bims-librar 2026-02-15 papers

bims-librar

Biomed News

on Biomedical librarianship

Issue of 2026–02–15
thirty-two papers selected by
Thomas Krichel, Open Library Society

Ten quick tips for using the NIH Comparative Genomics Resource.
Easy Read Health Information for People With Intellectual Disabilities: A Systematic Review of the Evidence.
Using Large Language Models to Summarize Evidence in Biomedical Articles: Exploratory Comparison Between AI- and Human-Annotated Bibliographies.
Benchmark evaluation of video large language models in quality assessment of science popularization videos for dry eye.
Sources of information on HIV/AIDS used by adolescents and young people: A scoping review protocol.
[Quality of health information on pharmaceutical products in audiovisual social media: influence of educational content].
Comparing AI and physician medical advice quality and humanistic care on social media platforms.
Optimizing Large Language Model Responses to Medical Queries: a Cross-sectional Study On the Effective Use of Chatgpt for Cancer-related Questions.
Comparison of Artificial Intelligence and Guidelines in Answering Questions on Gestational Diabetes: a CLEAR Tool Analysis.
Readability, Accuracy, and Lexical Diversity of New ChatGPT Models for Common Carpal Tunnel Syndrome Questions.
Performance of large language models in answering frequently-asked questions on celiac disease.
Assessing the accuracy, reliability, quality, and readability of artificial intelligence chatbots in patient education: insights from zirconia crowns.
Utility of ChatGPT-4o in Creating Patient Handouts in Ophthalmology: A Comparison With American Academy of Ophthalmology Educational Materials.
Artificial intelligence in pediatric otorhinolaryngology: Assessing readability, understandability, and actionability of postoperative instructions.
Assessing the Content and Quality of Online Patient Education Material on Clinical Trials From NCI-Designated Comprehensive Cancer Centers.
Leveraging AI for Analysis of Digital Health Information on Cancer Prevention Among Arab Youth and Adults: Content Analysis.
Quality and safety of youtube videos on epilepsy-specific exercises: A systematic analysis using a novel evaluation tool.
Evaluating the accuracy and reliability of overactive bladder-related YouTube videos: A digital health quality analysis using DISCERN and GQS tools.
Assessing the educational quality of YouTube videos on celiac plexus blocks: Expert review and AI-based evaluation.
Reliability and educational value of YouTube videos on penile prosthesis information.
Evaluating the quality and reliability of Kawasaki disease-related content on TikTok and Bilibili: a cross-sectional study.
Swipe, watch, learn? An analysis of TikTok as a source of patient education on spondylolisthesis.
The quality and reliability of short videos on acute myeloid leukemia on Bilibili and TikTok: A cross-sectional study.
A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms.
The quality and reliability of short videos about pulmonary hypertension on Bilibili and TikTok: a cross-sectional study.
Comment on "Analysis of Quality, Reliability, and Content of Cervical Cancer-Related Chinese Videos on TikTok".
"Google Didn't Get a Medical Degree": Understanding the Influence of Patient Online Health Information-Seeking on Shared Decision-Making.
Facilitators and barriers to health information-seeking behavior in cancer patients: A meta-synthesis.
Impaired belief revision yet intact information seeking in positive schizotypy: A modified task of bias against disconfirmatory evidence.
"I Still Need Your Help": Online information seeking behavior of International Students in the United States on Reddit.
Avian influenza: how well is relevant biosecurity information communicated via online resources?
From awareness to action: exploring health information seeking behavior in coronary heart disease patients: a cross-sectional study.

PLoS Comput Biol. 2026 Feb;22(2): e1013919

Ten quick tips for using the NIH Comparative Genomics Resource.

Eric S Tvedte, Cecilia Arighi, Matthew B Carson, Luke V Rasmussen, Kristi Holmes, Terence D Murphy.

DOI: https://doi.org/10.1371/journal.pcbi.1013919
J Appl Res Intellect Disabil. 2026 Jan;39(1): e70195

Easy Read Health Information for People With Intellectual Disabilities: A Systematic Review of the Evidence.

Hollyanna Wilson, Karen Irvine, Regi T Alexander, Silvana E Mengoni.

   BACKGROUND: Easy Read materials are sometimes provided by healthcare services to help people with intellectual disabilities to understand written information. This study examined literature on the development, review, regulation, delivery, and impact of Easy Read health information (ERHI) with the aim of elucidating best practice.
METHODS: A systematic review of five bibliographic databases and three grey literature databases was registered, conducted, and synthesised using meta-aggregation. Studies from 2006 onward regarding ERHI for individuals with intellectual disabilities were included.
RESULTS: The twenty-nine included studies revealed variability in ERHI development, review, and quality control processes. Individuals with intellectual disabilities valued ERHI and assistance in appraising it, however empirical evidence of ERHI effectiveness was limited.
CONCLUSIONS: ERHI's empirical evidence base is underdeveloped and largely consists of low-quality research. Subjective and inconsistent application of guidance leads to variable ERHI quality. Standardised resources and rigorous research are needed to evaluate ERHI as a health education intervention.

Keywords:  accessible information; easy read; health promotion; intellectual disability; patient education; physical health

DOI:  https://doi.org/10.1111/jar.70195
JMIR Form Res. 2026 Feb 12. 10 e69707

Using Large Language Models to Summarize Evidence in Biomedical Articles: Exploratory Comparison Between AI- and Human-Annotated Bibliographies.

Michelle Colder Carras, Riaz Qureshi, Kevin Naaman, Faisal Aldayel, Mayank Date, Dahlia AlJuboori, Johannes Thrul.

