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Evaluating the Readability of Pediatric Neurocutaneous Syndromes–Related Patient Education Material Created by a Custom GPT With Retrieval Augmentation

Evaluating the Readability of Pediatric Neurocutaneous Syndromes–Related Patient Education Material Created by a Custom GPT With Retrieval Augmentation

Readability was assessed by averaging the following eight readability formulas: Automated Readability Index, Flesch Reading Ease Formula, Gunning Fog Index, Flesch-Kincaid Grade Level Formula, Coleman-Liau Index, SMOG (Simple Measure of Gobbledygook) Index, Linsear Write Formula, and FORCAST Readability Formula (Multimedia Appendix 2) [8]. Two-tailed t tests and an ANOVA were used for comparison.

Nneka Ede, Robyn Okereke

JMIR Dermatol 2025;8:e59054

Improving the Readability of Institutional Heart Failure–Related Patient Education Materials Using GPT-4: Observational Study

Improving the Readability of Institutional Heart Failure–Related Patient Education Materials Using GPT-4: Observational Study

As prior data regarding accuracy have been promising, an emerging focus has been on investigating the readability of the model’s output. Prior studies have shown Chat GPT provides accurate and comprehensive responses to questions related to heart failure, and another demonstrated its responses were at a college reading level, highlighting the need for further assessment of the readability of GPT’s outputs [12,18].

Ryan C King, Jamil S Samaan, Joseph Haquang, Vishnu Bharani, Samuel Margolis, Nitin Srinivasan, Yuxin Peng, Yee Hui Yeo, Roxana Ghashghaei

JMIR Cardio 2025;9:e68817

Large Language Model–Assisted Surgical Consent Forms in Non-English Language: Content Analysis and Readability Evaluation

Large Language Model–Assisted Surgical Consent Forms in Non-English Language: Content Analysis and Readability Evaluation

The AI-generated consent forms were directly compared with the original version for readability and content quality. To assess the impact of LLM-based simplification, we conducted readability and structural comparisons between the original (before) and AI-edited consent (after) forms. Readability was quantitatively measured using KRead and Natmal—the 2 established readability indices for the Korean language [10,11].

Namkee Oh, Jongman Kim, Sunghae Park, Sunghyo An, Eunjin Lee, Hayeon Do, Jiyoung Baik, Suk Min Gwon, Jinsoo Rhu, Gyu-Seong Choi, Seonmin Park, Jai Young Cho, Hae Won Lee, Boram Lee, Eun Sung Jeong, Jeong-Moo Lee, YoungRok Choi, Jieun Kwon, Kyeong Deok Kim, Seok-Hwan Kim, Gwang-Sik Chun

J Med Internet Res 2025;27:e73222

Enhancing the Readability of Online Patient Education Materials Using Large Language Models: Cross-Sectional Study

Enhancing the Readability of Online Patient Education Materials Using Large Language Models: Cross-Sectional Study

While improvements in readability scores have been made over time [17] and human intervention can assist in improving readability [19], challenges remain in bringing readability to an appropriate level on a mass scale. Large language models (LLMs) can consume massive amounts of data and perform a wide array of tasks that have made them useful tools to understand and generate text [26], making them an enticing option to improve the readability of PEMs.

John Will, Mahin Gupta, Jonah Zaretsky, Aliesha Dowlath, Paul Testa, Jonah Feldman

J Med Internet Res 2025;27:e69955

Assessing the Quality and Reliability of ChatGPT’s Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4

Assessing the Quality and Reliability of ChatGPT’s Responses to Radiotherapy-Related Patient Queries: Comparative Study With GPT-3.5 and GPT-4

To evaluate readability, responses from both versions were assessed using a web-based Flesch Reading Ease Score (FRES) calculator. This calculator determined the responses’ readability using two different indices: the FRES and the Flesch-Kincaid Grade Level (FKGL). These readability tests use mathematical formulas that consider factors such as sentence length and word count.

