Bilgiç B, Turan S. Accuracy and reproducibility of ChatGPT responses to parent and patient inquiries on attention-deficit/hyperactivity disorder. World J Psychiatry 2026; 16(6): 119773 [DOI: 10.5498/wjp.v16.i6.119773]
Corresponding Author of This Article
Serkan Turan, MD, PhD, Associate Professor, Department of Child and Adolescent Psychiatry, Uludag University Faculty of Medicine, Gorukle Campus, Bursa 16059, Türkiye. serkanturan@uludag.edu.tr
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Psychiatry
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Bilgiç B, Turan S. Accuracy and reproducibility of ChatGPT responses to parent and patient inquiries on attention-deficit/hyperactivity disorder. World J Psychiatry 2026; 16(6): 119773 [DOI: 10.5498/wjp.v16.i6.119773]
World J Psychiatry. Jun 19, 2026; 16(6): 119773 Published online Jun 19, 2026. doi: 10.5498/wjp.v16.i6.119773
Accuracy and reproducibility of ChatGPT responses to parent and patient inquiries on attention-deficit/hyperactivity disorder
Berrin Bilgiç, Serkan Turan
Berrin Bilgiç, Department of Child and Adolescent Psychiatry, Adnan Menderes University Faculty of Medicine, Aydın 09100, Türkiye
Serkan Turan, Department of Child and Adolescent Psychiatry, Uludag University Faculty of Medicine, Bursa 16059, Türkiye
Author contributions: Bilgiç B conceptualized and designed the study, drafted the manuscript; Turan S supervised the research, performed the statistical analysis, critically revised the manuscript for important intellectual content; Bilgiç B and Turan S collected the data; all authors reviewed and approved the final manuscript.
AI contribution statement: AI-based tools (e.g., ChatGPT and language editing tools) were used in a limited manner to support language refinement and clarity.
Institutional review board statement: This study did not require institutional review board approval, as no patient data, clinical records, or personally identifiable information were used. The study was based exclusively on publicly available questions and artificial intelligence-generated responses. The authors declare no affiliation with OpenAI, the developer of ChatGPT.
Informed consent statement: Informed consent was not required because this study did not involve human participants or patient data.
Conflict-of-interest statement: Conflict of interests: The authors declare that there are no conflicts of interest regarding the publication of this article.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Data sharing statement: The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Corresponding author: Serkan Turan, MD, PhD, Associate Professor, Department of Child and Adolescent Psychiatry, Uludag University Faculty of Medicine, Gorukle Campus, Bursa 16059, Türkiye. serkanturan@uludag.edu.tr
Received: February 10, 2026 Revised: February 23, 2026 Accepted: March 12, 2026 Published online: June 19, 2026 Processing time: 108 Days and 1 Hours
Core Tip
Core Tip: The clinical reliability of large language models (LLMs) in addressing attention-deficit/hyperactivity disorder (ADHD)-related questions from patients and caregivers has not been sufficiently characterized. This study systematically evaluates the accuracy and reproducibility of ChatGPT (GPT-4o) across clinically relevant domains in child and adolescent psychiatry. The findings indicate stronger and more consistent performance in basic informational and diagnostic domains, whereas greater variability was observed in clinically sensitive areas such as treatment, medication use, and long-term outcomes. These results highlight both the potential utility and the limitations of LLM-based tools in ADHD-related information-seeking, emphasizing the need for cautious, developmentally informed interpretation in higher-risk clinical contexts.
