Araştırma Makalesi
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Evaluation of Nurse Academicians’ Knowledge, Attitudes/Behaviours, and Anxiety Levels Regarding Artificial Intelligence Applications

Yıl 2024, Cilt: 34 Sayı: 6, 875 - 881, 31.12.2024
https://doi.org/10.54005/geneltip.1561529

Öz

Aim: This study was conducted to evaluate the knowledge, attitude/behavior and anxiety levels of nurse academics about artificial intelligence applications.
Material and Methods: The research was conducted online with 202 nurse academicians in a descriptive type. Data Collection Form, Artificial Intelligence Anxiety Scale were used to collect data. SPSS 21 package program was used to evaluate the data. Descriptive statistics, Kolmogorov-Smirnov, Shapiro-Wilk, Spearman, Mann-Whitney U, Kruskal-Wallis H tests were used to evaluate the data. p<0.05 was considered significant.
Results: The study was completed with 202 nursing academicians. It was determined that the average score of the academicians on the Artificial Intelligence Anxiety Scale was 57.59±8.84. All participants stated that they had heard of the concept of artificial intelligence before. It was determined that there was a significant relationship between the academicians' receiving training on artificial intelligence, their belief that artificial intelligence will affect the nursing profession in the future, and their average score on the Artificial Intelligence Anxiety Scale.
Conclusion: It has been detected that nursing academicians have high levels of anxiety about artificial intelligence. It has been determined that academicians' anxiety levels about artificial intelligence are affected by lack of knowledge and negative attitudes. Our recommendation is to inform nursing academicians about artificial intelligence and provide the necessary support for them to take an active role in the inclusion of artificial intelligence in educational processes.

Etik Beyan

Before starting the study, ethical approval (Date: 05.04.2023) and permission to use the Artificial Intelligence Anxiety Scale were obtained. Participants were provided information about the study through the text at the beginning of the survey questionnaire. Only voluntary participants were included in the study.

Destekleyen Kurum

This research received no external funding.

Teşekkür

We would like to thank all the nurse academicians who participated in our study.

