What is it about?
This paper explores how citation analysis can improve the process of creating and updating living systematic reviews (LSRs) in biomedical research. It shows how traditional methods like semantic classification and crowdsourcing can miss important studies, and how citation analysis—using techniques like backward and forward snowballing—can help identify relevant papers that were overlooked. By analyzing citations, researchers can better ensure that the LSR includes all relevant studies and excludes those that are irrelevant.
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Why is it important?
The use of citation analysis is timely because it addresses gaps in traditional methods of reviewing scientific literature. While semantic classification and crowdsourcing are valuable, they can miss important papers that are indirectly related to the topic of interest. By incorporating citation analysis, researchers can more accurately identify relevant studies and avoid including irrelevant ones, leading to more comprehensive and reliable systematic reviews. This method can significantly enhance the quality of LSRs and ensure that they reflect the most current and relevant evidence.
Perspectives
From my perspective, this publication highlights a crucial, yet often overlooked, technique in the realm of systematic reviews. Citation analysis offers a practical and effective complement to existing methods, and its incorporation could greatly improve the accuracy and relevance of LSRs. Given the increasing volume of research and the complexities involved in reviewing literature, integrating citation analysis is a significant step forward. This approach not only refines the selection process but also ensures that systematic reviews are as inclusive and precise as possible.
Houcemeddine Turki
Universite de Sfax
Read the Original
This page is a summary of: Citation analysis is also useful to assess the eligibility of biomedical research works for inclusion in living systematic reviews, Journal of Clinical Epidemiology, May 2018, Elsevier,
DOI: 10.1016/j.jclinepi.2017.11.002.
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