ACTA FAC MED NAISS 2019;36(3):235-247

Original article

UDC: 61:001.4:811.111

DOI: 10.5937/afmnai1903236S

 

Understanding the Research Process and Historical Trends in English for Medical Purposes Using Scientometrics and Co-Occurrence Analysis

 

Nematullah Shomoossi1, Mostafa Rad2, Mansoureh Fiezabadi3, Esmaeil Vaziri4, Mostafa Amiri5

1Department of English, School of Medicine, Sabzevar University of Medical Sciences, Sabzevar, Iran
2Department of Nursing, School of Nursing, Sabzevar University of Medical Sciences, Sabzevar, Iran
3Department of Information Science and Knowledge Studies, School of Medicine, Sabzevar University of Medical Sciences, Sabzevar, Iran
4Department of Information Science and Knowledge Studies, Faculty of Humanities, University of Zabol, Zabol, Iran
5Department of Basic Sciences, School of Medicine, Gonabad University of Medical Sciences, Gonabad, Iran



summary


The present study used scientometrics and word co-occurrence analysis to identify the most important topics and to assess trends in English for medical purposes over time. Documents indexed in Scopus and Web of Science were used to examine various indicators such as keywords, countries, organizations, and authors. Search results were preprocessed through BibExcel to create a file for mapping, and word co-occurrence analysis was applied to evaluate the publications. Also, scientific maps, author’s network, and country contributions were depicted using VOSviewer and NetDraw. The most productive authors and countries were determined. Regarding the trend analysis, highly frequent words were examined at six-year intervals. The findings indicated that 81 countries, 1,304 authors, and 799 organizations have contributed to the scientific mobility of this field. Keyword co-occurrence analysis indicated that topics have shifted from language-specific foci to interactive domains. These findings offer evidence-based information about the past and present trends in EMP research topics and trends, as well as its future directions, moving from linear patterns (solely related to linguistic components) towards a more interrelated pattern of issues clustering around a medical education and learning topics.



Key words: English for medical purposes (EMP), English for specific purposes (ESP), medical English, scientometrics, word co-occurrence analysis