Is Information About Musculoskeletal Malignancies From Large Language Models or Web Resources at a Suitable Reading Level for Patients?

Patients and caregivers may experience immense distress when receiving the diagnosis of a primary musculoskeletal malignancy and subsequently turn to internet resources for more information. It is not clear whether these resources, including Google and ChatGPT, offer patients information that is readable, a measure of how easy text is to understand. Since many patients turn to Google and artificial intelligence resources for healthcare information, we thought it was important to ascertain whether the information they find is readable and easy to understand. The objective of this study was to compare readability of Google search results and ChatGPT answers to frequently asked questions and assess whether these sources meet NIH recommendations for readability. (1) What is the readability of ChatGPT-3.5 as a source of patient information for the three most common primary bone malignancies compared with top online resources from Google search? (2) Do ChatGPT-3.5 responses and online resources meet NIH readability guidelines for patient education materials? This was a cross-sectional analysis of the 12 most common online questions about osteosarcoma, chondrosarcoma, and Ewing sarcoma. To be consistent with other studies of similar design that utilized national society frequently asked questions lists, questions were selected from the American Cancer Society and categorized based on content, including diagnosis, treatment, and recovery and prognosis. Google was queried using all 36 questions, and top responses were recorded. Author types, such as hospital systems, national health organizations, or independent researchers, were recorded. ChatGPT-3.5 was provided each question in independent queries without further prompting. Responses were assessed with validated reading indices to determine readability by grade level. An independent t-test was performed with significance set at p < 0.05. Google (n = 36) and ChatGPT-3.5 (n = 36) answers were recorded, 12 for each of the three cancer types. Reading grade levels based on mean readability scores were 11.0 ± 2.9 and 16.1 ± 3.6, respectively. This corresponds to the eleventh grade reading level for Google and a fourth-year undergraduate student level for ChatGPT-3.5. Google answers were more readable across all individual indices, without differences in word count. No difference in readability was present across author type, question category, or cancer type. Of 72 total responses across both search modalities, none met NIH readability criteria at the sixth-grade level. Google material was presented at a high school reading level, whereas ChatGPT-3.5 was at an undergraduate reading level. The readability of both resources was inadequate based on NIH recommendations. Improving readability is crucial for better patient understanding during cancer treatment. Physicians should assess patients' needs, offer them tailored materials, and guide them to reliable resources to prevent reliance on online information that is hard to understand. Level III, prognostic study.

Guirguis PG ，Youssef MP ，Punreddy A ，Botros M ，Raiford M ，McDowell S ... -  《-》

Dr. Google vs. Dr. ChatGPT: Exploring the Use of Artificial Intelligence in Ophthalmology by Comparing the Accuracy, Safety, and Readability of Responses to Frequently Asked Patient Questions Regarding Cataracts and Cataract Surgery.

Cohen SA ，Brant A ，Fisher AC ，Pershing S ，Do D ，Pan C ... -  《-》

Appropriateness and readability of Google Bard and ChatGPT-3.5 generated responses for surgical treatment of glaucoma.

To evaluate the appropriateness and readability of the medical knowledge provided by ChatGPT-3.5 and Google Bard, artificial-intelligence-powered conversational search engines, regarding surgical treatment for glaucoma. In this retrospective, cross-sectional study, 25 common questions related to the surgical management of glaucoma were asked on ChatGPT-3.5 and Google Bard. Glaucoma specialists graded the responses' appropriateness, and different scores assessed readability. Appropriate answers to the posed questions were obtained in 68% of the responses with Google Bard and 96% with ChatGPT-3.5. On average, the responses generated by Google Bard had a significantly lower proportion of sentences, having more than 30 and 20 syllables (23% and 52% respectively) compared to ChatGPT-3.5 (66% and 82% respectively), as noted by readability. Google Bard had significantly (p<0.0001) lower readability grade scores and significantly higher "Flesch Reading ease score", implying greater ease of readability amongst the answers generated by Google Bard. Many patients and their families turn to LLM chatbots for information, necessitating clear and accurate content. Assessments of online glaucoma information have shown variability in quality and readability, with institutional websites generally performing better than private ones. We found that ChatGPT-3.5, while precise, has lower readability than Google Bard, which is more accessible but less precise. For example, the Flesch Reading Ease Score was 57.6 for Google Bard and 22.6 for ChatGPT, indicating Google Bard's content is easier to read. Moreover, the Gunning Fog Index scores suggested that Google Bard's text is more suitable for a broader audience. ChatGPT's knowledge is limited to data up to 2021, whereas Google Bard, trained with real-time data, offers more current information. Further research is needed to evaluate these tools across various medical topics. The answers generated by ChatGPT-3.5™ AI are more accurate than the ones given by Google Bard. However, comprehension of ChatGPT-3.5™ answers may be difficult for the public with glaucoma. This study emphasized the importance of verifying the accuracy and clarity of online information that glaucoma patients rely on to make informed decisions about their ocular health. This is an exciting new area for patient education and health literacy.

Ichhpujani P ，Parmar UPS ，Kumar S 《-》

Patient education resources for oral mucositis: a google search and ChatGPT analysis.

Oral mucositis affects 90% of patients receiving chemotherapy or radiation for head and neck malignancies. Many patients use the internet to learn about their condition and treatments; however, the quality of online resources is not guaranteed. Our objective was to determine the most common Google searches related to "oral mucositis" and assess the quality and readability of available resources compared to ChatGPT-generated responses. Data related to Google searches for "oral mucositis" were analyzed. People Also Ask (PAA) questions (generated by Google) related to searches for "oral mucositis" were documented. Google resources were rated on quality, understandability, ease of reading, and reading grade level using the Journal of the American Medical Association benchmark criteria, Patient Education Materials Assessment Tool, Flesch Reading Ease Score, and Flesh-Kincaid Grade Level, respectively. ChatGPT-generated responses to the most popular PAA questions were rated using identical metrics. Google search popularity for "oral mucositis" has significantly increased since 2004. 78% of the Google resources answered the associated PAA question, and 6% met the criteria for universal readability. 100% of the ChatGPT-generated responses answered the prompt, and 20% met the criteria for universal readability when asked to write for the appropriate audience. Most resources provided by Google do not meet the criteria for universal readability. When prompted specifically, ChatGPT-generated responses were consistently more readable than Google resources. After verification of accuracy by healthcare professionals, ChatGPT could be a reasonable alternative to generate universally readable patient education resources.

Hunter N ，Allen D ，Xiao D ，Cox M ，Jain K ... -  《-》

A Systematic Assessment of Google Search Queries and Readability of Online Gynecologic Oncology Patient Education Materials.

Martin A ，Stewart JR ，Gaskins J ，Medlin E ... -  《-》