手法を比較

	書誌計量学支援型ナラティブレビュー	システマティック・レビュー
分野	科学計量学	科学計量学
系統	Process / pipeline	Process / pipeline
提唱年	2017 (bibliometrix package); narrative review methodology is older	1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines)
提唱者	Aria & Cuccurullo (bibliometrix R package); narrative review as a traditional form predates this tool	Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004)
種類	Mixed quantitative-qualitative review methodology	Evidence synthesis methodology
原典	Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.	Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401.
別名	bibliometrix narrative review, R-bibliometrix narrative synthesis, quantitative-assisted narrative review	SLR, systematic review, evidence synthesis review, structured literature review
関連	6	5
概要	A bibliometrix-assisted narrative review combines the quantitative field-mapping capabilities of the bibliometrix R package with the interpretive flexibility of a traditional narrative review. Bibliometric indicators — publication trends, author and country productivity, co-citation networks, keyword co-occurrence — are computed and visualised first to orient the reviewer, then a discursive, thematic narrative synthesises the intellectual content of key sources. The result is a structured yet flexible overview of a field that is more transparent and reproducible than a purely informal narrative.	A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic.