Araştırma Makalesi
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Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors

Yıl 2026, Cilt: 11 Sayı: 1, 105 - 112, 28.01.2026
https://doi.org/10.61399/ikcusbfd.1640227

Öz

Objective: The acceptance and efficient implementation of artificial Intelligence (AI)-based applications in routine nursing activities depends on readiness towards artificial intelligence. This study aims to explore nurses' and nursing students' knowledge, opinions, and attitudes towards artificial intelligence and the factors that influence them.
Material and Method: The analytical cross-sectional study was conducted between March and May 2022, with 580 participants, including nurses (217) and nursing students (363) in a city in eastern Turkey. The data was collected using the “Information Form for Personal Details and Artificial Intelligence Knowledge of Nurses and Students” and the “Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MR)”.
Results: This study showed that 46.1% of nurses and 34.4% of nursing students did not know how to use artificial intelligence in nursing. Both nurses and nursing students’ sources of information regarding artificial intelligence in nursing were essentially “social media” and the application they mostly associated the concept of artificial intelligence with was “robots”. More than half of nurses and students were curious about using artificial intelligence in nursing care. The nurses’ and nursing students’ mean MAIRS-MR scores were 67.17±18.19 and 69.41±15.18, respectively.
Conclusion: The study demonstrated that nurses and nursing students had a moderate level of readiness for medical artificial intelligence.
Keywords: Artificial intelligence, nurse, nursing student, readiness.

Etik Beyan

Fırat Üniversitesi Sosyal Beşeri Bilimler Etik Kurulu'ndan etik kurul onayı (22.02.2022/04-4) alınmıştır.

