Reading Level Research Articles

Comparative analysis of whole exome sequencing kits for the canine genome.

As the public's interest in companion dogs grows, health issues in these animals are also emerging, necessitating the optimization of whole exome sequencing (WES) as a valuable method for disease prediction. While WES targeting the human genome is well established, WES targeting the canine genome is understudied, and there is a need to find effective analysis kits. We compared and analyzed the performance of three WES kits from Twist and Agilent using the canine genome as the target to perform genetic analysis of canine diseases effectively. The levels of total reads, the duplication rate, and variant calling in canine genomic DNA samples from seven healthy dogs (three beagles, one bichon fry, one maltese, one welsh corgi, and one mixed breed) without any interventions were examined through WES via Twist and Agilent kits. We found that while Twist had the lowest total read number, the number of reads in the SSXT series was significantly (P<0.05) greater. Twist showed low evenness and high standard deviation, but the SSXT series showed relatively high evenness. Compared with Twist, the SSXT series from a depth of 30× presented a significantly (P<0.05) greater target ratio. Among the four kits, the significantly lowest duplicate ratio was confirmed for SSXT (O/N) (30% lower than Twist). The most important performance of the kit, the number of variants detected, was 48,302 for Twist and 130,506 for SSXT (O/N). On the basis of the performance comparison results, SSXT (O/N) was found to have the best performance.

Readability Metrics in Patient Education: Where Do We Innovate?

The increasing use of digital applications in healthcare has led to a greater need for patient education materials. These materials, often in the form of pamphlets, booklets, and handouts, are designed to supplement physician–patient communication and aim to improve patient outcomes. However, the effectiveness of these materials can be hindered by variations in patient health literacy. Readability, a measure of text comprehension, is a key factor influencing how well patients understand these educational materials. While there has been growing interest in readability assessment in medicine, many studies have demonstrated that digital texts do not frequently meet the recommended sixth-to-eighth grade reading level. The purpose of this opinion article is to review readability from the perspective of studies in pediatric medicine, internal medicine, preventative medicine, and surgery. This article aims to communicate that while readability is important, it tends to not fully capture the complexity of health literacy or effective patient communication. Moreover, a promising avenue to improve readability may be in generative artificial intelligence, as there are currently limited tools with similar effectiveness.

Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study.

Recent surveys indicate that 48% of consumers actively use generative artificial intelligence (AI) for health-related inquiries. Despite widespread adoption and the potential to improve health care access, scant research examines the performance of AI chatbot responses regarding emergency care advice. We assessed the quality of AI chatbot responses to common emergency care questions. We sought to determine qualitative differences in responses from 4 free-access AI chatbots, for 10 different serious and benign emergency conditions. We created 10 emergency care questions that we fed into the free-access versions of ChatGPT 3.5 (OpenAI), Google Bard, Bing AI Chat (Microsoft), and Claude AI (Anthropic) on November 26, 2023. Each response was graded by 5 board-certified emergency medicine (EM) faculty for 8 domains of percentage accuracy, presence of dangerous information, factual accuracy, clarity, completeness, understandability, source reliability, and source relevancy. We determined the correct, complete response to the 10 questions from reputable and scholarly emergency medical references. These were compiled by an EM resident physician. For the readability of the chatbot responses, we used the Flesch-Kincaid Grade Level of each response from readability statistics embedded in Microsoft Word. Differences between chatbots were determined by the chi-square test. Each of the 4 chatbots' responses to the 10 clinical questions were scored across 8 domains by 5 EM faculty, for 400 assessments for each chatbot. Together, the 4 chatbots had the best performance in clarity and understandability (both 85%), intermediate performance in accuracy and completeness (both 50%), and poor performance (10%) for source relevance and reliability (mostly unreported). Chatbots contained dangerous information in 5% to 35% of responses, with no statistical difference between chatbots on this metric (P=.24). ChatGPT, Google Bard, and Claud AI had similar performances across 6 out of 8 domains. Only Bing AI performed better with more identified or relevant sources (40%; the others had 0%-10%). Flesch-Kincaid Reading level was 7.7-8.9 grade for all chatbots, except ChatGPT at 10.8, which were all too advanced for average emergency patients. Responses included both dangerous (eg, starting cardiopulmonary resuscitation with no pulse check) and generally inappropriate advice (eg, loosening the collar to improve breathing without evidence of airway compromise). AI chatbots, though ubiquitous, have significant deficiencies in EM patient advice, despite relatively consistent performance. Information for when to seek urgent or emergent care is frequently incomplete and inaccurate, and patients may be unaware of misinformation. Sources are not generally provided. Patients who use AI to guide health care decisions assume potential risks. AI chatbots for health should be subject to further research, refinement, and regulation. We strongly recommend proper medical consultation to prevent potential adverse outcomes.