   Background: Annotated bibliographies summarize literature, but training, experience, and time are needed to create concise yet accurate annotations. Summaries generated by artificial intelligence (AI) can save human resources, but AI-generated content can also contain serious errors.
Objective: To determine the feasibility of using AI as an alternative to human annotators, we explored whether ChatGPT can generate annotations with characteristics that are comparable to those written by humans.
Methods: We had 2 humans and 3 versions of ChatGPT (3.5, 4, and 5) independently write annotations on the same set of 15 publications. We collected data on word count and Flesch Reading Ease (FRE). In this study, 2 assessors who were masked to the source of the annotations independently evaluated (1) capture of main points, (2) presence of errors, and (3) whether the annotation included a discussion of both the quality and context of the article within the broader literature. We evaluated agreement and disagreement between the assessors and used descriptive statistics and assessor-stratified binary and cumulative mixed-effects logit models to compare annotations written by ChatGPT and humans.
Results: On average, humans wrote shorter annotations (mean 90.20, SD 36.8 words) than ChatGPT (mean 113, SD 16 words) which were easier to interpret (human FRE score, mean 15.3, SD 12.4; ChatGPT FRE score, mean 5.76, SD 7.32). Our assessments of agreement and disagreement revealed that one assessor was consistently stricter than the other. However, assessor-stratified models of main points, errors, and quality/context showed similar qualitative conclusions. There was no statistically significant difference in the odds of presenting a better summary of main points between ChatGPT- and human-generated annotations for either assessor (Assessor 1: OR 0.96, 95% CI 0.12-7.71; Assessor 2: OR 1.64, 95% CI 0.67-4.06). However, both assessors observed that human annotations had lower odds of having one or more types of errors compared to ChatGPT (Assessor 1: OR 0.31, 95% CI 0.09-1.02; Assessor 2: OR 0.10, 95% CI 0.03-0.33). On the other hand, human annotations also had lower odds of summarizing the paper's quality and context when compared to ChatGPT (Assessor 1: OR 0.11, 95% CI 0.03-0.33; Assessor 2: OR 0.03, 95% CI 0.01-0.10). That said, ChatGPT's summaries of quality and context were sometimes inaccurate.
Conclusions: Rapidly learning a body of scientific literature is a vital yet daunting task that may be made more efficient by AI tools. In our study, ChatGPT quickly generated concise summaries of academic literature and also provided quality and context more consistently than humans. However, ChatGPT's discussion of the quality and context was not always accurate, and ChatGPT annotations included more errors. Annotated bibliographies that are AI-generated and carefully verified by humans may thus be an efficient way to provide a rapid overview of literature. More research is needed to determine the extent that prompt engineering can reduce errors and improve chatbot performance.

Keywords:  ChatGPT; annotated bibliography; artificial intelligence; evidence synthesis; information management; large language model

DOI:  https://doi.org/10.2196/69707
Sci Rep. 2026 Feb 13.

Benchmark evaluation of video large language models in quality assessment of science popularization videos for dry eye.

Shiqi Zhou, Mingxue Huang, Jiawen Wei, Huihui Fang, Weihua Yang, Hanyi Yu, Yanwu Xu.

  The rapid growth of short-video platforms has reshaped how individuals access health information, but it has also fueled the spread of misinformation and disinformation. Dry eye, a prevalent ocular surface disorder, provides a representative case for examining these challenges. Reliable and scalable methods are urgently needed to identify and mitigate misinformation risks in online health content. We proposed a framework employing Video Large Language Models (VideoLLMs) for automated evaluation of science popularization videos. Three representative VideoLLMs (VideoLLaMA3, QwenVL, and InternVL) were benchmarked using three established instruments: Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), Global Quality Score (GQS), and Video Information and Quality Index (VIQI). A dataset of 185 Chinese-language videos on dry eye was collected from TikTok and independently annotated by two ophthalmologists. Agreement between VideoLLM-generated scores and expert ratings was quantified using the Intraclass Correlation Coefficient (ICC). Across most metrics, VideoLLMs demonstrated poor agreement with expert annotations (ICC < 0.40), except for the actionability dimension of PEMAT-A/V, where QwenVL and InternVL achieved ICCs of 0.50 and 0.43, respectively, with the experts. This work establishes the first benchmark of VideoLLMs for evaluating ophthalmic science popularization videos and reveals substantial limitations in the performance of current models, with agreement levels falling well short of practical acceptability. Rather than demonstrating readiness for deployment, our open-source framework serves as a reference tool for systematically assessing model behavior, highlighting existing gaps, and motivating further methodological improvements before VideoLLMs can be considered for automated evaluation or governance of medical video content.

Keywords:  Automatic quality assessment; Digital health misinformation; Dry eye disease; Science popularization videos; Video large language model

DOI:  https://doi.org/10.1038/s41598-026-39444-0
PLoS One. 2026 ;21(2): e0340787

Sources of information on HIV/AIDS used by adolescents and young people: A scoping review protocol.

Vanessa Carla do Nascimento Gomes Brito, Luzia Cibele de Souza Maximiano, Fernanda Belmiro de Andrade, Rogeria Moreira de Abrantes, Yenifer Lizeth Gañan Rojas, Jocellem Alves de Medeiros, Raissa Martins de Andrade, Elanna Nayele de Freitas Costa, Samuel da Silva Guedes, Beatriz de Oliveira Fernandes Felipe, Alexsandra Rodrigues Feijão.

OBJECTIVE: To describe the protocol for a scoping review of the main sources of information about HIV/AIDS used by adolescents and young people.
CONTEXT: Studies have shown that adolescents and young people are increasingly using digital technologies as a source of information about HIV/AIDS. Although these digital technologies offer potential benefits to the educational process, their implementation and use are not always free from challenges and implications. In this sense, it is essential to investigate the reliability of the information sources accessed by adolescents and young people.
DESIGN: Scoping review protocol, conducted in accordance with JBI guidelines.
METHOD: This is a protocol for a scoping review to be conducted following the JBI guidelines, in three phases and using the following data sources: Scopus, Cumulative Index to Nursing and Allied Health Literature, Medical Literature Analysis and Retrieval System Online (MEDLINE), Scientific Electronic Library Online (SciELO), Latin American and Caribbean Literature in Health Sciences (LILACS), Web of Science and later, Google School, Capes Catalog of Theses and Dissertations, Theses Canada and USP Digital Library of Theses and Dissertations. The inclusion criteria are studies that address the theme, available in full, free of charge and without time or language restrictions. The exclusion criteria are opinion articles, letters to the editor and editorials. The results will be presented through discussions, tables, graphs and percentages. Expected results: The results are expected to reveal the main sources of information used by adolescents and young people regarding HIV/AIDS, allowing the identification of their preferences regarding the means and formats of access to content. This protocol is available for access through the following electronic address: https://osf.io/aunkh/ with https://doi.org/10.17605/OSF.IO/AUNKH.
CONCLUSION: Data analysis will help to identify potentialities and limitations in strategies for accessing information about HIV/AIDS by adolescents and young people. This scoping review can foster knowledge about information needs, guiding the creation of more effective content, supporting health decision-making and strengthening communication between professionals, users and institutions, contributing to the access of reliable data.

DOI: https://doi.org/10.1371/journal.pone.0340787
Rev Esp Salud Publica. 2026 Feb 09. pii: e202602010. [Epub ahead of print]100

[Quality of health information on pharmaceutical products in audiovisual social media: influence of educational content].

Rocío Romeral Cortina, Beatriz Jiménez Gómez, Carlos Antonio Ruiz Núñez, Mª Del Carmen Lozano Estevan, Iván Herrera Peco.