Destekleyen Kurum

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Teşekkür

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Kaynakça

  • Van Bulck L, Couturier R, Moons P. Applications of artificial intelligence for nursing: Has a new era arrived? Eur J Cardiovasc Nurs. 2023 Apr 12;22(3):e19-e20. https://doi.org/10.1093/eurjcn/zvac097
  • Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019 Jan;112(1):22-8. doi:10.1177/0141076818815510.
  • Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018 Oct;2(10):719-31. doi: 10.1038/s41551-018-0305-z.
  • Seibert K, Domhoff D, Bruch D, Schulte- Althoff M, Fürstenau D, Biessmann F, Wolf- Ostermann K. Application scenarios for artificial intelligence in nursing care: Rapid review. J Med Internet Res. 2021 Nov 29;23(11):e26522. doi: 10.2196/26522.
  • Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on the domains of nursing: Scoping review. JMIR Nurs. 2021 Jan 28;4(1):e23933. doi:10.2196/23933.
  • Carroll W. Artificial intelligence, nurses and the quadruple aim. Online J Nurs Inform, 2018 22:(2).
  • Pepito JA, Locsin R. Can nurses remain relevant in a technologically advanced future? Int J Nurs Sci. 2018 Oct 4;6(1):106-110. https://doi.org/10.1016/j.ijnss.2018.09.013.
  • McGrow K. Artificial intelligence: Essentials for nursing. Nursing. 2019 Sep;49(9):46-9. doi:10.1097/01.NURSE.0000577716.57052.8d.
  • Moreno-Fergusson ME, Guerrero Rueda WJ, Ortiz Basto GA, Arevalo Sandoval IAL, Sanchez-Herrera B. Analytics and lean health resort to address nurse resort management challenges for in patients in emerging economies. J Nurs Scholarsh. 2021 Nov;53(6):803-14. doi: 10.1111/jnu.12711.
  • Liu Q, Yang L, Peng Q. Artificial intelligence technology-based medical information processing and emergency first aid nursing management. Comput Math Methods Med. 2023 Dec 6;2023:9868521. doi: 10.1155/2023/9868521.
  • Zhou J, Zhang F, Wang H, Yin Y, Wang Q, Yang L, Dong B, Yuan J, Liu S, Zhao L, Luo W. Quality and efficiency of a standardized e-handover system for pediatric nursing: A prospective interventional study. J Nurs Manag. 2022 Nov;30(8):3714-25. doi: 10.1111/jonm.13549.
  • 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 Internet Res. 2019 Oct 29;21(10):e14658. doi: 10.2196/14658.
  • Joseph J, Moore ZEH, Patton D, O'Connor T, Nugent LE. (2020). The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review. J Clin Nurs. 2020 Jul;29(13-14):2125-37. https://doi.org/10.1111/jocn.15261.
  • Yılmaz Y, Yılmaz DU, Yıldırım D, Korha EA, Derya O. Artificial intelligence and the artificial use intelligence in health: Opinions of health sciences students. SüleymanDemirel Univ J Health Science. 2021;12(3): 297-308.
  • Fan KY, Hu R, Singla R. introduction machine learning for medical students: A pilot. Med Educ. 2020 Nov;54(11):1042-1043. doi:10.1111/medu.14318.
  • Ngo B, Nguyen D, vanSonnenberg E. Artificial intelligence: Has its time come for inclusion in medical school education? Maybe...Maybe not. MedEdPublish 2021 Sep 3;10:131. doi:10.15694/mep.2021.000131.2.
  • Reznick RK, Harris K, Horsley T, Hassani, MS. Task force Report on artificial intelligence and emerging digital technologies. R Coll Physicians Surg Canada. 2020:1-52.
  • Topol E. The Topol Review: Preparing the healthcare workforce to deliver the digital future [Internet]. National Health Service; 2017 [Date of access: 2022-04-30]. Available from: https:// topol.hee.nhs.uk/wp-content/uploads/HEE-Topol-Review-2019.pdf
  • United States Agency for International Development. Artificial Intelligence in Global Health: Defining a Collective Path Forward [Internet]. 2019 Apr Access: https://www.usaid.gov/cii/ai-in-global-health [ Date of access: 2022-02-01].
  • Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019 Oct 29;17(1):195. doi: 10.1186/s12916-019-1426-2.
  • Horowitz MC, Kahn, L. What influences attitudes about artificial intelligence adoption: Evidence from US local officials. PLoS One. 2021 Oct 20;16(10):e0257732. doi: 10.1371/journal.pone.0257732.
  • Swan BA. Assessing the Knowledge and Attitudes of Registered Nurses about Artificial Intelligence in Nursing and Health Care. Nurs Econ.$. 2021;39(3):139-43.
  • Ergin E, Karaarslan D, Sahan S, Çınar Yücel S. Artificial intelligence and robot nurses: From nurse managers ' perspective: A descriptive cross-sectional study. J Nurs Manag. 2022 Nov;30(8):3853-62. https://doi.org/10.1111/jonm.13646
  • Sheela J. Attitude of Nursing Students towards Artificial Intelligence Int J Sci Healthc Res. 2022;7(2):344-7. https://doi.org/10.52403/ijshr.20220447
  • Abdullah R, Fakieh B. Health care employees' perceptions of the use of artificial intelligence applications: Survey study. J Med Internet Res. 2020 May 14;22(5):e17620.. https://doi.org/10.2196/ 17620
  • WHO, 2020 State of the world's nursing 2020: investing in education, jobs and leadership https://www.who.int/publications/i/item/9789240003279
  • Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, Cato K, Hardiker N, Junger A, Michalowski M, Nyrup R, Rahimi S, Reed DN, Salakoski T, Salanterä S, Walton N, Weber P, Wiegand T, Topaz M. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021 Sep;77(9):3707-3717. doi: 10.1111/jan.14855.
  • Cuschieri S. The STROBE guidelines. Saudi J Anaesth. 2019 Apr;13(Suppl 1):S31-S34. doi: 10.4103/sja.SJA_543_18.
  • Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007 May;39(2):175-91. doi: 10.3758/bf03193146.
  • Karaca O, Caliskan SA, Demir K. Medical artificial intelligence readiness scale for medical students (MAIRS-MS) – development, validity and reliability study. BMC Med Educ. 2021 Feb 18;21(1):112. https://doi.org/10.1186/s12909-021-02546-6
  • Xuan PY, Fahumida MIF, Hussain MIAN, Jayathilake NT, Khobragade S, Soe HHK, Moe S, Htay MNN. Readiness towards artificial intelligence among undergraduate medical students in Malaysia. Journal of Education in Medicine. 2023;15(2):49-60. DOI: 10.21315/eimj2023.15.2.4
  • Tamori H, Yamashina H, Mukai M, Morii Y, Suzuki T, Ogasawara K. Acceptance of the use of artificial intelligence in medicine among Japan's doctors and the public: a questionnaire survey. JMIR Hum Factors. 2022 Mar 16;9(1):e24680. doi: 10.2196/24680.
  • Maraş G, Albayrak Günday E, Sürme Y. Examining the Anxiety and Preparedness Levels of Nurses and Nurse Candidates for Artificial Intelligence Health Technologies. J Clin Nurs. Published online November 18, 2024. doi:10.1111/jocn.17562
  • Ghalibaf AM, Moghadasin M, Emadzadeh A, Mastour H. Psychometric properties of the persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). BMC Med Educ. 2023 Aug 15;23(1):577. doi: 10.1186/s12909-023-04553-1.
  • AlZaabi A, AlMaskari S, AalAbdulsalam A. Are physicians andmedical students ready for artificial intelligence applications in healthcare? Digit Health. 2023 Jan 26;9:20552076231152167.
  • Li J, Huang JS. Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society.2020;63(4):101410. https://doi.org/10.1016/j.techsoc.2020.101410
  • Elsayed WA, Sleem WF. Nurse Managers' perception and Attitudes toward Using Artificial Intelligence Technology in Health Settings. Assiut Scientific Nursing Journal. 2021;9(24):182-92. doi:10.21608/asnj.2021.72740.1159
  • Cruz JP, Sembekova A, Omirzakova D, Bolla SR, Balay-odao EM. General Attitudes Towards and Readiness for Medical Artificial Intelligence among Medical and Health Sciences Students in Kazakhstan. J Int Med Res Preprints. 2023:1-31. https://doi.org/10.2196/preprints.49536
  • Menekli T, Şentürk S. The relationship between artificial intelligence concerns and perceived spiritual care in internal medicine nurses. YOBU Faculty of Health Sciences Journal. 2022;3(2):210-8.
  • Kloka JA, Holtmann SC, Nürenberg-Goloub E, Piekarski F, Zacharowski K, Friedrichson B. Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study. JMIR Form Res. 2023 Jun 12;7:e43896. doi: 10.2196/43896.

