HEMŞİRELİK ÖĞRENCİLERİNİN SAĞLIK HİZMETLERİNDE YAPAY ZEKA VE ROBOT TEKNOLOJİLERİ KULLANIMINA İLİŞKİN GÖRÜŞLERİ: NİTEL BİR ÇALIŞMA

Öz

Amaç: Bu çalışma, hemşirelik öğrencilerinin sağlık hizmetlerinde yapay zeka ve robot teknolojilerine ilişkin algılarını keşfetmeyi amaçladı. Yöntem: Bu çalışma, 43 hemşirelik öğrencisinin deneyimlerini incelemek amacıyla tanımlayıcı nitel bir araştırma deseniyle yürütüldü. Araştırma, 2023-2024 akademik yılının bahar döneminde Türkiye'deki bir devlet üniversitesinde gerçekleştirildi. Veriler, “Katılımcı Bilgi Formu” ve yarı yapılandırılmış “Sağlık Hizmetlerinde Yapay Zeka ve Robotik Teknolojilerin Kullanımına İlişkin Öğrenci Görüşme Formu” aracılığıyla toplandı. Nicel veriler tanımlayıcı istatistiklerle özetlendi, nitel yanıtlar ise tematik analizle değerlendirildi. Araştırma öncesinde etik onay alındı. Bulgular: Katılımcıların %53.5’i erkek olup, %58.2’si 23-25 yaş aralığındaydı. Ayrıca %32.6’sı günde dört saat veya daha fazla süreyle internet kullandığını bildirdi. Öğrencilerin %51.2’si yapay zekâ kavramına aşina olduğunu belirtirken %44.2’si bu teknolojinin sağlık hizmetlerindeki uygulamalarına kısmen aşina olduğunu ifade etti. Tematik analiz sonucunda beş ana tema belirlendi: Uygulama Alanları, Hasta-Hemşire Etkileşimine Olumlu Etki, Hasta-Hemşire Etkileşimine Olumsuz Etki, Etik Sorunlar ve Gelecek Potansiyeli. Öğrenciler yapay zekânın verimlilik, doğruluk ve bakım kalitesini artırma konusundaki faydalarını kabul ettiler, ancak etik sorunlar, empati kaybı ve hemşire-hasta ilişkisinin zayıflaması gibi endişeleri de dile getirdiler. Sonuç: Bulgular, hemşirelik öğrencilerinin sağlık hizmetlerinde yapay zekâ ve robotik teknolojilerin kullanımına ilişkin hem fırsatların hem de zorlukların farkında olduklarını göstermektedir. Öğrencilerin bakış açıları, geleceğin hemşirelerinin gelişen teknolojilerle eleştirel bir biçimde ilişki kurabilme becerisiyle donatılmasının önemini ortaya koymaktadır. Bu nedenle hemşirelik müfredatına yapay zekâ ve robotik sistemler hakkında kapsamlı içeriklerin dâhil edilmesi, bunun yanında etik akıl yürütme ve klinik karar verme konularında eğitim verilmesi önerilmektedir. Ayrıca bu tür yeniliklerin klinik uygulamalara entegre edilmesinde kapsamlı risk değerlendirmeleri yapılmalı ve hasta güvenliği ile insancıl bakımın korunması öncelikli olarak gözetilmelidir.

Anahtar Kelimeler

• Hemşirelik
• Nitel Araştırma
• Robotik
• Yapay Zeka

NURSING STUDENTS' PERSPECTIVES ON THE USE OF ARTIFICIAL INTELLIGENCE AND ROBOTIC TECHNOLOGIES IN HEALTHCARE: A QUALITATIVE STUDY

