Skip Navigation
Skip to contents

J Korean Acad Nurs : Journal of Korean Academy of Nursing

OPEN ACCESS

Search

Page Path
HOME > Search
11 "Network"
Filter
Filter
Article category
Keywords
Publication year
Authors
Research Papers
National Petition Analysis Related to Nursing: Text Network Analysis and Topic Modeling
Ko, HyunJung , Jeong, Seok Hee , Lee, Eun Jee , Kim, Hee Sun
J Korean Acad Nurs 2023;53(6):635-651.   Published online December 31, 2023
DOI: https://doi.org/10.4040/jkan.23052
AbstractAbstract PDF
Purpose
This study aimed to identify the main keyword, network structure, and main topics of the national petition related to “nursing” in South Korea.
Methods
Data were gathered from petitions related to the national petition in Korea Blue House related to the topic “nursing” or “nurse” from August 17, 2017, to May 9, 2022. A total of 5,154 petitions were searched, and 995 were selected for the final analysis. Text network analysis and topic modeling were analyzed using the Netminer 4.5.0 program.
Results
Regarding network characteristics, a density of 0.03, an average degree of 144.483, and an average distance of 1.943 were found. Compared to results of degree centrality and betweenness centrality, keywords such as “work environment,” “nursing university,” “license,” and “education” appeared typically in the eigenvector centrality analysis. Topic modeling derived four topics: (1) “Improving the working environment and dealing with nursing professionals,” (2) “requesting investigation and punishment related to medical accidents,” (3) “requiring clear role regulation and legislation of medical and nonmedical professions,” and (4) “demanding improvement of healthcare-related systems and services.” Conclusion: This is the first study to analyze Korea's national petitions in the field of nursing. This study's results confirmed both the internal needs and external demands for nurses in South Korea. Policies and laws that reflect these results should be developed.

Citations

Citations to this article as recorded by  
  • Voice of Customer Analysis of Nursing Care in a Tertiary Hospital: Text Network Analysis and Topic Modeling
    Hyunjung Ko, Nara Han, Seulki Jeong, Jeong A Jeong, Hye Ryoung Yun, Eun Sil Kim, Young Jun Jang, Eun Ju Choi, Chun Hoe Lim, Min Hee Jung, Jung Hee Kim, Dong Hyu Cho, Seok Hee Jeong
    Journal of Korean Academy of Nursing Administration.2024; 30(5): 529.     CrossRef
  • A Study on Internet News for Patient Safety Campaigns: Focusing on Text Network Analysis and Topic Modeling
    Sun-Hwa Shin, On-Jeon Baek
    Healthcare.2024; 12(19): 1914.     CrossRef
  • 397 View
  • 13 Download
  • 1 Web of Science
  • 2 Crossref
Close layer
Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing
Ha, Ju-Young , Park, Hyo-Jin
J Korean Acad Nurs 2023;53(1):55-68.   Published online February 28, 2023
DOI: https://doi.org/10.4040/jkan.22117
AbstractAbstract PDF
Purpose
The purpose of this study was to identify the main keywords, network properties, and main topics of news articles related to artificial intelligence technology in the field of nursing.
Methods
After collecting artificial intelligence-and nursing-related news articles published between January 1, 1991, and July 24, 2022, keywords were extracted via preprocessing. A total of 3,267 articles were searched, and 2,996 were used for the final analysis. Text network analysis and topic modeling were performed using NetMiner 4.4.
Results
As a result of analyzing the frequency of appearance, the keywords used most frequently were education, medical robot, telecom, dementia, and the older adults living alone. Keyword network analysis revealed the following results: a density of 0.002, an average degree of 8.79, and an average distance of 2.43; the central keywords identified were ’education,’ ‘medical robot,’ and ‘fourth industry.’ Five topics were derived from news articles related to artificial intelligence and nursing: ‘Artificial intelligence nursing research and development in the health and medical field,’ ‘Education using artificial intelligence for children and youth care,’ ‘Nursing robot for older adults care,’ ‘Community care policy and artificial intelligence,’ and ‘Smart care technology in an aging society.’ Conclusion: The use of artificial intelligence may be helpful among the local community, older adult, children, and adolescents. In particular, health management using artificial intelligence is indispensable now that we are facing a super-aging society. In the future, studies on nursing intervention and development of nursing programs using artificial intelligence should be conducted.

Citations

Citations to this article as recorded by  
  • Mapping the Landscape of AI-Driven Human Resource Management: A Social Network Analysis of Research Collaboration
    Mehrdad Maghsoudi, Motahareh Kamrani Shahri, Mehrdad Agha Mohammad Ali Kermani, Rahim Khanizad
    IEEE Access.2025; 13: 3090.     CrossRef
  • The Impact of Artificial Intelligence-Assisted Learning on Nursing Students' Ethical Decision-making and Clinical Reasoning in Pediatric Care
    Hyewon Shin, Jennie C. De Gagne, Sang Suk Kim, Minjoo Hong
    CIN: Computers, Informatics, Nursing.2024; 42(10): 704.     CrossRef
  • Research trends over 10 years (2010-2021) in infant and toddler rearing behavior by family caregivers in South Korea: text network and topic modeling
    In-Hye Song, Kyung-Ah Kang
    Child Health Nursing Research.2023; 29(3): 182.     CrossRef
  • 1,259 View
  • 47 Download
  • 2 Web of Science
  • 3 Crossref
Close layer
Images of Nurses Appeared in Media Reports Before and After Outbreak of COVID-19: Text Network Analysis and Topic Modeling
Park, Min Young , Jeong, Seok Hee , Kim, Hee Sun , Lee, Eun Jee
J Korean Acad Nurs 2022;52(3):291-307.   Published online June 30, 2022
DOI: https://doi.org/10.4040/jkan.22002
AbstractAbstract PDF
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.