Kaynakça

  • 1. Frith KH. Artificial intelligence: What does it mean for nursing?. Nurs Educ Perspect 2019; 40(4): 261. http://dx.doi.org/10.1097/01.NEP.0000000000000543
  • 2. Sendir M, Simsekoglu N, Kaya A, Sumer K. Nursing in the technology of the future. J Nurs Health Sci Univ 2019; 1(3): 209-214.
  • 3. Betriana F, Tanioka R, Gunawan J, Locsin RC. Healthcare robots and human generations: Consequences for nursing and healthcare. Collegian 2022; 29(5): 767-773. https://doi.org/10.1016/j.colegn.2022.01.008
  • 4. Hughes JD, Chivers P, Hoti K. The clinical suitability of an artificial intelligence-enabled pain assessment tool for use in infants: Feasibility and usability evaluation study. J Med Internet Res 2023; 25: e41992. https://doi.org/10.2196/41992
  • 5. McGrow K. Artificial intelligence: Essentials for nursing. Nurs 2019; 49(9): 46. https://doi.org/10.1097/01.NURSE.0000577716.57052.8d
  • 6. Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Nursing in the age of artificial intelligence: Protocol for a scoping review. JMIR Res Protocols 2020; 9(4): e17490. https://doi.org/10.2196/17490
  • 7. Bodur G, Dincer M, Tutak Z, Akyuz GE, Uyanik S, Kuvan D. The effects of artificial intelligence on the future of health: An example of a qualitative study from the perspective of university students. J Göbeklitepe Health Sci 2022; 5(7): 106-115. https://doi.org/10.55433/gsbd.149
  • 8. Lukić A, Kudelić N, Antičević V, Lazić-Mosler E, Glunčić V, Hren D, et al. First-year nursing students’ attitudes towards artificial intelligence: Cross-sectional multi-center study. Nurs Educ Pract 2023; 71: 103735. https://doi.org/10.1016/j.nepr.2023.103735
  • 9. Mathur P, Burns ML. Artificial intelligence in critical care. Int Anesthesiol Clin 2019: 57(2): 89-102. https://doi.org/10.1097/AIA.0000000000000221
  • 10. Jeong GH. Artificial intelligence, machine learning, and deep learning in women's health nursing. Korean J Women Health Nurs 2020; 26(1): 5-9. https://doi.org/10.4069/kjwhn.2020.03.11
  • 11. Labrague LJ, Aguilar-Rosales R, Yboa BC, Sabio JB. Factors influencing student nurses' readiness to adopt artificial intelligence (AI) in their studies and their perceived barriers to accessing AI technology: A cross-sectional study. Nurs Educ Today 2023; 130: 105945. https://doi.org/10.1016/j.nedt.2023.105945
  • 12. Cetin B, Eroglu N. Innovative technologies in nursing care. Acta Medica Nicomedia 2020; 3(3): 120-126. https://dergipark.org.tr/tr/pub/actamednicomedia
  • 13. Shorey S, Ang E, Yap J, Ng ED, Lau ST, Chui CK. A virtual counseling application using artificial intelligence for communication skills training in nursing education: development study. J Med Int Res 2019; 21(10). e14658. https://doi.org/10.2196/14658
  • 14. Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on nursing education: Scoping review. JMIR Nurs 2021; 4(1): e23933. https://doi.org/10.2196/23933
  • 15. Wang YY, Wang YS. Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interact Learn Environ 2019; 1-16. https://doi.org/10.1080/10494820.2019.1674887
  • 16. Akkaya B, Ozkan A, Ozkan H. Artificial Intelligence Anxiety Scale: Adaptation to Turkish, validity and reliability study. Alanya Acad Overview 2021; 5(2): 1125-1146. https://doi.org/10.29023/alanyaakademik.833668
  • 17. Filiz E, Guzel S, Sengul A. Examining the artificial intelligence anxiety states of healthcare professionals. J Acad Value Stud 2022; 8(1): 47-55. . http://dx.doi.org/10.29228/javs.57808
  • 18. Gumus E, Uysal Kasap E. The level of artificial intelligence anxiety in the health ecosystem: A sample of nurses. J Artificial Intelligence Health Sci 2022; 2(3): 1-7. https://doi.org/10.52309/jaihs.v2i2.43
  • 19. Menekli T, Senturk S. The relationship between internal medicine nurses' artificial intelligence concerns and spiritual care perceptions. J YOBU Health Fac Sci 2022; 3(2): 210-218.
  • 20. Akyuz HO, Alkan S, Yucebas SC. Examining the knowledge levels of Health Services Vocational School students about artificial intelligence. Med Res Rep 2021; 4(3): 28-35.
  • 21. Yilmaz Y, Yilmaz DU, Yildirim D, Korhan EA, Ozer D .Opinions of health sciences faculty students regarding artificial intelligence and the use of artificial intelligence in health. J Süleyman Demirel Univ Health Sci 2021; 12(3): 297-308. https://doi.org/10.22312/sdusbed.950372
  • 22. Orhan M, Bulez A. Evaluation of healthcare personnel's thoughts about artificial intelligence. Kesit Acad Magazine 2022; 8(33): 52-69. ISSN:2149-9225.
  • 23. Sapci AH, Sapci HA. Artificial intelligence education and tools for medical and health informatics students: Systematic review. JMIR Med Educ 2020; 6(1): E19285. https://doi.org/10.2196/19285
  • 24. Hosgor DG, Gungordu H, Hosgor H. Health professionals' views on artificial intelligence: A metaphorical research. Al-Farabi Int J Soc Sci 2023; 8(1): 71-87. https://doi.org/10.46291/Al-Farabi.080105
  • 25. Harmon J, Pitt V, Summons P, Inder KJ. Use of artificial intelligence and virtual reality within clinical simulation for nursing pain education: A scoping review. Nurs Educ Today 2021; 97: 104700. https://doi.org/10.1016/j.nedt.2020.104700
  • 26. Aslan F, Subasi A. A different perspective on artificial intelligence technologies from the perspective of nursing education and nursing process. J Nurs Health Sci Univ 2022; 4(3): 153-158. https://doi.org/10.48071/sbuhemsirelik.1109187
  • 27. Hooda M, Rana C, Dahiya O, Rizwan A, Hossain MS. Artificial intelligence for assessment and feedback to enhance student success in higher education. Math Prob Engineering 2022. https://doi.org/10.1155/2022/5215722
  • 28. Huang AY, Lu OH, Yang SJ. Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Comput Educ 2023; 194: 104684. https://doi.org/10.1016/j.compedu.2022.104684
  • 29. Liaw SY, Tan JZ, Lim S, Zhou W, Yap J, Ratan R, et al. Artificial intelligence in virtual reality simulation for interprofessional communication training: Mixed method study. Nurs Educ Today 2023; 122: 105718. https://doi.org/10.1016/j.nedt.2023.105718
  • 30. Tam W, Huynh T, Tang A, Luong S, Khatri Y, Zhou W. Nursing education in the age of artificial intelligence powered Chatbots (AI-Chatbots): Are we ready yet?. Nurs Educ Today 2023; 129: 105917. https://doi.org/10.1016/j.nedt.2023.105917
  • 31. Cifci BS, Basfirinci C. Examining the subject of artificial intelligence within the context of gender: A research on professions. J Çukurova Univ Soc Sci Institute 2020; 29(4): 183-203.
  • 32. Dogan Merih Y, Akdogan E. Artificial intelligence in nursing. In 4th International Eurasian Conference on Biological and Chemical Sciences (EurasianBioChem 2021) November (pp. 24-26). 2021.
  • 33. Yigit D, Acikgoz A. Evaluation of comfort behavior levels of newborn by artificial intelligence techniques. J Perinatal Neonatal Nurs 2024; 38(3): E38-E45. https://doi.org/10.1097/JPN.0000000000000768
  • 34. Ozdemir L, Bilgin A. Use of artificial intelligence in health and ethical issues. J Health Nurs Manage 2021; 8(3): 439-445.
  • 35. Ergin E, Karaarslan D, Sahan S, Cinar Yucel S. Artificial intelligence and robot nurses: From nurse managers' perspective: A descriptive cross‐sectional study. J Nurs Manage 2022; 30(8): 3853-3862. https://doi.org/10.1111/jonm.13646

