synthesis-matrix

Systematic reviews require organizing extracted study data into structured matrices capturing study characteristics, populations, interventions, outcomes, and effect sizes. This skill automates that organization, letting you load study exports and generate evidence matrices ready for synthesis and manuscript preparation.

Evidence synthesis matrices typically include study identifiers, population details, study design, intervention descriptions, measured outcomes, effect sizes, and quality assessments. This skill standardizes extraction across studies, enabling consistent comparison and cross-study pattern identification for narrative synthesis.

Yes. Once your studies are organized in a structured matrix, you can identify patterns and contrasts across study characteristics, designs, and outcomes. This cross-study comparison supports evidence synthesis and helps highlight methodological differences relevant to your review conclusions.

Evidence matrices structured with study characteristics, outcomes, and quality metrics can be exported and included directly in manuscripts or supplementary materials. This skill formats your synthesis data into publication-ready matrices, reducing manual table construction.

Extracted study data in CSV format loads directly into evidence matrix workflows. The skill accepts structured exports from data extraction tools and standardizes them into matrix schema with fields for study, population, design, intervention, outcome, effect size, and quality.

Yes. Quality assessment scores and risk-of-bias ratings integrate into the evidence matrix as part of study quality fields. This allows you to track methodological limitations across studies and weight evidence synthesis by study quality.