Hemşirelerin ve Hemşirelik Öğrencilerinin Sağlık Hizmetlerinde Yapay Zeka Kullanımına Hazır Bulunuşlukları ve Etkileyen Faktörler

Yıl 2026, Cilt: 11 Sayı: 1, 105 - 112, 28.01.2026
https://doi.org/10.61399/ikcusbfd.1640227

Öz

Amaç: Rutin hemşirelik faaliyetlerinde yapay zekâ (artificial Intelligence, AI) tabanlı uygulamaların kabulü ve etkin bir şekilde uygulanması, yapay zekaya karşı hazır olmaya bağlıdır. Bu çalışmanın amacı, hemşirelerin ve hemşirelik öğrencilerinin yapay zekaya yönelik bilgi, görüş, hazır bulunuşlukları ve bunları etkileyen faktörleri araştırmaktır.
Gereç ve Yöntem: Bu çalışma Mart 2022 ile Mayıs 2022 arasında, Türkiye'nin doğusundaki bir şehirde hemşireler (217) ve hemşirelik öğrencileri (363) olmak üzere 580 katılımcıyla kesitsel-analitik tipte yürütülmüştür. Veriler, “Hemşirelerin ve Öğrencilerin Kişisel Bilgi ve Yapay Zekaya İlişkin Bilgi Formu” ve “Tıbbi Yapay Zekâ Hazır Bulunuşluk Ölçeği” kullanılarak toplanmıştır.
Bulgular: Bu çalışma, hemşirelerin %46,1'inin ve hemşirelik öğrencilerinin %34,4'ünün hemşirelikte yapay zeka kullanımı hakkında hiçbir bilgisinin olmadığını göstermiştir. Hem hemşirelerin hem de hemşirelik öğrencilerinin hemşirelikte yapay zeka ile ilgili temel bilgi kaynaklarının “sosyal medya” ve yapay zeka kavramını en çok ilişkilendirdikleri uygulamanın “robotlar” olduğu belirlenmiştir. Hemşirelerin ve öğrencilerin yarısından fazlasının hemşirelik bakımında yapay zekanın kullanımı konusunda meraklı olduğu bulunmuştur. Çalışmada hemşirelerin ve hemşirelik öğrencilerinin Tıbbi Yapay Zekâ Hazır Bulunuşluk Ölçeği puan ortalamaları sırasıyla 67,17±18,19 ve 69,41±15,18 olarak bulunmuştur.
Sonuç: Çalışma, hemşirelerin ve hemşirelik öğrencilerinin tıbbi yapay zekaya orta düzeyde hazır bulunduklarını göstermiştir.
Anahtar Kelimeler: Yapay zeka, hemşire, hemşirelik öğrencisi, hazır bulunuşluk.

