Flesch-Kincaid Research Articles

Predicting the difficulty of EFL reading comprehension tests based on linguistic indices

Estimating the difficulty of reading tests is critical in second language education and assessment. This study was aimed at examining various text features that might influence the difficulty level of a high-stakes reading comprehension test and predict test takers’ scores. To this end, the responses provided by 17,900 test takers on the reading comprehension subsection of a major high-stakes test, the Iranian National University Entrance Exam for the Master’s Program were examined. Overall, 63 reading passages in different versions of the test from 2017 to 2019 were studied with a focus on 16 indices that might help explain the reading difficulty and test takers’ scores. The results showed that the content word overlap index and the Flesch-Kincaid Reading Ease formula had significant correlations with the observed difficulty and could therefore be considered better predictors of test difficulty compared to other variables. The findings suggest the use of various indices to estimate the reading difficulty before administering tests to ensure the equivalency and validity of tests.

The readability of online patient education materials on maxillomandibular advancement surgery.

Maxillomandibular advancement (MMA) is an effective surgical option for patients suffering from obstructive sleep apnea (OSA). As a relatively new treatment option, patients may turn to the Internet to learn more. However, online patient education materials (OPEMs) on MMA may be written at a higher literacy level than recommended for patients. The aim of this study was to analyze the readability of OPEMs on MMA. A Google search of "maxillomandibular advancement" was performed, and the first 100 results were screened. Websites that met eligibility criteria were analyzed for their readability using the Automated Readability Index (ARI), Coleman-Liau Index (CLI), Flesch-Kincaid Grade Level (FKGL), Gunning Fog (GF), and Simple Measure of Gobbledygook (SMOG) and compared to the recommended sixth-grade reading level using one-tailed t tests. Readability scores were compared based on the type of website, including hospitals/universities or physician clinics, using ANOVA tests. The mean (SD) for ARI, CLI, FKGL, GF, and SMOG was 11.91 (2.43), 13.42 (1.81), 11.91 (2.06), 14.32 (2.34), and 13.99 (1.56), respectively. All readability scores were significantly higher than a sixth-grade reading level (p < 0.001). After comparing readability scores between different website types (university/hospital, clinic, and other), there was no statistical difference found. The available OPEMs on MMA surgery for OSA are above the recommended sixth-grade reading level. Identifying and reducing the gap between the reading levels of OPEMs and the reading level of the patient are needed to encouragea more active role, informed decisions, and better patient satisfaction.

A Corpus-Based Study of America Media Discourse on Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) has played a significant role in the lives of the Chinese people and is gradually entering the global arena. The process of its globalization can be mirrored by the mass media, such as newspapers, due to their capacity of reflecting the changes in the culture and ideology of a certain region. This study explored the changing trends in America Media Discourse on TCM from 1860 to 1959 in the aspects of vocabulary, readability, and content, based on the analysis of a self-built corpus. The findings reveal that over a century, American media reports on TCM have been picking words that are relatively simple and close to daily life, with a low content of academic vocabulary; scored high for the Flesch Reading Ease Readability formula, decreasing the difficulty of being understood by readers; ranged from shallow to deep in the overall perspective, reflecting the historical process of TCMs transmission and development in global terms.

Improving Health Literacy of Domestic Household Disinfection Use: Readability of Consumer-Facing Information on Domestic Household Disinfectant Products on Sale in the UK—An Infodemiology Study

Disinfectants purchased from retail outlets form the cornerstone of infection control and prevention within the domestic household. The growing utilisation of the concept of “hospital-at-home” places greater emphasis on domestic disinfection by the householder in helping to prevent the acquisition of infections within the home. No reports or data exist that indicate how readable the information provided on disinfectants is, which would help householders use disinfectants optimally. The aim of this study was therefore to quantitatively examine the readability (Flesch Reading Ease; Flesch–Kinkaid Grade Level; text metrics) of consumer (public)-facing information (n = 108) of domestic household disinfectants sourced from (i) UK high street supermarket chains (n = 4) and (ii) disinfectant manufacturers (n = 6). The readability of all supermarket and manufacturer information (n = 108) gave a mean Flesch Reading Ease score of 51.7 (target ≥ 60) and a Flesch–Kinkaid Grade Level score of 8.1 (target ≤ 8), thereby failing to achieve readability reference target values. Authors preparing information on the domestic use of disinfectants should be aware of the value of quantitative readability metrics and online tools to help support their writing of such information in order to produce materials which are within target readability values, thereby further supporting health literacy in this population and disinfectant efficacy.

