HEMŞİRELİK ÖĞRENCİLERİNİN YAPAY ZEKAYA YÖNELİK GENEL TUTUMLARI VE ETKİLEYEN FAKTÖRLER

Abstract

Bu araştırma, hemşirelik öğrencilerinin yapay zekaya yönelik genel tutumlarını ve etkileyen faktörleri incelemek amacıyla tanımlayıcı ve kesitsel tipte bir çalışma olarak yapılmıştır. Araştırmanın evrenini Kütahya Üniversitesi Sağlık Bilimleri Fakültesi Hemşirelik Bölümü öğrencileri (n=550) oluşturmaktadır. Örneklem seçimine gidilmemiş olup, çalışmaya katılmaya gönüllü olan öğrencilerle (n=420) 15.04.2024-01.05.2024 tarihleri arasında yürütülmüştür ve evrenin %76.36’sına ulaşılmıştır. Veriler, SPSS 22.00 kullanılarak sayı, yüzde, ortalama, standart sapma, t testi, tek yönlü varyans analizi, Scheffe ve Tukey testleri kullanılarak analiz edilmiştir. Yaş ortalaması 20.83 ±1.72 olan öğrencilerin %77.9’unun kadın, %55’inin üç ve daha fazla kardeşi olduğu, %74’ünün Anadolu Lisesi mezunu olduğu, %51.7’sinin annesinin ilkokul mezunu, %32.9’unun babasının lise mezunu olduğu bulunmuştur. Yapay zekanın günlük kullanımı hakkında öğrencilerin %80.5’inin bilgisinin olduğu, %50.7’sinin ise yapay zekanın hemşirelik alanında kullanımı hakkında bilgisinin olduğu saptanmıştır. Öğrencilerin yapay zekaya yönelik genel tutum ölçeği puan ortalaması 68.00±10.59’dur. Cinsiyet, anne ve baba eğitim durumu, gelir durumu ve yapay zekanın günlük hayatta kullanımı hakkında bilgi sahibi olma durumunun yapay zekaya yönelik tutumları etkilediği bulunmuştur. Bu sonuçlar da sosyodemografik özelliklerin yapay zekaya yönelik tutumlarda önemli rol oynadığını göstermektedir. Bu nedenle cinsiyet, eğitim farklılıkları, müfredat boşlukları gibi konularda çalışmaların ve iyileştirmelerin planlanması önerilebilir.

Keywords

• Hemşirelik öğrencisi
• sağlık
• tutum
• yapay zeka

GENERAL ATTITUDES OF NURSING STUDENTS TOWARDS ARTIFICIAL INTELLIGENCE AND AFFECTING FACTORS

Abstract

This research was conducted as a descriptive and cross-sectional study in order to examine the general attitudes of nursing students towards artificial intelligence and the influencing factors. The universe of the research consists of students of Kütahya University, Faculty of Health Sciences, Department of Nursing (n=550). No sample selection was made, the study was conducted between 15.04.2024 and 01.05.2024 with students who volunteered to participate (n=420), and 76.36% of the universe was reached. Data were analyzed using SPSS 22.00 using numbers, percentages, mean, standard deviation, t test, one-way analysis of variance, Scheffe and Tukey tests. It was found that 77.9% of the students, whose average age was 20.83 ±1.72, were female, 55% had three or more siblings, 74% were Anatolian High School graduates, 51.7% of their mothers were primary school graduates, and 32.9% of their fathers were high school graduates. It was determined that 80.5% of the students had knowledge about the daily use of artificial intelligence, and 50.7% had knowledge about the use of artificial intelligence in the field of nursing. The students' general attitude scale score average towards artificial intelligence is 68.00±10.59. It was found that gender, mother and father's education level, income level and knowledge about the use of artificial intelligence in daily life affect attitudes towards artificial intelligence. These results also show that sociodemographic characteristics play an important role in attitudes towards artificial intelligence. Therefore, it can be suggested to plan studies and improvements on issues such as gender, educational differences and curriculum gaps.