Hemşire Akademisyenlerin Yapay Zeka Uygulamaları Hakkında Bilgi, Tutum/Davranış ve Kaygı Düzeylerinin Değerlendirilmesi

Yıl 2024, Cilt: 34 Sayı: 6, 875 - 881, 31.12.2024
https://doi.org/10.54005/geneltip.1561529

Öz

Amaç: Bu çalışma, hemşire akademisyenlerin yapay zeka uygulamaları hakkında bilgi, tutum/davranış ve kaygı düzeylerinin değerlendirilmesi amacıyla yapılmıştır.
Gereç ve Yöntemler: Araştırma tanımlayıcı tipte, online olarak 202 hemşire akademisyen ile yapılmıştır. Verilerin toplanmasında; Veri Toplama Formu, Yapay Zeka Kaygı Ölçeği kullanılmıştır. Verilerin değerlendirilmesinde SPSS 21 paket programı kullanılmıştır. Verilerin değerlendirilmesinde; tanımlayıcı istatistikler, Kolmogorov-Smirnov, Shapiro-Wilk, Spearman, Mann-Whitney U, Kruskal-Wallis H testi kullanılıştır. p<0.05 değeri anlamlı kabul edilmiştir.
Bulgular: Çalışma, 202 hemşire akademisyen ile tamamlanmıştır. Akademisyenlerin Yapay Zeka Kaygı Ölçeği puan ortalamalarının 57.59±8.84 olduğu belirlenmiştir. Katılımcıların hepsi yapay zeka kavramını daha önce duyduğunu belirtmiştir. Akademisyenlerin yapay zeka ile ilgili eğitim alma, yapay zekanın gelecekte hemşirelik mesleğini ekileceğini düşünme durumu ile Yapay Zeka Kaygı Ölçeği puan ortalamaları arasında anlamlı bir ilişki olduğu belirlenmiştir.
Sonuç: Hemşire akademisyenlerin yapay zeka kaygı düzeylerinin yüksek olduğu tespit edilmiştir. Akademisyenlerin yapay zekaya ilişkin kaygı düzeylerinin bilgi eksikliği ve olumsuz tutumlardan etkilendiği belirlenmiştir. Önerimiz; hemşire akademisyenlerin yapay zekaya ilişkin bilgilendirilmesi ve yapay zekanın eğitim süreçlerine dahil edilmesinde aktif rol alması için gerekli desteğin verilmesidir.

