The Role of Socio-Demographic Characteristics in Physicians’ Attitudes Towards Artificial Intelligence

Öz

Aim: This study aims to determine the role of demographic characteristics in physicians’ attitudes toward the general applications of artificial intelligence (AI) and their attitudes toward the applications of AI in medicine.

Method: The descriptive, cross-sectional, and quantitative study consists of data collected from 265 physicians working at a tertiary education and research hospital using stratified sampling. The data collection tools included demographic characteristics, a general AI attitude scale, and an attitude scale toward AI applications in medicine.

Results: The findings show that physicians generally have a positive attitude toward AI, but male physicians have a more positive attitude than female physicians. Negative attitudes were found to be higher among physicians working in surgical clinics. Furthermore, demographic characteristics such as gender, clinic, and title were found to be significantly associated with physicians’ attitudes toward the general application of AI, while gender and department worked in had a significant association with attitudes toward the application of AI in medicine.

Conclusion: Physicians’ attitudes toward AI were found to differ according to demographic factors. In light of these findings, it is recommended that targeted education programs and policies be developed to increase physicians’ knowledge levels for a more effective integration of AI into the field of medicine. Strategies to raise awareness and address knowledge gaps and concerns are particularly important for female physicians and physicians working in surgical clinics.

Anahtar Kelimeler

• Artificial intelligence
• artificial intelligence in medicine
• physician attitude

Etik Beyan

Ethics committee permission for this study was obtained from the Gulhane Education and Research Hospital Education Planning Board and Ethics Committee (Date: 14.11.2024 , Issue no: 2024/69).

Hekimlerin Yapay Zekaya Karşı Tutumlarında Demografik Özelliklerin Rolü

Öz

Amaç: Bu çalışma, hekimlerin yapay zekânın (YZ) genel uygulamalarına yönelik tutumları ile YZ'nin tıptaki uygulamalarına yönelik tutumlarında demografik özelliklerin rolünü belirlemeyi amaçlamaktadır.

Yöntem: Betimleyici, kesitsel ve nicel yaklaşımla yapılan araştırma, üçüncü basamak bir eğitim ve araştırma hastanesinde görevli 265 hekimden tabakalı örneklem yöntemiyle toplanan verilerden oluşmaktadır. Veri toplama aracı olarak demografik özellikler, genel YZ tutum ölçeği ve tıpta YZ uygulamalarına yönelik tutum ölçeği kullanılmıştır.

Bulgular: Bulgular, hekimlerin YZ'ye karşı genel olarak olumlu bir tutum sergilediğini göstermekle birlikte, erkek hekimlerin kadın hekimlere göre daha olumlu tutuma sahip olduğunu ortaya koymuştur. Olumsuz tutumlar ise cerrahi klinikte çalışan hekimlerde daha yüksek bulunmuştur. Ayrıca demografik özelliklerden cinsiyet, çalışılan klinik ve unvanın, hekimlerin YZ'nin genel uygulamalarına yönelik tutumları üzerinde, cinsiyet ve çalışılan kliniğin ise YZ’nin tıptaki uygulamalarına yönelik tutumları üzerinde anlamlı bir etkiye sahip olduğunu göstermektedir.

Sonuç: Hekimlerin YZ'ye yönelik tutumlarının demografik faktörlere göre farklılaştığı tespit edilmiştir. Bu bulgular ışığında, YZ'nin tıp alanına daha etkili entegrasyonu için hekimlerin bilgi düzeylerini artırmaya yönelik hedeflenmiş eğitim programlarının ve politikaların geliştirilmesi önerilmektedir. Özellikle kadın hekimler ve cerrahi klinik bölümlerde çalışan hekimler için farkındalık, bilgi eksikliklerini ve endişelerini giderecek stratejiler önem taşımaktadır.

Anahtar Kelimeler

• Yapay zeka
• tıpta yapay zeka
• hekim tutumu

Etik Beyan

Bu çalışma için Gülhane Eğitim ve Araştırma Hastanesi Eğitim Planlama Kurulu ve Etik Komitesi'nden onay alınmıştır (Tarih: 14.11.2024, Sayı: 2024/69).