Citations

Citations to this article as recorded by  
  • Honoring donors: medical students’ reflections on cadaveric dissection
    Young Gyu Kwon, Myeong Namgung, Song Hee Park, Mi Kyung Kim, Chan Woong Kim, Hyo Hyun Yoo
    BMC Medical Education.2025;[Epub]     CrossRef
  • Voice of Customer Analysis of Nursing Care in a Tertiary Hospital: Text Network Analysis and Topic Modeling
    Hyunjung Ko, Nara Han, Seulki Jeong, Jeong A Jeong, Hye Ryoung Yun, Eun Sil Kim, Young Jun Jang, Eun Ju Choi, Chun Hoe Lim, Min Hee Jung, Jung Hee Kim, Dong Hyu Cho, Seok Hee Jeong
    Journal of Korean Academy of Nursing Administration.2024; 30(5): 529.     CrossRef
  • Impact of a game-based interprofessional education program on medical students’ perceptions: a text network analysis using essays
    Young Gyu Kwon, Myeong Namgung, Song Hee Park, Mi Kyung Kim, Sun Jung Myung, Eun Kyung Eo, Chan Woong Kim
    BMC Medical Education.2024;[Epub]     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
  • Medical students’ perceptions of improving physician satisfaction and patient care: a text network analysis approach
    Young Gyu Kwon, Myeong Namgung, Song Hee Park, Mi Kyung Kim, Hyo Hyun Yoo, Chan Woong Kim
    BMC Medical Education.2024;[Epub]     CrossRef
  • Socialisation of children to nurse and nursing images: A Goffman‐inspired thematic analysis of children's picture books in a Swedish context
    Stinne Glasdam, Hongxuan Xu, Sigrid Stjernswärd
    Nursing Inquiry.2024;[Epub]     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
  • Research trends over 10 years (2010-2021) in infant and toddler rearing behavior by family caregivers in South Korea: text network and topic modeling
    In-Hye Song, Kyung-Ah Kang
    Child Health Nursing Research.2023; 29(3): 182.     CrossRef
  • The Analysis of Research Trends and Public Awareness of Smart Farms using Text Mining
    Sung-Ho Kil, Hye-Mi Park, Eunseok Lee, Jin-Young Kim, Ji-Woo Kim
    Journal of People, Plants, and Environment.2023; 26(1): 9.     CrossRef
  • National Petition Analysis Related to Nursing: Text Network Analysis and Topic Modeling
    HyunJung Ko, Seok Hee Jeong, Eun Jee Lee, Hee Sun Kim
    Journal of Korean Academy of Nursing.2023; 53(6): 635.     CrossRef
  • An analysis of Research Published in the Journal of Korean Academy of Psychiatric and Mental Health Nursing from 2013 to 2022 using Text Network Analysis and Topic Modeling
    Eun Jo Kim, Kuem-Sun Han
    Journal of Korean Academy of psychiatric and Mental Health Nursing.2023; 32(2): 188.     CrossRef
  • Chronological Changes in the Portrayal of Korean Nurses in TV Documentaries
    Eunjin Kim, Gumhee Baek, Aram Cho, Mijin Byun
    Journal of Korean Academy of Nursing Administration.2023; 29(4): 341.     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
  • 450 View
  • 12 Download
  • 8 Web of Science
  • 13 Crossref
Close layer
Interorganizational Networks for Smoking Prevention and Cessation: A Blockmodeling Approach
Park, Eun-Jun , Kim, Hyeongsu , Lee, Kun Sei , Cho, Junghee , Kim, Jin Hyeong , Jeong, Ho Jin , Lee, Ji An
J Korean Acad Nurs 2022;52(2):202-213.   Published online April 30, 2022
DOI: https://doi.org/10.4040/jkan.21192
AbstractAbstract PDF
Purpose
This study examined characteristics and patterns of interorganizational networks for smoking prevention and cessation in Korea.
Methods
We surveyed two community health centers, ninety-five hospitals or clinics, ninety- two pharmacies, and sixty-five health welfare organizations in two districts of Seoul in 2020. Data on the organizations’ characteristics of smoking cessation and interorganizational activities for information sharing, client referral, and program collaboration were collected and analyzed using network statistics and blockmodeling.
Results
Network size was in the order of information sharing, client referral, and program collaboration networks. Network patterns for interorganizational activities on information sharing, client referral, and program collaboration among four organizations were similar between the two districts. Community health centers provided information and received clients from a majority of the organizations. Their interactions were not unidirectional but mutual with other organizations. Pharmacies were involved in information sharing with health welfare organizations and client referrals to hospitals or clinics. Health welfare organizations were primarily connected with the community health centers for client referrals and program collaboration.
Conclusion
A community health center is the lead agency in interorganizational activities for smoking prevention and cessation. However, hospitals or clinics, pharmacies, and health welfare organizations also participate in interorganizational networks for smoking prevention and cessation with diverse roles. This study would be evidence for developing future interorganizational networks for smoking prevention and cessation.
  • 185 View
  • 7 Download
Close layer
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
Yun, Eun Kyoung , Kim, Jung Ok , Byun, Hye Min , Lee, Guk Geun
J Korean Acad Nurs 2021;51(4):442-453.   Published online August 31, 2021
DOI: https://doi.org/10.4040/jkan.20287
AbstractAbstract PDF
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
  • 396 View
  • 6 Download
  • 6 Web of Science
  • 12 Crossref
Close layer
Information Resource Network Analysis of Factors Influencing Breastfeeding Planning and Duration
Lee, Eunyoung , Cho, Insook , Cho, Seong Jin , Lee, Eunju
J Korean Acad Nurs 2021;51(2):232-244.   Published online April 30, 2021
DOI: https://doi.org/10.4040/jkan.20280
AbstractAbstract PDF
Purpose
This study aimed to identify the modifiable factors affecting breastfeeding planning and duration among healthy mothers and their use of breastfeeding information resources.
Methods
A cross-sectional survey was conducted in a community setting. Four hundreds participants were recruited at five pediatric clinics and three community health centers located in Paju-si and Goyang-si, Gyeonggi-do, between January and May 2019. Based on the breastfeeding decision-making model, driven by Martens and Young’s work, the survey items consisted of demographics, childbirth and breastfeeding characteristics, and breastfeeding information resources. In the analysis, 389 responses were used in the t-test, ANOVA, and logistic regression. Information resource networks were compared before and after childbirth including a subgroup analysis depending on the breastfeeding duration.
Results
The modifiable factors affecting breastfeeding planning and duration were antenatal and postpartum breastfeeding education and the provision of information in the hospital. The frequency of Internet use and websites visited were notable and potentially modifiable factors, which were also observed in the networks showing different relationship patterns according to participant subgroups and times. The childbirth event increased the centralization of the network in the planned group, while the network of the non-planned group was more diffused after childbirth. The network of the short-term breastfeeding group was characterized by a more centralized pattern and the resources of high betweenness centrality than the long-term group.
Conclusion
Breastfeeding education is a consistent factor that affects breastfeeding behavior. A well-designed internet-based approach would be an effective nursing intervention to meet the needs of women seeking breastfeeding information and changing their behaviors.

