Journals / Anadolu Üniversitesi Sosyal Bilimler Dergisi / 2026 / Cilt: 26 Sayı: 1

A Study on the Relationship Between Medical Secretary Candidates’ Levels of Concern Regarding Artificial Intelligence and Their Artificial Intelligence Literacy

Tıbbi Sekreter Adaylarının Yapay Zekâ Konusundaki Kaygı Düzeylerinin Yapay Zekâ Okuryazarlığıyla İlişkisi Üzerine Bir Araştırma

Pages
91–109
Publication Date
2026-03-28
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Abstract

The aim of this study is to determine the levels of anxiety towards artificial intelligence among students of the Medical Documentation and Secretarial Programme and to reveal the relationship between this anxiety and artificial intelligence literacy. This descriptive and cross-sectional study involved a sample group of 287 students enrolled at Mersin, Tarsus, and Çağ Universities during the 2024-2025 academic year. Data were collected using the Artificial Intelligence Anxiety Scale (AIAS), the Artificial Intelligence Literacy Scale (AILS), and a questionnaire designed to obtain sociodemographic information about the students. The average AAS score of the participants was 47.30±13.72, while the average ALE score was 99.84±39.06. Female students experienced more anxiety than male students, second-year students experienced more anxiety than first-year students, and students who did not believe in the necessity of artificial intelligence or were undecided experienced more anxiety than students who believed in it. A weak positive correlation was found between AIOL and AIAS. The study recommends updating educational curricula and organising awareness programmes to increase artificial intelligence literacy and reduce anxiety.

Özet

Bu çalışmanın amacı, Tıbbi Dokümantasyon ve Sekreterlik Programı öğrencilerinin yapay zekâya yönelik kaygı düzeylerini belirlemek ve bu kaygıyla yapay zekâ okuryazarlığı arasındaki ilişkiyi ortaya koymaktır. Tanımlayıcı ve kesitsel nitelikte olan bu araştırmanın örneklem grubunu 2024-2025 Eğitim Öğretim Yılında Mersin, Tarsus ve Çağ Üniversitelerinde öğrenim gören 287 öğrenci oluşturmuştur. Verilerin toplanmasında, Yapay Zekâ Kaygı Ölçeği (YZKÖ), Yapay Zekâ Okuryazarlığı Ölçeği (YZOÖ) ve öğrencilere ait sosyodemografik bilgileri elde etmeye yönelik hazırlanan soruların yer aldığı Anket Formu kullanılmıştır. Katılımcıların YZKÖ puan ortalaması 47,30±13,72, YZOÖ puan ortalaması ise 99,84±39,06’dır. Kadın öğrenciler erkek öğrencilere, ikinci sınıf öğrencileri birinci sınıf öğrencilerine ve yapay zekânın gerekliliğine inanmayan veya kararsız olan öğrenciler inanan öğrencilere göre daha fazla kaygı yaşamaktadır. YZKÖ ile YZOÖ arasında zayıf düzeyde pozitif bir ilişki saptanmıştır. Çalışmada, yapay zekâ okuryazarlığını artırmak ve kaygıyı azaltmak için eğitim müfredatlarının güncellenmesi ve farkındalık programlarının düzenlenmesi önerilmektedir.

Keywords
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Cite This Article

Sarı, B. (2026). A Study on the Relationship Between Medical Secretary Candidates’ Levels of Concern Regarding Artificial Intelligence and Their Artificial Intelligence Literacy. Anadolu Üniversitesi Sosyal Bilimler Dergisi, Cilt: 26 Sayı: 1, 91–109. https://doi.org/10.18037/ausbd.1735626

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References (53)

