Çağdaş DEMİROĞLU
Anatolian Journal of Obstetrics and Gynecology Research - 2026;3(1):46-51
Purpose: Human papillomavirus (HPV) is a highly prevalent sexually transmitted pathogen, with nearly 80% of sexually active individuals becoming infected during their lifetime. Although recently developed vaccines provide effective protection, increasing reliance on internet-based and artificial intelligence (AI)-generated medical information raises concerns regarding the accuracy and adequacy of such content. This study aimed to evaluate the accuracy, quality, and readability of HPV vaccine-related information generated by ChatGPT. Methods: The 25 most-searched for HPV vaccine-related keywords were identified through Google Trends. ChatGPT responses to these queries were collected and assessed using the Ensuring Quality Information for Patients (EQIP) criteria, the Flesch-Kincaid Grade Level (FKGL), the Flesch-Kincaid Reading Ease (FKRE), and two Likert scales (3-point and 5-point). Evaluations were independently performed by two healthcare professionals. Statistical comparisons were made across EQIP categories and readability indices. Results: The three most frequently searched phrases were "vaccine for HPV," "HPV vaccine side effects," and "HPV side effects." The mean EQIP score was 62.48, the mean FKRE score was 44.89, and the mean FKGL level was 12.08. The mean scores on the 5-point and 3-point Likert scales were 4.12 and 2.2, respectively. No statistically significant differences were observed between EQIP categories (p=0.332) or in FKGL and FKRE comparisons (p=0.244 and p=0.157). Conclusion: ChatGPT provided generally satisfactory information regarding HPV vaccines; however, several quality limitations were identified. The content demonstrated adequate scientific accuracy but required a reading level consistent with high school education. EQIP scoring indicated that the information was of "good quality with minor issues". In particular, simplifying technical language, improving structural organization, and incorporating more patient-centered explanations may substantially increase the accessibility and practical value of AI-generated medical content.
