RT Journal Article T1 Comparison of MeSH terms and KeyWords Plus terms for more accurate classification in medical research fields. A case study in cannabis research A1 Valderrama Zurián, Juan Carlos A1 García Zorita, José Carlos A1 Marugán Lázaro, Sergio A1 Sanz Casado, Elías AB KeyWords Plus and Medical Subject Headings (MeSH) are widely used in bibliometric studies for topic mapping. The objective of this study is to compare the two description systems in documents about cannabis research to find the concordance between systems and establish whether there is neutrality in topic mapping. A total of 25,593 articles from 1970 to 2019 were drawn from Web of Science's Core Collection and Medline and analyzed. The tidytext library, Zipf's law, topic modeling tools, the contingency coefficient, Cramer's V, and Cohen's kappa were used. The results included 10,107 MeSH terms and 28,870 KeyWords Plus terms. The Zipf distribution of the terms was different for each system in terms of slope and specificity. The documents were classified into seven topics, and the MeSH system proved better at classification. The kappa coefficient between the two systems was 0.477 (for gamma ≥ 0.2); the topics related with human beings presented higher concordance. The use of KeyWords Plus for topic analyses in biomedical areas is not neutral, and this point needs to be taken into account in interpreting results. PB Elsevier SN 0306-4573 YR 2021 FD 2021-09-01 LK https://hdl.handle.net/10016/39088 UL https://hdl.handle.net/10016/39088 LA eng NO Juan Carlos Valderrama-Zurián was the beneficiary of a grant from the Valencian Regional Ministry of Innovation, Universities, Science, and Digital Society to carry out postdoctoral research at Carlos III University of Madrid (BEST/2020/121).This research has also been funded by Program H2019/HUM-5744 CM-INCLUSIVA-CM, under the Community of Madrid's 2019 call for grants for R&D programs in social sciences and humanities. DS e-Archivo RD 1 jul. 2024