OBJECTIVE: Audiovisual social media platforms are becoming increasingly prominent as sources of health information. Pharmacists are gaining visibility as content creators in this space; however, the quality of the information they share about pharmaceutical products remains underexplored. The objective of this paper was to assess the quality of information on medications disseminated by pharmacists on audiovisual social media platforms and to analyze the influence of educational framing and declared advertising on that quality.
METHODS: A cross-sectional observational study was conducted. A total of 755 videos were collected in March 2024 from the ten most-followed pharmacist accounts (≥1,000 followers) on Instagram, TikTok, and YouTube. Two independent reviewers evaluated the quality using the abbreviated DISCERN scale (1-5). Educational content (yes/no) and declared advertising were coded. Robust linear regression models were applied to estimate the association between predictors and DISCERN scores.
RESULTS: Overall quality was moderate to low (mean DISCERN score: 2.43±0.40), with no significant statistical differences across platforms (p=0.327). Educational videos (28.2%) achieved higher scores (2.62±0.38) compared to non-educational ones (2.34±0.39; p<0.001). Declared advertising decreased quality scores by -0.30 points (p<0.001), with a stronger effect observed on TikTok (-0.50).
CONCLUSIONS: Educational framing consistently enhances the informational quality of pharmacist-generated content, regardless of the platform, whereas declared advertising undermines it, especially on TikTok. Promoting evidence-based micro-educational content and enforcing transparent sponsorship labeling may improve the reliability of pharmaceutical information on social media.

Keywords: Health communication; Health education; Pharmacy; Social media; Spain
Digit Health. 2026 Jan-Dec;12:12 20552076261421341

Comparing AI and physician medical advice quality and humanistic care on social media platforms.

Zhaorui Wang, Youfu He, Linlin Guo, Yu Qian, Liqiong Ai, Jing Huang, Ruiting Feng, Qiang Wu.

   Objective: To evaluate the level of quality, professionalism, and humanistic care in medical advice given by artificial intelligence (AI) and healthcare experts on social media platforms, with an emphasis on short video content and in-person question-and-answer (Q&A) sessions.
Methods: The mDISCERN, GQS, and VIQI scores were used to assess the quality and creator opinion trends of the short videos on AI-assisted diagnosis that were gathered from YouTube, TikTok, and Bilibili. Patient inquiries from Dingxiang Health, a significant Chinese online consultation platform, were selected across medical departments. Simulated answers were produced by Deep Seek R1 and Chat-GPT O3-mini-high, and Bedside Manner Rating were used to evaluate the humanistic and high-quality treatment.
Results: Across platforms, 60.8% of videos preferred AI's diagnosis powers above medical professionals (Bilibili: 74.29%, TikTok: 56.67%, YouTube: 53.75%). Bilibili videos, particularly those produced by professionals, scored highest in quality (p < 0.05). In simulated consultations, AI fared better than doctors in terms of quality and humanistic care (p < 0.05), especially in structured expression and emotional response.
Conclusions: Higher-quality medical content is available on Bilibili, and AI shows benefits in terms of humanistic care and diagnostic quality in text-based, simulated consultations. Future research should explore examine how doctors and AI might work together to enhance healthcare delivery, with doctors using digital communication while also exercising professional judgment in real-world clinical settings.

Keywords:  Social media; artificial intelligence; empathy; humanistic care; medical advice quality; physician; short video; social media platforms

DOI:  https://doi.org/10.1177/20552076261421341
J Med Syst. 2026 Feb 10. 50(1): 20

Optimizing Large Language Model Responses to Medical Queries: a Cross-sectional Study On the Effective Use of Chatgpt for Cancer-related Questions.

Xinran Shao, Yihan Sun, Xingai Ju, Jianchun Cui.

  Large language models (LLMs) are increasingly used for medical advice; despite this, their response readability and quality remain suboptimal. Current research focuses on evaluating LLM outputs, with little investigation into practical optimization strategies for clinical use. On August 9, 2025, we identified the top 25 search keywords for five common cancers via Google Trends and adapted them into six prompt types. Each was posed to ChatGPT-4o and ChatGPT-5 between August 10 and August 12, 2025 under two query conditions: isolated (single question per page) and aggregated (all questions for one cancer type on the same page). Readability was assessed using four indices: Flesch-Kincaid Grade Level (FKGL), Flesch Reading Ease (FKRE), Gunning Fog Index (GFI), and the Simple Measure of Gobbledygook (SMOG). Quality was evaluated on a 5-point Likert scale across accuracy, relevance, comprehensiveness, empathy, and falsehood. ChatGPT-5 generated responses with significantly fewer words (316.81 ± 12.96), sentences (19.79 ± 1.01), syllables (551.93 ± 24.55), and hard words (62.33 ± 3.60) than ChatGPT-4o (292.85 ± 14.52, p = 0.003; 18.77 ± 1.07, p = 0.039; 515.01 ± 27.89, p = 0.006; 58.35 ± 4.05, p = 0.005), while also achieving higher scores in accuracy (W = 2.116, p = 0.034), relevance (W = 2.454, p = 0.014), comprehensiveness (W = 2.574, p = 0.010), and empathy (W = 2.174, p = 0.030). The 6th-grade prompt markedly improved readability over other strategies (ChatGPT-5: FKRE:64.92 ± 8.56, GFI:8.10 ± 1.13, FKGL:8.74 ± 1.73, SMOG:6.97 ± 1.26; ChatGPT-4o:65.44 ± 7.43, GFI:8.04 ± 1.48, FKGL:8.73 ± 1.80, SMOG:6.86 ± 1.53). Aggregating queries on a single page yielded higher accuracy, relevance, and comprehensiveness scores compared to isolated questioning (ChatGPT-4o: W = 4.451, p < 0.001; W = 4.356, p < 0.001; W = 1.965, p = 0.049. ChatGPT-5: W = 3.234, p < 0.001; W = 2.697, p = 0.007; W = 3.885, p < 0.001). ChatGPT-5 produces more concise and qualitatively superior responses than ChatGPT-4o. The patient prompt generated responses with high readability and strong empathy, and is therefore recommended for patient use. Consequently, aggregating related questions on a single page is advised to obtain higher-quality answers.

Keywords:  Cancer; ChatGPT; LLM; Prompt Engineering; Readability

DOI:  https://doi.org/10.1007/s10916-026-02344-x
Clin Lab. 2026 Feb 01. 72(2):

Comparison of Artificial Intelligence and Guidelines in Answering Questions on Gestational Diabetes: a CLEAR Tool Analysis.

