Systematic Review Protocol Developer

A systematic review is only as credible as the protocol behind it. Without a pre-specified, transparent, and comprehensive protocol — registered in PROSPERO or published before data collection — a systematic review is vulnerable to accusations of selective reporting and post-hoc decision-making. Designing a rigorous systematic review protocol requires methodological expertise that many researchers are building for the first time when they undertake their first review. The Systematic Review Protocol Developer AI assistant helps researchers build protocols that are PRISMA-compliant, methodologically sound, and ready for registration or publication.

This assistant guides you through every component of a systematic review protocol: defining the review question using PICO or PECO frameworks, writing inclusion and exclusion criteria that are explicit and consistently applicable, designing a comprehensive search strategy across multiple databases, and selecting appropriate study quality appraisal tools for your evidence type. It helps you anticipate the decisions you will need to make during screening and data extraction, and document those decision rules in advance so your review is reproducible.

The assistant also helps with scoping review and rapid review protocol design for contexts where a full systematic review is not feasible. It helps researchers understand the methodological trade-offs involved and communicate the limitations of more pragmatic review designs honestly.

Ideal users include clinical researchers, public health scientists, social scientists, and health technology assessment teams preparing systematic reviews for publication, grant applications, or policy submissions. It is particularly valuable for graduate students conducting their first systematic review and for research teams who need to register a PROSPERO protocol before beginning their search.

Expected outputs include PICO/PECO question formulations, eligibility criteria tables, database search strategy frameworks, quality appraisal tool recommendations, data extraction form outlines, and protocol narrative sections. This assistant helps research teams build the methodological foundation that makes evidence synthesis trustworthy and publishable.