Readability of information on stem cell therapies: a comparison between commercial websites and scientific articles

The aim of this paper is to evaluate and compare the readability level of the stem cell companies’ websites content and scientific articles devoted to this topic. Eight readability formulas were utilised to assess the readability of the information available on the 2020 top ten stem cell companies’ websites and of 24 scientific articles (12 research articles and 12 reviews) published in npj Regenerative Medicine between 2018 and 2020, selected on the basis of the search term “stem cell therapy human”. The average Flesch Reading Ease Score was 32.6 (difficult) for website pages, 35.8 (difficult) for original articles, and 22.4 (very difficult) for reviews. Based on the other seven readability algorithms applied here, none of the examined texts was written beyond the sixth-grade level of readability, indicating that neither scientific articles nor commercial materials from the companies’ websites delivered information on stem cell-based therapies that would be easily readable for an average adult.

AI-Generated Information for Vascular Patients: Assessing the Standard of Procedure-Specific Information Provided by the ChatGPT AI-Language Model.

Introduction Ensuring access to high-quality information is paramount to facilitating informed surgical decision-making. The use of the internet to access health-related information is increasing, along with the growing prevalence of AI language models such as ChatGPT. We aim to assess the standard of AI-generated patient-facing information through a qualitative analysis of its readability and quality. Materials and methods We performed a retrospective qualitative analysis of information regarding three common vascular procedures: endovascular aortic repair (EVAR), endovenous laser ablation (EVLA), and femoro-popliteal bypass (FPBP). The ChatGPT responses were compared to patient information leaflets provided by the vascular charity, Circulation Foundation UK. Readability was assessed using four readability scores: the Flesch-Kincaid reading ease (FKRE) score, the Flesch-Kincaid grade level (FKGL), the Gunning fog score (GFS), and the simple measure of gobbledygook (SMOG) index. Quality was assessed using the DISCERN tool by two independent assessors. Results The mean FKRE score was 33.3, compared to 59.1 for the information provided by the Circulation Foundation (SD=14.5, p=0.025) indicating poor readability of AI-generated information. The FFKGL indicated that the expected grade of students likely to read and understand ChatGPT responses was consistently higher than compared to information leaflets at 12.7 vs. 9.4 (SD=1.9, p=0.002). Two metrics measure readability in terms of the number of years of education required to understand a piece of writing: the GFS and SMOG. Both scores indicated that AI-generated answers were less accessible. The GFS for ChatGPT-provided information was 16.7 years versus 12.8 years for the leaflets (SD=2.2, p=0.002) and the SMOG index scores were 12.2 and 9.4 years for ChatGPT and the patient information leaflets, respectively (SD=1.7, p=0.001). The DISCERN scores were consistently higher in human-generated patient information leaflets compared to AI-generated information across all procedures; the mean score for the information provided by ChatGPT was 50.3 vs. 56.0 for the Circulation Foundation information leaflets (SD=3.38, p<0.001). Conclusion We concluded that AI-generated information about vascular surgical procedures is currently poor in both the readability of text and the quality of information. Patients should be directed to reputable, human-generated information sources from trusted professional bodies to supplement direct education from the clinician during the pre-procedure consultation process.

Comparison of large language models in management advice for melanoma: Google's AI BARD, BingAI and ChatGPT.

