ArticleCardiovascular digital health journal2022
Usability of a smartwatch for atrial fibrillation detection in older adults after stroke.
Article in Cardiovascular digital health journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 16 papers, 2 of them syntheses that pooled it.
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.
Smartwatch Monitoring for Atrial Fibrillation After Stroke
Smartwatches for Detection of Atrial Fibrillation (AFib) in Secondary Prevention of Cryptogenic Stroke - WATCH AFib A Prospective, Intraindividual-controlled, Multicenter Clinical Study
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Key stakeholder views on atrial fibrillation screening: a systematic mixed-studies review and interpretive analysis.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2026Pooled 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
- Perceptions of the use of smartwatches for the early detection of cardiac arrhythmias in Saudi Arabia: a cross-sectional study.BMC public health · 2026Article
- Article
- Trends in Mortality Related to Atrial Fibrillation and Dementia in Older Adults in the United States: A 2000-2020 Analysis.Journal of cardiovascular electrophysiology · 2025Article
- The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research.Journal of medical Internet research · 2024Review
- Attributes, Methods, and Frameworks Used to Evaluate Wearables and Their Companion mHealth Apps: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Health behavior outcomes in stroke survivors prescribed wearables for atrial fibrillation detection stratified by age.Journal of geriatric cardiology : JGC · 2024Article
- Atrial fibrillation: stroke prevention.The Lancet regional health. Europe · 2024Review
- Self-reported efficacy in patient-physician interaction in relation to anxiety, patient activation, and health-related quality of life among stroke survivors.Annals of medicine · 2023Article
- Accuracy, Usability, and Adherence of Smartwatches for Atrial Fibrillation Detection in Older Adults After Stroke: Randomized Controlled Trial.JMIR cardio · 2023Article
- Review
- Anxiety, patient activation, and quality of life among stroke survivors prescribed smartwatches for atrial fibrillation monitoring.Cardiovascular digital health journal · 2023Article
- A Smartwatch System for Continuous Monitoring of Atrial Fibrillation in Older Adults After Stroke or Transient Ischemic Attack: Application Design Study.JMIR cardio · 2023Article
- A smart devices based secondary prevention program for cerebrovascular disease patients.Frontiers in neurology · 2023Article
- Trends in Passive IoT Biomarker Monitoring and Machine Learning for Cardiovascular Disease Management in the U.S. Elderly Population.Advances in geriatric medicine and research · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 3 institutions in 1 country.
Funding
Abstract
Background: Smartwatches can be used for atrial fibrillation (AF) detection, but little is known about how older adults at risk for AF perceive their usability. Methods: We employed a mixed-methods study design using data from the ongoing Pulsewatch study, a randomized clinical trial (NCT03761394) examining the accuracy of a smartwatch-smartphone app dyad (Samsung/Android) compared to usual care with a patch monitor (Cardea SOLO™ ECG System) for detection of AF among older stroke survivors. To be eligible to participate in Pulsewatch, participants needed to be at least 50 years of age, have had an ischemic stroke, and have no major contraindications to anticoagulation therapy should AF be detected. After 14 days of use, usability was measured by the System Usability Scale (SUS) and investigator-generated questions. Qualitative interviews were conducted, transcribed, and coded via thematic analysis. Results: Ninety participants in the Pulsewatch trial were randomized to use a smartwatch-smartphone app dyad for 14 days (average age: 65 years, 41% female, 87% White), and 46% found it to be highly usable (SUS ≥68). In quantitative surveys, participants who used an assistive device (eg, wheelchair) and those with history of anxiety or depression were more likely to report anxiety associated with watch use. In qualitative interviews, study participants reported wanting a streamlined system that was more focused on rhythm monitoring and a smartwatch with a longer battery life. In-person training and support greatly improved their experience, and participants overwhelmingly preferred use of a smartwatch over traditional cardiac monitoring owing to its comfort, appearance, and convenience. Conclusion: Older adults at high risk for AF who were randomized to use a smartwatch-app dyad for AF monitoring over 14 days found it to be usable for AF detection and preferred their use to the use of a patch monitor. However, participants reported that a simpler device interface and longer smartwatch battery life would increase the system's usability.
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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.