A Scientometrics Analysis and Visualization of Depressive Disorder

Area of Science:

• Psychiatry and Mental Health
• Bibliometrics
• Scientific Literature Analysis

Background:

• While research on depressive disorder mechanisms and treatments is extensive, scientometric analyses are notably scarce.
• Understanding the landscape of depression research is crucial for identifying trends and future directions.

Purpose of the Study:

• To conduct a scientometric analysis and historical review of depressive disorder research from 1998 to 2018.
• To identify key research trends, hotspots, and emerging topics in the field of depression.

Main Methods:

• Utilized scientometric analysis to examine research output, field distribution, and knowledge structure.
• Employed historical review and keyword analysis to identify frequent terms, trends, and emerging topics.
• Analyzed 231,270 research papers published on depression over a 20-year period.

Main Results:

• Identified field distribution, knowledge structure, research topic evolution, and topic emergence as key areas of exploration.
• Highlighted the significance of induction factors, comorbidity, pathogenesis, therapy, and animal models in understanding depression.
• Observed a four-fold increase in depression research publications over the last two decades.

Conclusions:

• The study provides a comprehensive overview of the research landscape in depressive disorder.
• Findings offer a roadmap for future research by highlighting established and emerging areas of interest.
• The significant growth in publications underscores the increasing focus on understanding and treating depression.