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Lee, Park, Seomun, Kim, Hwang, Yu, Jeong, Jung, and Moon: 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
Original Article

Journal of Korean Academy of Nursing Administration 2017; 23(1): 101-110.

Published online: 31 January 2017

DOI: https://doi.org/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

Tae Wha Lee1, Kwang-Ok Park2, GyeongAe Seomun3, Miyoung Kim4, Jee-In Hwang5, Soyoung Yu6, Seok Hee Jeong7, Min Jung8, Mikyung Moon9

1College of Nursing, Mo-Im Kim Nursing Research Institute, Yonsei University, Korea.

2Department of Nursing, Sunchon National University, Korea.

3College of Nursing, Korea University, Korea.

4College of Nursing, Ewah Womans University, Korea.

5College of Nursing Science, Kyung Hee University, Korea.

6College of Nursing, CHA University, Korea.

7College of Nursing, Research Institute of Nursing Science, Chonbuk National University, Korea.

8School of Nursing, Cheju Halla University, Korea.

9College of Nursing, The Research Institute of Nursing, Kyungpook National University, Korea.

Corresponding author: Moon, Mikyung. College of Nursing, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu 41944, Korea. Tel: +82-53-200-4793, Fax: +82-53-421-2758, mkmoon@knu.ac.kr

Received 31 December 2016       Revised 17 January 2017       Accepted 17 January 2017

Copyright © 2017 Korean Academy of Nursing Administration

(open-access):

This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.

Keywords: Nursing research, Research analysis, Keywords, Text network analysis

Figures and Tables

Figure 1

Cluster map.

jkana-23-101-g001
Table 1

Characteristics of Published Articles

jkana-23-101-i001

*Multiple choice.

Table 2

Data Analysis Method for the Published Articles* (N=683)

jkana-23-101-i002

*Multiple choice.

Table 3

Key Words Analysis (N=679)

jkana-23-101-i003
Table 4

Degree Centrality and between Centrality of Keywords

jkana-23-101-i004

Notes

This manuscript was supported by Korean Academy of Nursing Administration.

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