Assessing the Readability of Online English and Spanish Resources for Polydactyly and Syndactyly.

Online patient education materials (PEMs) that are difficult to read disproportionately affect patients with low health literacy and educational attainment. Patients may not be fully informed or empowered to engage meaningfully with providers and advocate for their goals. We aim to assess the readability of online PEMs regarding polydactyly and syndactyly. Google was used to query "polydactyly" and "syndactyly" in English and Spanish. The first 50 results were categorized into institutional (government, medical school, teaching hospital), noninstitutional (private practice, blog), and academic (journal articles, book chapters). Readability scores were generated using the Simple Measure of Gobbledygook and Spanish Simple Measure of Gobbledygook scales. All polydactyly PEMs and >95% of syndactyly PEMs exceeded the National Institutes of Health recommended 6th-grade reading level. Altogether, English PEMs had an average reading level of a university freshman and Spanish PEMs had an average reading level of nearly a high school sophomore. For both diagnoses, English PEMs were harder to read than Spanish PEMs overall and when compared across the 3 categories between the 2 languages. Generally, noninstitutional PEMs were more difficult to read than their institutional counterparts. To improve patient education, health literacy, and language equity, online resources for polydactyly and syndactyly should be written at the 6th-grade level. Currently, these PEMs are too advanced, which can make accessing, understanding, and pursuing healthcare decisions more challenging. Understanding health conditions and information is crucial to empower patients, regardless of literacy.

Text readability: its impact on reading comprehension and reading time

Recently, the readability of texts has become the focus of reading research because it is believed to have implications for reading comprehension, which is of utmost importance in the field of English as a foreign language (EFL), particularly in the teaching, learning and assessment of reading comprehension. Unfortunately, the influence of text readability on reading comprehension (and reading time) has not been well studied in the EFL context. Most text readability studies are conducted in medical contexts, but these studies are often limited in predicting readability scores for sample texts. To address this gap, the current study aimed to evaluate the influence of text readability levels (based on the Flesch-Kincaid grade level (FKGL)) on students’ reading comprehension and reading time. Data were collected through reading test and analyzed using SPSS version 22. The Friedman test revealed that the distribution of students' reading comprehension score (X2=197.532, p=0.000) and reading time (X2=215.323, p=0.000) are different in each text, suggesting that the readability of texts has a significant influence on both. This study contributed to the practices of reading instruction and assessment. Limitations and suggestions for further research are briefly discussed.

Limited Availability and Readability of Spanish Language Patient Educational Material: A Review of the Nation's Top Children's Hospitals.

