Methodological Considerations in Comparative Readability Analyses of Large Language Model Outputs

Authors

DOI:

https://doi.org/10.66288/actamedi.2026.63

Keywords:

Artificial Intelligence, Large language models, Readability, Health Literacy, Patient Education

Abstract

This submission is a Letter to the Editor. Abstract is not required according to the journal guidelines.

References

Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics. New York: Springer; 2012. DOI: https://doi.org/10.1007/978-1-4614-1353-0

Benjamini Y, Hochberg Y. Controlling the false discovery rate. J R Stat Soc Series B. 1995;57(1):289–300. DOI: https://doi.org/10.1111/j.2517-6161.1995.tb02031.x

Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale: Lawrence Erlbaum; 1988.

Günay E, et al. Comparison of emergency medicine specialist, cardiologist, and GPT-4 in electrocardiography assessment. Am J Emerg Med. 2024;XX:XXX–XXX. DOI: https://doi.org/10.1016/j.ajem.2024.03.017

Shoemaker SJ, Wolf MS, Brach C. Development of the Patient Education Materials Assessment Tool. Patient Educ Couns. 2014;96(3):395–403. DOI: https://doi.org/10.1016/j.pec.2014.05.027

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Published

2026-03-19

How to Cite

Oğuzlar, F. Çağrı. (2026). Methodological Considerations in Comparative Readability Analyses of Large Language Model Outputs. Acta Medica Young Doctors, 2(2). https://doi.org/10.66288/actamedi.2026.63

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Section

Letter to the Editor

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