Reading Scores Research Articles

How artificial intelligence can provide information about subdural hematoma: Assessment of readability, reliability, and quality of ChatGPT, BARD, and perplexity responses.

Subdural hematoma is defined as blood collection in the subdural space between the dura mater and arachnoid. Subdural hematoma is a condition that neurosurgeons frequently encounter and has acute, subacute and chronic forms. The incidence in adults is reported to be 1.72-20.60/100.000 people annually. Our study aimed to evaluate the quality, reliability and readability of the answers to questions asked to ChatGPT, Bard, and perplexity about "Subdural Hematoma." In this observational and cross-sectional study, we asked ChatGPT, Bard, and perplexity to provide the 100 most frequently asked questions about "Subdural Hematoma" separately. Responses from both chatbots were analyzed separately for readability, quality, reliability and adequacy. When the median readability scores of ChatGPT, Bard, and perplexity answers were compared with the sixth-grade reading level, a statistically significant difference was observed in all formulas (P < .001). All 3 chatbot responses were found to be difficult to read. Bard responses were more readable than ChatGPT's (P < .001) and perplexity's (P < .001) responses for all scores evaluated. Although there were differences between the results of the evaluated calculators, perplexity's answers were determined to be more readable than ChatGPT's answers (P < .05). Bard answers were determined to have the best GQS scores (P < .001). Perplexity responses had the best Journal of American Medical Association and modified DISCERN scores (P < .001). ChatGPT, Bard, and perplexity's current capabilities are inadequate in terms of quality and readability of "Subdural Hematoma" related text content. The readability standard for patient education materials as determined by the American Medical Association, National Institutes of Health, and the United States Department of Health and Human Services is at or below grade 6. The readability levels of the responses of artificial intelligence applications such as ChatGPT, Bard, and perplexity are significantly higher than the recommended 6th grade level.

Identifying ChatGPT-written Patient Education Materials Using Text Analysis and Readability.

Artificial intelligence (AI)-based text generators such as Chat Generative Pre-Trained Transformer (ChatGPT) have come into the forefront of modern medicine. Given the similarity between AI-generated and human-composed text, tools need to be developed to quickly differentiate the two. Previous work has shown that simple grammatical analysis can reliably differentiate AI-generated text from human-written text. In this study, ChatGPT was used to generate 25 articles related to obstetric topics similar to those made by the American College of Obstetrics and Gynecology (ACOG). All articles were geared towards patient education. These AI-generated articles were then analyzed for their readability and grammar using validated scoring systems and compared to real articles from ACOG. Characteristics of the 25 AI-generated articles included fewer overall characters than original articles (mean 3,066 vs. 7,426; p < 0.0001), a greater average word length (mean 5.3 vs. 4.8; p < 0.0001), and a lower Flesch-Kincaid score (mean 46 vs. 59; p < 0.0001). With this knowledge, a new scoring system was develop to score articles based on their Flesch-Kincaid readability score, number of total characters, and average word length. This novel scoring system was tested on 17 new AI-generated articles related to obstetrics and 7 articles from ACOG, and was able to differentiate between AI-generated articles and human-written articles with a sensitivity of 94.1% and specificity of 100% (Area Under the Curve [AUC] 0.99). As ChatGPT is more widely integrated into medicine, it will be important for health care stakeholders to have tools to separate originally written documents from those generated by AI. While more robust analyses may be required to determine the authenticity of articles written by complex AI technology in the future, simple grammatical analysis can accurately characterize current AI-generated texts with a high degree of sensitivity and specificity. · More tools are needed to identify AI-generated text in obstetrics, for both doctors and patients.. · Grammatical analysis is quick and easily done.. · Grammatical analysis is a feasible and accurate way to identify AI-generated text..

