|
KMID : 0614820170230010101
|
|
Journal of Korean Academy of Nursing Administration
2017 Volume.23 No. 1 p.101 ~ p.110
|
|
|
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 Tae-Wha
Park Kwang-Ok
Seomun Gyeong-Ae
Kim Mi-Young
Hwang Jae-Sam
Yu So-Young
Jeong Seok-Hee
Jung Min
Moon Mi-Kyung
|
|
|
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
|
|
|
FullTexts / Linksout information
|
|
 
|
|
|
Listed journal information
|
|
 
|