Measuring The General Attitudes of Students Studying in Health Services Departments Towards Artificial Intelligence: The Example of Altınbaş University Health Services Vocational School
Öz
Over the past two decades, rapid technological advancements have taken place globally, gaining further momentum during the COVID-19 pandemic in response to emerging needs. This process has led to the widespread integration of artificial intelligence technologies into various domains. As a result, individuals have been compelled to adapt to this transformation, and AI-integrated systems have become an essential part of daily life. This transformation has had significant impacts not only on fields such as economics, communication, and industry but also on the healthcare sector. This study aims to examine the general attitudes of students enrolled in health services programmes towards artificial intelligence. Specifically, the study seeks to identify any existing biases before students enter their professional lives and to support the development of technological competencies in line with the demands of the digital era. To this end, the "General Attitudes Towards Artificial Intelligence Scale" was employed to measure individuals’ exposure to technology and their positive or negative perceptions of AI. The scale was administered via an online survey created through Google Forms. From a population of 3,200 students, the planned sample size was 343, and 368 valid responses were ultimately obtained. The collected data were analysed using descriptive and inferential statistical methods with the SPSS software package. The findings revealed that participants' attitudes towards AI significantly differed by gender. However, daily use of social media, computers, and mobile phones did not have a statistically significant effect on their attitudes towards artificial intelligence.
Anahtar Kelimeler
Kaynakça
- Alhejaily A. G. (2024). Artificial intelligence in healthcare (Review). Biomedical Reports, 22(1), 11. https://doi.org/10.3892/br.2024.1889 google scholar
- Aminatun, D., & Oktaviani, L. (2019). Using “Memrıse” To Boost Englısh For Busıness Vocabulary Mastery: Students’vıewpoınt. Proc. Univ. PAMULANG, 1(1). google scholar
- Association of American Medical Colleges. (2024). Artificial intelligence and academic medicine (Data snapshot & resources). https://www.aamc.org/ google scholar
- Association of American Medical Colleges. (2025). Artificial intelligence competencies for medical educators. https://www.aamc.org/ google scholar
- Bacaksız, F. E., Yılmaz, M., Ezizi, K., & Alan, H. (2020). Sağlık hizmetlerinde robotları yönetmek. Journal of Health and Nursing Management, 3(7), 458-465. https://dx.doi.org/10.5222/SHYD.2020.59455 google scholar
- Bartlett, M. S. (1954). A note on the multiplying factors for various χ 2 approximations. Journal of the Royal Statistical Society. Series B (Methodological), 296-298. https://www.jstor.org/stable/2984057 google scholar
- Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., Brynjolfsson, E., Buch, S., Card, D., Castellon, R., Chatterji, N. S., Chen, A., Creel, K., Davis, J. Q., … Liang, P. (2021). On the opportunities and risks of foundation models. ArXiv. https://ui.adsabs.harvard.edu/link_gateway/2021arXiv210807258B/doi:10.48550/arXiv.2108.07258 google scholar
- Chaddad, A., Peng, J., Xu, J., & Bouridane, A. (2023). Survey of explainable AI techniques in healthcare. Sensors, 23(2), 634. https://doi.org/10.3390/s23020634 google scholar
Ayrıntılar
Birincil Dil
İngilizce
Konular
Hastane İşletmeciliği
Bölüm
Araştırma Makalesi
Yazarlar
Agit Ferhat Özel
0000-0001-8208-2019
Türkiye
Canan Bulut
*
0000-0001-5092-5261
Türkiye
Gamze Turun
0000-0002-6237-2817
Türkiye
Yayımlanma Tarihi
18 Haziran 2026
Gönderilme Tarihi
2 Eylül 2025
Kabul Tarihi
13 Şubat 2026
Yayımlandığı Sayı
Yıl 2026 Sayı: 100