Gökhan Köker, Lütfullah Z Koç, Muhammed A Coşkuner, Yasin Şahintürk, Bilgin B Başgöz.

BACKGROUND: Gestational diabetes mellitus (GDM) affects millions of people worldwide. Patients often turn to the internet and artificial intelligence (AI)-based conversational models for information. The CLEAR tool evaluates the quality of health-related content produced by AI-based models. This study assessed the responses provided by medical guidelines, ChatGPT, and Google Bard to the ten most frequently asked online questions about GDM, uti-lizing the CLEAR tool for evaluation.
METHODS: The most common online questions about GDM were identified using Google Trends, and the top 10 questions were selected. Answers were then gathered from two experienced physicians, ChatGPT 4.0o-mini, and Google Bard, with responses categorized into 'Guide,' 'ChatGPT,' and 'Bard' groups. Answers from the AI models were obtained using two computers and two separate sessions to ensure consistency and minimize bias.
RESULTS: ChatGPT received higher scores than the medical guidelines, while Bard scored lower than ChatGPT. The medical guidelines provided more accessible answers for the general audience, while ChatGPT and Bard required higher literacy levels. Good reliability (0.781) was observed between the two reviewers. Regarding readability, the medical guidelines were the easiest to read, while Bard provided the most challenging text.
CONCLUSIONS: ChatGPT and Google Bard perform well in content completeness and relevance but face challenges in readability and misinformation. Future research should improve accuracy and readability, integrate AI with peer-reviewed sources, and ensure healthcare professionals guide patients to reliable AI information.

DOI: https://doi.org/10.7754/Clin.Lab.2025.250544
Hand (N Y). 2026 Feb 08. 15589447251415391

Readability, Accuracy, and Lexical Diversity of New ChatGPT Models for Common Carpal Tunnel Syndrome Questions.

Romir P Parmar, Sohail R Daulat, Rakshit Shah, Tyler T Brady, Michael Montague, Cameron Roth.

   BACKGROUND: Carpal tunnel syndrome (CTS) is a prevalent neuropathy in hand surgery that significantly affects people's quality of life. Frequently, patients conduct research online before seeking medical care. Large language models (LLMs) like ChatGPT are increasingly used for health information, yet concerns remain regarding the accuracy, readability, and complexity of their responses. Previous studies have assessed older ChatGPT models but have not comprehensively compared newer versions. The purpose of this study is to compare ChatGPT-4-generated, ChatGPT-4o-generated, and ChatGPT-o1-generated answers to common CTS-related patient questions.
METHODS: Six frequently asked CTS questions were queried of each LLM. Responses were independently graded by 2 board-certified hand surgeons using evidence-based guidelines. Lexical diversity was assessed using the Measure of Textual Lexical Diversity, and readability was evaluated using the Flesch-Kincaid Grade Level, Flesch Reading Ease Score, and Simple Measure of Gobbledygook. Analysis of variance or Kruskal-Wallis with post hoc tests were conducted to compare LLMs and questions.
RESULTS: All 3 ChatGPT models averaged 93% accuracy with no significant differences between them, though a significant difference in accuracy was observed between questions 3 and 5. Readability scores between models varied significantly, with ChatGPT-4o generating the most readable responses and ChatGPT-o1 producing the most complex answers.
CONCLUSIONS: While LLMs had similar accuracy, ChatGPT-4o offered the most patient-friendly content. Furthermore, the readability of all models remains above the recommended level for the general population. Future work should explore whether fine-tuning or advancements in model design can enhance accessibility for a broader audience.

Keywords:  ChatGPT; artificial intelligence; carpal tunnel syndrome; language learning model; readability

DOI:  https://doi.org/10.1177/15589447251415391
J Pediatr Gastroenterol Nutr. 2026 Feb 09.

Performance of large language models in answering frequently-asked questions on celiac disease.

Nadav Peled, Dror S Shouval, Peter Gillett, Hania Szajewska, Francesco Valitutti, Raanan Shamir, Anat Guz-Mark.

   OBJECTIVES: Celiac disease (CeD) is a common autoimmune condition requiring lifelong adherence to a gluten-free diet (GFD). Patients and caregivers increasingly seek information online, and large language models (LLMs) have emerged as potential educational tools. However, their reliability in CeD remains uncertain. This study aimed to evaluate the performance of three popular LLMs in answering frequently asked questions (FAQs) about CeD and GFD management.
METHODS: We conducted a cross-sectional comparative evaluation in which 12 FAQs were submitted to three LLMs: ChatGPT-4 (OpenAI), Gemini Flash 2.5 (Google), and Claude Sonnet 3.7 (Anthropic). Six pediatric gastroenterologists with expertise in CeD research and education, independently assessed and rated responses for accuracy, completeness, clarity, and overall quality using a 5-point Likert scale.
RESULTS: The mean overall score across models was 4.3 ± 0.35 out of 5. Clarity received the highest ratings (4.56 ± 0.21), followed by accuracy (4.26 ± 0.52), completeness (4.17 ± 0.21), and overall quality (4.20 ± 0.36). Responses to management-related questions scored significantly higher than those to diagnostic questions (4.4 vs. 4.2, p = 0.013). Inter-rater reliability was good (intraclass correlation coefficient = 0.74). Overall, Gemini achieved the highest ratings (p < 0.01).
CONCLUSIONS: LLMs provide clear and generally accurate responses to CeD FAQs, particularly on management-related topics. While they represent a promising tool for patient education, variability in accuracy highlights the need for clinician oversight when interpreting artificial intelligence-generated medical information.

Keywords:  artificial intelligence; coeliac disease; gluten‐free diet; patient education

DOI:  https://doi.org/10.1002/jpn3.70375
BMC Oral Health. 2026 Feb 12.

Assessing the accuracy, reliability, quality, and readability of artificial intelligence chatbots in patient education: insights from zirconia crowns.

Nihan Kaya Acar, Fatih Sengul, Enes Bardakci, Peris Celikel.



Keywords:  Dental restorations; Esthetics; Patient information; Pediatric dentistry; Prosthodontics

DOI:  https://doi.org/10.1186/s12903-026-07884-9
Transl Vis Sci Technol. 2026 Feb 02. 15(2): 14

Utility of ChatGPT-4o in Creating Patient Handouts in Ophthalmology: A Comparison With American Academy of Ophthalmology Educational Materials.

Linda L Wu, Alexander T Hong, Shaili S Davuluru, Edgar Alejandro Moreno-Diaz, Juan Carlos Gutiérrez-Hernández, Juan Carlos Martinez-Camarillo, Benjamin Y Xu, Sandy Zhang-Nunes.