Kaynakça

  • 1. Frith KH. Artificial intelligence: What does it mean for nursing?. Nurs Educ Perspect 2019; 40(4): 261. http://dx.doi.org/10.1097/01.NEP.0000000000000543
  • 2. Sendir M, Simsekoglu N, Kaya A, Sumer K. Nursing in the technology of the future. J Nurs Health Sci Univ 2019; 1(3): 209-214.
  • 3. Betriana F, Tanioka R, Gunawan J, Locsin RC. Healthcare robots and human generations: Consequences for nursing and healthcare. Collegian 2022; 29(5): 767-773. https://doi.org/10.1016/j.colegn.2022.01.008
  • 4. Hughes JD, Chivers P, Hoti K. The clinical suitability of an artificial intelligence-enabled pain assessment tool for use in infants: Feasibility and usability evaluation study. J Med Internet Res 2023; 25: e41992. https://doi.org/10.2196/41992
  • 5. McGrow K. Artificial intelligence: Essentials for nursing. Nurs 2019; 49(9): 46. https://doi.org/10.1097/01.NURSE.0000577716.57052.8d
  • 6. Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Nursing in the age of artificial intelligence: Protocol for a scoping review. JMIR Res Protocols 2020; 9(4): e17490. https://doi.org/10.2196/17490
  • 7. Bodur G, Dincer M, Tutak Z, Akyuz GE, Uyanik S, Kuvan D. The effects of artificial intelligence on the future of health: An example of a qualitative study from the perspective of university students. J Göbeklitepe Health Sci 2022; 5(7): 106-115. https://doi.org/10.55433/gsbd.149
  • 8. Lukić A, Kudelić N, Antičević V, Lazić-Mosler E, Glunčić V, Hren D, et al. First-year nursing students’ attitudes towards artificial intelligence: Cross-sectional multi-center study. Nurs Educ Pract 2023; 71: 103735. https://doi.org/10.1016/j.nepr.2023.103735
  • 9. Mathur P, Burns ML. Artificial intelligence in critical care. Int Anesthesiol Clin 2019: 57(2): 89-102. https://doi.org/10.1097/AIA.0000000000000221
  • 10. Jeong GH. Artificial intelligence, machine learning, and deep learning in women's health nursing. Korean J Women Health Nurs 2020; 26(1): 5-9. https://doi.org/10.4069/kjwhn.2020.03.11
  • 11. Labrague LJ, Aguilar-Rosales R, Yboa BC, Sabio JB. Factors influencing student nurses' readiness to adopt artificial intelligence (AI) in their studies and their perceived barriers to accessing AI technology: A cross-sectional study. Nurs Educ Today 2023; 130: 105945. https://doi.org/10.1016/j.nedt.2023.105945
  • 12. Cetin B, Eroglu N. Innovative technologies in nursing care. Acta Medica Nicomedia 2020; 3(3): 120-126. https://dergipark.org.tr/tr/pub/actamednicomedia
  • 13. Shorey S, Ang E, Yap J, Ng ED, Lau ST, Chui CK. A virtual counseling application using artificial intelligence for communication skills training in nursing education: development study. J Med Int Res 2019; 21(10). e14658. https://doi.org/10.2196/14658
  • 14. Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on nursing education: Scoping review. JMIR Nurs 2021; 4(1): e23933. https://doi.org/10.2196/23933
  • 15. Wang YY, Wang YS. Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interact Learn Environ 2019; 1-16. https://doi.org/10.1080/10494820.2019.1674887
  • 16. Akkaya B, Ozkan A, Ozkan H. Artificial Intelligence Anxiety Scale: Adaptation to Turkish, validity and reliability study. Alanya Acad Overview 2021; 5(2): 1125-1146. https://doi.org/10.29023/alanyaakademik.833668
  • 17. Filiz E, Guzel S, Sengul A. Examining the artificial intelligence anxiety states of healthcare professionals. J Acad Value Stud 2022; 8(1): 47-55. . http://dx.doi.org/10.29228/javs.57808
  • 18. Gumus E, Uysal Kasap E. The level of artificial intelligence anxiety in the health ecosystem: A sample of nurses. J Artificial Intelligence Health Sci 2022; 2(3): 1-7. https://doi.org/10.52309/jaihs.v2i2.43
  • 19. Menekli T, Senturk S. The relationship between internal medicine nurses' artificial intelligence concerns and spiritual care perceptions. J YOBU Health Fac Sci 2022; 3(2): 210-218.
  • 20. Akyuz HO, Alkan S, Yucebas SC. Examining the knowledge levels of Health Services Vocational School students about artificial intelligence. Med Res Rep 2021; 4(3): 28-35.