Large language models (LLMs) are emerging artificial intelligence (AI) technology refining research and healthcare. Their use in medicine has seen numerous recent applications. One area where LLMs have shown particular promise is in the provision of medical information and guidance to practitioners. This study aims to assess three prominent LLMs-Google's AI BARD, BingAI and ChatGPT-4 in providing management advice for melanoma by comparing their responses to current clinical guidelines and existing literature. Five questions on melanoma pathology were prompted to three LLMs. A panel of three experienced Board-certified plastic surgeons evaluated the responses for reliability using reliability matrix (Flesch Reading Ease Score, the Flesch-Kincaid Grade Level and the Coleman-Liau Index), suitability (modified DISCERN score) and comparing them to existing guidelines. t-Test was performed to calculate differences in mean readability and reliability scores between LLMs and p value<0.05 was considered statistically significant. The mean readability scores across three LLMs were same. ChatGPT exhibited superiority with a Flesch Reading Ease Score of 35.42 (±21.02), Flesch-Kincaid Grade Level of 11.98 (±4.49) and Coleman-Liau Index of 12.00 (±5.10), however all of these were insignificant (p>0.05). Suitability-wise using DISCERN score, ChatGPT 58 (±6.44) significantly (p=0.04) outperformed BARD 36.2 (±34.06) and was insignificant to BingAI's 49.8 (±22.28). This study demonstrates that ChatGPT marginally outperforms BARD and BingAI in providing reliable, evidence-based clinical advice, but they still face limitations in depth and specificity. Future research should improve LLM performance by integrating specialized databases and expert knowledge to support patient-centred care.

Readability of Reading Texts for EFL Students at Al-Baha University

Reading is an important skill for EFL university students, as it reinforces their critical and analytical thinking. EFL university students rely on reading texts to expand their knowledge of the outside world and enhance their memory functions, enabling them to use the target language more effectively. EFL instructors depend on the reading texts as the basis for curricular and extracurricular activities to enhance their learners&amp;#39; language skills, enabling them to use the language in everyday situations. Therefore, selecting suitable English textbooks with appropriate reading texts is crucial for students&amp;#39; achievement and progress. Research in the areas of readability of textbooks and reading texts is very important to assess the appropriateness of different texts for learners. Many readability studies have focused on examining the suitability of readability formulas for measuring the readability level of texts provided to learners. This study measured the readability level of the reading texts of Evolve 4 special edition (published by Cambridge University Press) offered to EFL university students using online digital software that utilizes a set of the most commonly used readability formulas, including the Flesch Reading Ease Formula, Gunning Fog index, and Coleman Liau index. This study also used a set of cloze tests administered to female EFL university students, designed by the researcher to measure the readability level of the reading texts and provide suggestions and recommendations for EFL instructors who teach the textbook at the university level. The findings of this study show that the readability level of the reading texts in the English book Evolve 4 special edition is fairly challenging for EFL university students, as measured by a set of readability instruments. Consequently, the study recommends that EFL instructors should utilize a diverse set of teaching strategies and cooperative work methods to help their students read and understand the reading texts in Evolve 4 special edition. Moreover, EFL instructors should take into account significant factors that can affect the readability of English reading texts, such as learners&amp;#39; interest, prior background, style of the text, and the content itself. These considerations should guide instructors in tailoring their approach to maximize student learning outcomes.

Information Quality and Readability: ChatGPT's Responses to the Most Common Questions About Spinal Cord Injury

This study aimed to assess the quality, readability, and comprehension of texts generated by ChatGPT in response to commonly asked questions about spinal cord injury (SCI). The study utilized Google Trends to identify the most frequently searched keywords related to SCI. The identified keywords were sequentially inputted into ChatGPT, and the resulting responses were assessed for quality using the Ensuring Quality Information for Patients (EQIP) tool. The readability of the texts was analyzed using the Flesch-Kincaid grade level and the Flesch-Kincaid reading ease parameters. The mean EQIP score of the texts was determined to be 43.02±6.37, the Flesch-Kincaid reading ease score to be 26.24±13.81, and the Flesch-Kincaid grade level was determined to be 14.84±1.79. The analysis revealed significant concerns regarding the quality of texts generated by ChatGPT, indicating serious problems with readability and comprehension. The mean EQIP score was low, suggesting a need for improvement in the accuracy and reliability of the information provided. The Flesch-Kincaid grade level indicated a high linguistic complexity, requiring a level of education equivalent to approximately 14 to 15years of formal education for comprehension. The results of this study show heightened complexity in ChatGPT-generated SCI texts, surpassing optimal health communication readability. ChatGPT currently cannot substitute comprehensive medical consultations. Enhancing text quality could be attainable through dependence on credible sources, the establishment of a scientific board, and collaboration with expert teams. Addressing these concerns could improve text accessibility, empowering patients and facilitating informed decision-making in SCI.