Cleft lip with or without cleft palate (CL/P) is a common congenital facial pathology that occurs at higher incidences in Hispanic communities. The authors analyzed the availability and readability of Spanish-written patient education materials (PEMs) on CL/P from top-ranking U.S. children's hospitals to determine the presence of health literacy barriers. Availability of PEM was evaluated by 2 methods: (1) Google search and (2) evaluation of the official hospital websites. For each institution, a Google search was conducted using the phrase, "labio leporino y/o paladar hendido (translation: CL/P) + (hospital name)." In addition, each hospital website was assessed for Spanish PEM availability. Spanish PEMs were then categorized by whether they had been generated by an automated translation function or if they were independently written Spanish text. English PEM readability was assessed using the Simple Measure of Gobbledygook (SMOG). Spanish PEM readability was assessed using spanish orthgraphic length (Spanish Orthographic Length), the SMOG converted for the Spanish language. Unpaired 2-tailed t tests were used to compare readability. Of a total of 85 pediatric hospitals, 28 (37.3%) had Spanish PEM. Five (6.7%) hospitals created their own Spanish-language document. The average spanish orthgraphic length reading level was 9.49 compared with an average SMOG of 11.38 (P < 0.001). Institutions that did not provide Spanish PEM in any format had a significantly higher SMOG for English PEM of 12.13 compared with 11.38 of those that had SMOG with English PEM (P = 0.04). Health literacy barriers not only exist for Spanish PEM but also for English PEM, indicating an opportunity to improve communication.

Enhancing patient understanding in obstetrics: The role of generative AI in simplifying informed consent for labor induction with oxytocin.

Informed consent is a cornerstone of ethical medical practice, particularly in obstetrics where procedures like labor induction carry significant risks and require clear patient understanding. Despite legal mandates for patient materials to be accessible, many consent forms remain too complex, resulting in patient confusion and dissatisfaction. This study explores the use of Generative Artificial Intelligence (GAI) to simplify informed consent for labor induction with oxytocin, ensuring content is both medically accurate and comprehensible at an 8th-grade readability level. GAI-generated consent forms streamline the process, automatically tailoring content to meet readability standards while retaining essential details such as the procedure's nature, risks, benefits, and alternatives. Through iterative prompts and expert refinement, the AI produces clear, patient-friendly language that bridges the gap between medical jargon and patient comprehension. Flesch Reading Ease scores show improved readability, meeting recommended levels for health literacy. GAI has the potential to revolutionize healthcare communication by enhancing patient understanding, promoting shared decision-making, and improving satisfaction with the consent process. However, human oversight remains critical to ensure that AI-generated content adheres to legal and ethical standards. This case study demonstrates that GAI can be an effective tool in creating accessible, standardized, yet personalized consent documents, contributing to better-informed patients and potentially reducing malpractice claims.

A Performance Evaluation of Large Language Models in Keratoconus: A Comparative Study of ChatGPT-3.5, ChatGPT-4.0, Gemini, Copilot, Chatsonic, and Perplexity

Background: This study evaluates the ability of six popular chatbots; ChatGPT-3.5, ChatGPT-4.0, Gemini, Copilot, Chatsonic, and Perplexity, to provide reliable answers to questions concerning keratoconus. Methods: Chatbots responses were assessed using mDISCERN (range: 15–75) and Global Quality Score (GQS) (range: 1–5) metrics. Readability was evaluated using nine validated readability assessments. We also addressed the quality and accountability of websites from which the questions originated. Results: We analyzed 20 websites, 65% “Private practice or independent user” and 35% “Official patient education materials”. The mean JAMA benchmark score was 1.40 ± 0.91 (0–4 points), indicating low accountability. Reliability, measured using mDISCERN, ranged from 42.91 ± 3.15 (ChatGPT-3.5) to 46.95 ± 3.53 (Copilot). The most frequent question was “What is keratoconus?” with 70% of websites providing relevant information. This received the highest mDISCERN score (49.30 ± 4.91) and a relatively high GQS score (3.40 ± 0.56) with an Automated Readability Level Calculator score of 13.17 ± 2.13. Moderate positive correlations were determined between the website numbers and both mDISCERN (r = 0.265, p = 0.25) and GQS (r = 0.453, p = 0.05) scores. The quality of information, assessed using the GQS, ranged from 3.02 ± 0.55 (ChatGPT-3.5) to 3.31 ± 0.64 (Gemini) (p = 0.34). The differences between the texts were statistically significant. Gemini emerged as the easiest to read, while ChatGPT-3.5 and Perplexity were the most difficult. Based on mDISCERN scores, Gemini and Copilot exhibited the highest percentage of responses in the “good” range (51–62 points). For the GQS, the Gemini model exhibited the highest percentage of responses in the “good” quality range with 40% of its responses scoring 4–5. Conclusions: While all chatbots performed well, Gemini and Copilot showed better reliability and quality. However, their readability often exceeded recommended levels. Continuous improvements are essential to match information with patients’ health literacy for effective use in ophthalmology.