  • 21. Yilmaz Y, Yilmaz DU, Yildirim D, Korhan EA, Ozer D .Opinions of health sciences faculty students regarding artificial intelligence and the use of artificial intelligence in health. J Süleyman Demirel Univ Health Sci 2021; 12(3): 297-308. https://doi.org/10.22312/sdusbed.950372
  • 22. Orhan M, Bulez A. Evaluation of healthcare personnel's thoughts about artificial intelligence. Kesit Acad Magazine 2022; 8(33): 52-69. ISSN:2149-9225.
  • 23. Sapci AH, Sapci HA. Artificial intelligence education and tools for medical and health informatics students: Systematic review. JMIR Med Educ 2020; 6(1): E19285. https://doi.org/10.2196/19285
  • 24. Hosgor DG, Gungordu H, Hosgor H. Health professionals' views on artificial intelligence: A metaphorical research. Al-Farabi Int J Soc Sci 2023; 8(1): 71-87. https://doi.org/10.46291/Al-Farabi.080105
  • 25. Harmon J, Pitt V, Summons P, Inder KJ. Use of artificial intelligence and virtual reality within clinical simulation for nursing pain education: A scoping review. Nurs Educ Today 2021; 97: 104700. https://doi.org/10.1016/j.nedt.2020.104700
  • 26. Aslan F, Subasi A. A different perspective on artificial intelligence technologies from the perspective of nursing education and nursing process. J Nurs Health Sci Univ 2022; 4(3): 153-158. https://doi.org/10.48071/sbuhemsirelik.1109187
  • 27. Hooda M, Rana C, Dahiya O, Rizwan A, Hossain MS. Artificial intelligence for assessment and feedback to enhance student success in higher education. Math Prob Engineering 2022. https://doi.org/10.1155/2022/5215722
  • 28. Huang AY, Lu OH, Yang SJ. Effects of artificial Intelligence–Enabled personalized recommendations on learners’ learning engagement, motivation, and outcomes in a flipped classroom. Comput Educ 2023; 194: 104684. https://doi.org/10.1016/j.compedu.2022.104684
  • 29. Liaw SY, Tan JZ, Lim S, Zhou W, Yap J, Ratan R, et al. Artificial intelligence in virtual reality simulation for interprofessional communication training: Mixed method study. Nurs Educ Today 2023; 122: 105718. https://doi.org/10.1016/j.nedt.2023.105718
  • 30. Tam W, Huynh T, Tang A, Luong S, Khatri Y, Zhou W. Nursing education in the age of artificial intelligence powered Chatbots (AI-Chatbots): Are we ready yet?. Nurs Educ Today 2023; 129: 105917. https://doi.org/10.1016/j.nedt.2023.105917
  • 31. Cifci BS, Basfirinci C. Examining the subject of artificial intelligence within the context of gender: A research on professions. J Çukurova Univ Soc Sci Institute 2020; 29(4): 183-203.
  • 32. Dogan Merih Y, Akdogan E. Artificial intelligence in nursing. In 4th International Eurasian Conference on Biological and Chemical Sciences (EurasianBioChem 2021) November (pp. 24-26). 2021.
  • 33. Yigit D, Acikgoz A. Evaluation of comfort behavior levels of newborn by artificial intelligence techniques. J Perinatal Neonatal Nurs 2024; 38(3): E38-E45. https://doi.org/10.1097/JPN.0000000000000768
  • 34. Ozdemir L, Bilgin A. Use of artificial intelligence in health and ethical issues. J Health Nurs Manage 2021; 8(3): 439-445.
  • 35. Ergin E, Karaarslan D, Sahan S, Cinar Yucel S. Artificial intelligence and robot nurses: From nurse managers' perspective: A descriptive cross‐sectional study. J Nurs Manage 2022; 30(8): 3853-3862. https://doi.org/10.1111/jonm.13646
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Klinik Tıp Bilimleri (Diğer)
Bölüm Original Article
Yazarlar

Deniz Yiğit 0000-0001-5627-7963

Ayfer Açıkgöz 0000-0002-3803-9678

Erken Görünüm Tarihi 30 Aralık 2024
Yayımlanma Tarihi 31 Aralık 2024
Gönderilme Tarihi 4 Ekim 2024
Kabul Tarihi 14 Kasım 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 34 Sayı: 6

Kaynak Göster

Vancouver Yiğit D, Açıkgöz A. Evaluation of Nurse Academicians’ Knowledge, Attitudes/Behaviours, and Anxiety Levels Regarding Artificial Intelligence Applications. Genel Tıp Derg. 2024;34(6):875-81.