Journal of Korean Academy of Nursing

Hye Min Byun

5 Articles

An Exploratory Study on Non-Contact Nursing Experiences of Clinical Nurses during the COVID-19 Pandemic: Hye Min Byun, Eun Kyoung Yun; J Korean Acad Nurs 2024;54(3):446-458. Published online August 31, 2024; DOI: https://doi.org/10.4040/jkan.24045

Abstract PDF: Purpose
This study aimed to understand the non-contact nursing experiences of clinical nurses during the COVID-19 pandemic.
Methods
A qualitative research design applying thematic analysis was used. The participants were purposive sampled from three institutes: a tertiary hospital, a general hospital, and a residential treatment center in Seoul. Data were collected between December 2021 and January 2022 through individual in-depth interviews with 12 clinical nurses. The data were analyzed using Braun and Clarke’s method to identify the meaning of the participants’ experiences.
Results
During the COVID-19 pandemic, the fields where the participants performed non-contact nursing included intensive care units and isolation wards of hospitals, a residential treatment center, and home cares. Their tasks in non-contact nursing commonly involved remote monitoring using digital devices or equipment, consultation and education. From their experiences performing tasks in these fields, the four theme clusters and nine themes were derived. The four theme clusters are as follows: (1) Confusion of nursing role; (2) Conflict due to insufficient support system; (3) Concern about the quality of nursing; (4) Reflection on the establishment of nursing professionalism.
Conclusion
This study highlights the necessity for institutionalizing professional nursing areas, nursing education, and practical support by clarifying the purpose and goals of non-contact nursing and developing nursing knowledge through frameworks.

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Topic Modeling and Keyword Network Analysis of News Articles Related to Nurses before and after “the Thanks to You Challenge” during the COVID-19 Pandemic: Eun Kyoung Yun, Jung Ok Kim, Hye Min Byun, Guk Geun Lee; J Korean Acad Nurs 2021;51(4):442-453. Published online August 31, 2021; DOI: https://doi.org/10.4040/jkan.20287

Purpose
This study was conducted to assess public awareness and policy challenges faced by practicing nurses.
Methods
After collecting nurse-related news articles published before and after ‘the Thanks to You Challenge’ campaign (between December 31, 2019, and July 15, 2020), keywords were extracted via preprocessing. A three-step method keyword analysis, latent Dirichlet allocation topic modeling, and keyword network analysis was used to examine the text and the structure of the selected news articles.
Results
Top 30 keywords with similar occurrences were collected before and after the campaign. The five dominant topics before the campaign were: pandemic, infection of medical staff, local transmission, medical resources, and return of overseas Koreans. After the campaign, the topics ‘infection of medical staff’ and ‘return of overseas Koreans’ disappeared, but ‘the Thanks to You Challenge’ emerged as a dominant topic. A keyword network analysis revealed that the word of nurse was linked with keywords like thanks and campaign, through the word of sacrifice. These words formed interrelated domains of ‘the Thanks to You Challenge’ topic.
Conclusion
The findings of this study can provide useful information for understanding various issues and social perspectives on COVID-19 nursing. The major themes of news reports lagged behind the real problems faced by nurses in COVID-19 crisis. While the press tends to focus on heroism and whole society, issues and policies mutually beneficial to public and nursing need to be further explored and enhanced by nurses.

