Visualization of clinical teaching citations using social network analysis

Area of Science:

• Medical Education Research
• Bibliometrics
• Social Network Analysis

Background:

• Analyzing clinical teaching literature reveals trends and future research directions.
• Social Network Analysis (SNA) visualizes co-authorship and collaboration patterns.

Purpose of the Study:

• To map and analyze the co-authorship networks in clinical teaching research.
• To identify influential authors and countries in the field.
• To understand the structure and cohesion of the research landscape.

Main Methods:

• Systematic literature search across Scopus, Web of Science, and PubMed (1980-2018).
• Identified 1229 publications on clinical teaching.
• Utilized Ravar PreMap, Netdraw, UCINet, and VOSviewer for data visualization and analysis.

Main Results:

• Clinical teaching research exhibits weak cohesion in author co-authorship networks (CC: 0.749, density: 0.0238).
• International collaboration networks also show moderate cohesion (CC: 0.655, density: 0.176), with the USA, UK, Canada, Australia, and the Netherlands playing central roles.
• Analysis revealed weak co-authorship among clinical researchers and identified 19 subject clusters, with a focus on competencies and skills.

Conclusions:

• Improving cohesion requires enhanced research collaboration, particularly between new and established researchers.
• Policies encouraging international and national collaboration between clinicians and specialists are essential.
• Future research directions include incorporating humanitarian aspects and clinical reasoning into clinical teaching.