Citations

Citations to this article as recorded by  
  • Survey on the Status of Breastfeeding in Korean Medical Institution Workers
    Tae Hyeong Kim, Sung-Hoon Chung, Jun Hwan Kim, Youngmin Ahn, Son Moon Shin, Woo Ryoung Lee, Eui Kyung Choi, Juyoung Lee, Hye-Jung Shin, Euiseok Jung, Ju Sun Heo, Jin A Lee, Soon Min Lee, Seong Phil Bae, Jeonglyn Song, Chae-Young Kim, Dae Yong Yi
    Journal of Korean Medical Science.2022;[Epub]     CrossRef
  • A Multi-Center Educational Research Regarding Breastfeeding for Pediatrics Residents in Korea
    Yong-Sung Choi, Sung-Hoon Chung, Eun Sun Kim, Eun Hee Lee, Euiseok Jung, So Yeon Lee, Wooryoung Lee, Hye Sun Yoon, Yong Joo Kim, Ji Kyoung Park, Son Moon Shin, Ellen Ai-Rhan Kim
    Neonatal Medicine.2022; 29(1): 28.     CrossRef
  • Breastfeeding Success Experience of Primiparas
    Sun Ok Lee, Sung Soon Na, Hee Sook Kim, Kyung Eui Bae, Mi Sun Youn, Eun Ju Oh
    Journal of The Korean Society of Maternal and Child Health.2022; 26(4): 254.     CrossRef
  • Breastfeeding experiences of women with gestational diabetes
    Seungmi Park, Soo-Young Yu
    The Journal of Korean Academic Society of Nursing Education.2021; 27(3): 274.     CrossRef
  • 269 View
  • 4 Download
  • 1 Web of Science
  • 4 Crossref
Close layer
Original Articles
Developing a Home Care Nursing Information System by utilizing Wire-Wireless Network and Mobile Computing System
Jung Ho Park, Sung Ae Park, Soon Nyoung Yoon, Sung Rye Kang
Journal of Korean Academy of Nursing 2004;34(2):290-296.   Published online March 28, 2017
DOI: https://doi.org/10.4040/jkan.2004.34.2.290
AbstractAbstract PDF
Purpose

The purpose of this study was to develop a home care nursing network system for operating home care effectively and efficiently by utilizing a wire-wireless network and mobile computing in order to record and send patients' data in real time, and by combining the headquarter office and the local offices with home care nurses over the Internet. It complements the preceding research from1999 by adding home care nursing standard guidelines and upgrading the PDA program.