Keywords

• Nursing student
• health
• attitude
• artificial intelligence

References

1. Wong SH, Al-Hasani H, Alam Z, Alam A. Artificial intelligence in radiology: how will we be affected? Eur Radiol. 2019;29:141-143. doi:10.1007/s00330-018-5644-3.
2. Truong NM, Vo TQ, Tran HTB, Nguyen HT, Pham VNH. Healthcare students’ knowledge, attitudes, and perspectives toward artificial intelligence in the southern Vietnam. Heliyon. 2023;9(12):e22653. doi:10.1016/j.heliyon.2023.e22653.
3. Jallad ST, Alsaqer K, Albadareen BI, Almaghaireh D. Artificial intelligence tools utilized in nursing education: Incidence and associated factors.Nurse Educ Today. 2024;142:106355. doi:10.1016/j.nedt.2024.106355.
4. Sheela J. Attitude of nursing students towards artificial intelligence. IJSHR. 2022;7(2):344-347. doi:10.52403/ijshr.20220447.
5. 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. Nurse Educ Today. 2023;130:105945. doi:10.1016/j.nedt.2023.105945.
6. Lukić A, Kudelić N, Antičević V, et al. First-year nursing students’ attitudes towards artificial intelligence: Cross-sectional multi-center study. Nurse Educ Pract. 2023;71:103735. doi:10.1016/j.nepr.2023.103735.
7. Horowitz MC, Kahn L. What influences attitudes about artificial intelligence adoption: Evidence from U.S. local officials. PLoS One. 2021;16(10):e0257732. doi:10.1371/journal.pone.0257732.
8. Migdadi MK, Oweidat IA, Alosta MR, Al-Mugheed K, Saeed Alabdullah AA, Farghaly Abdelaliem SM. The association of artificial intelligence ethical awareness, attitudes, anxiety, and intention-to-use artificial intelligence technology among nursing students. Digit Health. 2024;10:20552076241301958. doi:10.1177/205520 76241301958.

9. Schepman A, Rodway P. Initial validation of the general attitudes towards Artificial Intelligence Scale. Comput Hum Behav Rep. 2020;1:100014. doi:10.1016/j. chbr.2020.100014.
10. Kaya F, Aydin F, Schepman A, Rodway P, Yetişensoy O, Demir Kaya M. The roles of personality traits, al anxiety, and demographic factors in attitudes toward artificial intelligence. Int J Hum-Comput Int. 2022;40(2):497-514. doi:10.1080/10447318. 2022.2151730.
11. Kandemir F, Azizoğlu F. Hemşirelerin yapay zekaya yönelik genel tutumlarının incelenmesi. Yoğun Bakım Hemşireliği Dergisi, 2024;28(2):113-125. doi:10.62111/ ybhd.1502758.
12. Kwak Y, Ahn JW, Seo YH. Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nurs. 2022;21(1):267. doi:10.1186/s12912-022-01048-0.
13. Abou Hashish EA, Alnajjar H. Digital proficiency: assessing knowledge, attitudes, and skills in digital transformation, health literacy, and artificial intelligence among university nursing students. BMC Med Educ. 2024;24(1):508. doi:10.1186/s12909-024-05482-3.
14. Alruwaili MM, Abuadas FH, Alsadi M, et al. Exploring nurses’ awareness and attitudes toward artificial intelligence: Implications for nursing practice. Digit Health. 2024;10:20552076241271803. doi:10.1177/20552076241271803.
15. Wang X, Fei F, Wei J, et al. Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study. Front Public Health. 2024;12:1433252. doi:10.3389/fpubh.2024.1433252.
16. Salem GMM, El-Gazar HE, Mahdy AY, Alharbi TAF, Zoromba MA. Nursing students’ personality traits and their attitude toward artificial ıntelligence: A multicenter cross‐sectional study. J Nurs Manag. 2024;2024(1):6992824. doi:10.1155/ 2024/6992824.
17. Kilci Erciyas Ş, Cirban Ekrem E, Keten Edis E. Relationship between individual innovativeness levels and attitudes toward artificial intelligence among nursing and midwifery students. Comput Inform Nurs. 2024;42(11):802-808. doi:10.1097/ CIN.0000000000001170.
18. Amiri H, Peiravi S, Rezazadeh Shojaee SS, et al. Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis. BMC Med Educ. 2024;24(1):412. doi:10.1186/s12909-024-05406-1.
19. Ofosu-Ampong K. Gender differences in perception of artificial intelligence-based tools. JDAH. 2023;4(2):52-56. doi:10.33847/2712-8149.4.2_6.
20. Sumengen AA, Subasi DO, Cakir GN. Nursing students' attitudes and literacy toward artificial intelligence: a cross-sectional study. Teaching and Learning in Nursing. 2025; 20(1): e250-e257. doi:10.1016/j.teln.2024.10.022
21. 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. 2023;Preprints. doi:10.2196/ preprints.49536.
22. Al-Qerem W, Eberhardt J, Jarab A, et al. Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions’ students in Jordan. BMC Med Inform Decis Mak. 2023;23(1):288. doi:10.1186/s12911-023-02403-0.
23. Doğaner A. The approaches and expectations of the health sciences students towards artificial intelligence. Karya J Health Sci. 2021;2(1):5-11.