Health-Related Quality of Life in Patients With Ventricular Assist Device: Psychometric Evaluation of the German Version of the Quality of Life With a Ventricular Assist Device Questionnaire.

Ventricular assist device (VAD) implantation has become an alternative treatment for patients with end-stage heart failure. In Germany, valid and reliable instruments to assess health-related quality of life in patients with VAD are lacking. The aim of this study was to present the psychometric validation of the German version of the Quality of Life with a Ventricular Assist Device questionnaire. In a multicenter, cross-sectional study, 393 participants (mean age, 58.3 years; 85.8% male, 60.3% bridge to transplant, and 72.8% living with VAD for ≤2 years) completed the German Quality of Life with a Ventricular Assist Device questionnaire of physical, emotional, social, cognitive, and meaning/spiritual domains. Item and confirmatory factor analyses were conducted to test item difficulty and discrimination and the underlying structure, respectively. To examine internal consistency, Cronbach α was assessed. Convergent construct validity was tested using the Kansas City Cardiomyopathy Questionnaire and the Patient Health Questionnaire-9. Readability was examined using Flesch Reading Ease index and Vienna Factual Text Formula. The Quality of Life with a Ventricular Assist Device showed reasonable item difficulty (Ptotal = .67) and mostly moderate to high discriminatory power (rit > 0.30). In confirmatory factor analysis, root-mean-square error of approximation (0.07) was acceptable for model fit, but no other indices. Acceptable internal consistency was found (α ≥ 0.79), with the exception of the cognitive domain (α = 0.58). The overall questionnaire and single domains demonstrated convergent validity (r ≥ 0.45, P < .001). The questionnaire showed adequate readability (Flesch Reading Ease, 64.11; Vienna Factual Text Formula, 6.91). Findings indicate a promising standardized clinical instrument to assess health-related quality of life in patients with VAD.

Readability of Online Information on the Latarjet Procedure.

Introduction A common complication of first-time or recurrent shoulder dislocations is bone loss at the humeral head and glenoid. Recurrent shoulder instability is often a result of bony defects in the glenoid following shoulder dislocations. In the setting of glenoid bone loss, surgical interventions are generally required to restore stability. The Latarjet procedure is a challenging operation and, due to its complexity, may be associated with operative complications. It can be difficult to explain the procedure to patients in a manner that is easily comprehensible, which may lead to confusion or being overwhelmed with information. Hence, it is important that the information available to patients is easily accessible and perceivable to allow for adequate health literacy. Health literacy is defined as the ability to make health decisions in the context of everyday life. Methods The search engines Google and Bing were accessed on a single day in the month of July 2023, searching the terms "Latarjet surgery" and "Latarjet procedure." For each term on both search engines, the first three pages were evaluated, resulting in a total of 114 websites for review. Out of these, 25 websites met the inclusion criteria and underwent further in-depth analysis through the online readability software, WEB FX. This software generated a Flesch Reading Ease Score (FRES) and a Reading Grade Level (RGL) for each website. Results In our study, the mean FRES was 50.3 (SD ±12.5), categorizing the data as 'fairly difficult to read.' The mean RGL score was 8.12 (SD ±2.35), which exceeds the recommended target. Conclusion In conclusion, the results of this study have demonstrated that the material available on the Internet about the Latarjet procedure is above the recommended readability levels for the majority of the population. Our findings align with similar studies assessing the readability of online patient information. Based on these findings, physicians should provide patients with vetted information to facilitate a better understanding of the procedure, thereby enabling patients to make more informed decisions regarding their health.

Evaluation of Oropharyngeal Cancer Information from Revolutionary Artificial Intelligence Chatbot.