Pregnancy Loss: A Comparative Analysis of Information Delivery Between ACOG FAQs and ChatGPT [ID 2683594

INTRODUCTION: Pregnancy loss is a sensitive topic, and clear, reliable information is crucial. This study compares the readability and accuracy of ChatGPT's responses to ACOG's frequently asked questions (FAQ) sheets on the subject. METHODS: Within the five FAQ sheets under “Pregnancy Loss,” 66 questions were assessed using ChatGPT-3.5. Readability scores, ie, Flesch–Kincaid Reading Ease, Flesch–Kincaid Grade Level, Gunning Fog Score, Smog Index, Coleman Liau Index, and Automated Readability Index were computed for each response. The quality of responses were also graded by two maternal–fetal medicine specialists using a 1–4 scale, where 1 represents a comprehensive response and 4 indicates an incorrect response. Statistical analysis utilized a two-tailed t-test. A weighted Cohen’s kappa coefficient evaluated interrater reliability. RESULTS: ACOG attained better readability scores over ChatGPT across all six metrics with statistical significance (P&lt;.001). Among grading, ACOG also outperformed ChatGPT in quality of information with a summative mean of 1.53 (SD 0.60) versus 1.85 (SD 0.90) with statistical significance (P&lt;.001). Grading for ACOG possessed a Cohen's kappa coefficient of 0.493, implying moderate agreement between graders. Grading for ChatGPT possessed a Cohen's kappa coefficient of 0.744, implying substantial agreement between graders. CONCLUSION: The responses by ACOG to frequently asked questions on pregnancy loss were both clearer and more comprehensive than those of ChatGPT with consistent agreement between graders. Although ChatGPT can be a convenient source of medical queries, further improvements ought to be made to these large-language models to provide clear and accurate information regarding pregnancy loss to patients.

Can Generative Artificial Intelligence Enhance Health Literacy About Lateral Epicondylitis?

Health literacy is a critical determinant of a patient's overall health status, and studies have demonstrated a consistent link between poor health literacy and negative health outcomes. The Centers for Disease Control and Prevention (CDC) and the National Institutes of Health (NIH) advise that patient educational materials (PEMs) should be written at an eighth-grade reading level or lower, matching the average reading level of adult Americans. The purpose of this study was to investigate the ability of generative artificial intelligence (AI) to edit PEMs from orthopaedic institutions to meet the CDC and NIH guidelines. PEMs about lateral epicondylitis (LE) from the top 25 ranked orthopaedic institutions from the 2022 U.S. News & World Report Best Hospitals Specialty Ranking were gathered. ChatGPT Plus (version 4.0) was then instructed to rewrite PEMs on LE from these institutions to comply with CDC and NIH-recommended guidelines. Readability scores were calculated for the original and rewritten PEMs, and paired t-tests were used to determine statistical significance. Analysis of the original and edited PEMs about LE revealed significant reductions in reading grade level and word count of 3.70 ± 1.84 (p<0.001) and 346.72 ± 364.63 (p<0.001), respectively. Our study demonstrated generative AI's ability to rewrite PEM about LE at a reading comprehension level that conforms to the CDC and NIH guidelines. Hospital administrators and orthopaedic surgeons should consider the findings of this studyand the potential utility of artificial intelligence when crafting PEMs of their own.

Navigating Intimate Partner Violence: A Comparative Analysis Between ACOG and ChatGPT on Patient Education [ID 2683552

