PATHOMORPHOLOGY EDUCATION IN WARTIME UKRAINE: EDUCATIONAL NEEDS OF MEDICAL STUDENTS IN KYIV
DOI:
https://doi.org/10.32782/eddiscourses/2026-2-5Keywords:
Education, Medical, Undergraduate, Students, Medical, Pathology, Warfare, Needs Assessment, Surveys and Questionnaires, Ukraine.Abstract
Medical education is undergoing substantial transformation under the influence of digital technologies, molecular medicine, and artificial intelligence. Pathology, traditionally centered on morphological analysis, is increasingly developing into an integrated discipline that combines morphological, molecular, and computational approaches. In Ukraine, this transformation is unfolding under conditions of prolonged wartime disruption, which affects access to clinical training and educational resources. Objective. To assess the educational needs of medical students during pathology training and to evaluate changes in the perception and delivery of pathology education under wartime disruption in Kyiv, Ukraine. Methods. A cross-sectional descriptive study was conducted using a structured questionnaire administered to third- year medical students at Bogomolets National Medical University (Kyiv, Ukraine) during the 2022/2023 and 2024/2025 academic years. The study included 514 participants. The questionnaire addressed learning resources, perceived effectiveness of educational methods, use of digital tools, and the perceived role of pathology in professional training. Data were analyzed using descriptive statistics and Pearson’s χ² test. Results. Pathology remained an important discipline; however, the proportion of students identifying it as a key component of medical education decreased from 78.3% to 62.2% (p < 0.001), while uncertainty increased. Students consistently prioritized competencies related to critical thinking, communication, and decision-making under uncertainty. Traditional learning resources remained predominant, whereas digital tools were used only moderately. Reported barriers included insufficient educational materials and limited integration of modern technologies into the educational process. Conclusions. Pathology education in Ukraine is shifting toward a hybrid model that combines traditional and digital approaches. Although the perceived centrality of the discipline has declined, its contribution to the development of core clinical competencies remains substantial. Stronger integration of morphological, clinical, and digital components is needed to align pathology education with contemporary healthcare demands under conditions of prolonged disruption.
References
Topol E. J. High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine. 2019. Vol. 25, No. 1. P. 44–56. DOI: https://doi.org/10.1038/s41591-018-0300-7
Artificial intelligence in digital pathology – new tools for diagnosis and precision oncology / K. Bera et al. Nature Reviews Clinical Oncology. 2019. Vol. 16, No. 11. P. 703–715. DOI: https://doi.org/10.1038/s41571-019-0252-y
Robbins and Cotran Pathologic Basis of Disease / Vinay Kumar et al. 11th ed. Philadelphia: Elsevier, 2025. 1280 p. ISBN: 9780443264528
Digital pathology and artificial intelligence in diagnostic pathology / P. Jariyapan et al. Malaysian Journal of Pathology. 2025. Vol. 47, No. 1. P. 3–12. https://www.mjpath.org.my/2025/v47n1/digital-pathology-and-AI.pdf
Validation of a digital pathology system including remote review during the COVID-19 pandemic / M. G. Hanna et al. Modern Pathology. 2020. Vol. 33, No. 11. P. 2115–2127. DOI: https://doi.org/10.1038/s41379-020-0601-5
Routine digital pathology workflow: The Catania experience / E. Rossi et al. Journal of Pathology Informatics. 2017. Vol. 8, No. 1. P. 51. DOI: https://doi.org/10.4103/jpi.jpi_58_17
van der Laak J., Litjens G., Ciompi F. Deep learning in histopathology: the path to the clinic. Nature Medicine. 2021. Vol. 27, No. 5. P. 775–784. DOI: https://doi.org/10.1038/s41591-021-01343-4
Translational AI and Deep Learning in Diagnostic Pathology / A. Serag et al. Frontiers in Medicine. 2019. Vol. 6. Article 185. DOI: https://doi.org/10.3389/fmed.2019.00185
Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology / S. Mukhopadhyay et al. The American Journal of Surgical Pathology. 2018. Vol. 42, No. 1. P. 39–52. DOI: https://doi.org/10.1097/PAS.0000000000000948
Virtual Reality in Preclinical and Clinical Education–An Insight into Current Advancements and Future Perspectives / A. Brachet et al. Applied Sciences. 2025. Vol. 15, No. 24. Article 12941. DOI: https://doi.org/10.3390/app152412941
Kuzyk P. V., Verbytskyi V. V. [Assessment of the impact of the COVID-19 pandemic and war on changes in educational strategies in medical universities in Ukraine] Perspektyvy ta innovatsii nauky. 2025. No. 8 (54). P. 2212–2229. DOI: https://doi.org/10.52058/2786-4952-2025-8(54)-2212-2229
Movlianova N. V., Kuzyk P. V., Komyshan I. V. [Preparation of future medical professionals in Ukraine during martial law]. Perspektyvy ta innovatsii nauky. 2025. No. 4 (50). P. 2382–2398. DOI: https://doi.org/10.52058/2786-4952-2025-4(50)-2382-2398
A Practical Guide to Writing Effective Needs Assessments in Graduate Medical Education / M. Davis et al. Journal of Graduate Medical Education. 2025. Vol. 17, No. 3. P. 266–270. DOI: https://doi.org/10.4300/JGME-D-25-00338.1
Mehmeti F., Reshani A., Tezci E. Development of scale to measure teachers curriculum assessment. Journal of Pedagogical Research. 2024. Vol. 8, No. 4. P. 66–89. DOI: https://doi.org/10.33902/JPR.202429249
Pathology in medical education: Impact on speciality choices and awareness amongst clinical-year students / E. Ozturk et al. Journal of Diagnostic and Academic Pathology. 2025. Vol. 2, No. 1. P. 14–22. DOI: https://doi.org/10.4103/jdap.jdap_10_25
Histology Education in an Integrated, Time‐restricted Medical Curriculum: Academic Outcomes and Students’ Study Adaptations / W. Gribbin et al. Anatomical Sciences Education. 2022. Vol. 15, No. 4. P. 671–684. DOI: https://doi.org/10.1002/ase.2127
Singun A. Unveiling the barriers to digital transformation in higher education institutions: a systematic literature review. Discover Education. 2025. Vol. 4. Article 37. DOI: https://doi.org/10.1007/s44217-025-00430-9
Digital learning of clinical skills and its impact on medical students’ academic performance: a systematic review / R. G. McGee et al. BMC Medical Education. 2024. Vol. 24. Article 1477. DOI: https://doi.org/10.1186/s12909-024-06471-2
Pathology exposure in Spanish medical schools: a review of forty-one institutions with insights into pathology curriculum for an international approach / F. Reyes-Albaladejo et al. Academic Pathology. 2026. Vol. 13, No. 1. Article 100228. DOI: https://doi.org/10.1016/j.acpath.2025.100228
Implementation of virtual pathology teaching in health professions education: A systematic review: BEME Systematic Review No. 95 / J. Hau et al. Medical Teacher. 2025. Vol. 47, No. 12. P. 1918–1926. DOI: https://doi.org/10.1080/0142159X.2025.2497890
Automation Bias in AI-assisted Medical Decision-making under Time Pressure in Computational Pathology / E. Rosbach et al. In: Palm, C., et al. Bildverarbeitung für die Medizin 2025. BVM 2025. Informatik aktuell. Springer Vieweg, Wiesbaden. DOI: https://doi.org/10.1007/978-3-658-47422-5_27
Schukow C. P., Allen T. C. A New Generation of Pathologists: Addressing Modern Curriculum and Educational Scholarship for Pathology Educators and Trainees After the End of the COVID-19 Pandemic. 2025. Vol. 149, No. 6. P. 578–588. DOI: https://doi.org/10.5858/arpa.2024-0114-RA
Virtual Versus Light Microscopy Usage among Students: A Systematic Review and Meta-Analytic Evidence in Medical Education / S. Maity et al. Diagnostics. 2023. Vol. 13, No. 3. Article 558. DOI: https://doi.org/10.3390/diagnostics13030558
Blended and digital approaches in histology and pathology teaching: A scoping review / E. Nava et al. Anatomical Sciences Education. 2025. DOI: https://doi.org/10.1002/ase.70169
Goh P.-S., Sandars J. A vision of the use of technology in medical education after the COVID-19 pandemic. MedEdPublish. 2020. Vol. 9. Article 49. DOI: https://doi.org/10.15694/mep.2020.000049.1