Method

Method/1 and Prototyping were adopted to develop the main network system.

Result

The detailed research process is as follows : 1)home care nursing standard guidelines for Diabetes, cancer and peritoneal-dialysis were added in 12 domains of nursing problem fields with nursing assessment/intervention algorithms. 2) complementing the PDA program was done by omitting and integrating the home care nursing algorhythm path which is unnecessary and duplicated. Also, upgrading the PDA system was done by utilizing the machinery and tools where the PDA and the data transmission modem are integrated, CDMX-1X base construction, in order to reduce a transmission error or transmission failure.

Citations

Citations to this article as recorded by  
  • Development and Application of a Web-based Expert System using Artificial Intelligence for Management of Mental Health by Korean Emigrants
    Jeongyee Bae
    Journal of Korean Academy of Nursing.2013; 43(2): 203.     CrossRef
  • Developing an Electronic Nursing Record System for Clinical Care and Nursing Effectiveness Research in a Korean Home Healthcare Setting
    EUN JOO LEE, MIKYOUNG LEE, SUE MOORHEAD
    CIN: Computers, Informatics, Nursing.2009; 27(4): 234.     CrossRef
  • 103 View
  • 2 Download
  • 2 Crossref
Close layer
A Study on the Knowledge Structure of Cancer Survivors based on Social Network Analysis
Sun Young Kwon, Ka Ryeong Bae
J Korean Acad Nurs 2016;46(1):50-58.   Published online February 29, 2016
DOI: https://doi.org/10.4040/jkan.2016.46.1.50
AbstractAbstract PDF
Purpose

The purpose of this study was to identify the knowledge structure of cancer survivors.

Methods

For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords.

Results

According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'.

Conclusion

Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

Citations

Citations to this article as recorded by  
  • Effectiveness of Self-Assessment, TAilored Information, and Lifestyle Management for Cancer Patients’ Returning to Work (START): A Multi-center, Randomized Controlled Trial
    Danbee Kang, Ka Ryeong Bae, Yeojin Ahn, Nayeon Kim, Seok Jin Nam, Jeong Eon Lee, Se Kyung Lee, Young Mog Shim, Dong Hyun Sinn, Seung Yeop Oh, Mison Chun, Jaesung Heo, Juhee Cho
    Cancer Research and Treatment.2023; 55(2): 419.     CrossRef
  • Web-Based Research Trends on Child and Adolescent Cancer Survivors Over the Last 5 Years: Text Network Analysis and Topic Modeling Study
    Hyun-Yong Kim, Kyung-Ah Kang, Suk-Jung Han, Jiyoung Chun
    Journal of Medical Internet Research.2022; 24(2): e32309.     CrossRef
  • Network analysis based on big data in social media of Korean adolescents’ diet behaviors
    JongHwi Song, SooYeun Yoo, JunRyul Yang, SangKyun Yun, YunHee Shin, Girish C. Melkani
    PLOS ONE.2022; 17(8): e0273570.     CrossRef
  • An Overview of Cognitive Reserve in Aging Based on Keyword Network Analysis
    Jihyun Kim, Mi So Kim
    INQUIRY: The Journal of Health Care Organization, Provision, and Financing.2022;[Epub]     CrossRef
  • Analysis of research on metabolic syndrome in cancer survivors using topic modeling and social network analysis
    Ji-Su Kim, Hyejin Kim, Eunkyung Lee, Yeji Seo
    Science Progress.2021;[Epub]     CrossRef
  • An Identification of the Knowledge Structure on the Resilience of Caregivers of People with Dementia using a Text Network Analysis
    Eun Young Kim, Sung Ok Chang
    Journal of Korean Gerontological Nursing.2021; 23(1): 66.     CrossRef
  • Research Topics and Trends in Interprofessional Education in Nursing
    Kisook Kim, Ki-Seong Lee
    CIN: Computers, Informatics, Nursing.2021; 39(10): 554.     CrossRef
  • Social Determinants of Health of Multicultural Adolescents in South Korea: An Integrated Literature Review (2018~2020)
    Youlim Kim, Hyeonkyeong Lee, Hyeyeon Lee, Mikyung Lee, Sookyung Kim, Kennedy Diema Konlan
    Journal of Korean Academy of Community Health Nursing.2021; 32(4): 430.     CrossRef
  • A Network Analysis of Research Topics and Trends in End-of-Life Care and Nursing
    Kisook Kim, Seung Gyeong Jang, Ki-Seong Lee
    International Journal of Environmental Research and Public Health.2021; 18(1): 313.     CrossRef
  • Research Trends on Factors Influencing the Quality of Life of Cancer Survivors: Text Network Analysis and Topic Modeling Approach
    Jin-Hee Park, Mison Chun, Sun Hyoung Bae, Hee-Jun Kim
    Asian Oncology Nursing.2021; 21(4): 231.     CrossRef
  • Knowledge Structure of Nursing Studies on Heart Failure Patients in South Korea through Text Network Analysis
    Seang Ryu, Hyunyoung Park, Yun-Hee Kim
    Korean Journal of Adult Nursing.2020; 32(4): 409.     CrossRef
  • Semantic Network Analysis of Iussues Related to Mental Illness in Korea Media: Focusing on the Five Major Media from 2016 to 2018
    Sun Joo Park, Na Ri Shin, Seung Hye Kim, Su Bin Park, Chul Eung Kim
    Journal of Korean Neuropsychiatric Association.2020; 59(1): 72.     CrossRef
  • Identification of the Knowledge Structure of Cancer Survivors’ Return to Work and Quality of Life: A Text Network Analysis
    Kisook Kim, Ki-Seong Lee
    International Journal of Environmental Research and Public Health.2020; 17(24): 9368.     CrossRef
  • Using Text Network Analysis for Analyzing Academic Papers in Nursing
    Chan Sook Park
    Perspectives in Nursing Science.2019; 16(1): 12.     CrossRef
  • Identification of Knowledge Structure of Pain Management Nursing Research Applying Text Network Analysis
    Chan Sook Park, Eun-Jun Park
    Journal of Korean Academy of Nursing.2019; 49(5): 538.     CrossRef
  • Exploring the Knowledge Structure of Nursing Care for Older Patients With Delirium
    Jung Eun Choi, Mi So Kim
    CIN: Computers, Informatics, Nursing.2018; 36(5): 216.     CrossRef
  • A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis
    Eun-Jun Park, Youngji Kim, Chan Sook Park
    Journal of Korean Academy of Nursing.2017; 47(5): 600.     CrossRef
  • The Network Analysis of Nursing Diagnoses for Children Admitted in Pediatric Units Determined by Nursing Students
    Mikyung Moon
    Journal of Health Informatics and Statistics.2017; 42(3): 223.     CrossRef
  • 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 Lee, Kwang-Ok Park, GyeongAe Seomun, Miyoung Kim, Jee-In Hwang, Soyoung Yu, Seok Hee Jeong, Min Jung, Mikyung Moon
    Journal of Korean Academy of Nursing Administration.2017; 23(1): 101.     CrossRef
  • Social Network Analysis on Mapping the Knowledge Structure of Dementia Research
    Jung-Hee Han, Young-Hee Yom
    Journal of Korean Gerontological Nursing.2017; 19(2): 69.     CrossRef
  • 195 View
  • 1 Download
  • 20 Crossref
Close layer
A Social Network Analysis of Research Topics in Korean Nursing Science
Soo-Kyoung Lee, Senator Jeong, Hong-Gee Kim, Young-Hee Yom
J Korean Acad Nurs 2011;41(5):623-632.   Published online October 31, 2011
DOI: https://doi.org/10.4040/jkan.2011.41.5.623
AbstractAbstract PDF
Purpose