Öz

Objective: This study aimed to explore nursing students’ perceptions of artificial intelligence and robotic technologies in healthcare. Method: A descriptive qualitative research design was employed to explore the experiences of 43 nursing students. The study was carried out at a public university in Türkiye during the spring semester of the 2023-2024 academic year. Data were collected via a “Participant Information Form” and a semi-structured “Student Interview Form on the Use of Artificial Intelligence and Robotic Technologies in Healthcare”. Descriptive statistics summarized the quantitative data, while thematic analysis was applied to the qualitative responses. Ethical approval was obtained before the study. Results: Among the participants, 53.5% were male, and 58.2% were between 23 and 25 years of age. Additionally, 32.6% reported using the internet for four or more hours per day. Furthermore, 51.2% of the students stated that they were familiar with the concept of artificial intelligence, while 44.2% reported having partial familiarity with its applications in healthcare. Thematic analysis identified five major themes: Areas of Application, Positive Impact on Patient-Nurse Interaction, Negative Impact on Patient-Nurse Interaction, Ethical Issues, and Future Potential. Students acknowledged the benefits of artificial intelligence in improving efficiency, accuracy, and care quality, but also raised concerns about ethical challenges, empathy loss, and weakened nurse-patient relationships. Conclusion: The findings indicate that nursing students are aware of both the opportunities and challenges associated with the use of artificial intelligence and robotics in healthcare. Their perspectives highlight the importance of preparing future nurses to critically engage with emerging technologies. Therefore, it is recommended that nursing curricula include comprehensive content on AI and robotic systems, accompanied by training in ethical reasoning and clinical judgment. Furthermore, when implementing such innovations in clinical practice, it is essential to conduct thorough risk assessments and to prioritize patient safety and the preservation of compassionate care.

Anahtar Kelimeler

• Artificial Intelligence
• Nursing
• Qualitative Research
• Robotics

Kaynakça

1. Akalın B, Veranyurt Ü. Digitalization in health and artificial intelligence. SDU Healthcare Management Journal. 2020;2(2):131-141.
2. Cilhoroz Y, Isık O. Artificial intelligence: Applications in healthcare services. Ankara Hacı Bayram Veli University Journal of Faculty of Economics and Administrative Sciences. 2021;23(2):573-588.
3. Doğaner A. The approaches and expectations of the health sciences students towards artificial intelligence. Karya Journal of Health Science. 2021;2(1):5-11.
4. Teng M, Singla R, Yau O, et al. Health care students’ perspectives on artificial intelligence: countrywide survey in Canada. JMIR medical education. 2022;8(1):e33390.
5. Yılmaz Y, Yılmaz DU, Yıldırım D, Korhan EA, Kaya DÖ. Artificial intelligence and health sciences faculty students’ views on the use of artificial intelligence in healthcare. Süleyman Demirel University Journal of Health Sciences. 2021;12(3):297-308.
6. Akgerman A, Yavuz EDO, Kavaslar I, Gungor S. Artificial intelligence and nursing. Journal of Artificial Intelligence in Health Sciences. 2022;2(1):21-27.
7. Cetin B, Eroglu N. Innovative Technologies in Nursing Care. Acta Medica Nicomedia. 2020;3(3):120-126.
8. Seibert K, Domhoff D, Bruch D, et al. Application scenarios for artificial intelligence in nursing care: rapid review. J. Med. Internet Res. 2021;23(11):e26522.