  1. Abdullah, R., & Fakieh, B. (2020). Health care employees’ perceptions of the use of artificial intelligence applications: Survey study. Journal of Medical Internet Research, 22(5), e17620. http://doi:10.2196/17620
  2. Abuzaid, M. M., Elshami, W., Tekin, H., & Issa, B. (2022). Assessment of the willingness of radiologists and radiographers to accept the integration of artificial intelligence into radiology practice. Academic Radiology, 29(1), 87-94. https://doi.org/10.1016/j.acra.2020.09.014
  3. Akkaya, B., Özkan, A., & Özkan, H. (2021). Yapay zekâ kaygı (YZK) ölçeği: Türkçeye uyarlama, geçerlik ve güvenirlik çalışması. Alanya Akademik Bakış, 5(2), 1125-1146. https://doi.org/10.29023/alanyaakademik.833668
  4. Aktaş Reyhan, F., & Dağlı, E. (2023). Ebelik öğrencilerin yapay zekâ kaygı durumlarının değerlendirilmesi. Cumhuriyet Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 8(Special Issue), 290-296. https://doi.org/10.51754/cusbed.1286594
  5. Ali, M., & Mughari, S. (2024). Effect of AI literacy on online information search competencies among medical students in Pakistan. Information Development. https://doi.org/10.1177/02666669241299765
  6. Berghea, E. C., Ionescu, M. D., Gheorghiu, R. M., Tincu, I. F., Cobilinschi, C. O., Craiu, M., Balgradean, M., & Berghea, F. (2024). Integrating artificial intelligence in pediatric healthcare: parental perceptions and ethical implications. Children (Basel, Switzerland), 11(2), 240. https://doi.org/10.3390/children11020240
  7. Bisdas, S., Topriceanu, C.-C., Zakrzewska, Z., Irimia, A.-V., Shakallis, L., Subhash, J., Casapu, M.-M., Leon-Rojas, J., dos Santos, D., Andrews, D. M., Zeicu, C., Bouhuwaish, A. M., Lestari, A. N., Abu-Ismail, L., Sadiq, A. S., Khamees, A., Mohammed, K. M. G., Williams, E., Omran, A. I., & Ebrahim, E. H. (2021). Artificial intelligence in medicine: A multinational multi-center survey on the medical and dental students’ perception. Frontiers in Public Health, 9, 795284. https://doi.org/10.3389/fpubh.2021.795284
  8. Büyüköztürk, Ş. (2021). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni SPSS uygulamaları ve yorum (29. bs.). Pegem Akademi.
  9. Castagno, S., & Khalifa, M. (2020). Perceptions of artificial intelligence among healthcare staff: A qualitative survey study. Frontiers in Artificial Intelligence, 84. https://doi.org/10.3389/frai.2020.578983
  10. Clipper, B., Batcheller, J., Thomaz, A. L., & Rozga, A. (2018). Artificial intelligence and robotics: A nurse leader's primer. Nurse Leader, 16(6), 379-384. https://doi.org/10.1016/j.mnl.2018.07.015
  11. Dağaşan, A. (2025). Dijital okuryazarlık ile yapay zekâ okuryazarlığı arasındaki ilişkide bilgi ve iletişim teknolojilerine yönelik tutumun aracı rolü. Uluslararası Türkçe Edebiyat Kültür Eğitim (TEKE) Dergisi, 14(1), 238-251. https://doi.org/10.7884/teke.1628023
  12. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
  13. dos Santos, D. P., Giese, D., Brodehl, S., Chon, S. H., Staab, W., Kleinert, R., Maintz, D., & Baßler, B. (2019). Medical students’ attitude towards artificial intelligence: A multicentre survey. European Radiology, 29(4), 1640–1646. https://doi.org/10.1007/s00330-018-5601-1
  14. Filiz, E., Güzel, Ş., & Şengül, M. (2022). Sağlık profesyonellerinin yapay zeka kaygı durumlarının incelenmesi, Journal of Academic Value Studies, 8(1), 47-55
  15. Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254-280. https://doi.org/10.1016/j.techfore.2016.08.019
  16. Gunkel, D. J. (2020). An introduction to artificial intelligence and ethics. MIT Press.
  17. Güzel, Ş., Dömbekci, H. A., & Eren, F. (2022). Yapay zekânın sağlık alanında kullanımı: nitel bir araştırma. Celal Bayar Üniversitesi Sağlık Bilimleri Enstitüsü Dergisi, 9(4), 509-519. https://doi.org/10.34087/cbusbed.1140122
