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Currently accepted at: Interactive Journal of Medical Research

Date Submitted: Feb 27, 2026
Open Peer Review Period: Feb 27, 2026 - Apr 24, 2026
Date Accepted: Jun 10, 2026
Date Submitted to PubMed: Jun 11, 2026
(closed for review but you can still tweet)

This paper has been accepted and is currently in production.

It will appear shortly on 10.2196/94317

The final accepted version (not copyedited yet) is in this tab.

An "ahead-of-print" version has been submitted to Pubmed, see PMID: 42274223

Enhancing Transparency, Auditability, and Reproducibility of Deduplication in Systematic Reviews: A Tutorial for the Rayyan Method and Systematic Auto Resolver Feature

  • Mimi Kim; 
  • Amin M. Shanaa; 
  • Hossam Hammady; 
  • Mohammad Aboelnour; 
  • Robert Ayan

ABSTRACT

Background:

Deduplication across search results is the initial and critical step in the systematic review methodological process; yet, existing solutions often lack the transparency, auditability, and reproducibility. Many automated deduplication tools introduce the strong potential for bias through predetermined algorithms, while also potentially removing relevant references through false positive identification.

Objective:

We provide a methodological description and feature demonstration of the Rayyan Method, a novel and fully integrated deduplication approach that combines high-sensitivity duplicate detection with user-controlled resolution criteria to enhance transparency and methodological rigor in systematic reviews.

Methods:

The Rayyan Method employs a fully platform-integrated, two-stage process: 1) high-sensitivity detection of possible duplicates using advanced algorithms; and 2) user-controlled resolution through customizable deduplication criteria (AutoResolver). The unique platform feature, Auto-Resolver, enables research teams to define, apply, and document their own deduplication standards rather than relying on predetermined automated decisions.

Results:

The Rayyan Method successfully separates duplicate detection from resolution, allowing maximum sensitivity without false positive risk. Users apply deduplication criteria, iteratively, and observe results after each pass — maintaining complete control over methodological decisions. This approach is fully documented including applied criteria and resolution rationale, which enables and enhances transparent reporting and independent validation of the deduplication processes.

Conclusions:

The Rayyan Method addresses critical limitations in current deduplication approaches by preserving reviewer expertise 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 document their deduplication methodology in entirety.


 Citation

Please cite as:

Kim M, Shanaa AM, Hammady H, Aboelnour M, Ayan R

Enhancing Transparency, Auditability, and Reproducibility of Deduplication in Systematic Reviews: A Tutorial for the Rayyan Method and Systematic Auto Resolver Feature

Interactive Journal of Medical Research. 10/06/2026:94317 (forthcoming/in press)

DOI: 10.2196/94317

URL: https://preprints.jmir.org/preprint/94317

PMID: 42274223

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