[A social network analysis of research topics in Korean nursing science]

Natural Language Processing Application in Nursing Research: A Study Using Text Network Analysis and Topic Modeling

Although the potential of natural language processing and an increase in its application in nursing research is evident, there is a lack of understanding of the research trends. This study conducts text network analysis and topic modeling to uncover the underlying knowledge structures, research trends, and emergent research themes within nursing literature related to natural language processing. In addition, this study aims to provide a foundation for future scholarly inquiries and enhance the integration of natural language processing in the analysis of nursing research. We analyzed 443 literature abstracts and performed core keyword analysis and topic modeling based on frequency and centrality. The following topics emerged: (1) Term Identification and Communication; (2) Application of Machine Learning; (3) Exploration of Health Outcome Factors; (4) Intervention and Participant Experience; and (5) Disease-Related Algorithms. Nursing meta-paradigm elements were identified within the core keyword analysis, which led to understanding and expanding the meta-paradigm. Although still in its infancy in nursing research with limited topics and research volumes, natural language processing can potentially enhance research efficiency and nursing quality. The findings emphasize the possibility of integrating natural language processing in nursing-related subjects, validating nursing value, and fostering the exploration of essential paradigms in nursing science.

Exploring the Knowledge Structures of Korean and International Nursing Research on Premature Infants Using Text Network Analysis

This study aimed to identify the knowledge structures of Korean and international nursing studies on premature infants using text network analysis, which represents a text as a network graph that describes how keywords are linked. This network graph refers to a knowledge structure. International and Korean journal databases were searched to extract nursing studies regarding premature infants published in academic journals from 1998 to 2020. Abstracts from the selected studies were analyzed using the following four steps: word extraction and refinement, keyword extraction, co-occurrence matrix generation, and text network visualization. The results demonstrated that 182 Korean and 2502 international studies were published. The common keywords of Korean and international studies were "kangaroo mother care," "stress," and "child." The keywords of the international studies had more branches linking to other keywords than those of the Korean studies. Thus, the knowledge structure of international studies included diverse concepts. These findings will serve as important guidance for future research worldwide. Furthermore, studies to develop a more comprehensive knowledge structure of international research on premature infants are needed. The knowledge structure of Korean studies mainly included concepts related to mothers. Korean studies regarding hospitalized premature infants and communication with parents need to be conducted.

Identifying Latent Topics and Trends in Premature Infant-Related Nursing Studies Using a Latent Dirichlet Allocation Method

This study aimed to identify topics and within-topic core keywords in premature infant-related nursing studies published in Korean and international academic journals using topic modeling and to compare and analyze the trends in Korean and international studies. Journal databases were searched to extract nursing studies involving premature infants from 1998 to 2020. Journal databases included MEDLINE, Web of Science, CINAHL, and EMBASE for international studies and DBpia, the National Digital Science Library, the Korea Citation Index, and the Research Information Sharing Service for Korean studies. Abstracts from the selected 182 Korean and 2502 international studies were analyzed using NetMiner4.4.3e. In results, four similar topics (Korean vs international) were "pain intervention" versus "pain management"; "breast feeding practice" versus "breast feeding"; "kangaroo mother care"; and "parental stress" versus "stress & depression." Two topics that appeared only in the international studies were "infection management" and "oral feeding & respiratory care." Overall, the international studies dealt with diverse topics directly associated with premature. Korean studies mainly dealt with topics related to mothers of premature infants, whereas studies related to premature infants were insufficient. Nursing research in Korea needs to be expanded to research topics addressing premature infants.

Research trends related to problematic smartphone use among school-age children including parental factors: a text network analysis

PURPOSE

This study aimed to identify the main keywords and research topics used in research on problematic smartphone use (PSU) among children (6-12 years old), including parental factors.

METHODS

The publication period for the literature was set from January 2007 to January 2022, as smartphones were first released in 2007. In total, 395 articles were identified, 230 of which were included in the final analysis. Text network analysis was performed using NetMiner 4.5.

