Skip Navigation
Skip to contents

J Korean Acad Nurs : Journal of Korean Academy of Nursing

OPEN ACCESS

Author index

Page Path
HOME > Browse articles > Author index
Search
Chan Sook Park 2 Articles
Identification of Knowledge Structure of Pain Management Nursing Research Applying Text Network Analysis
Chan Sook Park, Eun-Jun Park
J Korean Acad Nurs 2019;49(5):538-549.   Published online January 15, 2019
DOI: https://doi.org/10.4040/jkan.2019.49.5.538
AbstractAbstract PDF
Abstract Purpose

This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis.

Methods

321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis.

Results

In both Korean and international studies, the most important, core-keywords were “pain,” “patient,” “pain management,” “registered nurses,” “care,” “cancer,” “need,” “analgesia,” “assessment,” and “surgery.” While some keywords like “education,” “knowledge,” and “patient-controlled analgesia” found to be important in Korean studies; “treatment,” “hospice palliative care,” and “children” were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were “pain and accompanying symptoms,” “target groups of pain management,” and “RNs’ performance of pain management.” It is only in recent years (2016~17), that keywords such as “performance,” “attitude,” “depression,” and “sleep” have become more important in Korean studies than, while keywords such as “assessment,” “intervention,” “analgesia,” and “chronic pain” have become important in international studies.

Conclusion

It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients’ use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.

Citations

Citations to this article as recorded by  
  • Temporal Exploration of New Nurses’ Field Adaptation Using Text Network Analysis
    Shin Hye Ahn, Hye Won Jeong, Seong Gyeong Yang, Ue Seok Jung, Myoung Lee Choi, Heui Seon Kim
    Journal of Korean Academy of Nursing.2024; 54(3): 358.     CrossRef
  • Content Analysis of Patient Safety Incident Reports Using Text Mining: A Secondary Data Analysis
    On-Jeon Baek, Ho Jin Moon, Hyosun Kim, Sun-Hwa Shin
    Korean Journal of Adult Nursing.2024; 36(4): 298.     CrossRef
  • Text Network Analysis of Research Topics and Trends on Simulations Using Virtual Patients in Nursing Education
    Miok Song, Jeong Eun Moon, Aeri Jang
    CIN: Computers, Informatics, Nursing.2023; 41(9): 639.     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
  • 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
  • Content Analysis of Feedback Journals for New Nurses From Preceptor Nurses Using Text Network Analysis
    Shin Hye Ahn, Hye Won Jeong
    CIN: Computers, Informatics, Nursing.2023; 41(10): 780.     CrossRef
  • Capturing New Nurses' Experiences and Supporting Critical Thinking
    Sun Hee Seon, Hye Won Jeong, Deok Ju, Jung A. Lee, Shin Hye Ahn
    CIN: Computers, Informatics, Nursing.2023; 41(6): 434.     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
  • Factors Affecting Nurses’ Performance of Cancer Pain Management in a Tertiary Hospital
    Minhwa Kang, Minjeong Seo
    The Korean Journal of Hospice and Palliative Care.2022; 25(3): 99.     CrossRef
  • Knowledge Structure of Chronic Obstructive Pulmonary Disease Health Information on Health-Related Websites and Patients’ Needs in the Literature Using Text Network Analysis
    Ja Yun Choi, Su Yeon Lim, So Young Yun
    Journal of Korean Academy of Nursing.2021; 51(6): 720.     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
  • 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
  • Effect of Knowledge and Attitudes of Cancer Pain Management and Patient-Centered Care on Performance of Cancer Pain Management among Nurses at an Oncology Unit
    Mikyung Kim, Yun Mi Lee
    Korean Journal of Adult Nursing.2020; 32(1): 57.     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
  • 480 View
  • 8 Download
  • 9 Web of Science
  • 15 Crossref
Close layer
A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis
Eun-Jun Park, Youngji Kim, Chan Sook Park
J Korean Acad Nurs 2017;47(5):600-612.   Published online October 31, 2017
DOI: https://doi.org/10.4040/jkan.2017.47.5.600
AbstractAbstract PDF
Purpose

This study aimed to identify and compare hospice care research topics between Korean and international nursing studies using text network analysis.

Methods

The study was conducted in four steps: 1) collecting abstracts of relevant journal articles, 2) extracting and cleaning keywords (semantic morphemes) from the abstracts, 3) developing co-occurrence matrices and text-networks of keywords, and 4) analyzing network-related measures including degree centrality, closeness centrality, betweenness centrality, and clustering using the NetMiner program. Abstracts from 347 Korean and 1,926 international studies for the period of 1998–2016 were analyzed.

Results

Between Korean and international studies, six of the most important core keywords-“hospice,” “patient,” “death,” “RNs,” “care,” and “family”-were common, whereas “cancer” from Korean studies and “palliative care” from international studies ranked more highly. Keywords such as “attitude,” “spirituality,” “life,” “effect,” and “meaning” for Korean studies and “communication,” “treatment,” “USA,” and “doctor” for international studies uniquely emerged as core keywords in recent studies (2011~2016). Five subtopic groups each were identified from Korean and international studies. Two common subtopics were “hospice palliative care and volunteers” and “cancer patients.”