Purpose: This study compares the readability and quality of ChatGPT-4o-generated and American Academy of Ophthalmology (AAO) patient handouts in English and Spanish, as AAO materials are expert developed but not publicly accessible.
Methods: Ten AAO handouts on common ocular conditions were obtained in English and Spanish. ChatGPT-4o was queried to create handouts at an 8th-grade reading level of comparable length. English readability was assessed with Simple Measure of Gobbledygook (SMOG) and Flesch-Kincaid Reading Ease, and Spanish readability was assessed with five validated metrics, including the Szigriszt-Pazos Perspicuity Index (SPPI) and the Flesch-Szigriszt Index (INFLESZ). Grade levels were measured by the Flesch-Kincaid Grade Level and Crawford-Nivel-de-Grado. Three ophthalmologist graders per language assessed content with the Quality of Generated Language Outputs for Patients (QGLOP), indicated their preferred handout, and attempted to identify its source.
Results: ChatGPT-4o handouts had English readability similar to that of AAO (SMOG 7.86 ± 0.53 vs. 7.49 ± 0.76; P = 0.35) but significantly lower Spanish SPPI scores (60.26 ± 4.47 vs. 64.82 ± 2.97; P = 0.04). Grade levels were comparable. English QGLOP scores were similar (14.73 vs. 14.87; P = 0.97), but Spanish ChatGPT handouts scored higher in all categories (15.83 vs. 14.23; P < 0.001). ChatGPT-4o handouts were correctly identified by 17 of 30 in English (56.7%) and by 3 of 30 in Spanish (10.0%). They were favored 23 out of 30 times in English (76.7%) and 29 out of 30 times in Spanish (96.7%).
Conclusions: ChatGPT-generated materials matched or exceeded AAO handouts in readability and content quality, with Spanish versions being most preferred.
Translational Relevance: Integrating artificial intelligence-generated patient education materials into ophthalmic care can enhance health literacy for multilingual patient populations.

DOI: https://doi.org/10.1167/tvst.15.2.14
Am J Otolaryngol. 2026 Feb 09. pii: S0196-0709(26)00013-X. [Epub ahead of print]47(2): 104798

Artificial intelligence in pediatric otorhinolaryngology: Assessing readability, understandability, and actionability of postoperative instructions.

Alya AlZabin, Hisham AlMutawa, Lulwah AlTurki, Yasser AlBalawi, Mazyad M AlEnezi, Danah AlJomah.

   BACKGROUND: Despite the increasing use of artificial intelligence (AI) platforms in healthcare communication, their efficacy in producing patient-facing materials for pediatric surgeries is still unexplored. The readability, understandability, and actionability of postoperative instructions generated by three AI platforms (ChatGPT, Gemini, and DeepSeek) for common pediatric otorhinolaryngology (ORL) surgeries were compared in this study.
METHODS: Postoperative instructions were generated from each AI platform using a standardized prompt. Readability was assessed using the Flesch-Kincaid Reading Ease (FKRE) and Grade Level (FKGL). Understandability and actionability were evaluated using the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P). Comparative statistical analyses and Pearson correlation coefficients were calculated.
RESULTS: ChatGPT showed the highest readability with FKRE 64.57 (±7.20) and the lowest FKGL 7.40 (±1.54), significantly outperforming others in FKRE (p = 0.030). The Gemini had the highest understandability (83.20% ± 1.56; p = 0.027), while the DeepSeek led in actionability (71.10% ± 3.81; p = 0.140). No AI platform met all the adequacy thresholds (FKGL <6, FKRE >60, PEMAT-P > 80%) at one time. Across the procedures, the differences in the readability, understandability, and the actionability were not statistically significant (all p > 0.5). The correlation analysis showed that there is significant inverse relationships of FKRE with FKGL (r = -0.711, p = 0.032) and FKRE with understandability (r = -0.669, p = 0.049). The actionability was not significantly correlated with any metric.
CONCLUSION: Although each AI platform shown strengths in some domains, none consistently fulfilled the criteria for optimal patient education. These findings underscore the necessity for enhanced AI training utilizing pediatric and caregiver-specific data to improve the quality of postoperative guidance in pediatric ORL care.

Keywords:  Artificial intelligence; ChatGPT; DeepSeek; Gemini; Machine learning; Otolaryngology; Post-operative instructions

DOI:  https://doi.org/10.1016/j.amjoto.2026.104798
J Natl Compr Canc Netw. 2025 Dec 18. pii: e257082. [Epub ahead of print]24(1):

Assessing the Content and Quality of Online Patient Education Material on Clinical Trials From NCI-Designated Comprehensive Cancer Centers.

Trista A Beard, Diana L Morales, Alena Arshaid, Charmi Suchi Desai, Welela Solomon, Aali Sharief, Isabella Villanueva, Fatimata Sanogo, Anthony B El-Khoueiry, Mariana C Stern, Chanita Hughes Halbert.

BACKGROUND: Online patient educational material (PEM) on cancer clinical trials (CCTs) is an essential resource for patients seeking to learn more about treatment options. Assessing its quality and content themes may lead to improved educational content. Using qualitative analysis, this study examined the quality and content themes of online PEM related to CCTs published by comprehensive cancer centers (CCCs).
METHODS: A random sample of CCCs (N=21) was chosen to represent the national network of cancer centers. Each website was searched for webpages containing patient-oriented clinical trial information. Official YouTube channels were also searched for relevant video material. Each webpage and video (n=196) was assessed for quality and content themes.
RESULTS: Common content themes in the sample (n=196) of online PEM from CCCs were "purpose of trials," "physician speaker," "animated or illustrated elements," and "phases of trials." Online PEM had an average score of 83 for understandability and 26 for actionability, an area noted for improvement (high quality scores for the Patient Education Materials Assessment Tool [PEMAT] are >70). Online webpages that mixed text and video scored highest on the quality assessment, whereas video-only content scored lowest. Only a small percentage of PEM included FAQs (10%), instructions on how to find a trial (16%), mentioned consent (14%), or costs associated with trials (12%). Mentions or depictions of minority populations were not commonly observed in the material (11%).
CONCLUSIONS: Cancer centers should add various audiovisual formats and patient-centered resource tools (eg, planning kit, question guide) to their clinical trial webpages to increase the quality of the educational resources. Including representation of historically underserved populations and adding actionable advice can potentially engage and empower patients to consider trials as part of their care plan, and thereby increase enrollment in CCTs.