Utilizing Artificial Intelligence to Increase the Readability of Patient Education Materials in Pediatric Otolaryngology.

Objectives: To identify the reading levels of existing patient education materials in pediatric otolaryngology and to utilize natural language processing artificial intelligence (AI) to reduce the reading level of patient education materials. Methods: Patient education materials for pediatric conditions were identified from the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) website. Patient education materials about the same conditions, if available, were identified and selected from the websites of 7 children's hospitals. The readability of the patient materials was scored before and after using AI with the Flesch-Kincaid calculator. ChatGPT version 3.5 was used to convert the materials to a fifth-grade reading level. Results: On average, AAO-HNS pediatric education material was written at a 10.71 ± 0.71 grade level. After requesting the reduction of those materials to a fifth-grade reading level, ChatGPT converted the same materials to an average grade level of 7.9 ± 1.18 (P < .01). When comparing the published materials from AAO-HNS and the 7 institutions, the average grade level was 9.32 ± 1.82, and ChatGPT was able to reduce the average level to 7.68 ± 1.12 (P = .0598). Of the 7 children's hospitals, only 1 institution had an average grade level below the recommended sixth-grade level. Conclusions: Patient education materials in pediatric otolaryngology were consistently above recommended reading levels. In its current state, AI can reduce the reading levels of education materials. However, it did not possess the capability to reduce all materials to be below the recommended reading level.

Lived experiences of senior high school learners with reading difficulties: A case in the Philippines

This phenomenological study delves into the lived experiences of learners struggling with frustration levels in reading. Recognizing the significance of aiding such individuals, and comprehending the multifaceted impacts of their difficulties on emotional, social, cultural. and academic domains becomes imperative, thereby necessitating a tailored reading intervention program. Employing a mixed-methods approach integrating qualitative and quantitative methodologies, data were collected through questionnaires and guided interviews, and then analyzed through a comprehensive six-phase method. The study encompassed 15 learner- participants and 10 teacher-participants. Results highlighted the diverse challenges encountered by these learners in reading-related tasks, with consequential results across aspects. Furthermore, the findings emphasized the adoption of coping mechanisms by learners and highlighted the indispensable support systems from parents, peers, teachers, and the educational institution. In conclusion, the implementation of a reading intervention program emerged as pivotal in empowering learners with a frustration level of reading and fostering their holistic development.