RESULTS

Research on this topic has steadily increased since 2007, with 40 papers published in 2021. Eight main research topics were derived: group 1, parental attitudes; group 2, children's PSU behavior and parental support; group 3, family environment and behavioral addiction; group 4, social relationships; group 5, seeking solutions; group 6, parent-child relationships; group 7, children's mental health and school adaptation; and group 8, PSU in adolescents.

CONCLUSION

Parental factors related to PSU have been studied in various aspects. However, more active research on school-age children's PSU needs to be conducted due to the paucity of research in this population compared to studies conducted among adolescents. The results of this study provide useful data for selecting research topics in the field of PSU.

Analysis of research on metabolic syndrome in cancer survivors using topic modeling and social network analysis

This study aimed to identify the relationships between the keywords of research on metabolic syndrome in cancer survivors and the entire knowledge research structure, through topic extraction from a macro perspective. From six electronic databases, 918 studies published between 1996 and 2019 were identified and reviewed, and 365 were included. Keyword network analysis and topic modeling were applied to examine the studies. In keyword network analysis, "obesity," "treatment," "breast cancer," "body mass index," and "prostate cancer" were the major keywords, whereas "obesity" and "breast" were the dominant keywords and ranked high in frequency, degree centrality, and betweenness centrality. In topic modeling, five clustered topics emerged, namely metabolic syndrome component, post CTX(chemotherapy) sequence, prostate-specific antigen-sensitive plot, lifestyle formation, and insulin fluctuation. Topic 2, post CTX sequence, showed the highest salience in earlier studies, but this has decreased over time, and the themes of the studies have also broadened. This study may provide critical basic data for determining the changing trends of research on metabolic syndrome in cancer survivors and for predicting the direction of future research through the visualization of the effects and interactions between the major keywords in research on metabolic syndrome in cancer survivors.

Trends of Nursing Research on Accidental Falls: A Topic Modeling Analysis

This descriptive study analyzed 1849 international and 212 Korean studies to explore the main topics of nursing research on accidental falls. We extracted only nouns from each abstract, and four topics were identified through topic modeling, which were divided into aspects of fall prevention and its consequences. "Fall prevention program and scale" is popular among studies on the validity of fall risk assessment tools and the development of exercise and education programs. "Nursing strategy for fall prevention" is common in studies on nurse education programs and practice guidelines to improve the quality of patient safety care. "Hospitalization by fall injury" is used in studies about delayed discharge, increased costs, and deaths of subjects with fall risk factors hospitalized at medical institutions due to fall-related injuries. "Long-term care facility falls" is popular in studies about interventions to prevent fall injuries that occur in conjunction with dementia in long-term care facilities. It is necessary to establish a system and policy for fall prevention in Korean medical institutions. This study confirms the trends in domestic and international fall-related research, suggesting the need for studies to address insufficient fall-related policies and systems and translational research to be applied in clinical trials.

Identification of the Knowledge Structure of Cancer Survivors' Return to Work and Quality of Life: A Text Network Analysis

This study aimed to understand the trends in research on the quality of life of returning to work (RTW) cancer survivors using text network analysis. Titles and abstracts of each article were examined to extract terms, including "cancer survivors", "return to work", and "quality of life", which were found in 219 articles published between 1990 and June 2020. Python and Gephi software were used to analyze the data and visualize the networks. Keyword ranking was based on the frequency, degree centrality, and betweenness centrality. The keywords commonly ranked at the top included "breast", "patients", "rehabilitation", "intervention", "treatment", and "employment". Clustering results by grouping nodes with high relevance in the network led to four clusters: "participants and method", "type of research and variables", "RTW and education in adolescent and young adult cancer survivors", and "rehabilitation program". This study provided a visualized overview of the research on cancer survivors' RTW and quality of life. These findings contribute to the understanding of the flow of the knowledge structure of the existing research and suggest directions for future research.