INTRODUCTION: With the surge in artificial intelligence usage, there is an increasing need to assess its applicability in conveying public health information. We compare the readability and quality of responses between ChatGPT and the American College of Obstetricians and Gynecologists (ACOG) in answering frequently asked questions (FAQs) on intimate partner violence (IPV). METHODS: Twelve questions from ACOG's “Intimate Partner Violence” FAQs were posed to ChatGPT-3.5 (July 19 Version). Readability and grade-level scores were determined. The quality of responses were also graded by two obstetrician–gynecologists using a 1–4 scale, where 1 represents a comprehensive response and 4 indicates an incorrect response. Statistical analysis utilized a two-tailed t-test. A weighted Cohen’s kappa coefficient evaluated interrater reliability. RESULTS: Mean readability favored ACOG over ChatGPT, but only the Coleman Liau Index was statistically significant (ACOG: 12.71; ChatGPT: 15.76; P=.003). Other readability measures demonstrated no significant differences. The ACOG responses were graded with an average of 1.29, alongside a Cohen’s kappa coefficient of 0.375, implying fair agreement between graders. All ChatGPT’s responses were graded a 1 with a Cohen’s kappa coefficient of 1, indicating perfect agreement. The difference in grades between ACOG and ChatGPT was statistically significant (P=.013). CONCLUSION: The ACOG FAQ responses are relatively equivalent in readability when compared to ChatGPT-generated responses with only one statistically significant difference across the indices. However, ChatGPT's responses were more comprehensive and accurate. Although patients can use ACOG as a source, ChatGPT provides equivalently clear and more comprehensive information on IPV.

Comparison of ChatGPT versions in informing patients with rotator cuff injuries

BackgroundThe aim of this study is to evaluate whether ChatGPT can be recommended as a resource for informing patients planning rotator cuff repairs, and to assess the differences between ChatGPT 3.5 and 4.0 versions in terms of information content and readability. MethodsIn August 2023, 13 commonly asked questions by patients with rotator cuff disease were posed to Chat GPT-3.5 and Chat GPT-4 programs using different IP computers by three experienced surgeons in rotator cuff surgery. After converting the answers of both versions into text, the quality and readability of the answers were examined. ResultsThe average JAMA score for both versions was 0, and the average Discern score was 61.6. A statistically significant and strong correlation was found between ChatGPT 3.5 and 4.0 Discern scores. There was excellent agreement in Discern scores for both versions among the three evaluators. Chat GPT 3.5 was found to be less readable than 4.0. ConclusionsThe information provided by the ChatGPT conversational system was evaluated as of high quality, but there were significant shortcomings in terms of reliability due to the lack of citations. Despite the ChatGPT 4.0 version having higher readability scores, both versions were considered difficult to read.

Readability Analysis of Patient Education Material on Rotator Cuff Injuries From the Top 25 Ranking Orthopaedic Institutions

Introduction: Rotator cuff injuries (RCIs) are incredibly common in the US adult population. Forty-three percent of adults have basic or below-basic literacy levels; nonetheless, patient educational materials (PEMs) are frequently composed at levels exceeding these reading capabilities. This study investigates the readability of PEMs on RCIs published by leading US orthopaedic institutions. Methods: The top 25 orthopaedic institutions on the 2022 U.S. News &amp; World Report Best Hospitals Specialty Ranking were selected. Readability scores of PEMs related to RCI were calculated using the www.readabilityformulas.com website. Results: Among the 25 analyzed PEM texts, all exceeded the sixth-grade reading level. Only four of 168 scores (2.4%) were below the eighth-grade level. Discussion: This study indicates that PEMs on rotator cuff injuries from top orthopedic institutions are too complex for many Americans, with readability levels ranging from 8.5 to 16th grade, well above the CDC-recommended eighth-grade level. The research highlights a widespread issue with high reading levels across healthcare information and underscores the need for healthcare providers to adopt patient-centered communication strategies to improve comprehension and accessibility. Conclusion: PEMs on rotator cuff injuries from leading orthopedic institutions often have a reading level beyond that of many Americans, exceeding guidelines from the NIH and CDC that recommend PEMs be written at an eighth-grade reading level. To increase accessibility, enhance healthcare literacy, and improve patient outcomes, institutions should simplify these materials to meet recommended readability standards.