Use of chatgpt-4 to explain kawasaki disease to parents and paediatric trainees

Abstract Background Paediatric trainees and parents of Kawasaki disease (KD) patients may face challenges when managing the disease due to insufficient accessibility to KD information. Chat Generative Pre-Trained Transformer (ChatGPT) based on large language models may help explain KD information to paediatric trainees and patient parents. Purpose This study aims to determine the usefulness of Chat Generative Pre- Trained Transformer -4 (ChatGPT-4) in explaining Kawasaki Disease (KD) and its management to parents and paediatric trainees managing KD patients. Methods We created 2 sets of clinical scenarios. In the first set, ChatGPT-4 was instructed to respond to 10 questions based on enquiries from parents of KD patients. Responses were scored in terms of "factual accuracy", "coherence", "comprehensiveness", and "humaneness" by 3 paediatric cardiologists using Likert scale of 0-10. Readability were calculated using Flesch reading-ease test. In the second set, ChatGPT-4 was instructed to respond to 8 KD-related questions based on enquiries from paediatric trainees. Responses are graded based on "relevance", "reliability" and "comprehensiveness" using Likert scale of 0-10 by 3 paediatric cardiologists independently. Reviewers would determine whether major advice from chatGPT-4 would be adopted in clinical judgement. Results For parent-targeted responses, ChatGPT-4 achieved the highest scores in ‘humaneness’ (median 9.00, IQR 8.00 to 9.00) and ‘coherence’ (median 8.00, IQR 7.00 to 8.00). Inaccurate information regarding disease prognosis, actions as well as prescription of medications and surgery is found in 80% of scenarios. Missing information regarding long-term coronary complications, antiplatelet management and cardiac assessments is found in all 10 scenarios. Mean readability of parent-targeted responses is 71.70 ± 6.26, a readability level easily understood by 12-year-olds. For paediatrician-targeted responses, ChatGPT-4 achieved the highest scores in ‘relevance’ (median 9.50, IQR 7.25 to 9.0). Inaccurate information regarding coronary interventions, patient education and immunization recommendations is spotted in 37.5% of the scenarios. Missing information regarding patient education and stress imaging is found in 25% of the scenarios. All reviewers would adopt ChatGPT-4’s advice in 87.5% of the scenarios. Conclusions ChatGPT-4 has significant limitations in accuracy and lacks salient information when providing KD recommendations for parents and paediatric trainees.Performance in parent-targeted questionsPerformance in trainee-targeted question

Validity and reliability of a physical literacy knowledge, attitudes, self-efficacy and behaviors questionnaire for early childhood educators (PLKASB-ECE): An exploratory factor analysis.

Nurturing physical literacy in young children offers a unique opportunity to address global physical inactivity trend. Early childhood education and care (ECEC) environments, with their extensive reach into this age group, and early childhood educators, through their daily interactions with children, are strategically positioned to influence children's physical literacy development. However, enhancing educators' ability to foster physical literacy requires valid and reliable assessment tools to measure holistic physical literacy constructs (i.e., cognitive, affective, behavioral) to assess the impact of physical literacy educational interventions. The purpose of this study was to develop a holistic digital tool to measure physical literacy knowledge, attitudes, self-efficacy, and behaviors of early childhood educators (PLKASB-ECE) for both their professional teaching context as well as the educator's own personal physical literacy behaviours. This study was conducted in two phases. Phase 1 involved item generation and content validation. Phase 2 employed a cross-sectional validation study design to assess the psychometric properties of the PLKASB-ECE tool. Based on a literature review an initial 19-item instrument was developed that subsequently underwent three rounds of expert content validation. Six additional items were added, resulting in a final 25-item self-report measure with a readability score equivalent to an 8th grade reading level (Flesch-Kincaid Grade Level: 8.7). This included 1 global rating item, 2 qualitative response items, 7 knowledge items, and 15 items addressing physical literacy attitudes, self-efficacy and behaviors using a 7-point Likert response scale. The PLKASB-ECE tool was administered to 470 educators in Alberta, Canada between 2019 to 2022. The 15 items were subjected to exploratory factor analysis and resulted in a five-factor scale with one item not loading. The five-factor scale held with the final 14 items with loadings ranging from 0.481 to 0.886, Cronbach's alpha ranging from 0.70 to 0.82, with ordinal omega ranging from 0.72 to 0.82. Usability, as assessed by completion time, was 8.15 minutes. These findings demonstrate good indices of reliability and validity for the PLKASB-ECE tool. This tool will be valuable as a research outcome measure for assessing educational interventions aimed at enhancing educators' understanding, confidence, and strategies for fostering holistic concepts of physical literacy in young children within ECECs.

