Research Article
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2004'ten 2024'e Hemşirelikte Yapay Zeka Trendi: Web of Science'a Dayalı Bibliyometrik Bir Analiz

Year 2024, , 67 - 77, 27.08.2024
https://doi.org/10.58770/joinihp.1481083

Abstract

Bu çalışma hemşirelik alanında yapay zeka ile ilgili yapılan çalışmaların bibliyometrik analiz yöntemiyle incelenmesini amaçlamaktadır. Çalışma verilerine ulaşmak için Web of Science kullanılmıştır. Çalışma 01- 20 Ocak 2024 tarihleri arasında “artificial intelligence OR ChatGPT OR Chatbot AND nursing OR midwifery AND practice OR innovation OR machine learning OR deep learning” anahtar kelimeleri ile taranarak elde edilmiştir. Yapılan tarama sonucunda hemşirelik alanında yapay zeka ile ilgili toplam 164 çalışmaya ulaşılmıştır. Yapılan çalışmaların %65.85’inin araştırma makalesi olduğu, en fazla Journal of Nursing Management (dokuz çalışma) adlı dergide ve en fazla çalışmanın 2023 yılında yayınlandığı belirlenmiştir. En fazla çalışması olan yazar (yedi çalışma) Rozzano Locsin, en fazla yayının yapıldığı ülke Amerika Birleşik Devletleri ve en fazla çalışmanın yapıldığı kurumlar Florida Atlantic University ve Tokushima University olarak belirlenmiştir. En fazla kullanılan anahtar kelime ‘’artificial intelligence’’, toplam atıf sayısı 1010 ve h- indeksi 20 olarak belirlenmiştir. Hemşirelik alanında yapay zeka ile ilgili çalışmalara olan ilginin gittikçe arttığı ve özellikle son yıllarda çalışmaların nicelik bakımından gittikçe artış gösterdiği saptanmıştır.