DOI: https://doi.org/10.6004/jnccn.2025.7082
JMIR Infodemiology. 2026 Feb 09. 6 e77888

Leveraging AI for Analysis of Digital Health Information on Cancer Prevention Among Arab Youth and Adults: Content Analysis.

Alia Komsany, Obada Al Zoubi, Laetitia Sebaaly, Gabrielle Harrison, Orysya Soroka, Safa ElKefi, David Scales, Erica Phillips, Laura C Pinheiro, Israa Ismail, Perla Chebli.

   BACKGROUND: As TikTok (ByteDance) grows as a major platform for health information, the quality and accuracy of Arabic-language cancer prevention content remain unknown. Limited access to culturally relevant and evidence-based information may exacerbate disparities in cancer knowledge and prevention behaviors. Although large language models offer scalable approaches for analyzing online health content, their utility for short-form video data, especially in underrepresented languages, has not been well established.
OBJECTIVE: We aimed to characterize and evaluate the quality of Arabic-language TikTok videos on cancer prevention and explore the use of large language models for scalable content analysis.
METHODS: We used the TikTok research application programming interface and a GPT-assisted keyword strategy to collect Arabic-language TikTok videos (2021-2024). From an initial collection of 1800 TikTok videos, 320 were eligible after preprocessing. Of these, the top 25% (N=30) most-viewed were analyzed and manually coded for content type, cancer type, uploader identity, tone and register, scientific citation, and disclaimers. Video quality was assessed using the Patient Education Materials Assessment Tool for Audiovisual Materials for understandability and actionability, and the Global Quality Scale (GQS). GPT-4 was used to generate artificial intelligence annotations, which were compared to human coding for select variables.
RESULTS: The top 25% (N=30) most-viewed videos amassed a total of 21.6 million views. Diet and alternative therapies were most common (15/30, 50%), which included recommendations to reduce hydrogenated oils, increase fruit and vegetable intake, and the use of traditional remedies such as garlic and black seed. Only 6.6% (2/30) of videos cited scientific literature. General cancer (15/30, 53%), breast (5/30, 17%), and cervical (4/30, 13%) cancers were most frequently mentioned. Doctors led 30% (9/30) of videos and were more likely to produce higher quality content, including significantly higher global quality scores (GQS=4, median 4, IQR 4-4 vs 3, median 3, IQR 2-3, P=.06). Over half of the videos had low understandability (16/30, 53%) and actionability (18/30, 60%). Emotionally framed content had the highest engagement across likes and shares, although this did not reach statistical significance (P=.08 and P=.05, respectively). However, emotional tone was significantly associated with lower GQS scores (P=.01). GPT-4 showed high agreement with human coders for cancer type (Cohen κ=1.0), strong agreement for GQS (κ=0.94), but low agreement for tone classification (κ=0.15), due to misclassification of emotional delivery from text-only input.
CONCLUSIONS: Arabic-language TikTok cancer prevention content is highly engaging but variable in quality, with emotionally framed videos attracting substantial attention despite lower informational value. Artificial intelligence-assisted tools show strong potential for scalable, multilingual health content analysis, but multimodal approaches are needed to accurately interpret tonal and audiovisual features.

Keywords:  AI-driven content analysis; TikTok; cancer prevention; digital health communication; engagement

DOI:  https://doi.org/10.2196/77888
Seizure. 2026 Feb 03. pii: S1059-1311(26)00030-0. [Epub ahead of print]136 51-59

Quality and safety of youtube videos on epilepsy-specific exercises: A systematic analysis using a novel evaluation tool.

Yakup Gonulal, Tuba Denizci, Mehmetcan Yesilkaya, Eda Agascioglu, Serdar Aykac, Rabia Hurrem Ozdurak Singin.

   OBJECTIVE: Exercise benefits people with epilepsy (PWE) by reducing seizure frequency, improving quality of life, and fostering social participation. YouTube, a popular platform for health information, hosts numerous exercise videos for PWE, yet their quality, reliability, and safety remain unevaluated. This study aimed to evaluate the quality, reliability, and engagement of YouTube videos on epilepsy-specific exercises using the novel Epilepsy Content Evaluation (ECE) tool, alongside DISCERN, JAMA, and Global Quality Score (GQS).
METHOD: A systematic search conducted on July 22, 2025, identified 45 English-language YouTube videos, which were independently evaluated by two neurologists using the ECE, DISCERN, JAMA, and GQS tools. Video characteristics, publisher sources, and engagement metrics were analyzed.
RESULTS: Most videos (53.3%) were rated low quality (ECE score 0-7), with only one (2.2%) achieving high quality (ECE score 12-15). The Safety and Risk Management subdomain scored lowest (median: 2, IQR: 1.25), reflecting inadequate attention to seizure triggers and supervision. Athlete-targeted videos outperformed general-population videos in quality (p < 0.05). View counts negatively correlated with ECE scores (r = -0.375 to -0.712, p < 0.05). ECE demonstrated strong convergent validity with DISCERN (Phi = 0.606, p = 0.035).
CONCLUSION: In conclusion, most YouTube videos on epilepsy-specific exercises lack clinical reliability and safety guidance, posing potential risks for PWE. The ECE tool effectively identifies these deficiencies, enabling clinicians to recommend ILAE-aligned videos to enhance patient safety. Curated, evidence-based digital resources could empower millions of PWE to engage in safe physical activity, reducing stigma and improving health outcomes.

Keywords:  Content evaluation; ECE; Epilepsy; Exercise; Patient safety; Youtube

DOI:  https://doi.org/10.1016/j.seizure.2026.02.002
Urologia. 2026 Feb 08. 3915603261418195

Evaluating the accuracy and reliability of overactive bladder-related YouTube videos: A digital health quality analysis using DISCERN and GQS tools.

Basri Cakiroglu, Ali Egemen Avci.