Conclusion

For a better quality of hospice care in Korea, it is recommended that nursing researchers focus on study topics of patients with non-cancer disease, children and family, communication, and pain and symptom management.

Citations

Citations to this article as recorded by  
  • A knowledge structure of unmet medical needs of people with disabilities
    Jinah Park, Mi So Kim, Kyung-Hwa Choi, Jung Ae Kim, Eunhye Jeong
    Health Informatics Journal.2024;[Epub]     CrossRef
  • 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
  • Research Trends in Family-Centered Care for Children With Chronic Disease
    YeoJin Im, Sunyoung Jung, YoungAh Park, Jeong Hee Eom
    CIN: Computers, Informatics, Nursing.2024; 42(7): 504.     CrossRef
  • Natural Language Processing Application in Nursing Research
    Minji Mun, Aeri Kim, Kyungmi Woo
    CIN: Computers, Informatics, Nursing.2024; 42(12): 889.     CrossRef
  • Exploring the phenomenon of veganphobia in vegan food and vegan fashion
    Yeong-Hyeon Choi, Sangyung Lee
    The Research Journal of the Costume Culture.2024; 32(3): 381.     CrossRef
  • Periodical Co-Occurrence Analysis of Korean and International Research Trends on Residential Satisfaction
    Ju-Yeon Han, Suk-Kyung Kim
    Journal of the Korean Housing Association.2023; 34(3): 021.     CrossRef
  • Content Analysis of Feedback Journals for New Nurses From Preceptor Nurses Using Text Network Analysis
    Shin Hye Ahn, Hye Won Jeong
    CIN: Computers, Informatics, Nursing.2023; 41(10): 780.     CrossRef
  • Analysis of Research Trends in Relation to the Yellow Sea using Text Mining
    Kyu Won Hwang, Jinkyung Kim, Seung-Koo Kang, Gil Mo Kang
    Journal of the Korean Society of Marine Environment and Safety.2023; 29(7): 724.     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
  • Analysis of Telephone Counseling of Patients in Chemotherapy Using Text Mining Technique
    Seoyeon Kim, Jihyun Jung, Heiyoung Kang, Jeehye Bae, Kayoung Sim, Miyoung Yoo, Eunyoung, E. Suh
    Asian Oncology Nursing.2022; 22(1): 46.     CrossRef
  • A Topic Modeling Analysis of the Crisis Response Stage during the COVID-19 Pandemic
    Kyung-Sook Cha, Eun-Man Kim
    International Journal of Environmental Research and Public Health.2022; 19(14): 8331.     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
  • Identifying the Knowledge Structure and Trends of Outreach in Public Health Care: A Text Network Analysis and Topic Modeling
    Sooyeon Park, Jinkyung Park
    International Journal of Environmental Research and Public Health.2021; 18(17): 9309.     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
  • A study on research trends for gestational diabetes mellitus and breastfeeding: Focusing on text network analysis and topic modeling
    Junglim Lee, Youngji Kim, Eunju Kwak, Seungmi Park
    The Journal of Korean Academic Society of Nursing Education.2021; 27(2): 175.     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
  • 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
  • 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
  • Text Network Analysis of Oncology Nursing Studies Published in the Journal of Asian Oncology Nursing
    Miji Kim, Jaehee Jeon, Eunjung Ryu
    Asian Oncology Nursing.2019; 19(4): 193.     CrossRef
  • The Analysis of the Visitors' Experiences in Yeonnam-dong before and after the Gyeongui Line Park Project - A Text Mining Approach -
    Sae-Ryung Kim, Yunwon Choi, Heeyeun Yoon
    Journal of the Korean Institute of Landscape Architecture.2019; 47(4): 33.     CrossRef
  • Research Trend about Complementary and Alternative Therapy in Korea using Text Network Analysis
    Hae Ree Sung, Jung Lim Lee, Youngji Kim, Jeong Sig Kim
    The Korean Journal of Rehabilitation Nursing.2018; 21(2): 61.     CrossRef
  • Text Network Analysis Related to Disclosure of Cancer Diagnosis among Korea and other Countries
    Jin Hui Yun, Eunjung Ryu, So Young Lee
    Asian Oncology Nursing.2018; 18(3): 154.     CrossRef
  • Text Network Analysis of Newspaper Articles on Life-sustaining Treatments
    Eun-Jun Park, Dae Woong Ahn, Chan Sook Park
    Journal of Korean Academy of Community Health Nursing.2018; 29(2): 244.     CrossRef
  • Exploring Research Topics and Trends in Nursing-related Communication in Intensive Care Units Using Social Network Analysis
    Youn-Jung Son, Soo-Kyoung Lee, SeJin Nam, Jae Lan Shim
    CIN: Computers, Informatics, Nursing.2018; 36(8): 383.     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
  • Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service
    Minji Kim, Mona Choi, Yoosik Youm
    Journal of Korean Academy of Nursing.2017; 47(6): 806.     CrossRef
  • 384 View
  • 4 Download
  • 27 Crossref
Close layer

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