Methodological lineages of concept analysis and mapping of reporting elements in nursing and health-related disciplines: A scoping review protocol

INTRODUCTION: Concept analysis is widely used in nursing and health-related disciplines to clarify ambiguous constructs, refine disciplinary language and support theory development, instrument construction, education and practice. However, concept analysis is methodologically plural rather than a single uniform method. Different approaches vary in their assumptions, data sources, analytic steps and expected outputs. AIMS: This scoping review will identify methodological lineages of concept analysis and map reporting elements across nursing and health-related disciplines. It will examine both the cross-lineage applicability and the empirical distribution of candidate reporting elements. METHODS: The review will follow Joanna Briggs Institute guidance for scoping reviews and will be reported according to the PRISMA extension for Scoping Reviews. Ten English- and Chinese-language databases will be searched from inception to the final search date, supplemented by targeted citation searching for foundational methodological sources. Two reviewers will independently screen records after calibration on a purposively enriched set of 25 records containing likely inclusions, likely exclusions and borderline records. Formal screening will begin after both overall raw agreement and positive agreement for the include/uncertain decision reach at least 75%; raw agreement and Cohen's kappa will be reported before consensus. Data will be charted using a piloted form and synthesised descriptively through deductive-inductive framework analysis. Reporting elements will be mapped by both methodological applicability and empirical distribution. CONCLUSION: The review will provide a structured account of concept analysis methods and reporting elements. It represents an evidence-mapping and candidate-item generation stage and will not itself produce a formal reporting guideline. The protocol is registered on the Open Science Framework: https://osf.io/xru7f.