Text network analysis of research topics and trends on global health nursing literature from 1974 -2017

AIMS

The purpose of this study is to examine the relationship between keywords in existing global health nursing studies during 44 years (1974-2017) and to develop schematic diagrams of the relationship between these keywords from a macro perspective. It is to identify the trend of the literature in global health nursing field.

DESIGN

A descriptive bibliometric analysis of publications in global health nursing.

METHODS

The keywords from 7,115 articles and literatures were examined using the Text Rank Analyzer via the applied text network analysis with NetMiner 4.0.

RESULTS

As for global health nursing, keywords with the most frequent appearance and the highest networking degree in centrality were 'study', 'patient', 'nurse', and 'women'. Six central keywords were also found highly related to other keywords: 'global health nursing', 'study', 'patient', 'care', 'nurse', and 'education'. By measuring the degree of keywords connected to other keywords in centrality, six clusters were established. Then, emerging topics assessed by time periods were identified as follows: the beginning phase ('breastfeeding', 'women', and 'children'), the development phase ('quality', 'life', and 'human immunodeficiency virus'), the maturation phase ('mental health', 'depression', and 'global health'), and the expansion phase ('pregnancy', 'palliative care', and 'infectious disease').

CONCLUSION

The identified trends on this study will help nurse leaders to grasp the trends and insights for global health and to train future nurses to serve clients better in the practice fields.

IMPACT

Keywords with the highest appearance and centrality in the network were found in the global health articles. The bibliometric analysis showed various subjects according to the following phases: beginning development maturation and expansion. The awareness of the trend change in the global health helps nursing researchers and educators modify the curriculum of global health nursing and train future nurses to be equipped with the global health competencies.

[Identification of Knowledge Structure of Pain Management Nursing Research Applying Text Network Analysis]

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.

[A Comparison of Hospice Care Research Topics between Korea and Other Countries Using Text Network Analysis]

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.

Analysis of Research on Nurses’ Job Stress Using Network Analysis

This study established a network related to nurses’ job stress by conducting a social network analysis of titles, keywords, and abstracts, and it identified emerging topics of research. NetMiner 4.0 visualized an interconnection between critical keywords and investigated their frequency of appearance to construe the trends in nurses’ job stress measures used in studies conducted over 55 years (1960-2015). Text Rank Analyzer examined a collection of 9,218 keywords from 2,662 studies. The analysis revealed four groups of newly emerging keywords in the research. The following five clusters were identified: concept, subject, method and tool, outcome and response, and solution and management. Thus, if new researchers refer to existing trends to establish the subject of their study, replication studies can be reduced, and the direction of the development of future research on nurses’ job stress can be predicted. Further application of new interventions, development of objective indicators, working environment, and broader participants are needed.

[Trends of research articles in the Korean Journal of Medical Education by social network analysis]

PURPOSE

This aim of this study is to examine trends in medical education research in the Korean Journal of Medical Education(KJME) and suggest improvements for medical education research.

METHODS

The main variables were keywords from research papers that were published in KJME. Abstracts of papers (n=499) that were published from 1991 through 2015 were analyzed by social network analysis (NetMiner 4.0) a common research methodfor trends in academic subjects.

RESULTS

The most central keywords were "medical education," "clinical competence," "medical student," and "curriculum." After introduction into graduate medical school, newly appearing keywords were "professional behavior," "medical humanities," "communication,"and "physician-patient relation." Based on these results, we generated a schematic of the network, in which the five groups before introduction to graduate medical school expanded to nine groups after introduction.

CONCLUSION

Medical education research has been improving qualitatively and quantitatively, and research subjects have been expanded, subdivided, and specific. While KJME has encompassed medical education studies comprehensively, studies on medical students have risen in number. Thus, the studies that are published in KJME were consistent with the direction of journal and a new study on the changes in medical education is being conducted.

Visualization of e-Health Research Topics and Current Trends Using Social Network Analysis

BACKGROUND

E-health has been grown rapidly with significant impact on quality and safety of healthcare. However, there is a large gap between the postulated and empirically demonstrated benefits of e-health technologies and a need for a clearer mapping of its conceptual domains. Therefore, this study aimed to critically review the main research topics and trends of international e-health through social network analysis.