Greater utilization of executive functions networks when listening to stories with visual stimulation is related to lower reading abilities in children

Narrative comprehension relies on basic sensory processing abilities, such as visual and auditory processing, with recent evidence for utilizing executive functions (EF), which are also engaged during reading. EF was previously related to the “supporter” of engaging the auditory and visual modalities in different cognitive tasks, with evidence of lower efficiency in this process among those with reading difficulties in the absence of a visual stimulus (i.e. while listening to stories). The current study aims to fill out the gap related to the level of reliance on these neural circuits while visual aids (pictures) are involved during story listening in relation to reading skills. Functional MRI data were collected from 44 Hebrew-speaking children aged 8–12 years while listening to stories with vs without visual stimuli (i.e., pictures). Functional connectivity of networks supporting reading was defined in each condition and compared between the conditions against behavioral reading measures. Lower reading skills were related to greater functional connectivity values between EF networks (default mode and memory networks), and between the auditory and memory networks for the stories with vs without the visual stimulation. A greater difference in functional connectivity between the conditions was related to lower reading scores. We conclude that lower reading skills in children may be related to a need for greater scaffolding, i.e., visual stimulation such as pictures describing the narratives when listening to stories, which may guide future intervention approaches.

Examining the effects of prekindergarten to second grade classroom quality on early elementary achievement

Previous research has investigated the influence of preschool interventions in early elementary environments with some results suggesting that high quality early preschool experiences may have meaningful effects on student academic outcomes not only immediately following the preschool years but also in the long term. This study aimed to investigate this topic further by using a novel cross-classified model to account for the complex hierarchical structure of a large-scale longitudinal and multilevel dataset. First, we examined the carryover classroom effects from prekindergarten (PK), kindergarten (K), and first grade on later grades’ reading and mathematics scores. Second, we explored the effect of PK to second grade classroom quality on students’ K, first, and second grade reading and mathematics scores. Our analyses yielded significant PK carryover classroom effects for reading; these results provide evidence that a student’s PK classroom continues to impact that student for at least three years after. Additionally, one domain of PK classroom quality —classroom organization—was found to be positively related to students’ K, first, and second grade reading outcomes.

Utilizing Machine Learning Techniques for Learning Analytics: A Case Study of Moodle LMS Activity Log Analysis

Learning analytics collects data, analyzes, and interprets the learning process that has taken place. The output of this method can be used to improve the quality of teaching or learning. Moodle is a popular learning management system (LMS) used for online learning. Various learning activities carried out by students are recorded in the activity log. This paper shows the potential of using machine learning methods to analyze activity logs taken from Moodle LMS. The sample used in this study refers to implementing the Digital Society course, which students from different fields of science attend. This paper describes using supervised and unsupervised learning on activity log data taken from the Moodle LMS. The variables used as datasets include the frequency of activity reading pdf material, scores, videos, forums, quizzes, and graduation status. The supervised learning model that was built succeeded in obtaining an accuracy of 100% in the application of logistic regression and Naïve Bayes Classification. Unsupervised learning clustered all the data and showed the cluster related to the frequency of online learning activities and students' assessment success status.

Investigation of the quality and health literacy demand of online information on pelvic floor exercises to reduce stress urinary incontinence.

Many women are embarrassed to discuss pelvic floor exercises with health professionals during pregnancy; instead they search the internet for information on pelvic floor exercises. This project investigated the quality and health literacy demand in terms of readability, understandability and actionability of information available on the internet relating to pelvic floor exercises. An analysis was conducted on 150 websites and 43 videos obtained from three consecutive Google searches relating to pelvic floor exercises. Websites were assessed for Health on the Net certification. Readability was assessed using a readability calculator, and understandability/actionability of website and video information was assessed using the Patient Education Materials Assessment Tool (PEMAT) for Print or Audiovisual Materials. Less than one-third (24%) of the websites were certified for quality. The median readability score for the websites was grade 9 and the websites and videos both rated highly for understandability and actionability. The median understandability score for the website information was 87%, and the median actionability score was 71%. The median understandability score of the video information was 95.5% and the median actionability score was 100%. The understandability and actionability of video information was also significantly greater than that for website information (P < 0.01). Clinicians could consider directing patients to video-based resources when advising online pelvic floor exercise resources for women during pregnancy, especially those with lower health literacy.

Quantitative Comparison of Chatbots on Common Rhinology Pathologies.