   BACKGROUND: Overactive bladder (OAB) is a prevalent condition, and patients increasingly turn to online platforms such as YouTube for information, raising concerns about accuracy and reliability.
PURPOSE: This study aimed to evaluate the quality and reliability of YouTube videos related to overactive bladder (OAB) using two validated instruments: the DISCERN tool and the Global Quality Scale (GQS).
METHODS: A systematic and structured YouTube search strategy, adapted from systematic review methodology but tailored for digital platforms, was conducted using the keyword overactive bladder. The first 100 videos retrieved were screened, and 60 met the inclusion criteria: English language, duration of at least 60 s, and relevant educational content. Exclusion criteria included non-English language, duplicates, advertisements, and purely promotional material. Two independent urologists evaluated each video using the DISCERN tool (range: 16-80) and GQS (range: 1-5). Additional data collected included video length, view count, uploader type, and thematic content. Descriptive statistics and correlation analyses were performed.
RESULTS: The median video duration was 5.6 min (IQR: 3.4-8.2), with a median view count of 34,200 (IQR: 12,500-89,000). The mean DISCERN and GQS scores were 45.2 ± 10.1 and 2.9 ± 0.8, respectively, indicating moderate overall quality. Videos uploaded by healthcare professionals or institutions had significantly higher DISCERN and GQS scores compared to those uploaded by individuals or commercial entities (p < 0.001). Only 28% of videos addressed neurogenic causes of OAB, and 41% did not mention behavioral therapy. A weak but statistically significant positive correlation was observed between GQS score and view count (ρ = 0.34, p = 0.01).
CONCLUSIONS: YouTube contains a wide array of OAB-related videos, but their quality and reliability vary considerably. While some content is accurate and informative, significant gaps remain, particularly regarding neurogenic etiologies and behavioral management. Healthcare professionals should guide patients toward trustworthy resources and consider producing evidence-based content to improve digital health literacy.

Keywords:  DISCERN; Global Quality Scale; YouTube; digital health; health information quality; overactive bladder; patient education

DOI:  https://doi.org/10.1177/03915603261418195
Interv Pain Med. 2026 Mar;5(1): 100740

Assessing the educational quality of YouTube videos on celiac plexus blocks: Expert review and AI-based evaluation.

Julia Zhu, David Hao, Robert Jason Yong.

   Background: YouTube is an open-access platform increasingly used for both medical and patient education, but its user-generated content is not subject to peer review and shows wide variability in accuracy and quality. Celiac plexus blocks are technically complex procedures that are presented on YouTube, yet the educational quality of these instructional videos has not yet been systematically evaluated.
Objective: To evaluate the educational quality of YouTube videos on celiac plexus blocks and to explore the utility of ChatGPT-4o as a secondary, adjunctive tool for assessing video quality.
Methods: YouTube was searched on June 2nd, 2025 using the keywords "celiac plexus neurolysis," "celiac block for cancer pain," "celiac plexus block," and "celiac plexus injection." The 17 most-viewed videos were independently evaluated by two board-certified chronic pain physicians and by ChatGPT-4o using a modified DISCERN scale (mDISCERN), the Global Quality Scale (GQS), and a usefulness classification.
Results: Based on human expert ratings, only 18 % of videos contained highly reliable information as assessed by the mDISCERN scale, and 24 % demonstrated moderate to excellent information quality on the Global Quality Scale. Overall, 65 % of videos were classified as useful. Inter-rater reliability between human experts ranged from poor to moderate across the three scales of evaluation, while agreement between human expert and ChatGPT-4o assessment was poor.
Conclusions: The educational quality of YouTube videos on celiac plexus blocks was generally poor. Unlike similar studies investigating other procedures, the quality of videos produced by physician and hospital sources was not better than that of videos by nonacademic sources. These findings highlight the need to improve the quality of educational content produced by physicians, hospitals, and professional societies.

Keywords:  Celiac plexus block; Medical education; Online health information; YouTube

DOI:  https://doi.org/10.1016/j.inpm.2026.100740
Adv Clin Exp Med. 2026 Feb 13.

Reliability and educational value of YouTube videos on penile prosthesis information.

Ahmet Emin Doğan, Görkem Özenç, İbrahim Üntan, Mehmet Altan, Metin Yığman, Çağrı Akpınar, Sertaç Çimen, Berk Yasin Ekenci, Hilmi Sarı.

   BACKGROUND: In the contemporary era, acquiring online information has become a prevalent practice. As with any affliction, individuals are inclined to investigate the potential therapeutic avenues for erectile dysfunction (ED) on the internet.
OBJECTIVES: To evaluate the quality, comprehensibility and informative content of YouTube videos on penile prosthesis implantation, with a focus on videos produced by healthcare professionals, and to address the videos according to the class of physician producing the video.
MATERIAL AND METHODS: A search for "penile prosthesis" was conducted on YouTube using a censored network to ensure privacy and prevent bias. The first 100 relevant videos uploaded in the last decade were analyzed. They were categorized by source (academicians, government or private hospital physicians, and non-physicians) and assessed for quality using the modified Quality Criteria for Consumer Health Information (DISCERN) scale, Global Quality Scale (GQS) and a newly developed Total Informative Score based on the European Association of Urology Patient Information Forms. The Kruskal-Wallis H test, Kendall's tau correlation test and Spearman's test were used for statistical analysis.
RESULTS: Of the videos analyzed, 87% provided informative content, with the majority (51%) uploaded by academic sources. The median duration time was 185 s (111-397). The average modified DISCERN score was low (median: 2, Q1-Q3: 2-3), indicating generally inadequate quality, with 54% rated as poor. No statistical significance occurred between GQS scores for the videos published by the upload source. Videos by government hospital physicians scored the highest in quality measures, while non-physician videos garnered more views and likes. The Patient Education Materials Assessment Tool (PEMAT) understandability and actionability scores showed that videos from healthcare professionals had higher understandability (70%) than those from other sources.
CONCLUSIONS: The overall quality of YouTube videos on penile prostheses is low, despite most being informative. Videos created by physicians are more reliable and easier to understand. Implementing stricter guidelines for content creators and promoting public awareness initiatives are recommended to improve patient access to high-quality information.

Keywords:  PEMAT; YouTube; modified DISCERN; penile prosthesis

DOI:  https://doi.org/10.17219/acem/205521
Front Public Health. 2025 ;13 1664542

Evaluating the quality and reliability of Kawasaki disease-related content on TikTok and Bilibili: a cross-sectional study.

Nan Shen, Chang Xu, Yongkun Yang, Dongli Zhang.

