Knowledge, attitudes, and use of artificial intelligence among adult and pediatric hematologists in Türkiye: a national cross-sectional survey.
- 1Department of Hematology, İstanbul Medipol University International School of Medicine, and Istanbul Medipol Mega University Hospital, İstanbul, Türkiye. [email protected].
- 2Department of Hematology, Bursa Yüksek İhtisas Training and Research Hospital, Bursa, Türkiye.
- 3Division of Hematology, Department of Internal Medicine, Faculty of Medicine, Karadeniz Technical University, Trabzon, Türkiye.
Abstract
Background
Artificial intelligence (AI), including generative AI and large language models, is entering hematology practice and research, but real-world integration depends on clinicians' knowledge, attitudes, use, and governance rather than algorithm performance alone. Evidence specific to hematologists is scarce, and no national study in Türkiye has jointly assessed knowledge, clinical and research use, trust and governance, attitudes toward patients' AI use, and educational needs.Methods
We conducted a national, cross-sectional, self-administered online survey (Google Forms), reported per the CHERRIES guideline. Practicing adult and pediatric hematologists were invited through the verified member e-mail list of the Turkish Society of Hematology (a closed survey) and surveyed from 15-30 May 2026 after ethics approval. The instrument covered seven domains (participant profile; awareness/knowledge; clinical use; research/writing use; trust-risk-ethics-governance; attitudes to patients' chatbot use; education and professional future). Categorical data are summarized as n(%) and ordinal items as median (IQR); groups were compared with non-parametric tests (effect sizes; Benjamini-Hochberg correction for exploratory analyses), with multivariable logistic and ordinal regression. Analyses used R.Results
Of 639 invited members, 146 completed the survey (response rate 22.8%); 65.8% practiced adult hematology. Clinical AI use in the prior three months was reported by 87%, yet only 14% had received structured AI training. Generative AI for research/writing was used by 55.5%, of whom 81% had encountered fabricated references or incorrect information. Nearly half (48.6%) had entered patient data into non-approved public chatbots, most in anonymized form only (40.4%), while 8.2% entered identifiable personal or institutional information; written institutional AI policies were rarely reported or recognized (4.8% reported one, 64.4% reported none, and 30.8% were unaware). Responsible-use norms were strong (90% endorsed verification; 73% endorsed declaring AI use), and few felt professionally threatened (8.2%). Educational need was high and internally consistent (Cronbach's α = 0.92). Higher digital literacy was independently associated with research/manuscript-writing AI use (adjusted OR 1.87 per point); an association with clinical AI use was also observed, but that model was underpowered and is reported as exploratory. Attitudes did not differ between adult and pediatric hematologists.Conclusions
Hematologists have rapidly adopted AI while maintaining cautious, verification-oriented attitudes, but adoption is outpacing training and institutional governance. Hematology-specific policies, literacy-targeted training (especially safe generative-AI use), and supervised, institution-approved tools are needed for responsible integration.
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BibTeX
@article{cınar2026knowledge,
title = {{Knowledge, attitudes, and use of artificial intelligence among adult and pediatric hematologists in Türkiye: a national cross-sectional survey.}},
author = {Olgu Erkin Çınar and Hilmi Erdem Gözden and Özlen Balta and Turkish Society of Hematology Artificial Intelligence Scientific Subcommittee (Türk Hematoloji Derneği Yapay Zekâ Bilimsel Alt Komitesi, YZ-BAK)},
journal = {BMC medical education},
year = {2026},
month = aug,
doi = {10.1186/s12909-026-10065-5},
url = {https://europepmc.org/article/MED/42958214},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Knowledge, attitudes, and use of artificial intelligence among adult and pediatric hematologists in Türkiye: a national cross-sectional survey.
AU - Olgu Erkin Çınar
AU - Hilmi Erdem Gözden
AU - Özlen Balta
AU - Turkish Society of Hematology Artificial Intelligence Scientific Subcommittee (Türk Hematoloji Derneği Yapay Zekâ Bilimsel Alt Komitesi, YZ-BAK)
PY - 2026
DA - 2026/08/04
JO - BMC medical education
DO - 10.1186/s12909-026-10065-5
UR - https://europepmc.org/article/MED/42958214
AB - Background Artificial intelligence (AI), including generative AI and large language models, is entering hematology practice and research, but real-world integration depends on clinicians' knowledge, attitudes, use, and governance rather than algorithm performance alone. Evidence specific to hematologists is scarce, and no national study in Türkiye has jointly assessed knowledge, clinical and research use, trust and governance, attitudes toward patients' AI use, and educational needs.Methods We conducted a national, cross-sectional, self-administered online survey (Google Forms), reported per the CHERRIES guideline. Practicing adult and pediatric hematologists were invited through the verified member e-mail list of the Turkish Society of Hematology (a closed survey) and surveyed from 15-30 May 2026 after ethics approval. The instrument covered seven domains (participant profile; awareness/knowledge; clinical use; research/writing use; trust-risk-ethics-governance; attitudes to patients' chatbot use; education and professional future). Categorical data are summarized as n(%) and ordinal items as median (IQR); groups were compared with non-parametric tests (effect sizes; Benjamini-Hochberg correction for exploratory analyses), with multivariable logistic and ordinal regression. Analyses used R.Results Of 639 invited members, 146 completed the survey (response rate 22.8%); 65.8% practiced adult hematology. Clinical AI use in the prior three months was reported by 87%, yet only 14% had received structured AI training. Generative AI for research/writing was used by 55.5%, of whom 81% had encountered fabricated references or incorrect information. Nearly half (48.6%) had entered patient data into non-approved public chatbots, most in anonymized form only (40.4%), while 8.2% entered identifiable personal or institutional information; written institutional AI policies were rarely reported or recognized (4.8% reported one, 64.4% reported none, and 30.8% were unaware). Responsible-use norms were strong (90% endorsed verification; 73% endorsed declaring AI use), and few felt professionally threatened (8.2%). Educational need was high and internally consistent (Cronbach's α = 0.92). Higher digital literacy was independently associated with research/manuscript-writing AI use (adjusted OR 1.87 per point); an association with clinical AI use was also observed, but that model was underpowered and is reported as exploratory. Attitudes did not differ between adult and pediatric hematologists.Conclusions Hematologists have rapidly adopted AI while maintaining cautious, verification-oriented attitudes, but adoption is outpacing training and institutional governance. Hematology-specific policies, literacy-targeted training (especially safe generative-AI use), and supervised, institution-approved tools are needed for responsible integration.
SN - 1472-6920
ER -