Readability of Patient-Reported Outcome Measures Used in Voice Disorders

ObjectivesThis study aims to evaluate Turkish patient-reported outcome measures (PROM) used in voice disorders using different readability formulas and to examine the relationship between text-based features and readability values. Study DesignA search was conducted to identify published Turkish PRO questionnaires related to dysphonia that are completed by patients. MethodsSearch was conducted to identify published PROM related to dysphonia that are completed by patients in a self-administered format. Reading grade levels were analyzed for voice-related PROM using the Ateşman readability and the Bezirci-Yılmaz new readability formulas as computed by a readability calculations software package. Text-based quantitative features are obtained. Descriptive statistics were also computed across the questionnaires. ResultsA total of 14 PROMs were found. In the analysis, the mean of the Ateşman readability values of the PROM was calculated as 70.66 (±5.55). This value is defined as 'easy', according to the Ateşman readability measures. The average Bezirci-Yılmaz new readability value is 6,03 (±1,07). This value corresponds to the 6th grade reading level in the Turkish education system. ConclusionsResults show that more than half of the PROMs in the Turkish language have the recommended reading level. PROMs allow healthcare professionals to objectively understand the patient's symptoms, both qualitatively and quantitatively. Therefore, it is critical that patients accurately understand and respond to these outcome measures. This is why developers should consider reading as a testable structure. Speech and language therapists should consider the reading level required to understand a specific PROMs in order to obtain the most useful information for treatment planning and outcome assessments.

Cognitive status and demographics modify the association between subjective cognition and amyloid.

This study examined the effect of cognitive status, education, and sex on the association between subjective cognitive decline (SCD) and Alzheimer's disease (AD) biomarkers in non-demented older adults. Vanderbilt Memory and Aging Project participants (n = 129), dementia or stroke free, completed fasting lumbar puncture, SCD assessment, and cognitive assessment. Cerebrospinal fluid (CSF) biomarkers for AD were analyzed. Linear regression models related SCD to CSF AD biomarkers and follow-up models assessed interactions of SCD × cognitive status, sex, reading level, and education on AD biomarkers. In main effect models, higher SCD was associated with more amyloidosis (p-values <0.004). SCD was not associated with tau, p-tau, or neurofilament light (NFL) levels (p-values >0.38). SCD score interacted with cognitive status (p < 0.02), sex (p = 0.03), and education (p-values <0.005) on amyloidosis. In stratified models, higher SCD was associated with more amyloid in cognitively unimpaired (p-values <0.003), men (p = 0.0003), and higher education. No SCD score × reading-level interaction was found (p-values >0.51) though SCD related to amyloid markers in the higher reading-level group (p-values <0.004). Higher SCD was associated with greater cerebral amyloid accumulation, one of the earliest pathological AD changes. SCD appears most useful in detecting early AD-related brain changes prior to objective cognitive impairment, in men, and those with higher quantity and quality of education and highlight the importance of considering these factors.

The Content and Form of School Reading as a Factor Influencing Text Comprehension in Society 4.0

The content and form of School reading lists significantly impact pupils' understanding of various types of texts, including artistic, non-artistic, and electronic. To this end, a research study explores whether recommended School reading lists at secondary technical schools in the Moravian-Silesian and Zlín regions of the Czech Republic are available electronically on school websites. Additionally, the study aims to determine whether they include everyday life texts that reflect the current characteristics of Society 4.0, influenced by digitisation, automation, and electronicisation. The study examined factors influencing readers' comprehension of printed and electronic digital texts through a questionnaire-based survey of 439 pupils from four Czech secondary technical schools and two vocational schools. It also explored how the content and form of secondary school reading impact the comprehension of various types of traditional and non-traditional texts. The research findings indicated that Czech secondary school students tend to engage with texts from everyday life on social networks and electronic texts in their free time. However, they frequently struggle to understand journalistic texts such as reviews and do not frequently engage with everyday life texts in their schoolwork. These results provide valuable insights into the concept of traditional and non-traditional readers, along with current typologies of texting. Moreover, they highlight factors influencing functional literacy and reading comprehension, viewed through the lens of secondary school students in Society 4.0. It is worth noting that international research by PISA (2018, 2021) has drawn attention to the average to below-average reading and digital literacy levels among Czechs, particularly 15-year-old boys.

