Author’s Response

Abstract

We thank the authors for their interest in our study, “Exploring the role of artificial intelligence in Turkish orthopedic progres- sion exams,” and appreciate the opportunity to address their comments. The use of true/false questions reflects the current format of the UEGS exam. While this approach has limitations in assessing deeper clinical reasoning, we clearly acknowledged this in our discussion and emphasized the need for future studies using more complex question types. We chose to present all questions in their original Turkish form with- out modification to preserve the content’s integrity and avoid intro- ducing bias. Each question was submitted separately to avoid any memory effects, as detailed in our methods. Question classification was done independently by two orthope- dic residents, with disagreements resolved by a senior author. This method is consistent with similar studies.1,2 While involving more reviewers might add perspective, it’s unclear whether it would sig- nificantly change the outcomes. As for the observation about letter count and accuracy, we presented it cautiously and only as a secondary finding. We noted it may relate to question complexity or clarity; while we acknowledge its limitations, we believe it raises potentially valuable questions for future research. Finally, our comparison with resident scores aimed to explore how such tools might support medical education. We made it clear that this was not a direct comparison of clinical competence, but an initial look at performance on the same exam format. In summary, while many of the points raised reflect limitations we have already addressed, we appreciate the continued dialogue. We hope our study contributes to the broader conversation on digital tools in medical education.