Project Number

Yok

References

  • Ahuja, A. S. (2019). The impact of artificial intelligence in medicine on the future role of the physician. PeerJ, 7, e7702. https://doi.org/10.7717/peerj.7702
  • Akgerman, A., Özdemir Yavuz, E. D., Kavaslar, İ., & Güngör, S. (2022). Yapay zeka ve hemşirelik. Sağlık Bilimlerinde Yapay Zeka Dergisi, 2(1), 21-27. https://doi.org/10.52309/jaihs.v2i1.36
  • Al, U., Şahiner, M., & Tonta, Y. (2006). Arts and humanities literature: Bibliometric characteristics of contributions by Turkish authors. Journal of the American Society for Information Science and Technology, 57(8), 1011-1022. https://doi.org/10.1002/asi.20366
  • Burmaoğlu, S., Kıdak, L. B., Haydar, S., & Demir, H. (2016). Sistem yaklaşımı ve sağlık alanında sistem dinamikleri uygulamaları: Bibliyometrik bir analiz. Hacettepe Sağlık İdaresi Dergisi, 19(4), 443-463.
  • Büyükgöze, S., & Dereli, E. (2019). Dijital sağlık uygulamalarında yapay zeka. VI. Uluslararası Bilimsel ve Mesleki Çalışmalar Kongresi-Fen ve Sağlık, 7(10).
  • Chang, C. Y., Jen, H. J., & Su, W. S. (2022). Trends in artificial intelligence in nursing: Impacts on nursing management. Journal of Nursing Management, 30(8), 3644-3653. https://doi.org/10.1111/jonm.13770
  • Çobanoğlu, A., & Oğuzhan, H. (2023). Hemşirelikte teknolojinin gelişimi ve mesleğin Geleceğine etkileri. Hemşirelik Bilimi Dergisi, 6(2), 114-122. https://doi.org/10.54189/hbd.1036888
  • De Bellis, N. (2009). Bibliometrics and citation analysis: from the science citation index to cybermetrics.United States of America: Scarecrow press.
  • Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105, 1809-1831. https://doi.org/10.1007/s11192-015-1645-z
  • Erbağcı, A. B. (2009). Bir araştırmacının bilimsel değeri saptanabilir mi? H-indeksine bakış. Türk Klinik Biyokimya Dergisi, 7(3), 71-73.
  • Hall, K. L., Vogel, A. L., Huang, G. C., Serrano, K. J., Rice, E. L., Tsakraklides, S. P., & Fiore, S. M. (2018). The science of team science: A review of the empirical evidence and research gaps on collaboration in science. American Psychologist, 73(4), 532. https://doi.org/10.1037/amp0000319
  • Jeong, G. H. (2020). Artificial intelligence, machine learning, and deep learning in women’s health nursing. Korean Journal of Women Health Nursing, 26(1), 5-9. https://doi.org/10.4069/kjwhn.2020.03.11
  • Kantek, F., & Yesilbas, H. (2020). Conflict in nursing studies: A bibliometric analysis of the top 100 cited papers. Journal of Advanced Nursing, 76(10), 2531-2546. https://doi.org/10.1111/jan.14463
  • Karakaya, B. H., Akyol, A. S., & Doğan Merih, Y. (2022). Yapay zekâ teknolojisinin perinatal dönem bakımına entegrasyonu ve uygulama örnekleri. Türkiye Sağlık Enstitüleri Başkanlığı Dergisi, 5(2), 1-11. https://doi.org/10.54537/tusebdergisi.1154089
  • Khare, R., Leaman, R., & Lu, Z. (2014). Accessing biomedical literature in the current information landscape. Biomedical literature mining, 11-31. https://doi.org/10.1007/978-1-4939-0709-0_2
  • Kokol, P., & Vošner, H. B. (2019). Historical, descriptive and exploratory analysis of application of bibliometrics in nursing research. Nursing outlook, 67(6), 680-695. https://doi.org/10.1016/j.outlook.2019.04.009
  • Kokol, P., Vošner, H. B., & Železnik, D. (2017). Clinical simulation in nursing: A bibliometric analysis after its tenth anniversary. Clinical Simulation in Nursing, 13(4), 161-167. https://doi.org/10.1016/j.ecns.2016.11.007
  • Özkaya, M., & Körükcü, Ö. (2023). Web of Science-based analysis of the Journal of Human Lactation: An example of bibliometric analysis in nursing. Aydın Sağlık Dergisi, 9(2), 1-25.
  • Robert, N. (2019). How artificial intelligence is changing nursing. Nurs Manage, 50(9), 30-39. https://doi.org/10.1097/01.Numa.0000578988.56622.21
  • Ronquillo, C. E., Peltonen, L.-M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., . . . Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. Journal of Advanced Nursing, 77(9), 3707-3717. https://doi.org/10.1111/jan.14855
  • Shi, J., Wei, S., Gao, Y., Mei, F., Tian, J., Zhao, Y., & Li, Z. (2023). Global output on artificial intelligence in the field of nursing: A bibliometric analysis and science mapping. Journal of Nursing Scholarship, 55(4), 853-863. https://doi.org/10.1111/jnu.12852
  • Stokes, F., & Palmer, A. (2020). Artificial intelligence and robotics in nursing: ethics of caring as a guide to dividing tasks between AI and humans. Nursing Philosophy, 21(4), e12306. https://doi.org/10.1111/nup.12306
  • Şendir, M., & Kabuk, A. (2020). Hemşireler ve teknoloji-durdurulamaz ve kaçınılamaz iki güç. Ordu Üniversitesi Hemşirelik Çalışmaları Dergisi, 3(1), 54-58. https://doi.org/10.38108/ouhcd.713930
  • Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3

Trend of Artificial Intelligence in Nursing from 2004 to 2024: A Bibliometric Analysis Based on Web of Science