Utilization of Artificial Intelligence to Improve Equitable Healthcare Access for Breast Implant Patients

Abstract The recently mandated US Food and Drug Administration (FDA) patient decision checklists were developed with the goal of improving the informed decision-making process for patients considering breast implants. Yet, prior research has demonstrated that these checklists are written at reading levels far in excess of that recommended by the National Institutes of Health and the American Medical Association. Patients considering breast implants are required to sign these forms prior to surgery, even if they have little to no comprehension of their contents. This study aims to improve the accessibility, and therefore the utility, of the mandated FDA patient literature using the assistance of artificial intelligence (AI). Patient decision checklists were obtained from the three most utilized breast implant manufacturers in the United States– Allergan, Mentor, and Sientra. AI was then asked to synthesize a novel patient decision checklist, written at the 6th grade reading level, using these checklists as source material. The AI-assisted checklist was edited by plastic surgeons for both formatting and content. Readability analysis of all documents was performed using the Flesch Reading-Ease Score, Flesch-Kincaid Grade Level, Gunning-Fog Index, Coleman-Liau Index, Simplified Measure of Gobbledygook, and Automated Readability Index. Textual analysis included sentence count, word count, number and percentage of complex words, average number of words per sentence, and average number of syllables per word. The overall readability of Allergan, Mentor, and Sientra patient checklists correlated with the college reading level. These documents were of a statistically significantly higher reading level the AI-assisted checklist, which was written at the recommended 6th grade level. Text composition analysis similarly demonstrated substantial differences between the AI-assisted and FDA mandated literature. The currently mandated breast implant patient checklists are written at a college reading level and are inaccessible to the average patient. We propose a new patient decision checklist, generated with the assistance of artificial intelligence, in order to improve healthcare access within plastic surgery. This simplified material can be used as an adjunct to the current checklists in order to improve shared decision making.

Comparing ChatGPT vs. Surgeon-Generated Informed Consent Documentation for Plastic Surgery Procedures

Abstract Background Informed consent is a crucial requirement of a patient’s surgical care but can be a burdensome task. Artificial intelligence (AI) and machine learning language models may provide an alternative approach to writing detailed, readable consent forms in an efficient manner. No studies have assessed the accuracy and completeness of AI-generated consents for aesthetic plastic surgeries. Objectives This study aims to compare the length, reading level, accuracy, and completeness of informed consent forms that are AI chatbot (ChatGPT-4, OpenAI, San Francisco, CA)-generated versus plastic surgeon-generated for the most commonly performed aesthetic plastic surgeries. Methods This study is a cross-sectional design comparing informed consent forms created by the American Association of Plastic Surgeons (ASPS) with informed consent forms generated by ChatGPT-4 for the five most commonly performed plastic surgery procedures: liposuction, breast augmentation, abdominoplasty, breast lift, and blepharoplasty. Results The average word count of ChatGPT forms was lower than for the ASPS generated forms (1023 vs 2901, p=0.01). Average reading level for ChatGPT forms was also lower than ASPS forms (11.2 vs 12.5, p=0.02). There was no difference between accuracy and completeness scores for general descriptions of the surgery, risks, benefits, or alternatives. The mean overall impression score for ChatGPT consents was 2.33, whereas it was 2.23 for ASPS consent forms (p=0.18). Conclusions Our study demonstrates that informed consent forms generated by ChatGPT were significantly shorter and more readable than ASPS forms with no significant difference in completeness and accuracy.

Standard HIPAA Authorization Forms Decreased Response Rates for a Multi-site Pragmatic Trial.

