Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.

There is no study that comprehensively evaluates data on the readability and quality of "palliative care" information provided by artificial intelligence (AI) chatbots ChatGPT®, Bard®, Gemini®, Copilot®, Perplexity®. Our study is an observational and cross-sectional original research study. In our study, AI chatbots ChatGPT®, Bard®, Gemini®, Copilot®, and Perplexity® were asked to present the answers of the 100 questions most frequently asked by patients about palliative care. Responses from each 5 AI chatbots were analyzed separately. This study did not involve any human participants. Study results revealed significant differences between the readability assessments of responses from all 5 AI chatbots (P < .05). According to the results of our study, when different readability indexes were evaluated holistically, the readability of AI chatbot responses was evaluated as Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, from easy to difficult (P < .05). In our study, the median readability indexes of each of the 5 AI chatbots Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini® responses were compared to the "recommended" 6th grade reading level. According to the results of our study answers of all 5 AI chatbots were compared with the 6th grade reading level, statistically significant differences were observed in the all formulas (P < .001). The answers of all 5 artificial intelligence robots were determined to be at an educational level well above the 6th grade level. The modified DISCERN and Journal of American Medical Association scores was found to be the highest in Perplexity® (P < .001). Gemini® responses were found to have the highest Global Quality Scale score (P < .001). It is emphasized that patient education materials should have a readability level of 6th grade level. Of the 5 AI chatbots whose answers about palliative care were evaluated, Bard®, Copilot®, Perplexity®, ChatGPT®, Gemini®, their current answers were found to be well above the recommended levels in terms of readability of text content. Text content quality assessment scores are also low. Both the quality and readability of texts should be brought to appropriate recommended limits.

Hancı V ，Ergün B ，Gül Ş ，Uzun Ö ，Erdemir İ ，Hancı FB ... -  《-》

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

Ömür Arça D ，Erdemir İ ，Kara F ，Shermatov N ，Odacioğlu M ，İbişoğlu E ，Hanci FB ，Sağiroğlu G ，Hanci V ... -  《-》

Assessing the readability, quality and reliability of responses produced by ChatGPT, Gemini, and Perplexity regarding most frequently asked keywords about low back pain.

Patients who are informed about the causes, pathophysiology, treatment and prevention of a disease are better able to participate in treatment procedures in the event of illness. Artificial intelligence (AI), which has gained popularity in recent years, is defined as the study of algorithms that provide machines with the ability to reason and perform cognitive functions, including object and word recognition, problem solving and decision making. This study aimed to examine the readability, reliability and quality of responses to frequently asked keywords about low back pain (LBP) given by three different AI-based chatbots (ChatGPT, Perplexity and Gemini), which are popular applications in online information presentation today. All three AI chatbots were asked the 25 most frequently used keywords related to LBP determined with the help of Google Trend. In order to prevent possible bias that could be created by the sequential processing of keywords in the answers given by the chatbots, the study was designed by providing input from different users (EO, VH) for each keyword. The readability of the responses given was determined with the Simple Measure of Gobbledygook (SMOG), Flesch Reading Ease Score (FRES) and Gunning Fog (GFG) readability scores. Quality was assessed using the Global Quality Score (GQS) and the Ensuring Quality Information for Patients (EQIP) score. Reliability was assessed by determining with DISCERN and Journal of American Medical Association (JAMA) scales. The first three keywords detected as a result of Google Trend search were "Lower Back Pain", "ICD 10 Low Back Pain", and "Low Back Pain Symptoms". It was determined that the readability of the responses given by all AI chatbots was higher than the recommended 6th grade readability level (p < 0.001). In the EQIP, JAMA, modified DISCERN and GQS score evaluation, Perplexity was found to have significantly higher scores than other chatbots (p < 0.001). It has been determined that the answers given by AI chatbots to keywords about LBP are difficult to read and have low reliability and quality assessment. It is clear that when new chatbots are introduced, they can provide better guidance to patients with increased clarity and text quality. This study can provide inspiration for future studies on improving the algorithms and responses of AI chatbots.

Ozduran E ，Hancı V ，Erkin Y ，Özbek İC ，Abdulkerimov V ... -  《PeerJ》

Erratum: Eyestalk Ablation to Increase Ovarian Maturation in Mud Crabs.

《Jove-Journal of Visualized Experiments》

A Comparison of Prostate Cancer Screening Information Quality on Standard and Advanced Versions of ChatGPT, Google Gemini, and Microsoft Copilot: A Cross-Sectional Study.

Owens OL ，Leonard M 《-》