsParticipants (mean age 68 [SD 11]; 39% [12/31] women) used the relational agent for an average 17.8 (SD 10.0) days. The mean number of independent log-ins was 19.6 (SD 10.7), with a median of 20 times over 30 days. The mean number of Kardia uses was 26.5 (SD 5.9), and participants using Kardia were in AF for 14.3 (SD 11.0) days. AFEQT scores improved significantly from 64.5 (SD 22.9) at baseline to 76.3 (SD 19.4) units at 30 days (
conclusionsWe piloted a 30-day smartphone-based intervention that combined a relational agent with dedicated content for AF alongside Kardia heart rate and rhythm monitoring. Pilot participants had favorable improvements in HRQoL and self-reported medication adherence, as well as positive responses to the intervention. These data will guide a larger, enhanced randomized trial implementing the smartphone relational agent and the Kardia monitor system.
Indexed as
Identifiers
What OpenQuestion holds
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.