Kaynakça

  • Van Bulck L, Couturier R, Moons P. Applications of artificial intelligence for nursing: Has a new era arrived? Eur J Cardiovasc Nurs. 2023 Apr 12;22(3):e19-e20. https://doi.org/10.1093/eurjcn/zvac097
  • Reddy S, Fox J, Purohit MP. Artificial intelligence-enabled healthcare delivery. J R Soc Med. 2019 Jan;112(1):22-8. doi:10.1177/0141076818815510.
  • Yu KH, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng. 2018 Oct;2(10):719-31. doi: 10.1038/s41551-018-0305-z.
  • Seibert K, Domhoff D, Bruch D, Schulte- Althoff M, Fürstenau D, Biessmann F, Wolf- Ostermann K. Application scenarios for artificial intelligence in nursing care: Rapid review. J Med Internet Res. 2021 Nov 29;23(11):e26522. doi: 10.2196/26522.
  • Buchanan C, Howitt ML, Wilson R, Booth RG, Risling T, Bamford M. Predicted influences of artificial intelligence on the domains of nursing: Scoping review. JMIR Nurs. 2021 Jan 28;4(1):e23933. doi:10.2196/23933.
  • Carroll W. Artificial intelligence, nurses and the quadruple aim. Online J Nurs Inform, 2018 22:(2).
  • Pepito JA, Locsin R. Can nurses remain relevant in a technologically advanced future? Int J Nurs Sci. 2018 Oct 4;6(1):106-110. https://doi.org/10.1016/j.ijnss.2018.09.013.
  • McGrow K. Artificial intelligence: Essentials for nursing. Nursing. 2019 Sep;49(9):46-9. doi:10.1097/01.NURSE.0000577716.57052.8d.
  • Moreno-Fergusson ME, Guerrero Rueda WJ, Ortiz Basto GA, Arevalo Sandoval IAL, Sanchez-Herrera B. Analytics and lean health resort to address nurse resort management challenges for in patients in emerging economies. J Nurs Scholarsh. 2021 Nov;53(6):803-14. doi: 10.1111/jnu.12711.
  • Liu Q, Yang L, Peng Q. Artificial intelligence technology-based medical information processing and emergency first aid nursing management. Comput Math Methods Med. 2023 Dec 6;2023:9868521. doi: 10.1155/2023/9868521.
  • Zhou J, Zhang F, Wang H, Yin Y, Wang Q, Yang L, Dong B, Yuan J, Liu S, Zhao L, Luo W. Quality and efficiency of a standardized e-handover system for pediatric nursing: A prospective interventional study. J Nurs Manag. 2022 Nov;30(8):3714-25. doi: 10.1111/jonm.13549.
  • 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 Internet Res. 2019 Oct 29;21(10):e14658. doi: 10.2196/14658.
  • Joseph J, Moore ZEH, Patton D, O'Connor T, Nugent LE. (2020). The impact of implementing speech recognition technology on the accuracy and efficiency (time to complete) clinical documentation by nurses: A systematic review. J Clin Nurs. 2020 Jul;29(13-14):2125-37. https://doi.org/10.1111/jocn.15261.
  • Yılmaz Y, Yılmaz DU, Yıldırım D, Korha EA, Derya O. Artificial intelligence and the artificial use intelligence in health: Opinions of health sciences students. SüleymanDemirel Univ J Health Science. 2021;12(3): 297-308.
  • Fan KY, Hu R, Singla R. introduction machine learning for medical students: A pilot. Med Educ. 2020 Nov;54(11):1042-1043. doi:10.1111/medu.14318.
  • Ngo B, Nguyen D, vanSonnenberg E. Artificial intelligence: Has its time come for inclusion in medical school education? Maybe...Maybe not. MedEdPublish 2021 Sep 3;10:131. doi:10.15694/mep.2021.000131.2.
  • Reznick RK, Harris K, Horsley T, Hassani, MS. Task force Report on artificial intelligence and emerging digital technologies. R Coll Physicians Surg Canada. 2020:1-52.
  • Topol E. The Topol Review: Preparing the healthcare workforce to deliver the digital future [Internet]. National Health Service; 2017 [Date of access: 2022-04-30]. Available from: https:// topol.hee.nhs.uk/wp-content/uploads/HEE-Topol-Review-2019.pdf
  • United States Agency for International Development. Artificial Intelligence in Global Health: Defining a Collective Path Forward [Internet]. 2019 Apr Access: https://www.usaid.gov/cii/ai-in-global-health [ Date of access: 2022-02-01].
  • Kelly CJ, Karthikesalingam A, Suleyman M, Corrado G, King D. Key challenges for delivering clinical impact with artificial intelligence. BMC Med. 2019 Oct 29;17(1):195. doi: 10.1186/s12916-019-1426-2.
  • Horowitz MC, Kahn, L. What influences attitudes about artificial intelligence adoption: Evidence from US local officials. PLoS One. 2021 Oct 20;16(10):e0257732. doi: 10.1371/journal.pone.0257732.
