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Keyword Network Analysis and Topic Modeling of News Articles Related to Artificial Intelligence and Nursing
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Ju-Young Ha, Hyo-Jin Park
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J Korean Acad Nurs 2023;53(1):55-68. Published online February 28, 2023
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DOI: https://doi.org/10.4040/jkan.22117
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 Abstract
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- 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.
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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
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Effects of First Assisted Reproductive Technologies on Anxiety and Depression among InfertileWomen: A Systematic Review and Meta-Analysis
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Ju-Young Ha, Seon-Hwa Ban, Hae-Jung Lee, Misoon Lee
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J Korean Acad Nurs 2020;50(3):369-384. Published online June 30, 2020
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DOI: https://doi.org/10.4040/jkan.19187
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Abstract
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- Purpose
The purpose of this study was to analyze anxiety and depression among infertile women at different time points during the firstIn Vitro Fertilization (IVF) or Intracytoplasmic Sperm Injection (ICSI) treatment through a systematic review and meta-analysis.
Methods
Seven out of 3,011 studies were included for meta-analysis. To estimate the effect size, a meta-analysis of the studies was performedusing the RevMan 5.3 program. We compared the measurement outcomes at three time points: before the start of treatment (T0), cancellationof treatment after pregnancy detection (T2), one to six months after treatment (T3). The effect size used was the standardizedmean difference (SMD).
Results
In comparing the different time points of the pregnant women from their cycle, significantly lower levelsof depression were found at T2 than at T0. In non-pregnant women, anxiety at T2 and depression at T2 and T3 were significantly higherthan those at T0. At T2 and T3, the non-pregnant women reported higher levels of anxiety and depression compared with the pregnantwomen.
Conclusion
Anxiety and depression in infertile women undergoing the first IVF or ICSI are associated with the time points andpregnancy status after treatment. These findings suggest that attention should be paid to helping infertile women prepare for and copewith treatment and treatment failure.
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Citations
Citations to this article as recorded by - Effect of Stress on Each of the Stages of the IVF Procedure: A Systematic Review
Anastasia Tsambika Zanettoullis, George Mastorakos, Panagiotis Vakas, Nikolaos Vlahos, Georgios Valsamakis
International Journal of Molecular Sciences.2024; 25(2): 726. CrossRef - An Integrative Review of Psychosocial Intervention Programs for Infertile Females
Youjin Shin, Soo-Hyun Nam
STRESS.2023; 31(4): 158. CrossRef - The dynamics of mental health measures of pre- and postpartum women undergoing assisted reproductive technology
Maria E. Blokh, Varvara O. Anikina, Svetlana S. Savenysheva, Maria I. Levintsova
Journal of obstetrics and women's diseases.2023; 72(1): 17. CrossRef
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Effect of Smartphone Apps Applying BodyThink Program on Obesity in Adolescent Girls
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Min-Kyung Jun, Ju-Young Ha
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J Korean Acad Nurs 2016;46(3):390-399. Published online June 30, 2016
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DOI: https://doi.org/10.4040/jkan.2016.46.3.390
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Abstract
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Purpose
The purpose of this study was to determine the effects of smartphone apps applying BodyThink program on BMI, percentage of body fat, skeletal muscle rate, body image, and self-esteem of adolescent girls.
Methods
Sixty-eight high school girls with a BMI of over 25kg/m2 were recruited to participate in this study. Girls from four schools were divided into two groups: the experimental group, which used the smartphone apps applying BodyThink program, and the control group, which used smartphone apps and small group counseling. The experimental group received the BodyThink program 6 times, scheduled once a week, with each session lasting 40~50 minutes. Test measures were completed before and after the 6 week intervention period for all participants. Collected data was analyzed using Shapiro-Wilk test, descriptive statistics, χ2 test, independent t-test, Mann-Whitney U test with the SPSS/WIN 18.0 program.
Results
The girls in the experimental group significantly improved their results in BMI(Z=-1.67, p=.042), percentage of body fat (Z=-3.01, p=.001), skeletal muscle rate (t=-3.50, p<.001), and self-esteem (t=2.66, p=.005) after the program, compared to the girls in the control group.
Conclusion
Mobile applications applying psychological and emotional intervention programs have the potential to be effective alternative methods to improve the body composition and self-esteem of obese adolescent girls.
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Citations
Citations to this article as recorded by - Effectiveness of a virtual reality application‐based education programme on patient safety management for nursing students: A pre‐test–post‐test study
Jae Woo Oh, Ji Eun Kim
Nursing Open.2023; 10(12): 7622. CrossRef - Effects of a novel mobile health intervention compared to a multi-component behaviour changing program on body mass index, physical capacities and stress parameters in adolescents with obesity: a randomized controlled trial
A. Stasinaki, D. Büchter, C.-H. I. Shih, K. Heldt, S. Güsewell, B. Brogle, N. Farpour-Lambert, T. Kowatsch, D. l’Allemand
BMC Pediatrics.2021;[Epub] CrossRef - A Technology-Mediated Interventional Approach to the Prevention of Metabolic Syndrome: A Systematic Review and Meta-Analysis
Gaeun Kim, Ji-Soo Lee, Soo-Kyoung Lee
International Journal of Environmental Research and Public Health.2021; 18(2): 512. CrossRef - Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study
Ji-Soo Lee, Min-Ah Kang, Soo-Kyoung Lee
Journal of Medical Internet Research.2020; 22(7): e17031. CrossRef - Multidimensional Cognitive Behavioral Therapy for Obesity Applied by Psychologists Using a Digital Platform: Open-Label Randomized Controlled Trial
Meelim Kim, Youngin Kim, Yoonjeong Go, Seokoh Lee, Myeongjin Na, Younghee Lee, Sungwon Choi, Hyung Jin Choi
JMIR mHealth and uHealth.2020; 8(4): e14817. CrossRef - Current Barriers of Obesity Management of Children Using Community Child Care Centers and Potential Possibility of Utilizing Mobile Phones: A Qualitative Study for Children and Caregivers
Bo Young Lee, Mi-Young Park, Kirang Kim, Jea Eun Shim, Ji-Yun Hwang
Korean Journal of Community Nutrition.2020; 25(3): 189. CrossRef
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