  18. Hopson, S., Mildon, C., Hassard, K., Urie, P., & Corte, D. (2024). Equipping future physicians with artificial intelligence competencies through student associations. International Medical Education, 3(4), 388-394. https://doi.org/10.3390/ime3040029
  19. Horváth, L. (2024). Use of artificial intelligence in light of AI literacy and AI anxiety among Hungarian higher education students-a pilot study. Learning in the Age of AI: Towards Imaginative Futures, 60.
  20. Huang, M. H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172. https://doi.org/10.1177/1094670517752459
  21. Johnson, D. G., & Verdicchio, M. (2017). AI anxiety. Journal of the Association for Information Science and Technology, 68(9), 2267-2270. https://doi.org/10.1002/asi.23867
  22. Karaoğlan Yılmaz, F. G., & Yılmaz, R. (2023). Yapay zekâ okuryazarlığı ölçeğinin Türkçeye uyarlanması. Bilgi ve İletişim Teknolojileri Dergisi, 5(2), 172-190. https://doi.org/10.53694/bited.1376831
  23. Kimiafar, K., Sarbaz, M., Tabatabaei, S., Ghaddaripouri, K., Mousavi, A., Mehneh, M., … & Baigi, S. (2023). Artificial intelligence literacy among healthcare professionals and students: a systematic review. Frontiers in Health Informatics, 12, 168. https://doi.org/10.30699/fhi.v12i0.524
  24. Kong, S.-C., Man-Yin Cheung, W., & Zhang, G (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers and Education: Artificial Intelligence, 2, 100026. https://doi.org/10.1016/j.caeai.2021.100026
  25. Kuntman, B. D., & Polat, A. P. (2025). The correlation between artificial intelligence literacy and artificial intelligence anxiety in audiology students. https://doi.org/10.21203/rs.3.rs-6028948/v1
  26. Kwak, H., Ahn, J-W., & Seo, Y. H. (2022). Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nursing, 21, 267. https://doi.org/10.1186/s12912-022-01048-0
  27. Laupichler, M. C., Aster, A., Haverkamp, N., & Raupach, T. (2023). Development of the “scale for the assessment of non-experts’ AI literacy”-An exploratory factor analysis. Computers in Human Behavior Reports, 12, 100338. https://doi.org/10.1016/j.chbr.2023.100338
  28. Laupichler, M., Aster, A., Meyerheim, M., Raupach, T., & Mergen, M. (2024). Medical students’ AI literacy and attitudes towards AI: A cross-sectional two-center study using pre-validated assessment instruments. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-05400-7
  29. Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1-14. https://doi.org/10.1145/3313831.3376727
  30. Lukic, A., Kudelic, N., Anticevic, V., Lazic-Mosler, E., Gluncic, V., Hren, D., & Lukic, I. K. (2023). First-year nursing students’ attitudes towards artificial intelligence: cross-sectional multi-center study. Nurse Education in Practice, 71, 103735. https://doi.org/10.1016/j.nepr.2023.103735
  31. McCarthy, J. (2004). What is artificial intelligence? http://cse.unl.edu/~choueiry/S09-476-876/Documents/whatisai.pdf
  32. Nguyen, D. T., Nguyen, T. T., & Nguyen, T. H. (2020). Artificial intelligence literacy: A new requirement for the digital age. Journal of Educational Technology Development and Exchange, 13(1), 1-15. https://doi.org/10.18785/jetde.1301.01
  33. Ong, C.-S., & Lai, J.-Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816-829. https://doi.org/10.1016/j.chb.2004.03.006
  34. Oreg, S. (2003). Resistance to change: Developing an individual differences measure. Journal of Applied Psychology, 88(4), 680-693. https://doi.org/10.1037/0021-9010.88.4.680
  35. Pinto dos Santos, D., Giese, D., Brodehl, S., Chon, S. H., Staab, W., Kleinert, R., Maintz, D., & Baeßler, B. (2019). Medical students’ attitude towards artificial intelligence: A multicentre survey. European Radiology, 29(4), 1640-1646. https://doi.org/10.1007/s00330-018-5601-1