Understanding the strengths and weaknesses of chatbots as a source of patient information is critical for providers in the rising artificial intelligence landscape. This study is the first to quantitatively analyze and compare four of the most used chatbots available regarding treatments of common pathologies in rhinology. The treatment of epistaxis, chronic sinusitis, sinus infection, allergic rhinitis, allergies, and nasal polyps was asked to chatbots ChatGPT, ChatGPT Plus, Google Bard, and Microsoft Bing in May 2023. Individual responses were analyzed by reviewers for readability, quality, understandability, and actionability using validated scoring metrics. Accuracy and comprehensiveness were evaluated for each response by two experts in rhinology. ChatGPT, Plus, Bard, and Bing had FRE readability scores of 33.17, 35.93, 46.50, and 46.32, respectively, indicating higher readability for Bard and Bing compared to ChatGPT (p = 0.003, p = 0.008) and Plus (p = 0.025, p = 0.048). ChatGPT, Plus, and Bard had mean DISCERN quality scores of 20.42, 20.89, and 20.61, respectively, which was higher than the score for Bing of 16.97 (p < 0.001). For understandability, ChatGPT and Bing had PEMAT scores of 76.67 and 66.61, respectively, which were lower than both Plus at 92.00 (p < 0.001, p < 0.001) and Bard at 92.67 (p < 0.001, p < 0.001). ChatGPT Plus had an accuracy score of 4.39 which was higher than ChatGPT (3.97, p = 0.118), Bard (3.72, p = 0.002), and Bing (3.19, p < 0.001). On aggregate of the tested domains, our results suggest ChatGPT Plus and Google Bard are currently the most patient-friendly chatbots for the treatment of common pathologies in rhinology. N/A Laryngoscope, 134:4225-4231, 2024.

Readability of Trauma-related Patient Education Materials From the American Academy of Orthopaedic Surgeons and Orthopaedic Trauma Association Websites.

Web-based resources serve as a fundamental educational platform for orthopaedic trauma patients; however, they are frequently written above the recommended sixth-grade reading level, and previous studies have demonstrated this for the American Academy of Orthopaedic Surgeons (AAOS) web-based articles. In this study, we perform an updated assessment of the readability of AAOS trauma-related educational articles as compared with injury-matched education materials developed by the Orthopaedic Trauma Association (OTA). All 46 AAOS trauma-related web-based ( https://www.orthoinfo.org/ ) patient education articles were analyzed for readability. Two independent reviewers used (1) the Flesch-Kincaid Grade Level (FKGL) and (2) the Flesch Reading Ease (FRE) algorithms to calculate the readability level. Mean readability scores were compared across body part categories. A one-sample t -test was done to compare mean FKGL with the recommended sixth-grade readability level and the average American adult reading level. A two-sample t -test was used to compare the readability scores of the AAOS trauma-related articles with those of the OTA. The average (SD) FKGL and FRE for the AAOS articles were 8.9 (0.74) and 57.2 (5.8), respectively. All articles were written above the sixth-grade reading level. The average readability of the AAOS articles was significantly greater than the recommended sixth-grade reading level ( P < 0.001). The average FKGL and FRE for all AAOS articles were significantly higher compared with those of the OTA articles (8.9 ± 0.74 versus 8.1 ± 1.14, P < 0.001 and 57.2 ± 5.8 versus 65.6 ± 6.6, P < 0.001, respectively). Excellent agreement was observed between raters for the FKGL 0.956 (95% confidence interval, 0.922 to 0.975) and FRE 0.993 (95% confidence interval, 0.987 to 0.996). Our findings suggest that after almost a decade, the readability of the AAOS trauma-related articles remains unchanged. The AAOS and OTA trauma patient education materials have high readability levels and may be too difficult for patient comprehension. A need remains to improve the readability of these commonly used trauma education materials.