Year 2024, , 67 - 77, 27.08.2024
https://doi.org/10.58770/joinihp.1481083

Abstract

This study aims to conduct a bibliometric analysis of studies related to artificial intelligence (AI) in the field of nursing, accessed from the Web of Science database. The search was conducted using the keywords "artificial intelligence OR ChatGPT OR Chatbot) and (nursing OR nursing care) and (practice OR innovation OR machine learning OR deep learning)" between January 01-20, 2024. A total of 164 studies related to artificial intelligence in nursing were identified through the search. It was found that 65.85% of these studies were research articles, with the majority being published in the Journal of Nursing Management (nine studies), and the highest number of studies being published in 2023. The most prolific author, with seven studies, was identified as Rozzano Locsin, while the United States was determined to be the country with the highest number of publications, and Florida Atlantic University and Tokushima University were the institutions with the most studies. The most frequently used keyword was "artificial intelligence," with a total citation count of 1010 and an h-index of 20. The study indicates an increasing interest in AI-related research in nursing, particularly in recent years, with a trend towards quantitative growth.

Project Number

Yok

References

  • Ahuja, A. S. (2019). The impact of artificial intelligence in medicine on the future role of the physician. PeerJ, 7, e7702. https://doi.org/10.7717/peerj.7702
  • Akgerman, A., Özdemir Yavuz, E. D., Kavaslar, İ., & Güngör, S. (2022). Yapay zeka ve hemşirelik. Sağlık Bilimlerinde Yapay Zeka Dergisi, 2(1), 21-27. https://doi.org/10.52309/jaihs.v2i1.36
  • Al, U., Şahiner, M., & Tonta, Y. (2006). Arts and humanities literature: Bibliometric characteristics of contributions by Turkish authors. Journal of the American Society for Information Science and Technology, 57(8), 1011-1022. https://doi.org/10.1002/asi.20366
  • Burmaoğlu, S., Kıdak, L. B., Haydar, S., & Demir, H. (2016). Sistem yaklaşımı ve sağlık alanında sistem dinamikleri uygulamaları: Bibliyometrik bir analiz. Hacettepe Sağlık İdaresi Dergisi, 19(4), 443-463.
  • Büyükgöze, S., & Dereli, E. (2019). Dijital sağlık uygulamalarında yapay zeka. VI. Uluslararası Bilimsel ve Mesleki Çalışmalar Kongresi-Fen ve Sağlık, 7(10).
  • Chang, C. Y., Jen, H. J., & Su, W. S. (2022). Trends in artificial intelligence in nursing: Impacts on nursing management. Journal of Nursing Management, 30(8), 3644-3653. https://doi.org/10.1111/jonm.13770
  • Çobanoğlu, A., & Oğuzhan, H. (2023). Hemşirelikte teknolojinin gelişimi ve mesleğin Geleceğine etkileri. Hemşirelik Bilimi Dergisi, 6(2), 114-122. https://doi.org/10.54189/hbd.1036888
  • De Bellis, N. (2009). Bibliometrics and citation analysis: from the science citation index to cybermetrics.United States of America: Scarecrow press.
  • Ellegaard, O., & Wallin, J. A. (2015). The bibliometric analysis of scholarly production: How great is the impact? Scientometrics, 105, 1809-1831. https://doi.org/10.1007/s11192-015-1645-z
  • Erbağcı, A. B. (2009). Bir araştırmacının bilimsel değeri saptanabilir mi? H-indeksine bakış. Türk Klinik Biyokimya Dergisi, 7(3), 71-73.
  • Hall, K. L., Vogel, A. L., Huang, G. C., Serrano, K. J., Rice, E. L., Tsakraklides, S. P., & Fiore, S. M. (2018). The science of team science: A review of the empirical evidence and research gaps on collaboration in science. American Psychologist, 73(4), 532. https://doi.org/10.1037/amp0000319