This study was done to explore the knowledge structure of Korean Nursing Science.

Methods

The main variables were key words from the research papers that were presented in the Journal of Korean Academy of Nursing and journals of the seven branches of the Korean Academy of Nursing. English titles and abstracts of the papers (n=5,936) published from 1995 through 2009 were included. Noun phrases were extracted from the corpora using an in-house program (BiKE Text Analyzer), and their co-occurrence networks were generated via a cosine similarity measure, and then the networks were analyzed and visualized using Pajek, a Social Network Analysis program.

Results

With the hub and authority measures, the most important research topics in Korean Nursing Science were identified. Newly emerging topics by three-year period units were observed as research trends.

Conclusion

This study provides a systematic overview on the knowledge structure of Korean Nursing Science. The Social Network Analysis for this study will be useful for identifying the knowledge structure in Nursing Science.

Citations

Citations to this article as recorded by  
  • Exploring the Knowledge Structures of Korean and International Nursing Research on Premature Infants Using Text Network Analysis
    Myeong Seon Lee, Seonah Lee
    CIN: Computers, Informatics, Nursing.2024; 42(2): 109.     CrossRef
  • Natural Language Processing Application in Nursing Research
    Minji Mun, Aeri Kim, Kyungmi Woo
    CIN: Computers, Informatics, Nursing.2024; 42(12): 889.     CrossRef
  • Identifying Latent Topics and Trends in Premature Infant–Related Nursing Studies Using a Latent Dirichlet Allocation Method
    Myeong Seon Lee, Seonah Lee
    CIN: Computers, Informatics, Nursing.2023; 41(12): 957.     CrossRef
  • Research trends related to problematic smartphone use among school-age children including parental factors: a text network analysis
    Eun Jee Lee
    Child Health Nursing Research.2023; 29(2): 128.     CrossRef
  • Analysis of School Commuting Safety and Accident Trend by School Level: Text Network Analysis and Topic Modeling
    Beomjun Kim, Gwanjun Kim, Inseon Park
    Fire Science and Engineering.2023; 37(4): 60.     CrossRef
  • Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis
    Yeji Seo, Kyunghee Kim, Ji-Su Kim
    International Journal of Environmental Research and Public Health.2021; 18(8): 3963.     CrossRef
  • An Identification of the Knowledge Structure on the Resilience of Caregivers of People with Dementia using a Text Network Analysis
    Eun Young Kim, Sung Ok Chang
    Journal of Korean Gerontological Nursing.2021; 23(1): 66.     CrossRef
  • Analysis of research on metabolic syndrome in cancer survivors using topic modeling and social network analysis
    Ji-Su Kim, Hyejin Kim, Eunkyung Lee, Yeji Seo
    Science Progress.2021;[Epub]     CrossRef
  • Text network analysis of research topics and trends on global health nursing literature from 1974 ‐2017
    Hye Sun Hong, Soo‐Kyoung Lee
    Journal of Advanced Nursing.2021; 77(3): 1325.     CrossRef
  • Identification of the Knowledge Structure of Cancer Survivors’ Return to Work and Quality of Life: A Text Network Analysis
    Kisook Kim, Ki-Seong Lee
    International Journal of Environmental Research and Public Health.2020; 17(24): 9368.     CrossRef
  • Knowledge Structure of Nursing Studies on Heart Failure Patients in South Korea through Text Network Analysis
    Seang Ryu, Hyunyoung Park, Yun-Hee Kim
    Korean Journal of Adult Nursing.2020; 32(4): 409.     CrossRef
  • Analysis of Research on Nurses’ Job Stress Using Network Analysis
    Young-Su Kim, Soo-Kyoung Lee
    Western Journal of Nursing Research.2019; 41(3): 338.     CrossRef
  • Identification of Knowledge Structure of Pain Management Nursing Research Applying Text Network Analysis
    Chan Sook Park, Eun-Jun Park
    Journal of Korean Academy of Nursing.2019; 49(5): 538.     CrossRef
  • Using Text Network Analysis for Analyzing Academic Papers in Nursing
    Chan Sook Park
    Perspectives in Nursing Science.2019; 16(1): 12.     CrossRef