  36. Rhee, C. S., & Rhee, H. (2019). Expectations and anxieties affecting attitudes toward artificial intelligence revolution. The Journal of the Korea Contents Association, 19(9), 37-46. https://doi.org/10.5392/JKCA.2019.19.09.037
  37. Sainz, M., Meneses, J., Lopez, B.-S., & Fabregues, S. (2016). Gender stereotypes and attitudes towards information and communication technology professionals in a sample of spanish secondary students. Sex Roles, 74(3), 154-168. https://doi.org/10.1007/s11199-014-0424-2
  38. Saltı, A. K., Topalı, H., & Türkmen, O. O. (2025). Sağlık ile ilgili bölümlerde okuyan üniversite öğrencilerinin yapay zekâ okuryazarlığı. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 34(Uygarlığın dönüşümü: Yapay zekâ), 51-64. https://doi.org/10.35379/cusosbil.1625358
  39. Sarman, A., & Tuncay, S. (2024). Attitudes and anxiety levels of nursing students toward artificial intelligence. Teaching and Learning in Nursing, 20(2), e431-e438. https://doi.org/10.1016/j.teln.2024.12.006
  40. Seren İnteperler, Ş., Gül, G., & Akbaş, E. (2022). Artificial intelligence anxiety of nurses and associated factors, 2. Ulusal, 1. Uluslararası Hemşirelikte Yönetim Kongresi (ss. 44).
  41. Subaveerapandiyan, A., Mvula, D., Ahmad, N., Taj, A., & Ahmed, M. (2024). Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice. Journal of Health Organization and Management. https://doi.org/10.1108/jhom-04-2024-0154.
  42. Şirin, H., & Alarçin, E. Y. (2025). Sağlık çalışanlarının yapay zekâ uygulamalarına yönelik tutum analizi. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 25(2), 93-122.
  43. Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115-139. https://doi.org/10.2307/3250981
  44. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
  45. Wang, K., Cui, W., & Xue, Y. (2025). Artificial intelligence in higher education: the impact of need satisfaction on artificial intelligence literacy mediated by self-regulated learning strategies. Behavioral Sciences, 15(2), 165. https://doi.org/10.3390/bs15020165
  46. Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and future of humanity: A review and research agenda. Journal of Database Management, 30(1), 61-79. https://doi.org/10.4018/JDM.2019010104
  47. Wang, Y.-Y., & Wang, Y.-S. (2019). Development and validation of an artificial intelligence anxiety scale: An initial application in predicting motivated learning behavior. Interactive Learning Environments, 1-16. https://doi.org/10.1080/10494820.2019.1674887
  48. Yalcinkaya, T., Ergin, E., & Cinar Yucel, S. (2024). Exploring nursing students’ attitudes and readiness for articial intelligence: A cross-sectional study. Teaching and Learning in Nursing, 19(4), e722-e728. http://doi:10.1016/j.teln.2024.06.003
  49. Yılmaz, A. (2020). Yapay zekâ. KODLAB Yayın Dağıtım.
  50. Yılmaz, Y., Uzelli Yılmaz, D., Yıldırım, D., Akın Korhan, E., & Özer Kaya, D. (2021). Yapay zekâ ve sağlıkta yapay zekanın kullanımına yönelik sağlık bilimleri fakültesi öğrencilerinin görüşleri. Süleyman Demirel Üniversitesi Sağlık Bilimleri Dergisi, 12(3), 297-308. https://doi.org/10.22312/sdusbed.950372
  51. Zhang, B., & Dafoe, A. (2019). Artificial intelligence: American attitudes and trends. SSRN Electronic Journal, https://doi.org/10.2139/ssrn.3312874
  52. Zheng, B., Wu, M-N., Zhu, S-J., Zhou, H-X., Hao, X-L., Fei, F-Q., Jia, Y., Wu, J., Yang, W-H., & Pan, X- P. (2021). Attitudes of medical workers in China toward articial intelligence in ophthalmology: A comparative survey. BMC Health Services Research, 21(1), 1067. http://doi:10.1186/s12913-021-07044-5
  53. Zhou, L. Q., Wang, J. Y., Yu, S. Y., Wu, G. G., Wei, Q., Deng, Y. B., Wu, X-L., Cui, X-W., & Dietrich, C. F. (2019). Artificial intelligence in medical imaging of the liver. World Journal of Gastroenterology, 25(6), 672-682. http://doi:10.3748/wjg.v25.i6.672