MEDLINE citation tool accuracy: an analysis in two platforms.

Auto-citation generator Ovid MEDLINE PubMed biomedical databases citation on demand information literacy librarians

Journal

Journal of the Medical Library Association : JMLA
ISSN: 1558-9439
Titre abrégé: J Med Libr Assoc
Pays: United States
ID NLM: 101132728

Informations de publication

Date de publication:
01 Apr 2024
Historique:
medline: 9 8 2024
pubmed: 9 8 2024
entrez: 9 8 2024
Statut: ppublish

Résumé

Libraries provide access to databases with auto-cite features embedded into the services; however, the accuracy of these auto-cite buttons is not very high in humanities and social sciences databases. This case compares two biomedical databases, Ovid MEDLINE and PubMed, to see if either is reliable enough to confidently recommend to students for use when writing papers. A total of 60 citations were assessed, 30 citations from each citation generator, based on the top 30 articles in PubMed from 2010 to 2020. Error rates were higher in Ovid MEDLINE than PubMed but neither database platform provided error-free references. The auto-cite tools were not reliable. Zero of the 60 citations examined were 100% correct. Librarians should continue to advise students not to rely solely upon citation generators in these biomedical databases.

Sections du résumé

Background UNASSIGNED
Libraries provide access to databases with auto-cite features embedded into the services; however, the accuracy of these auto-cite buttons is not very high in humanities and social sciences databases.
Case Presentation UNASSIGNED
This case compares two biomedical databases, Ovid MEDLINE and PubMed, to see if either is reliable enough to confidently recommend to students for use when writing papers. A total of 60 citations were assessed, 30 citations from each citation generator, based on the top 30 articles in PubMed from 2010 to 2020.
Conclusions UNASSIGNED
Error rates were higher in Ovid MEDLINE than PubMed but neither database platform provided error-free references. The auto-cite tools were not reliable. Zero of the 60 citations examined were 100% correct. Librarians should continue to advise students not to rely solely upon citation generators in these biomedical databases.

Identifiants

pubmed: 39119157
doi: 10.5195/jmla.2024.1718
pii: jmla.2024.1718
pmc: PMC11305470
doi:

Types de publication

Case Reports Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

133-139

Informations de copyright

Copyright © 2024 Laurel Scheinfeld, Sunny Chung.

Auteurs

Laurel Scheinfeld (L)

laurel.scheinfeld@stonybrook.edu, Senior Assistant Librarian, Health Sciences Library, Stony Brook University, Stony Brook, NY.

Sunny Chung (S)

sunny.chung@stonybrook.edu, Senior Assistant Librarian, Health Sciences Library, Stony Brook University, Stony Brook, NY.

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Classifications MeSH