MATERIALS AND METHODS

Medical subject heading terms were used to retrieve 3,023 research articles published from 1979 through 2014 in the PubMed database. We extracted n-grams from the corpus using a text analysis program, generated co-occurrence networks, and then analyzed and visualized the networks using Pajek software. The hub and authority measures identified the most important research topics in e-health. Newly emerging topics by 4-year period units were identified as research trends.

RESULTS

The most important research topics in e-health are personal health records (PHR), health information technology, primary care, mobile health, clinical decision support systems (CDSS), and so on. The eight groups obtained through ego network analysis can be divided into four semantically different areas, as follows: information technology, infrastructure, services, and subjects. Also, four historical trends in e-health research are identified: the first focusing on e-health and telemedicine; the second, PHR and monitoring; the third, CDSS and alert; and the fourth, mobile health and health literacy.

CONCLUSIONS

This study promotes a systematic understanding of e-health by identifying topic networks, thereby contributing to the future direction of e-health research and education.

Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information

Objectives

Utilizing social network analysis, this study aimed to analyze the main keywords in the literature regarding the health literacy of and the use of online health information by aged persons over 65.

Methods

Medical Subject Heading keywords were extracted from articles on the PubMed database of the National Library of Medicine. For health literacy, 110 articles out of 361 were initially extracted. Seventy-one keywords out of 1,021 were finally selected after removing repeated keywords and applying pruning. Regarding the use of online health information, 19 articles out of 26 were selected. One hundred forty-four keywords were initially extracted. After removing the repeated keywords, 74 keywords were finally selected.

Results

Health literacy was found to be strongly connected with 'Health knowledge, attitudes, practices' and 'Patient education as topic.' 'Computer literacy' had strong connections with 'Internet' and 'Attitude towards computers.' 'Computer literacy' was connected to 'Health literacy,' and was studied according to the parameters 'Attitude towards health' and 'Patient education as topic.' The use of online health information was strongly connected with 'Health knowledge, attitudes, practices,' 'Consumer health information,' 'Patient education as topic,' etc. In the network, 'Computer literacy' was connected with 'Health education,' 'Patient satisfaction,' 'Self-efficacy,' 'Attitude to computer,' etc.

Conclusions

Research on older citizens' health literacy and their use of online health information was conducted together with study of computer literacy, patient education, attitude towards health, health education, patient satisfaction, etc. In particular, self-efficacy was noted as an important keyword. Further research should be conducted to identify the effective outcomes of self-efficacy in the area of interest.

Application of social network analysis to health care sectors

OBJECTIVES

This study aimed to examine the feasibility of social network analysis as a valuable research tool for indicating a change in research topics in health care and medicine.

METHODS

Papers used in the analysis were collected from the PubMed database at the National Library of Medicine. After limiting the search to papers affiliated with the National Institutes of Health, 27,125 papers were selected for the analysis. From these papers, the top 100 non-duplicate and most studied Medical Subject Heading terms were extracted. NetMiner V.3 was used for analysis. Weighted degree centrality was applied to the analysis to compare the trends in the change of research topics. Changes in the core keywords were observed for the entire group and in three-year intervals.

RESULTS

The core keyword with the highest centrality value was "Risk Factor," followed by "Molecular Sequence Data," "Neoplasms," "Signal Transduction," "Brain," and "Amino Acid Sequence." Core keywords varied between time intervals, changing from "Molecular Sequence Data" to "Risk Factors" over time. "Risk Factors" was added as a new keyword and its social network was expanded. The slope of the keywords also varied over time: "Molecular Sequence Data," with a high centrality value, had a decreasing slope at certain intervals, whereas "SNP," with a low centrality value, had an increasing slope at certain intervals.

CONCLUSIONS

The social network analysis method is useful for tracking changes in research topics over time. Further research should be conducted to confirm the usefulness of this method in health care and medicine.