ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study.

Introduction Artificial Intelligence (AI) platforms have gained widespread attention for their distinct ability to generate automated responses to various prompts. However, its role in assessing the quality and readability of a provided text remains unclear. Thus, the purpose of this study is to evaluate the proficiency of the conversational generative pre-trained transformer (ChatGPT) in utilizing the DISCERN tool to evaluate the quality of online content regarding shock wave therapy for erectile dysfunction. Methods Websites were generated using a Google search of "shock wave therapy for erectile dysfunction" with location filters disabled. Readability was analyzed using Readable software (Readable.com, Horsham, United Kingdom). Quality was assessed independently by three reviewers using the DISCERN tool. The same plain text files collected were inputted into ChatGPT to determine whether they produced comparable metrics for readability and quality. Results The study results revealed a notable disparity between ChatGPT's readability assessment and that obtained from a reliable tool, Readable.com (p<0.05). This indicates a lack of alignment between ChatGPT's algorithm and that of established tools, such as Readable.com. Similarly, the DISCERN score generated by ChatGPT differed significantly from the scores generated manually by human evaluators (p<0.05), suggesting that ChatGPT may not be capable of accurately identifying poor-quality information sources regarding shock wave therapy as a treatment for erectile dysfunction. Conclusion ChatGPT's evaluation of the quality and readability of online text regarding shockwave therapy for erectile dysfunction differs from that of human raters and trusted tools. Therefore, ChatGPT's current capabilities were not sufficient for reliably assessing the quality and readability of textual content. Further research is needed to elucidate the role of AI in the objective evaluation of online medical content in other fields. Continued development in AI and incorporation of tools such as DISCERN into AI software may enhance the way patients navigate the web in search of high-quality medical content in the future.

Ectopic Pregnancy Observed With Kyleena Intrauterine Device Use: A Case Report.

Kyleena (levonorgestrel 19.5 mg), a type of intrauterine device (IUD), has an efficacy rate of 99% in preventing pregnancy. Because the overall failure rate of IUDs is low, ectopic pregnancy (EP) with IUD use is uncommon. This case reports an EP observed in a female with the Kyleena IUD in place. She had no known risk factors for an EP, which makes this case noteworthy. Ultrasound and surgery confirmed a 4 cm EP in the ampulla of the left fallopian tube. Insufficient evidence exists to conclude whether the Kyleena IUD has a higher risk of EP compared to other hormonal IUDs. As the Kyleena IUD becomes a more popular option for women in search of an effective contraceptive, patients and clinicians should be aware of this potential risk. Our case emphasizes that continued research on the prevalence of EP with Kyleena use is necessary.