Development and acceptability of a culturally competent skills and knowledge assessment tool for patients with diabetes mellitus

BackgroundPatients newly diagnosed with type 2 diabetes mellitus (DM) and newly prescribed insulin need to learn essential self-care and management skills quickly. To optimize teaching, clinicians need to assess a patient’s basic understanding of DM and their skills. While DM patient assessments exist, this study reports the development of an assessment of patient DM management skills and knowledge, using feedback from DM clinicians, patients, and caregivers. Research Design and MethodsA systematic search of Pubmed/Medline and Scopus (1980–2017) of DM knowledge assessments was performed. Twenty-four studies were identified. Content from the existing assessments was adapted to create a 12 item DM-Skills Knowledge Assessment (SKA) to assess a patient’s DM management skills and knowledge. To assess cultural humility, modified cognitive interviews were conducted in individual user sessions and semi-structured focus groups. Audio-transcripts of the interviews/focus groups were independently coded, and codes were grouped into key themes. Participant demographic characteristics were assessed. ResultsFive focus groups and eleven key informant interviews were conducted, including 10 DM clinicians, 12 patients/caregivers, and 15 laypersons. All 10 clinicians reported that the DM-SKA addresses the key domains of DM education deemed to be of highest importance during the transition from hospital to home and that their patients would be willing to complete the assessment. More than half of the patient/caregiver/layperson participants self-reported race/ethnicity other than non-Hispanic white and performed similarly to non-Hispanic white participants in understanding each item, willingness to complete the DM-SKA, and perception that family or community members would be willing to complete the DM-SKA. The DM-SKA has a baseline Flesch reading score of 81.3, indicating low complexity language. ConclusionDM clinicians agreed that the DM-SKA assesses all essential DM management skills. For patients/caregivers, it has acceptable literacy, cognitive validity, and culturally acceptable for racial/ethnic minority populations in the study, including elderly persons.

Effects of different types of intraocular lens implantation on patient's visual quality and function after phacoemulsification

Objective: To explore the effects of different types of intraocular lens (IOL) implantation on patient's visual quality and function after phacoemulsification. Methods: The clinical data of patients with monocular cataract who underwent phacoemulsification in the Department of Ophthalmology, People's Hospital Affiliated to Shandong First Medical University between December 2021 and May 2023 were retrospectively analyzed. According to the types of IOL, the patients were divided into monofocal group, bifocal group and depth of focus extension group. Three months later, uncorrected distance visual acuity (UCDVA), best corrected distance visual acuity (BCDVA), uncorrected intermediate visual acuity (UCIVA), best corrected intermediate visual acuity (BCIVA), uncorrected near visual acuity (UCNVA) and best corrected near visual acuity (BCNVA) were detected. Contrast sensitivity and total wavefront aberration were measured by visual function analyzer. Satisfaction with visual quality was evaluated by hospital-made satisfaction questionnaire. Results: A total of 92 patients were included, with 31 males and 61 females, and their age was (61.8±5.2) years. There were 43, 28 and 21 cases in monofocal group, bifocal group and depth of focus extension group, respectively. No statistically significant difference was found in clinical baseline data among the three groups. UCIVA, UCDVA, BCIVA and BCDVA in depth of focus extension group were 1.01±0.13, 0.92±0.18, 1.21±0.19 and 1.20±0.23, respectively, which were higher than those in monofocal group (0.62±0.12, 0.74±0.13, 1.02±0.17, 1.07±0.19, respectively) and bifocal group (0.67±0.15, 0.78±0.14, 1.01±0.16, 1.01±0.18, respectively), while absolute value of spherical equivalent [(-0.42±0.07) D] was lower than that in the other two groups [ (-0.49±0.05) D and (-0.45±0.08) D] (both P<0.05). UCNVA and BCNVA in bifocal group were 0.91±0.18 and 1.25±0.18, which were higher than those in depth of focus extension group (0.63±0.24 and 1.19±0.17) (both P<0.05). There were no significant differences in contrast sensitivity among the three groups under day vision or between monofocal group and bifocal group under night vision (all P>0.05), but the contrast sensitivity was higher in depth of focus extension group under night vision (3.0, 6.0, 12.0 c/d) than other two groups (all P<0.05). The score of ocular discomfort was the highest in bifocal group, followed by depth of focus extension group and monofocal group (both P<0.05). The score of visual interference in bifocal group was lower than that in monofocal group and depth of focus extension group (both P<0.05). The scores of subjective feeling in bifocal group and depth of focus extension group were higher than that in monofocal group (both P<0.05). The reading score was the highest in bifocal group, followed by depth of focus extension group and monofocal group (both P<0.05). There was no significant difference in total low-order aberration among the three groups (P=0.472). The total aberration and higher-order aberration [(0.74±0.35) μm and (0.41±0.12) μm] were the highest in monofocal group, followed by bifocal group [(0.61±0.21) μm and (0.22±0.09) μm] and depth of focus extension group [(0.46±0.13) μm and (0.06±0.09) μm] (all P<0.05). Conclusions: IOL implantation with depth of focus extension can enhance visual range, night vision and contrast sensitivity, and thus effectively improve postoperative visual quality and function in cataract patients. The bifocal IOL can better improve the patient's UCNVA and BCNVA, resulting in high satisfaction with visual quality.

