J Korean Acad Nurs Adm.  2017 Jan;23(1):101-110. 10.11111/jkana.2017.23.1.101.

Analysis of Research Articles Published in the Journal of Korean Academy of Nursing Administration for 3 Years (2013~2015): The Application of Text Network Analysis

• Lee TW
• Park KO
• Seomun G
• Kim M
• Hwang JI
• Yu S
• Jeong SH
• Jung M
• Moon M

• KMID: 2369523
• DOI: http://doi.org/10.11111/jkana.2017.23.1.101

Abstract

PURPOSE
This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015.
METHODS
For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis.
RESULTS
Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism.
CONCLUSION
The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.

Keyword

Nursing research; Research analysis; Keywords; Text network analysis

MeSH Terms

Ethics, Research
Happiness
Nursing Administration Research
Nursing Research
Nursing*
Power (Psychology)
Professionalism
Research Design
Statistics as Topic

Figure

• 

  Figure 1 Cluster map.

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