  • Swan BA. Assessing the Knowledge and Attitudes of Registered Nurses about Artificial Intelligence in Nursing and Health Care. Nurs Econ.$. 2021;39(3):139-43.
  • Ergin E, Karaarslan D, Sahan S, Çınar Yücel S. Artificial intelligence and robot nurses: From nurse managers ' perspective: A descriptive cross-sectional study. J Nurs Manag. 2022 Nov;30(8):3853-62. https://doi.org/10.1111/jonm.13646
  • Sheela J. Attitude of Nursing Students towards Artificial Intelligence Int J Sci Healthc Res. 2022;7(2):344-7. https://doi.org/10.52403/ijshr.20220447
  • Abdullah R, Fakieh B. Health care employees' perceptions of the use of artificial intelligence applications: Survey study. J Med Internet Res. 2020 May 14;22(5):e17620.. https://doi.org/10.2196/ 17620
  • WHO, 2020 State of the world's nursing 2020: investing in education, jobs and leadership https://www.who.int/publications/i/item/9789240003279
  • Ronquillo CE, Peltonen LM, Pruinelli L, Chu CH, Bakken S, Beduschi A, Cato K, Hardiker N, Junger A, Michalowski M, Nyrup R, Rahimi S, Reed DN, Salakoski T, Salanterä S, Walton N, Weber P, Wiegand T, Topaz M. Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative. J Adv Nurs. 2021 Sep;77(9):3707-3717. doi: 10.1111/jan.14855.
  • Cuschieri S. The STROBE guidelines. Saudi J Anaesth. 2019 Apr;13(Suppl 1):S31-S34. doi: 10.4103/sja.SJA_543_18.
  • Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007 May;39(2):175-91. doi: 10.3758/bf03193146.
  • Karaca O, Caliskan SA, Demir K. Medical artificial intelligence readiness scale for medical students (MAIRS-MS) – development, validity and reliability study. BMC Med Educ. 2021 Feb 18;21(1):112. https://doi.org/10.1186/s12909-021-02546-6
  • Xuan PY, Fahumida MIF, Hussain MIAN, Jayathilake NT, Khobragade S, Soe HHK, Moe S, Htay MNN. Readiness towards artificial intelligence among undergraduate medical students in Malaysia. Journal of Education in Medicine. 2023;15(2):49-60. DOI: 10.21315/eimj2023.15.2.4
  • Tamori H, Yamashina H, Mukai M, Morii Y, Suzuki T, Ogasawara K. Acceptance of the use of artificial intelligence in medicine among Japan's doctors and the public: a questionnaire survey. JMIR Hum Factors. 2022 Mar 16;9(1):e24680. doi: 10.2196/24680.
  • Maraş G, Albayrak Günday E, Sürme Y. Examining the Anxiety and Preparedness Levels of Nurses and Nurse Candidates for Artificial Intelligence Health Technologies. J Clin Nurs. Published online November 18, 2024. doi:10.1111/jocn.17562
  • Ghalibaf AM, Moghadasin M, Emadzadeh A, Mastour H. Psychometric properties of the persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS). BMC Med Educ. 2023 Aug 15;23(1):577. doi: 10.1186/s12909-023-04553-1.
  • AlZaabi A, AlMaskari S, AalAbdulsalam A. Are physicians andmedical students ready for artificial intelligence applications in healthcare? Digit Health. 2023 Jan 26;9:20552076231152167.
  • Li J, Huang JS. Dimensions of artificial intelligence anxiety based on the integrated fear acquisition theory. Technology in Society.2020;63(4):101410. https://doi.org/10.1016/j.techsoc.2020.101410
  • Elsayed WA, Sleem WF. Nurse Managers' perception and Attitudes toward Using Artificial Intelligence Technology in Health Settings. Assiut Scientific Nursing Journal. 2021;9(24):182-92. doi:10.21608/asnj.2021.72740.1159
  • Cruz JP, Sembekova A, Omirzakova D, Bolla SR, Balay-odao EM. General Attitudes Towards and Readiness for Medical Artificial Intelligence among Medical and Health Sciences Students in Kazakhstan. J Int Med Res Preprints. 2023:1-31. https://doi.org/10.2196/preprints.49536
  • Menekli T, Şentürk S. The relationship between artificial intelligence concerns and perceived spiritual care in internal medicine nurses. YOBU Faculty of Health Sciences Journal. 2022;3(2):210-8.
  • Kloka JA, Holtmann SC, Nürenberg-Goloub E, Piekarski F, Zacharowski K, Friedrichson B. Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study. JMIR Form Res. 2023 Jun 12;7:e43896. doi: 10.2196/43896.
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Hemşirelik (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Seher Çevik Aktura 0000-0001-7299-1788