Which Type of Vocabulary-Knowledge Better Correlates with Reading-Comprehension, Meaning-Recognition or Meaning-Recall?

This study investigated the relationships between two types of vocabulary tests and second language reading-comprehension (RC) in a classroom assessment setting. A group of 40 learners completed a written-receptive meaning-recall measure of the Updated Vocabulary Levels Test (UVLT) and the written-receptive meaning-recognition UVLT. Correlation analysis was conducted to examine the relationships between scores from the two tests and The TEST of English for International Communication Reading scores. The results showed that the relationship between the meaning-recall and RC ( r =0 .85, p &lt;0 .001) was higher than between the meaning-recognition and RC ( r =0 .78, p &lt;0 .001) with a significant difference (Steiger's z = 3.06, p =0 .002). This suggests that meaning-recall knowledge is a better predictor of RC.

Evaluation of the Quality and Readability of Online Information about Alzheimer’s Disease in China

Background: With the increasing popularity of the internet, a growing number of patients and their companions are actively seeking health-related information online. Objective: The aim of this study was to assess the quality and readability of online information about Alzheimer’s disease (AD) in China. Methods: A total of 263 qualified AD-related web pages from different businesses, governments, and hospitals were obtained. The quality of the web pages was assessed using the DISCERN tool, and the readability of the web pages was assessed using a readability measurement website suitable for the Chinese language. The differences in readability and quality between different types of web pages were investigated, and the correlation between quality and readability was analyzed. Results: The mean overall DISCERN score was 40.93±7.5. The government group scored significantly higher than the commercial and hospital groups. The mean readability score was 12.74±1.27, and the commercial group had the lowest readability score. There was a positive correlation between DISCERN scores and readability scores. Conclusions: This study presents an evaluation of the quality and readability of health information pertaining to AD in China. The findings indicate that there is a need to enhance the quality and readability of web pages about AD in China. Recommendations for improvement are proposed in light of these findings.

The impact of multidirectional text typography on text readability in word clouds

Word clouds are an essential tool for text visualization, and the readability of word clouds significantly affects the reading comprehension of users. Consequently, this study investigates the influence of text typography direction and font size in word clouds on their readability. Besides, The study assesses how text typography affects the readability of information presented in word clouds through a combination of objective reading performance metrics and subjective evaluations. Objective reading performance is measured through a word search task, whereas subjective evaluations include three metrics: readability, fatigue, as well as aesthetic appeal, assessed employing a 9-level Likert scale questionnaire. Participating in all three experiments were 120 individuals and the independent variables were the direction and number of text typography directions and font size. The study determined that word clouds with horizontal typography exhibit remarkably higher reading search accuracy, readability scores, and fatigue scores in comparison to word clouds with vertical and diagonal typography. Furthermore, more text directions included in word clouds result in a significant decrease in reading search accuracy, reading ease scores, and fatigue scores. Additionally, the font size notably influences the legibility of text displayed in word clouds, and yet there is no substantial interaction effect between font size and direction on the readability of word clouds. Accordingly, the study draws the following conclusions. In the first place, the readability of word clouds with horizontal typography text is considerably higher than that of word clouds with vertical and diagonal typography text. Second, an increase in text typography directions results in a substantial decrease in readability. Third, font size seriously influences the readability of text, with larger font sizes contributing to higher readability on the word cloud. Fourth, the text typography direction and the number of text typography directions included lacking a substantial influence on the aesthetic appeal of word clouds. This research can be adopted to optimize the layout design of word clouds. Besides, the findings of this study have wide applications in multi-directional text typography scenarios, including graphic design, human–computer interaction, and information visualization.