  • A Literature Review of the Studies on Cultural Competency of Nurses and Nursing Students in Korea
    Min-A Kim, So-Eun Choi
    Journal of Korean Academy of Community Health Nursing.2018; 29(4): 450.     CrossRef
  • Co-occurrence Network Analysis of Keywords in Geriatric Frailty
    Youngji Kim, Soong-nang Jang, Jung Lim Lee
    Journal of Korean Academy of Community Health Nursing.2018; 29(4): 429.     CrossRef
  • The Network Analysis of Nursing Diagnoses for Children Admitted in Pediatric Units Determined by Nursing Students
    Mikyung Moon
    Journal of Health Informatics and Statistics.2017; 42(3): 223.     CrossRef
  • A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis
    Eun-Jun Park, Youngji Kim, Chan Sook Park
    Journal of Korean Academy of Nursing.2017; 47(5): 600.     CrossRef
  • Social Network Analysis on Mapping the Knowledge Structure of Dementia Research
    Jung-Hee Han, Young-Hee Yom
    Journal of Korean Gerontological Nursing.2017; 19(2): 69.     CrossRef
  • Analysis of Students Experience related of Nursing Management Clinical Practice: Text Network Analysis Method
    Kyeong Hwa Kang, Soyoung Yu
    Journal of Korean Academy of Nursing Administration.2016; 22(1): 80.     CrossRef
  • Exploratory Study of Publicness in Healthcare Sector through Text Network Analysis
    Hye Sook Min, Chang-Yup Kim
    Health Policy and Management.2016; 26(1): 51.     CrossRef
  • The Analysis of Knowledge Structure using Co-word Method in Quality Management Field
    Man-Hee Park
    Journal of the Korean society for quality management.2016; 44(2): 389.     CrossRef
  • Social Network Analysis of author's interest area in Journals about Computer
    Ju-Yeon Lee, Yoo-Hyun Park
    Journal of the Korea Institute of Information and Communication Engineering.2016; 20(1): 193.     CrossRef
  • Knowledge Structure of the Korean Journal of Occupational Health Nursing through Network Analysis
    Sun Young Kwon, Eun Jung Park
    Korean Journal of Occupational Health Nursing.2015; 24(2): 76.     CrossRef
  • A Critical Discussion on the Academic Fundamentals and the Missions of Child Health Nursing
    Kap-Chul Cho
    Child Health Nursing Research.2015; 21(4): 311.     CrossRef
  • Trends of research articles in the <i>Korean Journal of Medical Education</i> by social network analysis
    Hyo Hyun Yoo, Sein Shin
    Korean Journal of Medical Education.2015; 27(4): 247.     CrossRef
  • Visualization of e-Health Research Topics and Current Trends Using Social Network Analysis
    Youn-Jung Son, Senator Jeong, Byeong-Gwon Kang, Sun-Hyung Kim, Soo-Kyoung Lee
    Telemedicine and e-Health.2015; 21(5): 436.     CrossRef
  • Development of u-Health standard terminology and guidelines for terminology standardization
    Soo-Kyoung Lee
    Journal of the Korea Academia-Industrial cooperation Society.2015; 16(6): 4056.     CrossRef
  • A Study on the Factors Influencing Semantic Relation in Building a Structured Glossary
    Sun-Young Kwon
    Journal of the Korean Society for Library and Information Science.2014; 48(2): 353.     CrossRef
  • Social network analysis on consumers' seeking behavior of health information via the Internet and mobile phones
    Ji-Young An, Haeran Jang, Jinkyung Paik
    Journal of Korea Multimedia Society.2014; 17(8): 995.     CrossRef
  • Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information
    Haeran Jang, Ji-Young An
    Healthcare Informatics Research.2014; 20(3): 216.     CrossRef
  • Application of Social Network Analysis to Health Care Sectors
    Hae Lan Jang, Young Sung Lee, Ji-Young An
    Healthcare Informatics Research.2012; 18(1): 44.     CrossRef
  • Book Review: Social Networks and Health: Models, Methods, and Applications
    Ji-Young An
    Healthcare Informatics Research.2012; 18(4): 287.     CrossRef
  • 162 View
  • 1 Download
  • 33 Crossref
Close layer
Correlation of Social Network Types on Health Status of Korean Elders
Eui-Young Cheon
J Korean Acad Nurs 2010;40(1):88-98.   Published online February 28, 2010
DOI: https://doi.org/10.4040/jkan.2010.40.1.88
AbstractAbstract PDF
Purpose