  • Jeong, G. H. (2020). Artificial intelligence, machine learning, and deep learning in women’s health nursing. Korean Journal of Women Health Nursing, 26(1), 5-9. https://doi.org/10.4069/kjwhn.2020.03.11
  • Kantek, F., & Yesilbas, H. (2020). Conflict in nursing studies: A bibliometric analysis of the top 100 cited papers. Journal of Advanced Nursing, 76(10), 2531-2546. https://doi.org/10.1111/jan.14463
  • Karakaya, B. H., Akyol, A. S., & Doğan Merih, Y. (2022). Yapay zekâ teknolojisinin perinatal dönem bakımına entegrasyonu ve uygulama örnekleri. Türkiye Sağlık Enstitüleri Başkanlığı Dergisi, 5(2), 1-11. https://doi.org/10.54537/tusebdergisi.1154089
  • Khare, R., Leaman, R., & Lu, Z. (2014). Accessing biomedical literature in the current information landscape. Biomedical literature mining, 11-31. https://doi.org/10.1007/978-1-4939-0709-0_2
  • Kokol, P., & Vošner, H. B. (2019). Historical, descriptive and exploratory analysis of application of bibliometrics in nursing research. Nursing outlook, 67(6), 680-695. https://doi.org/10.1016/j.outlook.2019.04.009
  • Kokol, P., Vošner, H. B., & Železnik, D. (2017). Clinical simulation in nursing: A bibliometric analysis after its tenth anniversary. Clinical Simulation in Nursing, 13(4), 161-167. https://doi.org/10.1016/j.ecns.2016.11.007
  • Özkaya, M., & Körükcü, Ö. (2023). Web of Science-based analysis of the Journal of Human Lactation: An example of bibliometric analysis in nursing. Aydın Sağlık Dergisi, 9(2), 1-25.
  • Robert, N. (2019). How artificial intelligence is changing nursing. Nurs Manage, 50(9), 30-39. https://doi.org/10.1097/01.Numa.0000578988.56622.21
  • Ronquillo, C. E., Peltonen, L.-M., Pruinelli, L., Chu, C. H., Bakken, S., Beduschi, A., . . . Topaz, M. (2021). Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. Journal of Advanced Nursing, 77(9), 3707-3717. https://doi.org/10.1111/jan.14855
  • Shi, J., Wei, S., Gao, Y., Mei, F., Tian, J., Zhao, Y., & Li, Z. (2023). Global output on artificial intelligence in the field of nursing: A bibliometric analysis and science mapping. Journal of Nursing Scholarship, 55(4), 853-863. https://doi.org/10.1111/jnu.12852
  • Stokes, F., & Palmer, A. (2020). Artificial intelligence and robotics in nursing: ethics of caring as a guide to dividing tasks between AI and humans. Nursing Philosophy, 21(4), e12306. https://doi.org/10.1111/nup.12306
  • Şendir, M., & Kabuk, A. (2020). Hemşireler ve teknoloji-durdurulamaz ve kaçınılamaz iki güç. Ordu Üniversitesi Hemşirelik Çalışmaları Dergisi, 3(1), 54-58. https://doi.org/10.38108/ouhcd.713930
  • Van Eck, N., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
There are 24 citations in total.

Details

Primary Language English
Subjects Obstetrics and Gynocology Nursing
Journal Section Research Articles
Authors

Meltem Özkaya 0000-0002-1004-6040

Öznur Körükcü 0000-0001-5840-9114

Project Number Yok
Early Pub Date August 27, 2024
Publication Date August 27, 2024
Submission Date May 9, 2024
Acceptance Date August 5, 2024
Published in Issue Year 2024

Cite

IEEE M. Özkaya and Ö. Körükcü, “Trend of Artificial Intelligence in Nursing from 2004 to 2024: A Bibliometric Analysis Based on Web of Science”, Journal of Innovative Healthcare Practices, vol. 5, no. 2, pp. 67–77, 2024, doi: 10.58770/joinihp.1481083.