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REVIEW article
Front. Psychol.
Sec. Neuropsychology
Volume 16 - 2025 | doi: 10.3389/fpsyg.2025.1552821
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Background: Salivary cortisol has garnered increasing attention; the aim of this study was to employ bibliometric analysis to identify key papers in this research field and to explore its current status and trends. Methods: Data were sourced from Clari-vate Analytics' Web of Science core database, utilizing the search terms ‘TS = (‘Sali-vary cortisol’) AND (Human) NOT (animal)’. All articles published from January 1, 2004, to September 30, 2024, were included. Results: A total of 876 articles were identified. The United States has made a significant contribution to this field, with the highest number of publications at 291. The University of California system leads this research area, having published 40 articles. Professor Clemens Kirschbaum has au-thored 21 articles in this domain. The journal Psychoneuroendocrinology published the largest number of articles, totaling 99, which accounts for 11.3% of the overall articles. Additionally, Psychoneur-oendocrinology was the most cited journal, with 3,681 citations. High-frequency keywords reveal the developmental status and future trends of human salivary cortisol. As a biomarker and signaling molecule, salivary cortisol is closely linked to human gender, personality, psychology, and physiology. We identified that “mental health, ” “circadian rhythm,” and “assay” may become fo-cal points of interest in the coming years.Conclusions: Global publications related to human salivary cortisol were systematically reviewed. CiteSpace and VOSviewer were utilized to analyze their bibliometric characteristics, identify the most cited arti-cles in the field, and determine the leading countries, authors, and institutions, along with the interconnections among them. This analysis aims to elucidate the current sta-tus, hotspots, and trends in global research, while providing future development direc-tions for scientific inquiry and medical practitioners.
Keywords: salivary cortisol, a bibliometric analysis, co-occurrence network analysis, Cooperative network analysis, Clustering analysis
Received: 29 Dec 2024; Accepted: 03 Mar 2025.
Copyright: © 2025 Qin, Liu, Qin and Jia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Jing Jia, The Third Medical Center, Chinese PLA General Hospital, BeiJing, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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