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Integrating a Mobile App to Enhance Atrial Fibrillation Care: Key Insights From an Implementation Study Guided by the Consolidated Framework for Implementation Research

Integrating a Mobile App to Enhance Atrial Fibrillation Care: Key Insights From an Implementation Study Guided by the Consolidated Framework for Implementation Research

Identifying and managing risk factors are Class I (evidence or general agreement that a treatment or procedure is beneficial and effective) and Level B (data derived from a single randomized clinical trial or large nonrandomized studies) recommendations in atrial fibrillation clinical practice guidelines [29,30]. Patients scheduled for catheter ablation are introduced to the app by clinicians near the procedure date. Interested patients receive email instructions for downloading and signing up.

Sumudu Hewage, Sanjeewa Kularatna, William Parsonage, Tomos Walters, Steven McPhail, David Brain, Michelle J Allen

J Med Internet Res 2025;27:e66815

Preferences for Mobile App Features to Support People Living With Chronic Heart Diseases: Discrete Choice Study

Preferences for Mobile App Features to Support People Living With Chronic Heart Diseases: Discrete Choice Study

In this unlabeled experiment, the alternatives were referred to as mobile app A and B. Following best practice recommendations in health DCEs, respondents were allowed to opt out if the presented combinations of attribute levels for either app did not align with their preferences [16,34].

Sumudu Avanthi Hewage, Sameera Senanayake, David Brain, Michelle J Allen, Steven M McPhail, William Parsonage, Tomos Walters, Sanjeewa Kularatna

JMIR Mhealth Uhealth 2025;13:e58556

The Comprehensive Adaptive Multisite Prevention of University Student Suicide Trial: Protocol for a Randomized Controlled Trial

The Comprehensive Adaptive Multisite Prevention of University Student Suicide Trial: Protocol for a Randomized Controlled Trial

The primary goal of aim 1 is to identify the most effective ATS among the 4 embedded strategies (A+B, A+C, D+E, or D+F, as shown in Table 2) that leads to the greatest reduction in STB. This aim focuses on finding the best-performing ATS rather than testing a hypothesis. The sample size of 480 was found to ensure an 80% probability of correctly identifying the ATS with the lowest mean outcome, assuming that such a strategy exists.

Kyla Blalock, Jacqueline Pistorello, Shireen L Rizvi, John R Seeley, Francesca Kassing, James Sinclair, Linda A Oshin, Robert J Gallop, Cassidy M Fry, Ted Snyderman, David A Jobes, Jennifer Crumlish, Hannah R Krall, Susan Stadelman, Filiz Gözenman-Sapin, Kate Davies, David Steele, David B Goldston, Scott N Compton

JMIR Res Protoc 2025;14:e68441