Research trends related to childhood and adolescent cancer survivors in South Korea using word co-occurrence network analysis

ChatGPT integration within nursing education and its implications for nursing students: A systematic review and text network analysis

OBJECTIVE

This study aimed to explore prevalent topics related to integrating ChatGPT into nursing education, specifically focusing on its impact on nursing students.

DESIGN

A systematic review and text network analysis were conducted.

DATA SOURCES

Full-text articles from reputable scientific databases, including PubMed, Scopus, and ScienceDirect, along with relevant articles identified through Google Scholar, were utilized, and the search period ranged from January 20th to January 23rd, 2024.

REVIEW METHODS

The review centered on the main text of the articles, which were initially converted from PDFs to TXT files. Text cleaning and preprocessing were conducted using Python 3.11, followed by text analysis performed with InfraNodus.

RESULTS

Of 145 articles, 46 full-text articles were included in the final analysis. Four key topical clusters were identified: Academic Writing, Healthcare Simulation, Data Modeling, and Personal Development. Sentiments regarding the integration of ChatGPT into nursing education and its impact on nursing students were primarily positive (48 %), with a notable percentage expressing negative views (31 %) and a smaller proportion indicating neutrality (21 %).

CONCLUSION

This study highlights the transformative potential of ChatGPT in nursing education, advocating for its responsible integration to empower nursing students with advanced skills and uphold ethical standards in artificial intelligence (AI) utilization. The identified four topics and the sentiments are crucial for guiding educators, researchers, and practitioners in nursing education to navigate the integration of AI tools effectively. Further research and exploration in these areas can contribute to the ongoing discourse on the intersection of technology and nursing education.

Perspectives of Frontline Nurses Working in South Korea during the COVID-19 Pandemic: A Combined Method of Text Network Analysis and Summative Content Analysis

PURPOSE

This study aimed to explore the perspectives of frontline nurses working during the novel coronavirus disease 2019 (COVID-19) pandemic.

METHODS

An online qualitative study was conducted using a pragmatic approach. The data were collected in August 2021. Registered Korean nurses who provided direct nursing care to patients with confirmed COVID-19 were eligible for this study. An online survey was used to gather free-text data, which were then analyzed using machine-based network analysis and summative content analysis.

RESULTS

The analysis examined the responses of 126 participants and led to the identification of six prominent themes. These themes were further classified into three distinct levels: personal, task, and organizational. The identified themes are as follows: "collapse of personal life," "being overwhelmed by the numerous roles required," "personal protective equipment was sufficiently provided, but that is not enough," "changes in interprofessional collaboration," "inappropriate workforce management," and "diverted allocation of healthcare services and resources."

CONCLUSION

Our findings highlight areas for improvement in resources, systems, and policies to enhance preparedness for future pandemics.

Research trends over 10 years (2010-2021) in infant and toddler rearing behavior by family caregivers in South Korea: text network and topic modeling

PURPOSE

This study analyzed research trends in infant and toddler rearing behavior among family caregivers over a 10-year period (2010-2021).

METHODS

Text network analysis and topic modeling were employed on data collected from relevant papers, following the extraction and refinement of semantic morphemes. A semantic-centered network was constructed by extracting words from 2,613 English-language abstracts. Data analysis was performed using NetMiner 4.5.0.

RESULTS

Frequency analysis, degree centrality, and eigenvector centrality all revealed the terms ''scale," ''program," and ''education" among the top 10 keywords associated with infant and toddler rearing behaviors among family caregivers. The keywords extracted from the analysis were divided into two clusters through cohesion analysis. Additionally, they were classified into two topic groups using topic modeling: "program and evaluation" (64.37%) and "caregivers' role and competency in child development" (35.63%).

CONCLUSION

The roles and competencies of family caregivers are essential for the development of infants and toddlers. Intervention programs and evaluations are necessary to improve rearing behaviors. Future research should determine the role of nurses in supporting family caregivers. Additionally, it should facilitate the development of nursing strategies and intervention programs to promote positive rearing practices.

Exploring Korean adolescent stress on social media: a semantic network analysis

Background

Considering that adolescents spend considerable time on the Internet and social media and experience high levels of stress, it is difficult to find a study that investigates adolescent stress through a big data-based network analysis of social media. Hence, this study was designed to provide basic data to establish desirable stress coping strategies for adolescents based on a big data-based network analysis of social media for Korean adolescent stress. The purpose of this study was to (1) identify social media words that express stress in adolescents and (2) investigate the associations between those words and their types.

Methods

To analyse adolescent stress, we used social media data collected from online news and blog websites and performed semantic network analysis to understand the relationships among keywords extracted in the collected data.

Results

The top five words used by Korean adolescents were counselling, school, suicide, depression, and activity in online news, and diet, exercise, eat, health, and obesity in blogs. As the top keywords of the blog are mainly related to diet and obesity, it reflects adolescents' high degree of interest in their bodies; the body is also a primary source of adolescent stress. In addition, blogs contained more content about the causes and symptoms of stress than online news, which focused more on stress resolution and coping. This highlights the trend that social blogging is a new channel for sharing personal information.

Conclusions

The results of this study are valuable as they were derived through a social big data analysis of data obtained from online news and blogs, providing a wide range of implications related to adolescent stress. Hence this study can contribute basic data for the stress management of adolescents and their mental health management in the future.

An Overview of Cognitive Reserve in Aging Based on Keyword Network Analysis

Many studies have reported that Cognitive reserve is a critical mechanism affecting cognitive statuses, such as dementia. The purposes of this study were to identify the knowledge structure and the research trend on cognitive reserve by conducting keyword analysis on research papers ranging from the earliest to the most recent studies done on the topic and to suggest directions for future research. The Web of Science (WOS) database was used to search for articles on cognitive reserve in aging from 2001 to 2020. NetMiner version 4 (cyram, KOREA), a social network analysis program, was used for keyword network analysis. Data analysis showed keywords that could be categorized as cognitive reserve related keywords (cognitive reserve related concepts, cognitive reserve related factor, cognitive reserve diagnosis and measurement, cognitive reserve outcomes) and cognitive reserve research keywords (research subject/disease, research method, intervention, research field). Through trend analysis, we found that various keywords appeared, indicating that the research has gradually developed conceptually and methodically. Based on these findings, future CR studies require the development of multimodal interface-based tools by applying modern digital technology that can be used to more accurately diagnose and monitor CR; remotely, in real time. In addition, to improve CR, it is suggested that the development of cognitive stimulation interventions utilizing VR which fuses AI based interaction technology with the subjects. Finally, CR could develop further through a cooperation of multidisciplinary professionals such as psychology, medicine and nursing.