The purpose of this study was to identify the social network types of elders and to identify differences among latent classes by social network.

Methods

The data of 312 elders used in this study were collected from health, welfare, and other facilities and from elders living in the community. The interviews were conducted from July 16 to September 30, 2007 using a standard, structured questionnaire. Descriptive statistics, one way ANOVA with the SPSS 15.0 program and latent class analysis using Maximum Likelihood Latent Structure Analysis (MLLSA) program were used to analyze the data.

Results

Using latent class analysis, social network types among older adults were identified as diverse for 58.0% of the sample, as family for 34.0%, and as isolated for 8.0%. The health status of respondents differed significantly by network type. Elders in diverse networks had significantly higher health status and elders in isolated networks had significantly lower physical health status on average than those in all other networks.

Conclusion

The results of this study suggest that these network types have important practical implications for health status of elders. Social service programs should focus on different groups based on social network type and promote social support and social integration.

Citations

Citations to this article as recorded by  
  • Social Network Analysis of Self‐Management Behavior Among Older Adults With Diabetes
    Geumbo Ko, Youngshin Song
    Public Health Nursing.2025;[Epub]     CrossRef
  • Social Network Contact Frequency and Life Satisfaction of the Elderly: Focusing on the Moderating Effect of Digital Capabilities
    Eun Hye Kim
    Human Ecology Research.2024; 62(2): 217.     CrossRef
  • Always alone? Network transitions among detached older Europeans and their effects
    Howard Litwin, Michal Levinsky
    Ageing and Society.2021; 41(10): 2299.     CrossRef
  • Multilevel Factors Associated with Frailty among the Rural Elderly in Korea Based on the Ecological Model
    Ah Ram Jang, Ju Young Yoon
    International Journal of Environmental Research and Public Health.2021; 18(8): 4146.     CrossRef
  • The Role of Social Networks on Depressive Symptoms: A Comparison of Older Koreans in Three Geographic Areas
    Nan Sook Park, Yuri Jang, David A. Chiriboga, Soondool Chung
    The International Journal of Aging and Human Development.2021; 92(3): 364.     CrossRef
  • Association between social network structure and physical activity in middle-aged Korean adults
    So Mi Jemma Cho, Hokyou Lee, Jee-Seon Shim, Yoosik Youm, Sun Jae Jung, Dae Jung Kim, Hyeon Chang Kim
    Social Science & Medicine.2021; 282: 114112.     CrossRef
  • A Typology of Social Networks and Its Relationship to Psychological Well-Being in Korean Adults
    Nan Sook Park, David A. Chiriboga, Soondool Chung
    The International Journal of Aging and Human Development.2020; 90(3): 211.     CrossRef
  • Social network types, health, and well-being of older Asian Americans
    Nan Sook Park, Yuri Jang, David A. Chiriboga, Soondool Chung
    Aging & Mental Health.2019; 23(11): 1569.     CrossRef
  • A Urban-Rural Differences of Social Environment
    Junga Lee
    Journal of Digital Contents Society.2019; 20(4): 817.     CrossRef
  • Social support networks in Chinese older adults: health outcomes and health related behaviors: a path analysis
    Qi Xiao, Meiliyang Wu, Tieying Zeng
    Aging & Mental Health.2019; 23(10): 1382.     CrossRef
  • Social Support Networks and Quality of Life of Rural Men in a Context of Marriage Squeeze in China
    Sasa Wang, Xueyan Yang, Isabelle Attané
    American Journal of Men's Health.2018; 12(4): 706.     CrossRef
  • Associations of a social network typology with physical and mental health risks among older adults in South Korea
    N.S. Park, Y. Jang, B.S. Lee, D.A. Chiriboga, S. Chang, S.Y. Kim
    Aging & Mental Health.2018; 22(5): 631.     CrossRef
  • Social Network Types, Health, and Health-Care Use Among South Korean Older Adults
    Sojung Park, Ji Young Kang, Letha A. Chadiha
    Research on Aging.2018; 40(2): 131.     CrossRef
  • A Preliminary Study for the Development and Validation of an Instrument to Measure Social Environment Influencing Health
    Junga Lee
    Journal of Digital Contents Society.2018; 19(11): 2093.     CrossRef
  • Social network types among older Korean adults: Associations with subjective health
    Sung Yun Sohn, Won-tak Joo, Woo Jung Kim, Se Joo Kim, Yoosik Youm, Hyeon Chang Kim, Yeong-Ran Park, Eun Lee
    Social Science & Medicine.2017; 173: 88.     CrossRef