9. Chang CY, Jen HJ, Su WS. Trends in artificial intelligence in nursing: Impacts on nursing management. J Nurs Manag. 2022;30(8):3644-3653.
10. McGrow K. Artificial intelligence: Essentials for nursing. Nursing. 2019;46(9):46-49.
11. Goktas P, Kucukkaya A, Karacay P. Utilizing GPT 4.0 with prompt learning in nursing education: A case study approach based on Benner's theory. Teach Learn Nurs. 2024;19(2):e358-e367.
12. Kucukkaya A, Arikan E, Goktas P. Unlocking ChatGPT’s potential and challenges in intensive care nursing education and practice: A systematic review with narrative synthesis. Nursing Outlook. 2024;72(6):102287.
13. Robert N. How artificial intelligence is changing nursing. Nurs Manage. 2019;50(9):30-39.
14. Aslan F, Subası A. A Different Look at Artificial Intelligence Technologies from the Perspective of Nursing Education and Nursing Process. Health Sciences University Journal of Nursing. 2022;4(3):153-158.
15. Gümüs E, Kasap E. The future of the nursing profession: robot nurses. Journal of Artificial Intelligence in Health Sciences. 2021;1(2):20-25.
16. Sendir M, Simsekoglu N, Abdulsamed K, Sumer K. Nursing in future technology. Health Sciences University Journal of Nursing. 2019;1(3):209-214.
17. Yıldırım A, Şimşek H. Qualitative research methods in the social sciences. (8th ed.). Seckin Press. 2011.
18. Torres-Gordillo JJ, Rodríguez-Santero J. COREQ (Consolidated criteria for reporting qualitative research) checklist. 2023.
19. Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. 2007;19(6):349-357.
20. Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs. 2008;62(1):107-115.
21. Alcan AO, Soyer O, Van Giersbergen MY, Solak M, Yoltay HE. Examination of Nurses' Opinions on Robotic Surgery. J Health Sci Kocaeli Univ. 2019;5(1):5-9.
22. Coban N, Eryigit T, Seda D, Beydag D, Ortabag T. The place of artificial intelligence and robot technologies in the nursing profession. FBU-JOHS. 2022;2(1):378-385.
23. Badilla-Solórzano J, Spindeldreier S, Ihler S, Gellrich N-C, Spalthoff S. Deep-learning-based instrument detection for intra-operative robotic assistance. Int J Comput Assist Radiol Surg. 2022;17(9):1685-1695.
24. 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. Nurse Educ Today. 2021;97:104700.
25. Jiang M, Ma Y, Guo S, et al. Using machine learning technologies in pressure injury management: systematic review. JMIR Med. Inform. 2021;9(3):e25704.
26. Yen P-Y, Kellye M, Lopetegui M, et al. Nurses’ time allocation and multitasking of nursing activities: A time motion study. AMIA Annu Symp Proc. 2018;2018:1137-1146.
27. Goeldner M, Herstatt C, Tietze F. The emergence of care robotics-A patent and publication analysis. Technological Forecasting and Social Change. 2015;92:115-131.
28. Carroll WM. Artificial intelligence, critical thinking and the nursing process. Online J Nurs Inform. 2019;23(1).
29. Campbell B. Alone Together: Why We Expect More from Technology and Less from Each Other. Journal of Interdisciplinary Studies. 2021;33(1-2):196-199.
30. Turkle S. The tethered self: Technology reinvents intimacy and solitude. Continuing Higher Education Review. 2011;75:28-31.
31. Pepito JA, Locsin R. Can nurses remain relevant in a technologically advanced future? Int J Nurs Sci. 2019;6(1):106-110.
32. Asada M. Development of artificial empathy. Neuroscience Research. 2015;90:41-50.
33. Sharkey N, Sharkey A. The crying shame of robot nannies: an ethical appraisal. Interaction Studies. 2010;11(2):161-190.
34. Abdullah R, Fakieh B. Health care employees’ perceptions of the use of artificial intelligence applications: survey study. J Med Internet Res. 2020;22(5):e17620.
35. Taryudi T, Lindayani L, Purnama H, Mutiar A. Nurses' view towards the use of robotic during pandemic COVID-19 in Indonesia: a qualitative study. Macedonian Journal of Medical Sciences. 2022;10(G):14-18.
36. Ergin E, Karaarslan D, Sahan S, Cınar YUcel S. Artificial intelligence and robot nurses: from nurse managers' perspective: a descriptive cross‐sectional study. J Nurs Manag. 2022;30(8):3853-3862.
37. Higgins D, Madai VI. From bit to bedside: a practical framework for artificial intelligence product development in healthcare. Adv Intell Syst. 2020;2(10):2000052.