With burgeoning popularity of artificial intelligence-based chatbots, oropharyngeal cancer patients now have access to a novel source of medical information. Because chatbot information is not reviewed by experts, we sought to evaluate an artificial intelligence-based chatbot's oropharyngeal cancer-related information for accuracy. Fifteen oropharyngeal cancer-related questions were developed and input into ChatGPT version 3.5. Four physician-graders independently assessed accuracy, comprehensiveness, and similarity to a physician response using 5-point Likert scales. Responses graded lower than three were then critiqued by physician-graders. Critiques were analyzed using inductive thematic analysis. Readability of responses was assessed using Flesch Reading Ease (FRE) and Flesch-Kincaid Reading Grade Level (FKRGL) scales. Average accuracy, comprehensiveness, and similarity to a physician response scores were 3.88 (SD = 0.99), 3.80 (SD = 1.14), and 3.67 (SD = 1.08), respectively. Posttreatment-related questions were most accurate, comprehensive, and similar to a physician response, followed by treatment-related, then diagnosis-related questions. Posttreatment-related questions scored significantly higher than diagnosis-related questions in all three domains (p < 0.01). Two themes of the physician critiques were identified: suboptimal education value and potential to misinform patients. The mean FRE and FKRGL scores both indicated greater than an 11th grade readability level-higher than the 6th grade level recommended for patients. ChatGPT responses may not educate patients to an appropriate degree, could outright misinform them, and read at a more difficult grade level than is recommended for patient material. As oropharyngeal cancer patients represent a vulnerable population facing complex, life-altering diagnoses, and treatments, they should be cautious when consuming chatbot-generated medical information. NA Laryngoscope, 134:2252-2257, 2024.

Analysis of Farm Data License Agreements: Do Data Agreements Adequately Reflect on Farm Data Practices and Farmers’ Data Rights?

Farm data license agreements are legal documents that play an important role in informing farmers about farm data processing practices such as collection, use, safeguarding, and sharing. These legal documents govern the exchange, access, and dissemination of farm data and are expected to provide legal protection against misuse of data. Despite their significant influence on farm data processing and governance, there is limited understanding of the content of farm data license agreements and standards for drafting them. Although online privacy policy content has been extensively studied, farm data agreements’ evaluation and analysis have been overlooked. This study aims to investigate the structure, content, and transparency of farm data licenses. We collected 141 agricultural terms of use agreements and used natural language processing methods such as keyword and keyphrase analysis to perform text feature analysis, Flesch Readability Ease Score and Flesch Grade Level readability analysis, transparency analysis, and content analysis to gain insight into common data practices adopted by the agriculture technology providers. We also manually reviewed these agreements to validate the results and strengthen the observations. The findings show that data agreements are long, complex, and difficult to read and comprehend. The results suggest that 95% of the agreements fall under the difficult-to-read category and close to 75% of the policies require university-level education to understand the content. Furthermore, it is noted that some of the data management practices are not given adequate attention and are not as frequently mentioned in the agreements as expected. Finally, our analysis enabled us to provide recommendations on the content of farm data license agreements and strategies to improve them.

Content Words and Readability in Students’ Thesis Findings

This study investigates the content words and readability in bachelor’s thesis findings in the English Literature Program at the University of Sumatera Utara. Qualitative analysis was applied in this study. The data for this study were content words and sentences taken from the data sources of 13 bachelor’s thesis findings. The content words were collected using a lexical density online tool, and the data for readability was collected and analyzed using an online Flesch Reading Ease tool. The results show that the lexical density of the content words ranges from 50.47% – 57.5%. Whilst the readability of the 13 texts range from 19.1 – 61.7. The average score of content word density indicates that the theses’ findings present concise information as represented in scientific writing, and the readability style ranges from "very difficult to read” to “standard readable”. In conclusion, these findings can be categorized as densely written language and content words, supported by college students' increasingly intricate choice of words and sentences frequently read.

Assessing the Quality and Readability of Web-Based Information on Otoplasty.

Introduction: As health care-related internet use expands, parents and patients considering otoplasty frequently turn to online resources for further information to aid their decision making. Objective: In online resources related to otoplasty, what is the quality of the information and how readable is it based on standardized tests? Methods: A web search was performed on the three major search engines, using search terms related to otoplasty. The top 20 results from each search engine were selected. The DISCERN instrument was applied to assess the quality of health information, whereas the Flesch-Kincaid readability tests were used to assess readability. Results: The mean DISCERN score was 28.7 out of a possible score of 80 (poor quality) and commercial bias was common. The Flesch-Kincaid readability test results were significantly higher than the average reading level for adults in the United Kingdom. On the largest search engine, there was a correlation between search engine ranking and both readability and quality. Conclusion: Online patient information resources on otoplasty are generally of poor quality and difficult to read for the average patient.

