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  5. Guidance for the Reporting of Bibliometric Analyses: A Scoping Review

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Article
en
2024

Guidance for the Reporting of Bibliometric Analyses: A Scoping Review

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en
2024
DOI: 10.1101/2024.08.26.24312538

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David Moher
David Moher

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Jeremy Y. Ng
Henry Liu
Mehvish Masood
+8 more

Abstract

Abstract Despite the growth in the number of bibliometric analyses published in the peer-reviewed literature, few articles provide guidance on methods and reporting to ensure reliability, robustness, and reproducibility. Consequently, the quality of reporting in existing bibliometric studies varies greatly. In response, we are developing a preliminary Guidance List for the repOrting of Bibliometric AnaLyses (GLOBAL) , a reporting guideline for bibliometric analyses. This paper outlines a scoping review that aims to identify and categorise bibliometric recommendations from the literature to develop an initial list of candidate items for the GLOBAL. Five bibliographic databases, three preprint servers, and grey literature were systematically searched. Twenty-three out of 48,750 records fulfilled the inclusion criteria. Six documents contained bibliometric reporting recommendations based on a complete or partial literature review; all other sources (n = 17) contained opinion-based recommendations. A 32-item recommendation list that will inform the development of the GLOBAL was created. A paucity of evidence-based studies on bibliometric reporting exists in the literature, supporting the need to create a reporting guideline for bibliometric analyses. The next step in the GLOBAL project will focus on conducting a two-round Delphi study to achieve consensus on which of the 32 items should be included in GLOBAL.

How to cite this publication

Jeremy Y. Ng, Henry Liu, Mehvish Masood, Niveen Syed, Dimity Stephen, Ana Patricia Ayala, Michel Sabé, Marco Solmi, Ludo Waltman, Stefanie Haustein, David Moher (2024). Guidance for the Reporting of Bibliometric Analyses: A Scoping Review. , DOI: https://doi.org/10.1101/2024.08.26.24312538.

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Publication Details

Type

Article

Year

2024

Authors

11

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/2024.08.26.24312538

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