ArticleHeart rhythm O22026
Mobile applications for atrial fibrillation self-management: A systematic search and evaluation.
Article in Heart rhythm O2, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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6 authors.
Funding
Abstract
Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia, increasing the risk of stroke, heart failure, and healthcare costs. Although patient self-management can improve outcomes, sustaining long-term engagement is difficult. Mobile health applications may help address this gap, but their quality and clinical alignment have not been systematically assessed using a validated framework. Objective: This study aimed to systematically identify and evaluate AF self-management applications using the Mobile Application Rating Scale (MARS) and to assess how well these apps align with evidence-based practices for AF. Methods: We conducted a structured search of the Apple App Store and Google Play Store (June 2024, updated January 2025) for English-language, patient-focused apps supporting AF self-management (eg, symptom logging, medication reminders, and educational content). Eligible apps offered ≥1 self-management feature and either explicitly referenced AF or, for general self-management apps, provided features directly applicable to AF self-care. 2 reviewers independently rated app quality using the MARS across 4 domains (Engagement, Functionality, Aesthetics, and Information). Results: Of the 455 apps identified, 5 met all inclusion criteria. Common features included symptom tracking and medication logging, but coverage of guideline-recommended care domains varied. Mean MARS scores ranged from 4.07 to 4.53 (out of 5). Higher-performing apps excelled in functionality and information quality but often lacked features such as stroke-risk assessment and personalized feedback. Conclusion: Current AF self-management apps show high MARS quality but lack comprehensive, clinically grounded functionality, highlighting a gap in digital tools for AF self-care. Improved codesign processes and standardized evaluation frameworks may guide development of more effective apps.
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