Optimizing Ophthalmology Patient Education via ChatBot-Generated Materials: Readability Analysis of AI-Generated Patient Education Materials and The American Society of Ophthalmic Plastic and Reconstructive Surgery Patient Brochures.

This study aims to compare the readability of patient education materials (PEM) of the American Society of Ophthalmic Plastic and Reconstructive Surgery to that of PEMs generated by the AI-chat bots ChatGPT and Google Bard. PEMs on 16 common American Society of Ophthalmic Plastic and Reconstructive Surgery topics were generated by 2 AI models, ChatGPT 4.0 and Google Bard, with and without a 6th-grade reading level prompt modifier. The PEMs were analyzed using 7 readability metrics: Flesch Reading Ease Score, Gunning Fog Index, Flesch-Kincaid Grade Level, Coleman-Liau Index, Simple Measure of Gobbledygook Index Score, Automated Readability Index, and Linsear Write Readability Score. Each AI-generated PEM was compared with the equivalent American Society of Ophthalmic Plastic and Reconstructive Surgery PEM. Across all readability indices, PEM generated by ChatGPT 4.0 consistently had the highest readability scores, indicating that the material generated by this AI chatbot may be most difficult to read in its unprompted form (Flesch Reading Ease Score: 36.5; Simple Measure of Gobbledygook: 14.7). Google's Bard was able to generate content that was easier to read than both the American Society of Ophthalmic Plastic and Reconstructive Surgery and ChatGPT 4.0 (Flesch Reading Ease Score: 52.3; Simple Measure of Gobbledygook: 12.7). When prompted to produce PEM at a 6th-grade reading level, both ChatGPT 4.0 and Bard were able to significantly improve in their readability scores, with prompted ChatGPT 4.0 being able to consistently generate content that was easier to read (Flesch Reading Ease Score: 67.9, Simple Measure of Gobbledygook: 10.2). This study suggests that AI tools, when guided by appropriate prompts, can generate accessible and comprehensible PEMs in the field of ophthalmic plastic and reconstructive surgeries, balancing readability with the complexity of the necessary information.

Assessment of the Readability of the Online Patient Education Materials of Intensive and Critical Care Societies.

This study aimed to evaluate the readability of patient education materials (PEMs) on websites of intensive and critical care societies. Websites of intensive and critical care societies, which are members of The World Federation of Intensive and Critical Care and The European Society of Intensive Care Medicine. Cross-sectional observational, internet-based, website, PEMs, readability study. The readability of the PEMs available on societies' sites was evaluated. The readability formulas used were the Flesch Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG), and Gunning Fog (GFOG). One hundred twenty-seven PEM from 11 different societies were included in our study. In the readability analysis of PEM, the FRES was 58.10 (48.85-63.77) (difficult), the mean FKGL and SMOG were 10.19 (8.93-11.72) and 11.10 (10.11-11.87) years, respectively, and the mean GFOG score was 12.73 (11.37-14.15) (very difficult). All readability formula results were significantly higher than the recommended sixth-grade level ( p < 0.001). All PEMs were above the sixth-grade level when the societies were evaluated individually according to all readability results ( p < 0.05). Compared with the sixth-grade level recommended by the American Medical Association and the National Institutes of Health, the readability of PEMs in intensive and critical care societies is relatively high. PEMs in intensive and critical care societies should be prepared with attention to recommendations on readability.

Abstract 17100: Evaluating Chatgpt Responses on Atrial Fibrillation for Patient Education

