Conversational artificial intelligence HeAlth supporT in Atrial Fibrillation Self-Management (CHAT-AF-S): rationale and randomised controlled trial design

Introduction Atrial fibrillation (AF), a common arrhythmia, is associated with impaired quality of life and increased stroke risk and mortality. Clinical guidelines recommend leveraging digital technologies to support patient education and AF self-management. Conversational artificial intelligence (AI) technologies may support patient engagement with self-management by enabling human-like conversations. This study aims to evaluate the effectiveness of a conversational AI intervention (Conversational artificial intelligence HeAlth supporT in Atrial Fibrillation Self-Management (CHAT-AF-S)) in improving quality of life in patients with AF. Methods and analysis CHAT-AF-S is a 3-month randomised controlled trial with 1:1 allocation and embedded process evaluation. We will randomise 480 adults (aged 18 years and older) with documented AF to the CHAT-AF-S intervention or usual care. Primary outcome is the Atrial Fibrillation Effect on QualiTy-of-life overall score. We will follow the intention-to-treat principles and data analysts will be blinded. Intervention participants will be invited to complete a user experience survey and take part in an interview to explore the feasibility, acceptability, perceived use and barriers and enablers to implementing the intervention. Qualitative data will be analysed thematically. Ethics and dissemination Ethics approval was obtained from the Western Sydney Local Health District Human Ethics Research Committee (2023/ETH00765). Written and informed consent will be obtained from all study participants before commencing any study procedures. Results will be disseminated via peer-reviewed publications and presentations at international conferences. Trial registration number Australian New Zealand Clinical Trials Registry (registration number: ACTRN12623000850673).