Enhancing Transparency, Auditability, and Reproducibility of Deduplication in Systematic Reviews: Tutorial for the...

Deduplication across search results is one of the earliest and most critical steps in the systematic review methodological process; yet, existing solutions often lack the transparency, auditability, and reproducibility required by rigorous systematic review standards. Many automated deduplication tools introduce bias through opaque, nonconfigurable algorithmic decisions, while also potentially removing relevant references through false positive identification. We provide a tutorial on the Rayyan Method, including the Systematic Auto Resolver feature for the deduplication process. This method is defined by an enhanced deduplication approach that combines high-sensitivity duplicate detection with user-controlled resolution criteria. Systematic Auto Resolver enables research teams to define, apply, and document their own deduplication standards rather than relying on predetermined automated decisions. Users apply deduplication criteria, iteratively reviewing results after each pass, maintaining complete control over methodological decisions. The Rayyan Method addresses critical limitations in current deduplication approaches by supporting methodological rigor through user-controlled resolution while enhancing efficiency, transparency, and reproducibility. By empowering research teams to define their own deduplication criteria, this approach supports and aligns with the prescribed methodologically rigorous systematic review process. The method provides a citable framework for researchers to comprehensively document their deduplication methodology.