Anxiety among Medical Students Regarding Generative Artificial Intelligence Models: A Pilot Descriptive Study
Open accessAbstract
Despite the potential benefits of generative artificial intelligence (genAI), concerns about its psychological impact on medical students, especially about job displacement, are apparent. This pilot study, conducted in Jordan during July–August 2024, aimed to examine the specific fears, anxieties, mistrust, and ethical concerns medical students harbor towards genAI. Using a cross-sectional survey design, data were collected from 164 medical students studying in Jordan across various academic years, employing a structured self-administered questionnaire with an internally consistent FAME scale—representing Fear, Anxiety, Mistrust, and Ethics—comprising 12 items, with 3 items for each construct. Exploratory and confirmatory factors analyses were conducted to assess the construct validity of the FAME scale. The results indicated variable levels of anxiety towards genAI among the participating medical students: 34.1% reported no anxiety about genAI‘s role in their future careers (n = 56), while 41.5% were slightly anxious (n = 61), 22.0% were somewhat anxious (n = 36), and 2.4% were extremely anxious (n = 4). Among the FAME constructs, Mistrust was the most agreed upon (mean: 12.35 ± 2.78), followed by the Ethics construct (mean: 10.86 ± 2.90), Fear (mean: 9.49 ± 3.53), and Anxiety (mean: 8.91 ± 3.68). Their sex, academic level, and Grade Point Average (GPA) did not significantly affect the students’ perceptions of genAI. However, there was a notable direct association between the students’ general anxiety about genAI and elevated scores on the Fear, Anxiety, and Ethics constructs of the FAME scale. Prior exposure to genAI and its previous use did not significantly modify the scores on the FAME scale. These findings highlight the critical need for refined educational strategies to address the integration of genAI into medical training. The results demonstrate notable anxiety, fear, mistrust, and ethical concerns among medical students regarding the deployment of genAI in healthcare, indicating the necessity of curriculum modifications that focus specifically on these areas. Interventions should be tailored to increase familiarity and competency with genAI, which would alleviate apprehensions and equip future physicians to engage with this inevitable technology effectively. This study also highlights the importance of incorporating ethical discussions into medical courses to address mistrust and concerns about the human-centered aspects of genAI. In conclusion, this study calls for the proactive evolution of medical education to prepare students for new AI-driven healthcare practices to ensure that physicians are well prepared, confident, and ethically informed in their professional interactions with genAI technologies.
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Students report that using GenAI systems can cause anxiety due to lack of clear understanding of the policies governing their use or how detection methods work.
“students have reported that using such systems can also cause them to have anxiety due to the lack of a clear understanding of the policies that govern their use or how detection methods work [26]”
From The impact of generative artificial intelligence tools on assessment equity for non-native English-speaking medical students: a systematic review (2026) · cites this paper as [26]
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AI Anxiety: a comprehensive analysis of psychological factors and interventions
Kim, J. J. H., Soh, J. Y., Kadkol, S., Solomon, I., Yeh, H., Srivatsa, A. V., Nahass, G. R., Choi, J. Y., Lee, S., Nyugen, T., et al. (2025) · AI and Ethics · doi:10.1007/s43681-025-00686-9 · Cited by 160 · see citing works
Artificial Intelligence in Health Professions Education assessment: AMEE Guide No. 178
Masters, K., MacNeil, H., Benjamin, J., Carver, T., Nemethy, K., Valanci-Aroesty, S., Taylor, D. C. M., Thoma, B., & Thesen, T. (2025) · Medical Teacher · doi:10.1080/0142159x.2024.2445037 · Cited by 80 · see citing works
Sallam, M., Al-Mahzoum, K., Alaraji, H., Albayati, N., Alenzei, S., AlFarhan, F., Alkandari, A., Alkhaldi, S., Alhaider, N., Al-Zubaidi, D., et al. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1542769 · Cited by 41 · see citing works
Self-citationSallam, M., Al‐Salahat, K., Eid, H., Egger, J., & Puladi, B. (2024) · Advances in Medical Education and Practice · doi:10.2147/amep.s479801 · Cited by 36 · see citing works
Self-citationGenerative AI Techniques and Models
Gupta, R., Tiwari, S. M., & Chaudhary, P. (2025) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-031-82062-5_3 · Cited by 13 · see citing works
A pilot study of generative AI video for patient communication in radiology and nuclear medicine
Badawy, M. K., Khamwan, K., & Carrion, D. (2025) · Health and Technology · doi:10.1007/s12553-025-00945-z · Cited by 9 · see citing works
Devanadera, A. C. (2025) · LatIA · doi:10.62486/latia2025249 · Cited by 6 · see citing works
Ethical issues in medical AI education: challenges and prospects
Zheng, C., & Zhang, H. (2026) · International Journal of Ethics Education · doi:10.1007/s40889-026-00241-y · Cited by 6 · see citing works
Alnazly, E. K., Absy, N., & Absy, N. (2026) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2026.1779382 · Cited by 4 · see citing works
Embracing Generative AI in Education: A Global View on AI Anxiety Through Digital Literacy
Kristandl, G. (2025) · Springer eBooks · doi:10.1007/978-3-031-97999-6_5 · Cited by 3 · see citing works
From lecture hall to clinic: dental students’ AI readiness and anxiety across educational stages
Çakan, K. N., & İpek, İ. (2025) · BMC Medical Education · doi:10.1186/s12909-025-08181-9 · Cited by 3 · see citing works
Tazkarji, M. Y., Chou, C.-H., & Hamadeh, G. (2026) · Journal of Enterprise Information Management · doi:10.1108/jeim-12-2025-1253 · Cited by 4 · see citing works
Visci, P., Lupelli, F., Calò, F., Sirago, G., Solarino, B., Dell'Erba, A., & Ferorelli, D. (2026) · Medical Teacher · doi:10.1080/0142159x.2026.2663855 · Cited by 3 · see citing works
Árvai, N., Meskó, B., & Katonai, G. (2025) · doi:10.2196/preprints.85373 · Cited by 3 · see citing works
Glăveanu, S. M., & Maier, R. (2025) · Behavioral Sciences · doi:10.3390/bs15091179 · Cited by 3 · see citing works
Yılmaz, S. E., Celik, O. B., & Doğanülkü, H. A. (2025) · Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi · doi:10.18070/erciyesiibd.1773277 · Cited by 2 · see citing works
Ndacyayisenga, J. C. Y., Kidega, C., & Aciro Can, L. (2026) · BMC Medical Education · doi:10.1186/s12909-026-09303-7 · Cited by 1 · see citing works
“…that using such systems can also cause them to have anxiety due to the lack of a clear understanding of the policies that govern their use or how detection methods work [26], such an ambiguous situation creates a dual experience where GenAI is changing the way that students approach responding.”