An Analysis of the Readability of Online Sarcoidosis Resources.

Introduction Sarcoidosis is an inflammatory disease characterized by the formation of noncaseating granulomas in multiple organ systems. The presentation can vary widely; although some patients with sarcoidosis can be asymptomatic, sarcoidosis can also present in others with symptomatic multiorgan system involvement. Considering the potential severity of the disease, patients need to be well-informed about sarcoidosis to better manage their health. This study aims to assess the readability levels of online resources about sarcoidosis. Methods We conducted a retrospective cross-sectional study. The term "sarcoidosis" was searched online using both Google and Bing to find websites written in English. Each website was categorized by type: academic, commercial, government, nonprofit, and physician. The readability scores for each website were calculated using six different readability tests: the Flesch-Kincaid reading ease (FKRE), Flesch-Kincaid grade level (FKGL), Gunning fog score (GFS), Simple Measure of Gobbledygook (SMOG), automated readability index (ARI), and Coleman-Liau index (CLI). FKRE gives a score that corresponds to the difficulty of the text, while the remaining tests give a score that corresponds to a grade level in terms of reading ability. A one-sample t-test was used to compare all test scores with the national recommended standard of a sixth-grade reading level. Our null hypothesis was that the readability scores of the websites searched would not differ statistically significantly from the sixth-grade reading level and that there would be no significant differences across website categories. To evaluate the difference between the categories of websites, ANOVA testing was used. Results Thirty-four websites were analyzed. Each of the six readability tests for the websites had an average score, which corresponded to being significantly harder to read than the nationally recommended sixth-grade reading level (p<0.001). None of the mean readability scores showed a statistically significant difference across the five different website categories. Conclusions This is the first study, to our knowledge, to examine the readability of online English resources on sarcoidosis and calculate standardized readability scores for them. It implies that the online English material for sarcoidosis is above the health literacy recommended reading levels for patients. There is a need to simplify the material to be easier to read for patients.

Biomedical text readability after hypernym substitution with fine-tuned large language models.

The advent of patient access to complex medical information online has highlighted the need for simplification of biomedical text to improve patient understanding and engagement in taking ownership of their health. However, comprehension of biomedical text remains a difficult task due to the need for domain-specific expertise. We aimed to study the simplification of biomedical text via large language models (LLMs) commonly used for general natural language processing tasks involve text comprehension, summarization, generation, and prediction of new text from prompts. Specifically, we finetuned three variants of large language models to perform substitutions of complex words and word phrases in biomedical text with a related hypernym. The output of the text substitution process using LLMs was evaluated by comparing the pre- and post-substitution texts using four readability metrics and two measures of sentence complexity. A sample of 1,000 biomedical definitions in the National Library of Medicine's Unified Medical Language System (UMLS) was processed with three LLM approaches, and each showed an improvement in readability and sentence complexity after hypernym substitution. Readability scores were translated from a pre-processed collegiate reading level to a post-processed US high-school level. Comparison between the three LLMs showed that the GPT-J-6b approach had the best improvement in measures of sentence complexity. This study demonstrates the merit of hypernym substitution to improve readability of complex biomedical text for the public and highlights the use case for fine-tuning open-access large language models for biomedical natural language processing.