Yapay Zeka Destekli Gebelik Danışmanlığı Uygulanabilir mi? ChatGPT Yanıtlarının Kalitesinin Değerlendirilmesi

Abstract

Giriş: Gebelik döneminde sıkça sorulan sorulara ChatGPT tarafından üretilen yanıtların kalitesini, uzman değerlendirmelerine dayalı olarak ve tanımlı kriterler (doğruluk, eksiksizlik ve güvenlik) üzerinden değerlendirmek. Yöntem: Toplam 20 kadın hastalıkları ve doğum uzmanı, gebelikle ilgili sık karşılaşılan 15 soruya ChatGPT tarafından verilen yanıtları değerlendirmiştir. Her yanıt, üç alanda 5 puanlık Likert ölçeği ile puanlanmıştır. Kriterler ve soru kategorileri arasındaki farkları değerlendirmek için istatistiksel karşılaştırmalar yapılmıştır. Bulgular: ChatGPT, tüm kriterler üzerinden ortalama 4,1 puan almıştır. En yüksek puan doğruluk kriterinden elde edilmiştir (ortalama 4,27 ± 0,31), ardından eksiksizlik (3,85 ± 0,30) ve güvenlik (3,78 ± 0,36) gelmektedir (P = 0,019). Genel bilgi sorularına verilen yanıtlar, semptomlar veya takip önerileriyle ilgili sorulara göre anlamlı düzeyde daha yüksek puanlanmıştır (P = 0,041). En yüksek puanlanan yanıt gebelikte uyku pozisyonları ile ilgili olurken (ortalama 4,5), en düşük puanı ağrı kesici güvenliği ile ilgili yanıt almıştır (ortalama 3,5). Sonuç: ChatGPT, gebelikle ilgili doğru ve anlaşılır bilgi sunma konusunda güçlü bir potansiyel göstermektedir. Ancak özellikle semptom odaklı konularda klinik güvenlik ve bilgi eksiksizliği açısından sınırlılıkları bulunmaktadır. Bu nedenle profesyonel tıbbi danışmanlığın yerine değil, tamamlayıcı bir bilgi kaynağı olarak kullanılmalıdır. Hastaya yönelik eğitimde güvenli entegrasyonu sağlamak için farklı klinik senaryolarda ve standartlaştırılmış değerlendirme araçlarıyla daha fazla doğrulama çalışması gereklidir.

Keywords

• ChatGPT
• yapay zeka
• gebelik
• doğum
• hasta eğitimi
• tıbbi güvenlik
• uzman değerlendirmesi

Is Artificial Intelligence-Assisted Pregnancy Counseling Feasible? An Evaluation of the Quality of ChatGPT Responses

Abstract

Objective: To evaluate the quality of ChatGPT-generated responses to commonly asked questions during pregnancy, based on expert assessments using predefined criteria: accuracy, completeness, and safety. Methods: A total of 20 board-certified obstetricians evaluated 15 ChatGPT-generated responses to frequently encountered pregnancy-related questions. Each response was assessed using a 5-point Likert scale across three domains. Statistical comparisons were conducted to evaluate differences among criteria and question categories. Results: ChatGPT received an overall mean score of 4.1 across all criteria. Accuracy was the highest-rated criterion (mean 4.27 ± 0.31), followed by completeness (3.85 ± 0.30) and safety (3.78 ± 0.36) (P = 0.019). Responses to general knowledge questions scored significantly higher than those related to symptoms or follow-up guidance (P = 0.041). The most favorably rated response pertained to sleep positions during pregnancy (mean 4.5), while painkiller safety scored the lowest (mean 3.5). Conclusion: ChatGPT demonstrates strong potential in delivering accurate and comprehensible pregnancy-related information. However, its limitations in clinical safety and completeness—particularly in symptom-related topics—suggest that it should be used as an adjunct to, not a replacement for, professional medical guidance. Further validation across diverse clinical scenarios and standardized evaluation tools is necessary to ensure safe integration into patient education.

Keywords

• ChatGPT
• artificial intelligence
• pregnancy
• obstetrics
• patient education
• medical safety
• expert evaluation

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