Thematic Analysis and Scientific Mapping of Papers related to Depression Therapy in PubMed

A considerable amount of research is conducted in the area of depression therapy from all over the world. Exploration of the relationships between title keywords of the papers provides helpful information for researchers. The aim of this paper is to draw up scientific maps for this research area in PubMed.
This research is conducted based on scientometrics approaches. It uses the techniques of co-word analysis and social network analysis to identify conceptual relationship between papers related to the field of depression therapy. Using Ravar Matrix, Ucinet and Netdraw software packages, 6, 172 papers related to the treatment of depression in PubMed were analyzed during the period from 2005 to 2014.
Findings: The subject areas of Medication adherence and Suicidal ideation were identified as the most prevalent new and emerging topics in this field. Results of Closeness and Between Centrality indicators, revealed that the greatest value is related to the topics of »Psychology, Drug Therapy, and Anti-depressive Agents«.
According to the findings, Drug Therapy, Psychology, Anti-depressive agents, and Treatment outcome are the most active research areas. Scientific maps help users and policy makers get a better understanding of the structure of a research area, explore the research status of a field and make plans to improve the quality and quantity of scientific products.