The Health Insurance Portability and Accountability Act (HIPAA) aims to safeguard patient information; however, complex legal language may lead to confusion and mistrust, and hinder enrollment in clinical trials. To evaluate the effect of a standard HIPAA authorization included in mailed survey packets on study enrollment for a multi-site pragmatic trial. This study is nested within an advance care planning pragmatic trial at 50 primary care clinics across three University of California (UC) Health Systems. We included English and Spanish-speaking seriously ill patients. One third of eligible patients received and 2/3 did not receive the HIPAA authorization in their enrollment packet. We compared enrollment rates at 3months and assessed the readability, understandability, and actionability of the standard HIPAA form using the Federal Plain Language Guidelines Checklist for Plain Language, the Automatic Readability Checker consensus calculator (grade 8 is the average reading level for US adults), and the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P, 0-100%, 70% considered the minimum). Of 4632 eligible patients (mean age 71, 48% women, 11% Spanish-speaking, 40% racial/ethnic minority); 1543 received a mailed enrollment packet with a HIPAA form and 3089 did not. Patients mailed the HIPAA form were less likely to enroll (10.2% vs. 14.8%, p < 0.001). The standard HIPAA form scored at the 12th grade reading level, had a PEMAT-P Understandability score of 42%, had an Actionability score of 40%, and only met 50% of Federal Plain Language Guideline Checklist items. The inclusion of a standard HIPAA authorization in mailed enrollment packets for a large pragmatic trial led to lower rates of study enrollment. This study informs how HIPAA authorization forms should be redesigned to be more accessible to patients to prevent unnecessary barriers to research enrollment.

Application of large language models to intelligently analyze long construction contract texts

The emergence of large language models (LLMs) has provided an opportunity to assist humans in quickly reading, searching, and understanding the contents of construction contracts. However, the limited context length of LLMs restricts their ability to process lengthy contract documents, which hinders their application in the construction industry. This study proposes intelligent analysis methods for long construction contracts, which enables LLMs to handle contracts that exceed their context length through a two-stage text segmentation. We further utilized the segmented text chunks for content compression and intelligent question-answering applications. The FIDIC contract was used for testing. A condensed version of lengthy contracts summarizes the provisions in a shorter format. It maintains a high level of correctness and readability, offering practitioners additional options to read contracts of varying lengths based on their needs. The satisfaction rate of the question-answering outcomes reached 93.3%, allowing practitioners to quickly obtain specific clauses of interest and relevant contract knowledge through personalized queries. The performance of the 8K model using our methods is comparable to that of the 128K long-text models, while reducing computational power. This study expands the potential for applications of LLMs in contract management within the construction industry.

Development and Validation of an Artificial Intelligence-Assisted Patient Education Material for Ostomy Patients: A Methodological Study.

To develop and test the validity of an artificial intelligence-assisted patient education material for ostomy patients. A methodological study. The study was carried out in two main stages and five steps: (1) determining the information needs of ostomy patients, (2) creating educational content, (3) converting the educational content into patient education material, (4) validation of patient education material based on expert review and (5) measuring the readability of the patient education material. We used ChatGPT 4.0 to determine the information needs and create patient education material content, and Publuu Online Flipbook Maker was used to convert the educational content into patient education material. Understandability and applicability scores were assessed using the Patient Education Materials Assessment Tool submitted to 10 expert reviews. The tool inter-rater reliability was determined via the intraclass correlation coefficient. Readability was analysed using the Flesch-Kincaid Grade Level, Gunning Fog Index and Simple Measure of Gobbledygook formula. The mean Patient Education Materials Assessment Tool understandability score of the patient education material was 81.91%, and the mean Patient Education Materials Assessment Tool actionability score was 85.33%. The scores for the readability indicators were calculated to be Flesch-Kincaid Grade Level: 8.53, Gunning Fog: 10.9 and Simple Measure of Gobbledygook: 7.99. The AI-assisted patient education material for ostomy patients provided accurate information with understandable and actionable responses to patients, but is at a high reading level for patients. Artificial intelligence-assisted patient education materials can significantly increase patient information rates in the health system regarding ease of practice. Artificial intelligence is currently not an option for creating patient education material, and their impact on the patient is not fully known. The study followed the STROBE checklist guidelines. No patient or public contributions.