Trends in e-literature on cardiovascular diseases: A bibliometric analysis with reference to ClinicalKey (2015 -2019)

Abstract

ClinicalKey is a clinical search engine that helps doctors and other health professionals to make better decisions anywhere, anytime, in any patient scenario. ClinicalKey database provides access to thousands of online resources such as online medical books, e-journals, drug monographs, guidelines, patient education, clinical overviews and multimedia resources. This paper aims to describe the bibliometric study published in ClinicalKey from 2015 to 2019 on e-literature on cardiovascular diseases (CVDs) and to explore publishing trends in the relevant field. For the study, the literature was extracted in terms of fulltext research articles from ClinicalKey covering the period from January 2015 to December 2019. This quantitative study includes the bibliometric methods to analyze original articles and the data has been analyzed using statistical techniques in MS Excel and SPSS. During the period of study, a total of 8193 research articles were published, giving an average of 1639 pieces of literature per year. Results of this study revealed that the year-wise distribution of articles has a mean relative growth rate of 0.90 articles per annum and a doubling time of 2.27 years for the publications at the aggregate level. In the same way, month-wise results for the year 2015 and 2019 are, mean relative growth rate 0.45 and 0.41 articles per month and the doubling time 10.34 and 10.49 months respectively. Relative growth rate and doubling time of retrieved literature from 2015 to 2019 is stable and indicates an exponential growth of literature in the field. The analysis shows that there is a nucleus zone of journals (core journals) publishing cardiovascular diseases research output which is scattered among journals in cardiovascular diseases literature confirm to the Bradford's law of scattering.

Bibliometric Analysis on Recent Topics in ILS Research

“…The bibliometric analysis followed the three stages proposed by Aria and Cuccurullo (2017), beginning with the descriptive analysis of the document's bibliographic attributes such as publication year, author names, keywords, and other basic data. Bradford's Law (Pinto et al, 2013;Silva et al, 2023;Wadasinghe, 2020) was used to find the most relevant sources on a specific topic. Lotka's Law was also used to analyze the distribution of scientific productivity of authors in the field of study.…”