  • Risk Factors for Social Isolation in Older Korean Americans
    Yuri Jang, Nan Sook Park, David A. Chiriboga, Hyunwoo Yoon, Jisook Ko, Juyoung Lee, Miyong T. Kim
    Journal of Aging and Health.2016; 28(1): 3.     CrossRef
  • Longitudinal changes in social networks, health and wellbeing among older Koreans
    BORIN KIM, SOJUNG PARK, TONI C. ANTONUCCI
    Ageing and Society.2016; 36(9): 1915.     CrossRef
  • An Empirical Typology of Social Networks and Its Association With Physical and Mental Health: A Study With Older Korean Immigrants
    N. S. Park, Y. Jang, B. S. Lee, J. E. Ko, W. E. Haley, D. A. Chiriboga
    The Journals of Gerontology Series B: Psychological Sciences and Social Sciences.2015; 70(1): 67.     CrossRef
  • Prediction of Quality of Life among the Elderly at Care Facilities for the Elderly according to Health States, Physical and Cognitive Functions, and Social Supports-Focused on D Metropolitan City
    Jong-Im Kim
    Journal of the Korea Academia-Industrial cooperation Society.2015; 16(7): 4656.     CrossRef
  • Confidant Network Types and Well-Being Among Older Europeans
    H. Litwin, K. J. Stoeckel
    The Gerontologist.2014; 54(5): 762.     CrossRef
  • Social network properties and self-rated health in later life: comparisons from the Korean social life, health, and aging project and the national social life, health and aging project
    Yoosik Youm, Edward O Laumann, Kenneth F Ferraro, Linda J Waite, Hyeon Chang Kim, Yeong-Ran Park, Sang Hui Chu, Won-tak Joo, Jin A Lee
    BMC Geriatrics.2014;[Epub]     CrossRef
  • Social Activities and Health of Korean Elderly Women by Age Groups
    Ju-hyun Kim, Minhye Kim, Joongbaeck Kim
    Educational Gerontology.2013; 39(9): 640.     CrossRef
  • Social network type and health-related behaviors: Evidence from an American national survey
    Sharon Shiovitz-Ezra, Howard Litwin
    Social Science & Medicine.2012; 75(5): 901.     CrossRef
  • Social Network Type and Subjective Well-being in a National Sample of Older Americans
    H. Litwin, S. Shiovitz-Ezra
    The Gerontologist.2011; 51(3): 379.     CrossRef
  • The Association of Background and Network Type Among Older Americans
    Howard Litwin, Sharon Shiovitz-Ezra
    Research on Aging.2011; 33(6): 735.     CrossRef
  • 208 View
  • 5 Download
  • 25 Crossref
Close layer
Effects of a Network Program for Preventing Obesity of Patients Taking Antipsychotics or Antidepressants
Soyaja Kim, Kyung Mi Sung, Young Sin Hwang, Sook Ja Kim
Journal of Korean Academy of Nursing 2005;35(3):526-534.   Published online June 30, 2005
DOI: https://doi.org/10.4040/jkan.2005.35.3.526
AbstractAbstract PDF
Purpose

This study was designed to investigate the effects of a network program to prevent obesity and improve dietary habits for patients taking antipsychotics or antidepressants.

Method

Thirty-seven patients in two hospitals were assigned to a control group (21 patients) or an intervention group (16 patients). The intervention group was evaluated to analyze the effect of the network program for six weeks after the program.

Result

There was a difference in the rate of increased body weight between the control group and the intervention group. Notably, the body weight of both groups before the intervention was significantly increased. However, after the intervention the body weight of the intervention group rarely increased, whereas, the body weight of the control group was significantly increased as expected. There was an observed difference in diet between the control group and the intervention group. After the intervention, caloric intake per day of the intervention group decreased. Also, the duration of the meal of the intervention group after the intervention was longer than before.

Conclusion

The network program for preventing obesity and improving dietary habits of patients taking antipsychotics or antidepressants was effective. The study shows that a network program can be an important part of a nursing intervention in clinical practice.

Citations

Citations to this article as recorded by  
  • Review of Nursing Research on Psychotropic Drugs in Korea
    Jongeun Lee, Jeongyee Bae, Sookbin Im
    Journal of Korean Public Health Nursing.2013; 27(2): 338.     CrossRef
  • Effects of Weight Control Program on Body Weight and the Sense of Efficacy for Control of Dietary Behavior of Psychiatric Inpatients
    Mi Na Hong, Geum Sun Baek, Yong Hee Han, Myung Soon Kwon
    Journal of Korean Academy of Nursing.2008; 38(4): 533.     CrossRef
  • 106 View
  • 0 Download
  • 2 Crossref
Close layer

J Korean Acad Nurs : Journal of Korean Academy of Nursing
Close layer
TOP