Introduction: ChatGPT is an artificial intelligence (AI) chatbot released in November 2022. It is a large scale language model that has gained widespread popularity for its fine-tuned conversational abilities, attracting over 1.8 billion monthly visitors. A noted drawback to the AI chatbot is its tendency to confidently present users with inaccurate information. Goals: To evaluate the quality of ChatGPT responses to questions pertaining to atrial fibrillation for patient education. This includes the accuracy of answers, estimated grade level, and references of answers. Methods: ChatGPT was prompted four times then was asked 16 questions derived from the American Heart Association's frequently asked questions on atrial fibrillation. Prompts included: no prompt (Form 1), patient-friendly prompt (Form 2), physician-level prompt (Form 3), and prompting for statistics/references (Form 4). Responses were scored as incorrect, partially correct, correct, or correct with references (perfect). Flesch-Kincaid grade level and response lengths were recorded. Proportions of responses at differing scores were compared using chi-squared analysis. The relationship between form and grade level was assessed using ANOVA. Results: Across all forms scoring frequencies were: 1(1.6%) incorrect, 5 (7.8%) partially correct, 55 (85.9%) correct, and 3 (4.7%) perfect. Proportions of responses that were at least correct did not differ by form (p=0.350); responses that were perfect did (p&lt;0.001). Form 2 answers had a lower mean grade level (12.81 ± 3.38) than Forms 1 (14.23 ± 2.34), 3 (16.73 ± 2.65), and 4 (14.85 ± 2.76) (p&lt;0.01). Conclusions: ChatGPT provides accurate and comprehensive answers to most questions about atrial fibrillation regardless of prompting. Interestingly, when prompted as a patient, ChatGPT will provide lower grade level responses. Given ChatGPTs rapid popularity and usage, cardiologists may seek to further investigate its accuracy and utility for patients.

Assessment of Quality and Readability of Online Patient-Centered Arabic Web-Based Knowledge About Apicoectomy.

Background Endodontic microsurgery (apicectomy) can be considered in cases of persistent infection that is resistant to conventional root canal treatment. The aim of this study was to evaluate the quality and readability of the available online information regarding the apicectomy procedure in Arabic. Methods Online search on the three most commonly used websites (Google, Yahoo, and Bing) using one keyword. The first 100 websites from each search were analyzed for quality and readability using DISCERN instrument scores, the Journal of the American Medical Association (JAMA) benchmarks, the Health On the Net (HON) seal, Flesch Reading Ease Scores (FRES), Flesch-Kincaid Grade Level (FKGL), and the Simplified Measure of Gobbledygook (SMOG) Index. Results Searching using the Arabic translation for "root end resection surgery" revealed 349,900 websites. Following the inclusion criteria, 31 websites were selected and evaluated in this study. The selected websites belonged to either non-profit organizations or commercial websites. The quality of most of the selected websites received a moderate score (83.9%) using the DISCERN tool. None of the selected websites obtained the HON seal. Quality evaluation using the JAMA benchmarks revealed that currency was the most achieved item (45.2%), followed by authorship (22.6%). Evaluation of the readability of the selected websites using the FRES, FKGL, and SMOG showed that the included websites were considered readable. Conclusion Although the included websites were readable, the quality of the websites was moderate. There is an urgent need to create more trustworthy and readable websites explaining the different endodontic treatments.

Readability and Quality of Online Information on Sickle Cell Retinopathy for Patients

PurposeThis study aims to evaluate the readability and quality of internet-based health information on sickle cell retinopathy. DesignThe study is a retrospective cross-sectional website analysis. MethodsTo simulate a patient's online search, the terms “sickle cell retinopathy” and “sickle cell disease in the eye” were entered into the top three search engines (Google, Bing and Yahoo). The first 20 results of each search were retrieved and screened for analysis. The DISCERN questionnaire, the Journal of the American Medical Association (JAMA) standards and the Health on the Net (HON) criteria were used to evaluate the quality of the information. The Flesch-Kincaid Grade Level (FKGL), the Flesch Reading Ease (FRES) and the Automated Readability Index (ARI) were used to assess the readability of each website. ResultsOut of 16 online sources, 12 (75%) scored moderately on the DISCERN tool. The mean DISCERN score was 40.91 (SD 10.39; maximum possible, 80). None of the sites met all the JAMA benchmarks and only three (18.75%) of the websites had HONcode certification. All the websites had scores above the target American Medical Association grade level of six on both the FKGL and ARI. The mean FRES was 57.76 (±4.61), below the recommended FRES of 80-90. ConclusionThere is limited online information available on sickle cell retinopathy. Most included websites were fairly difficult to read and of substandard quality. The quality and readability of internet-based patient-focused information on sickle cell retinopathy needs to be improved.