Citation

Park MY, Jeong SH, Kim HS, Lee EJ. J. Korean Acad. Nurs. 2022; 291-307.

Copyright

(Copyright © 2022, Korean Society of Nursing Science)

DOI

10.4040/jkan.22002

PMID

unavailable

Abstract

PURPOSE@#The aims of study were to identify the main keywords, the network structure, and the main topics of press articles related to nurses that have appeared in media reports. @*Methods@#Data were media articles related to the topic "nurse" reported in 16 central media within a one-year period spanning July 1, 2019 to June 30, 2020. Data were collected from the Big Kinds database. A total of 7,800 articles were searched, and 1,038 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4. @*Results@#The number of media reports related to nurses increased by 3.86 times after the novel coronavirus (COVID-19) outbreak compared to prior. Pre- and post-COVID-19 network characteristics were density 0.002, 0.001; average degree 4.63, 4.92; and average distance 4.25, 4.01, respectively. Four topics were derived before and after the COVID-19 outbreak, respectively. Pre-COVID-19 example topics are "a nurse who committed suicide because she could not withstand the Taewoom at work" andf "a nurse as a perpetrator of a newborn abuse case," while post-COVID-19 examples are "a nurse as a victim of COVID-19," "a nurse working with the support of the people," and "a nurse as a top contributor and a warrior to protect from COVID-19." @*Conclusion@#Topic modeling shows that topics become more positive after the COVID-19 outbreak. Individual nurses and nursing organizations should continuously monitor and conduct further research on nurses' image.

Language: en