Concerns and Ethical Awareness of University Students Towards the Use of Generative AI
Yaacob, Y., Mahmud, M. M., Ahmad, R., A’seri, M. S. M., & Mustamam, N. I. (2025) · International Conference on Education Technology and Computer · doi:10.1109/icetc66579.2025.11387607 · Cited by 1 · see citing works
Öztürk, E. U., & Ilıman, E. (2026) · Doğuş Üniversitesi Dergisi · doi:10.31671/doujournal.1817098 · Cited by 1 · see citing works
Wang, Y., Romy, R. W., Deng, Y., & Chen, X. (2026) · Frontiers in Public Health · doi:10.3389/fpubh.2026.1916780 · Cited by 1 · see citing works
Bannor, G. A., Boateng, F. O., & Arthur, Y. D. (2025) · AI and Ethics · doi:10.1007/s43681-025-00755-z · Cited by 1 · see citing works
Generative AI's Impact on the Mental Health of Medical Students: Scenario Analysis
Árvai, N., Meskó, B., & Katonai, G. (2026) · JMIR Medical Education · doi:10.2196/85373 · Cited by 3 · see citing works
Closing Editorial: New Advancements in Medical Education
Pandit, R. (2026) · International Medical Education · doi:10.3390/ime5020042
Trust in Artificial Intelligence Physicians among Turkish Adults
Kantarcıoğlu, A. Ç. (2026) · Social medicine · doi:10.71164/socialmedicine.v19i2.2026.1965
Guansing, J., Leoveras, M. E. D. C., & Natividad, L. R. (2026) · Multidisciplinary Reviews · doi:10.31893/multirev.2026525
El-Helaly, M., Hussein, A. M., Taman, A., Farrag, N. S., Elfeky, A. A., Elhelaly, A. M., & Essam, N. (2026) · Scientific Reports · doi:10.1038/s41598-026-72964-3
Zhou, X., Zhou, X., & Wen, W. (2026) · Research Square · doi:10.21203/rs.3.rs-9730319/v1
AI Integration in Medical Imaging Education: A Nationwide Cross‐Sectional Survey
Wuni, A.-R., Deku, M., Akpabli, E., & Anudjo, M. N. K. (2026) · Radiology Research and Practice · doi:10.1155/rrp/5775572
Pan, Q., & Liu, N. (2026) · International Journal of Public Health · doi:10.3389/ijph.2026.1610073
Sağlık Yönetimi Bölümü Öğrencilerinin Yapay Zekâ Kaygısı: Kesitsel Bir Araştırma
Furkan, A. L. P., Aslan, Y., & Güvensoy, T. (2025) · Journal of Higher Education and Science · doi:10.5961/higheredusci.1785550 · Cited by 1 · see citing works
- Authors
- Sallam, M., Al-Mahzoum, K., Almutairi, Y. M., Alaqeel, O., Abu Salami, A., Almutairi, Z. E., Alsarraf, A. N., & Barakat, M.
- Affiliations
- University of Jordan (JO)
- School of Medicine, The University of Jordan, Amman 11942, Jordan
- Applied Science Private University (JO)
- Corresponding author
- Sallam, Malik
- Venue
- International Medical Education
- Publisher
- MDPI AG
- Published
- 2024-10-09
- Volume
- 3
- Issue
- 4
- Pages
- 406-425
- ISSN
- 2813-141X (ISSN-L)
- OpenAlex
- W4403242377
- Cited by
- 30
- References
- 96
- Citations by year
- 2026: 15 · 2025: 14 · 2024: 1
- FWCI
- 2.84
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Medical Education (publishedVersion, cc-by)
- Preprints.org (acceptedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Health Sciences › Health Professions › General Health Professions › Healthcare professionals’ stress and burnout
- Keywords
- generative AI, medical students, anxiety, fear, distrust, ethical considerations, job displacement, artificial intelligence in medical education, artificial intelligence in healthcare, medical ethics education, scale development, grade point average, sex differences, academic level
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