Abstract
INTRODUCTION: Stroke, a major global cause of death and disability, has a high recurrence rate that significantly affects patients' physical, psychological, and economic well-being. Despite the importance of health risk perception in preventive measures, most stroke patients struggle to accurately assess the risk of recurrence. Current research on stroke recurrence risk perception is still exploratory, with a lack of systematic understanding of the influencing factors. This study aims to comprehensively analyze the current state of stroke recurrence research and the factors that influenced recurrence and assess the effectiveness and limitations of various assessment tools to guide future research and intervention strategies. METHODS AND ANALYSIS: This scoping review will follow Arksey and O'Malley's methodological framework as well as the updated scoping review methodology guidance by the Joanna Briggs Institute (JBI). Review results will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The search strategy will be developed via keywords, such as stroke, recurrence risk perception, and influencing factors. We will systematically search seven English databases, PubMed, CINAHL, Web of Science, Embase, Cochrane Library, PsycInfo, and MEDLINE, as well as four Chinese databases, CNKI, Wanfang, VIP, and the China National Knowledge Infrastructure for Biomedical Literature. Studies published in both English and Chinese will be included. Data will be extracted via a standardized form and summarized through quantitative (frequency) and qualitative analyses (narrative synthesis). Furthermore, the findings will be reported. ETHICS AND DISSEMINATION: Since this review involves collecting data from existing literature and does not involve human participants, ethical approval is not required. Research findings will be disseminated through conference presentations and publications in peer-reviewed journals. REGISTRATION DETAILS: This protocol has been registered on the Open Science Framework (OSF). Relevant materials and potential following updates are available at https://osf.io/7kq5t.