DIGITAL CURIOSITY ABOUT FIBROMYALGIA: AN ANALYSIS OF THE QUALITY AND READABILITY OF ChatGPT’S RESPONSES BASED ON GOOGLE TRENDS

Objective: The aim of this study is to evaluate the quality and readability of patient education materials about fibromyalgia generated by ChatGPT to assess whether this AI application can be reliably used as an online health information source for the general population.Materials and Methods: In this study, Google Trends was used to identify the most frequently searched keywords related to fibromyalgia. The identified keywords were categorized into three groups: general information, diagnosis, and treatment, and were sequentially entered into ChatGPT. The quality of the generated responses was assessed using the modified DISCERN (mDISCERN) tool. The readability of the texts was evaluated using the Flesch-Kincaid Grade Level (FKGL) and Flesch-Kincaid Reading Ease (FRE) parameters.Results: The mean mDISCERN score of the texts was 44.31±4.67, the mean FKGL score was 15.29±2.29, and mean FRE score was 24.23±10.27. The average mDISCERN score indicated that the texts were of moderate quality. According to the mean Flesch-Kincaid scores, the texts were found to be quite difficult to read and were mostly appropriate for readers at the undergraduate level or higher. Furthermore, the statistical analysis among the three categories revealed no significant differences in mDISCERN, FKGL, and FKRE scores.Conclusion: AI language models like ChatGPT hold innovative potential in healthcare communication by providing accessible and unbiased information that can support health literacy and patient education. However, the high level of reading comprehension required currently limits their effectiveness and reliability for direct patient use. Therefore, the content generated by ChatGPT should be considered a complementary resource and should be critically examined by users.