Ana Grilo, Catarina Marques, Maria Corte-Real, Elisabete Carolino, Marco Caetano

JMIR Cancer 2025;11:e63677

Appropriateness of Web-Based Resources for Home Blood Pressure Measurement and Their Alignment With Guideline Recommendations, Readability, and End User Involvement: Environmental Scan of Web-Based Resources

Appropriateness of Web-Based Resources for Home Blood Pressure Measurement and Their Alignment With Guideline Recommendations, Readability, and End User Involvement: Environmental Scan of Web-Based Resources

However, previous research has shown that web-based educational resources for cardiovascular disease risk management do not provide appropriate information or meet the usability or readability needs of adults [18,25-29], and co-design involving end users (such as community members and medical professionals) is an underused method during resource development [24].

Eleanor Clapham, Dean Picone, Samuel Carmichael, Carissa Bonner, Niamh Chapman

JMIR Infodemiology 2025;5:e55248

Ability of ChatGPT to Replace Doctors in Patient Education: Cross-Sectional Comparative Analysis of Inflammatory Bowel Disease

Ability of ChatGPT to Replace Doctors in Patient Education: Cross-Sectional Comparative Analysis of Inflammatory Bowel Disease

The Chinese Readability Index Explorer (CRIE; version 3.0 [26]) was used. In addition to the evaluators’ subjective assessments, we introduced a quantitative Chinese readability tool, CRIE. It consists of 4 subsystems comprising 82 multilevel language features [27]. CRIE uses multilevel language features for text analysis, including vocabulary, syntax, semantics, and cohesion.

Zelin Yan, Jingwen Liu, Yihong Fan, Shiyuan Lu, Dingting Xu, Yun Yang, Honggang Wang, Jie Mao, Hou-Chiang Tseng, Tao-Hsing Chang, Yan Chen

J Med Internet Res 2025;27:e62857

Evaluation of the Quality of Delirium Website Content for Patient and Family Education: Cross-Sectional Study

Evaluation of the Quality of Delirium Website Content for Patient and Family Education: Cross-Sectional Study

These scores are credible tools that are widely used to evaluate readability [63]. The included websites were evaluated if they were written at the American Medical Association and National Institutes of Health recommendation of a grade 6 reading level [64,65]. A standardized data extraction template was created and piloted to ensure reviewers understood how to evaluate the quality, content, and readability of each website.

Karla Krewulak, Kathryn Strayer, Natalia Jaworska, Krista Spence, Nadine Foster, Scotty Kupsch, Khara Sauro, Kirsten M Fiest

J Med Internet Res 2025;27:e53087

Transforming Informed Consent Generation Using Large Language Models: Mixed Methods Study

Transforming Informed Consent Generation Using Large Language Models: Mixed Methods Study

However, for successful implementation, models must not only improve readability and actionability but also align with current regulatory requirements and ethical guidelines. The ability for LLMs to generate a complex clinical trial ICFs from a research protocol remains unexplored. This paper aims to evaluate the performance of the Mistral 8x22 B LLM in generating the key information sections of ICFs with improved readability, understandability, and actionability.

Qiming Shi, Katherine Luzuriaga, Jeroan J Allison, Asil Oztekin, Jamie M Faro, Joy L Lee, Nathaniel Hafer, Margaret McManus, Adrian H Zai

JMIR Med Inform 2025;13:e68139

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study

Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists’ Knowledge on COVID-19's Impacts in Pregnancy: Cross-Sectional Pilot Study

The readability of the 4 AI’s responses to the items of the fifth section of the validated questionnaire (Multimedia Appendix 3) was appraised by means of the Flesch-Kincaid Grade Level analysis, which is a test designed to indicate how difficult a passage in English is to understand. The formula was developed by Rudolf Flesch and J Peter Kincaid and was first used in the United States military to assess the readability of their technical manuals.

Nicola Luigi Bragazzi, Michèle Buchinger, Hisham Atwan, Ruba Tuma, Francesco Chirico, Lukasz Szarpak, Raymond Farah, Rola Khamisy-Farah

JMIR Form Res 2025;9:e56126