Kaynakça

1. 1. Keleş H. Tıpta yapay zeka uygulamaları. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi. 2022;24(3):604-613. doi:10.24938/kutfd.1214512.
2. 2. Liu DS, Sawyer J, Luna A, et al. Perceptions of us medical students on artificial ıntelligence in medicine: Mixed methods survey study. JMIR Med Educ. 2022;8(4). doi:10.2196/38325.
3. 3. Ahmed MM, Dirie NI, Mohamud AK, et al. Assessment of knowledge, attitudes, and practices in artificial intelligence among healthcare professionals in Mogadishu, Somalia. Research Square. Preprint posted online May 14, 2024. doi:10.21203/rs.3.rs-4359643/v1.
4. 4. Pedro AR, Dias MB, Laranjo L, Cunha AS, Cordeiro J V. Artificial intelligence in medicine: A comprehensive survey of medical doctor’s perspectives in Portugal. PLoS One. 2023;18(9 September). doi:10.1371/journal.pone.0290613.
5. 5. Chen M, Zhang B, Cai Z, et al. Acceptance of clinical artificial intelligence among physicians and medical students: A systematic review with cross-sectional survey. Front Med (Lausanne). 2022;9. doi:10.3389/fmed.2022.990604.
6. 6. Negash S, Gundlack J, Buch C, et al. Physicians’ attitudes and acceptance towards artificial intelligence in medical care: A qualitative study in Germany. Front Digit Health. 2025;7. doi:10.3389/fdgth.2025.1616827.
7. 7. Serin O, Yıldırım BF, Duman F, et al. Physician perspectives on Artificial Intelligence in healthcare: A cross-sectional study of child-focused care in a Turkish tertiary hospital. Int J Med Inform. 2025;203. doi:10.1016/j.ijmedinf.2025.106003.
8. 8. Hassan M, Kushniruk A, Borycki E. Barriers to and facilitators of artificial ıntelligence adoption in health care: Scoping review. JMIR Hum Factors. JMIR Publications Inc. 2024;11. doi:10.2196/48633.

9. 9. Lambert SI, Madi M, Sopka S, et al. An integrative review on the acceptance of artificial intelligence among healthcare professionals in hospitals. NPJ Digit Med. Nature Research. 2023;6(1). doi:10.1038/s41746-023-00852-5.
10. 10. Başar EE, Kes Erkul A. Factors affecting the attitude of medical doctors in Türkiye towards using artificial ıntelligence applications in healthcare services. Bezmialem Science. Published online July 31, 2024:297-308. doi:10.14235/bas.galenos.2024.26879.
11. 11. Schepman A, Rodway P. The general attitudes towards Artificial Intelligence Scale (gaaıs): Confirmatory validation and associations with personality, corporate distrust, and general trust. Int J Hum Comput Interact. 2023;39(13):2724-2741. doi:10.1080/10447318.2022.2085400.
12. 12. Kaya F, Aydin F, Schepman A, Rodway P, Yetişensoy O, Demir Kaya M. The roles of personality traits, AI anxiety, and demographic factors in attitudes toward artificial ıntelligence. Int J Hum Comput Interact. 2024;40(2):497-514. doi:10.1080/10447318.2022.2151730.
13. 13. Oh S, Kim JH, Choi SW, Lee HJ, Hong J, Kwon SH. Physician confidence in artificial intelligence: An online mobile survey. J Med Internet Res. 2019;21(3). doi:10.2196/12422.
14. 14. Kovacevic A, Demic E. The impact of gender, seniority, knowledge, and ınterest on attitudes to artificial ıntelligence. IEEE Access. 2024;12:129765-129775. doi:10.1109/ACCESS.2024.3454801.
15. 15. Al-Medfa MK, Al-Ansari AMS, Darwish AH, Qreeballa TA, Jahrami H. Physicians’ attitudes and knowledge toward artificial intelligence in medicine: Benefits and drawbacks. Heliyon. 2023;9(4). doi:10.1016/j.heliyon.2023.e14744.
16. 16. Chen Y, Wu Z, Wang P, et al. Radiology Residents’ Perceptions of artificial ıntelligence: Nationwide cross-sectional survey study. J Med Internet Res. 2023;25(1). doi:10.2196/48249.
17. 17. Alrashed FA, Ahmad T, Alsabih AO, Mahmoud S, Almurdi MM, Abdulghani HM. Exploring medical doctors’ confidence in artificial ıntelligence: The role of specialty, experience, and perceived job security. Healthcare (Switzerland). 2025;13(18). doi:10.3390/healthcare13182377.
18. 18. Sarwar S, Dent A, Faust K, et al. Physician perspectives on integration of artificial intelligence into diagnostic pathology. NPJ Digit Med. 2019;2(1). doi:10.1038/s41746-019-0106-0.
19. 19. Coppola F, Faggioni L, Regge D, et al. Artificial intelligence: Radiologists’ expectations and opinions gleaned from a nationwide online survey. Radiologia Medica. 2021;126(1):63-71. doi:10.1007/s11547-020-01205-y.