Citations

Citations to this article as recorded by

Patent Technology Trends of Oral Health: Application of Text Mining
Hee-Kyeong Bak, Yong-Hwan Kim, Han-Na Kim
Journal of Dental Hygiene Science.2024; 24(1): 9. CrossRef
Agendas on Nursing in South Korea Media: Natural Language Processing and Network Analysis of News From 2005 to 2022
Daemin Park, Dasom Kim, Ah-hyun Park
Journal of Medical Internet Research.2024; 26: e50518. CrossRef
Analysis of issues related to nursing law: Examination of news articles using topic modeling
JooHyun Lee, Hyoung Eun Chang, Jaehyuk Cho, Seohyun Yoo, Joonseo Hyeon, Andrea Cioffi
PLOS ONE.2024; 19(8): e0308065. CrossRef
Research Trends on Cancer-Related Cognitive Impairment in Patients with Non-Central Nervous System Cancer: Text Network Analysis and Topic Modeling
Hee-Jun Kim, Sun Hyoung Bae, Jin-Hee Park
Journal of Korean Academy of Fundamentals of Nursing.2023; 30(3): 313. CrossRef
Perspectives of Frontline Nurses Working in South Korea during the COVID-19 Pandemic: A Combined Method of Text Network Analysis and Summative Content Analysis
SangA Lee, Tae Wha Lee, Seung Eun Lee
Journal of Korean Academy of Nursing.2023; 53(6): 584. CrossRef
Nurses’ Experience in COVID-19 Patient Care
Soojin Chung, Mihyeon Seong, Ju-young Park
Journal of Korean Academy of Nursing Administration.2022; 28(2): 142. CrossRef
A topic modeling analysis for Korean online newspapers: Focusing on the social perceptions of nurses during the COVID-19 epidemic period
Soo Jung Chang, Sunah Park, Yedong Son
The Journal of Korean Academic Society of Nursing Education.2022; 28(4): 444. CrossRef
Images of Nurses Appeared in Media Reports Before and After Outbreak of COVID-19: Text Network Analysis and Topic Modeling
Min Young Park, Seok Hee Jeong, Hee Sun Kim, Eun Jee Lee
Journal of Korean Academy of Nursing.2022; 52(3): 291. CrossRef
Experience of Nurses in Charge of COVID-19 Screening at General Hospitals in Korea
Boo Young Ha, Yun-Sook Bae, Han Sol Ryu, Mi-Kyeong Jeon
Journal of Korean Academy of Nursing.2022; 52(1): 66. CrossRef
An Exploratory Study on Current Nursing Issues in the COVID-19 era through Newspaper Articles: The Application of Text Network Analysis
Young Joo Lee
Journal of Korean Academy of Nursing Administration.2022; 28(3): 307. CrossRef
Analysis of Headline News about Nurses Before and After the COVID-19 Pandemic
Su-Mi Baek, Myonghwa Park
Journal of Korean Academy of Nursing Administration.2022; 28(4): 319. CrossRef
Warmth and competence perceptions of key protagonists are associated with containment measures during the COVID-19 pandemic: Evidence from 35 countries
Maria-Therese Friehs, Patrick F. Kotzur, Christine Kraus, Moritz Schemmerling, Jessica A. Herzig, Adrian Stanciu, Sebastian Dilly, Lisa Hellert, Doreen Hübner, Anja Rückwardt, Veruschka Ulizcay, Oliver Christ, Marco Brambilla, Jonas De keersmaecker, Feder
Scientific Reports.2022;[Epub] CrossRef

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An Exploratory Study on the Policy for Facilitating of Health Behaviors Related to Particulate Matter: Using Topic and Semantic Network Analysis of Media Text: Hye Min Byun, You Jin Park, Eun Kyoung Yun; J Korean Acad Nurs 2021;51(1):68-79. Published online February 28, 2021; DOI: https://doi.org/10.4040/jkan.20213

Abstract PDF

Purpose
This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies.
Methods
After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6.
Results
In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured.
Conclusion
Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses’ care of vulnerable patients and public health promotion.

Citations

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Online community users’ perceptions of particulate matter in South Korea through topic modeling and semantic network analysis
Hansol Choi, Yong Pyo Kim, Yungwook Kim, Ji Yi Lee, Hyemi Lee
Environmental Advances.2025; 20: 100641. CrossRef
Changes in Public Sentiment under the Background of Major Emergencies—Taking the Shanghai Epidemic as an Example
Bowen Zhang, Jinping Lin, Man Luo, Changxian Zeng, Jiajia Feng, Meiqi Zhou, Fuying Deng
International Journal of Environmental Research and Public Health.2022; 19(19): 12594. CrossRef

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Development and Analysis of System Dynamics Model for Predicting on the Effect of Patient Transfer Counseling with Nurses: Hye Min Byun, Eun Kyoung Yun; J Korean Acad Nurs 2018;48(5):554-564. Published online October 31, 2018; DOI: https://doi.org/10.4040/jkan.2018.48.5.554

Abstract PDF: Purpose
This study aimed to construct a management model for patient transfer in a multilevel healthcare system and to predict the effect of counseling with nurses on the patient transfer process.
Methods
Data were collected from the electronic medical records of 20,400 patients using the referral system in a tertiary hospital in Seoul from May 2015 to April 2017. The data were analyzed using system dynamics methodology.
Results
The rates of patients who were referred to a tertiary hospital, continued treatment, and were terminated treatment at a tertiary hospital were affected by the management fee and nursing staffing in a referral center that provided patient transfer counseling. Nursing staffing in a referral center had direct influence on the range of increase or decrease in the rates, whereas the management fee had direct influence on time. They were nonlinear relations that converged the value within a certain period.
Conclusion
The management fee and nursing staffing in a referral center affect patient transfer counseling, and can improve the patient transfer process. Our findings suggest that nurses play an important role in ensuring smooth transitions between clinics and hospitals.

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