Semiha Dertli 0000-0003-0291-8045

Gönderilme Tarihi 14 Şubat 2025
Kabul Tarihi 11 Ağustos 2025
Yayımlanma Tarihi 28 Ocak 2026
Yayımlandığı Sayı Yıl 2026 Cilt: 11 Sayı: 1

Kaynak Göster

APA Çevik Aktura, S., & Dertli, S. (2026). Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, 11(1), 105-112. https://doi.org/10.61399/ikcusbfd.1640227
AMA Çevik Aktura S, Dertli S. Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors. İKÇÜSBFD. Ocak 2026;11(1):105-112. doi:10.61399/ikcusbfd.1640227
Chicago Çevik Aktura, Seher, ve Semiha Dertli. “Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11, sy. 1 (Ocak 2026): 105-12. https://doi.org/10.61399/ikcusbfd.1640227.
EndNote Çevik Aktura S, Dertli S (01 Ocak 2026) Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11 1 105–112.
IEEE S. Çevik Aktura ve S. Dertli, “Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors”, İKÇÜSBFD, c. 11, sy. 1, ss. 105–112, 2026, doi: 10.61399/ikcusbfd.1640227.
ISNAD Çevik Aktura, Seher - Dertli, Semiha. “Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi 11/1 (Ocak2026), 105-112. https://doi.org/10.61399/ikcusbfd.1640227.
JAMA Çevik Aktura S, Dertli S. Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors. İKÇÜSBFD. 2026;11:105–112.
MLA Çevik Aktura, Seher ve Semiha Dertli. “Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors”. İzmir Katip Çelebi Üniversitesi Sağlık Bilimleri Fakültesi Dergisi, c. 11, sy. 1, 2026, ss. 105-12, doi:10.61399/ikcusbfd.1640227.
Vancouver Çevik Aktura S, Dertli S. Readiness of Nurses and Nursing Students to Use Artificial Intelligence in Healthcare and Influencing Factors. İKÇÜSBFD. 2026;11(1):105-12.