   Background: As public interest in health and immunology grows, short video platforms have become an increasingly important source of medical information. Kawasaki disease, a pediatric immune-mediated vasculitis with potential cardiovascular complications, has attracted substantial attention; however, the accuracy and quality of related content on these platforms remain unexamined. This study aimed to evaluate the overall quality of Kawasaki disease-related videos on TikTok and Bilibili.
Method: On February 25, 2025, newly registered accounts were used to search the term "" (Kawasaki disease) on TikTok and Bilibili, and the top 100 videos from each platform were collected. Video quality was evaluated using the JAMA benchmark criteria, a modified DISCERN, and PEMAT, while user engagement metrics (likes, comments, saves, and shares) were analyzed for correlations.
Results: A total of 146 videos were included. Although TikTok videos demonstrated higher quality and popularity than those on Bilibili, overall video quality on both platforms remained suboptimal. Median JAMA scores were 2.00 and 1.00, modified DISCERN scores were both 3.00, intelligibility was 70% versus 64%, and operability was 67% on both platforms. Most videos were monologue-based and symptom-focused, with pediatricians and individual users as the main uploaders. Pediatricians and individual users were the two largest groups of content creators. Pediatrician-uploaded videos showed higher quality and engagement, whereas individual-user videos were more often misleading and less interactive. Five major misinformation themes were identified, including symptom oversimplification, incorrect etiological claims, promotion of non-evidence-based home treatments, misunderstanding of diagnostic criteria, and misleading statements about immunoglobulin therapy. Video quality was positively correlated with popularity, while longer duration was negatively associated with both quality and engagement. Heterogeneity was observed across platforms.
Conclusion: The quality and reliability of Kawasaki disease-related videos on short video platforms remain suboptimal, highlighting the need to address misinformation, refine evaluation tools, and promote high-quality content creation.

Keywords:  Bilibili; Kawasaki disease; TikTok; health education; quality assessment

DOI:  https://doi.org/10.3389/fpubh.2025.1664542
Brain Spine. 2026 ;6 105960

Swipe, watch, learn? An analysis of TikTok as a source of patient education on spondylolisthesis.

Celine Akta, Moses El Kayali, Lukas Schönnagel, Luis Bürck, Maximilian Muellner, Friederike Schömig, Matthias Pumberger, Tom Folkerts.

   Introduction: Social media has become a major source of health information. TikTok, a rapidly expanding global platform that enables broad dissemination of medical content, yet the accuracy and reliability of such information remain uncertain. In this context, assessing the educational quality of videos on spondylolisthesis is of increasing clinical relevance.
Research question: To evaluate the quality, reliability, and educational value of TikTok videos on spondylolisthesis and identify factors associated with higher-quality content.
Material and methods: TikTok was searched in August 2025 using the keyword "spondylolisthesis." Video metrics, uploader type and content category were recorded. Two orthopedic surgeons independently assessed reliability and quality using the DISCERN tool, Journal of the American Medical Association (JAMA) benchmarks, and Global Quality Score (GQS).
Results: A total of 254 TikTok videos were screened, of which 82 met inclusion criteria, totaling 4.15 million views and 55,967 likes. Private users uploaded 46.3%, surgeons 28.0%, physiotherapists 23.2%, and researchers 2.4%. Overall quality was poor (DISCERN 34.1 ± 17.6; JAMA 1.8 ± 1.1; GQS 2.6 ± 1.1). Videos by surgeons and physiotherapists scored significantly higher (p < 0.001), and educational content outperformed patient experiences (p < 0.001). Longer videos correlated with higher quality scores, while engagement metrics were not predictive.
Discussion and conclusion: Most TikTok videos on spondylolisthesis showed low quality and limited reliability. Educational content produced by healthcare professionals performed better, while popularity metrics were not indicative of quality. Spine specialists should recognize TikTok's growing role in patient education and contribute accurate, evidence-based content to improve information quality.

Keywords:  Digital health; Patient education; Social media; Spine surgery; Spondylolisthesis; TikTok

DOI:  https://doi.org/10.1016/j.bas.2026.105960
Medicine (Baltimore). 2026 Feb 13. 105(7): e47594

The quality and reliability of short videos on acute myeloid leukemia on Bilibili and TikTok: A cross-sectional study.

Siqin Yang, Yuqing Li, Jun Tao.

  Acute myeloid leukemia (AML) is a life-threatening hematological malignancy. With the rapid development of short video platforms, TikTok and Bilibili have become important sources of health information; however, the quality and reliability of AML-related content remain unclear. This study aims to evaluate the content, quality, and reliability of short AML videos on these platforms. The top 150 AML-related videos were collected from each platform using default ranking. Video quality was assessed using 3 validated instruments: the global quality score, modified DISCERN, and the Journal of American Medical Association benchmark. The correlations between user engagement metrics (likes, comments, shares, and favorites) and quality scores were also analyzed. In total, 176 videos were included. Most videos focused on treatment (TikTok and Bilibili: 31.6% and 36.1%, respectively) and prognosis (TikTok and Bilibili: 24.4% vs 17.3%, respectively), while pathogeny and clinical manifestations were insufficiently covered. The overall quality was modest: global quality score median 3.00 (interquartile range [IQR]: 2.00-4.00), modified DISCERN median 2.00 (IQR: 1.00-3.00), and Journal of American Medical Association median 2.00 (IQR: 2.00-3.00). TikTok videos demonstrated a significantly higher engagement than Bilibili videos (P < .05), whereas Bilibili videos were longer (P < .05). Videos uploaded by hematologists received the highest scores across all 3 tools (all P < .001) but showed relatively low user engagement. No correlation was found between engagement metrics and quality scores (P > .05). Short video platforms have become an important source of AML information; however, their overall content quality is limited. Videos created by hematologists are the most reliable; however, user engagement does not reflect information quality. Professional physicians should be encouraged to actively participate in science communication, and platform regulations and algorithm optimization should be strengthened to promote the dissemination of high-quality information.

Keywords:  Bilibili; TikTok; acute myeloid leukemia; information quality; public health; short video; social media

DOI:  https://doi.org/10.1097/MD.0000000000047594
Digit Health. 2026 Jan-Dec;12:12 20552076261421072

A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms.

Bingqi Wei, Xinyue Zhang, Liu Chen, Xingyue Ren, Yijing Li, Feiyang Chen, Luwei Zhang, Yunfang Fan, Zimeng Xie, Jiarong Li, Yueyang Chen, Shangzeng Wang.

   Objective: This study aims to systematically assess the content characteristics and information quality of knee arthroplasty-related videos on TikTok and Bilibili, in order to provide evidence to support the optimization of health science communication.
Methods: On February 13, 2025, we searched for "" (knee arthroplasty in Chinese) on TikTok and Bilibili, and initially collected 100 videos from each platform according to the default sorting order, which were then subjected to further screening. Videos containing irrelevant content, lacking audio, being non-original reposts, or intended for advertising and marketing purposes were excluded. The quality and reliability of the included videos were assessed by applying four validated instruments: the modified version of DISCERN (mDISCERN), the Global Quality Score (GQS), the Video Information and Quality Index (VIQI), and the Patient Education Materials Assessment Tool (PEMAT). Interplatform variations and correlations between quality and user interactions were analyzed via Mann‒Whitney U and chi-square tests.
Results: A total of 162 knee arthroplasty related videos were analyzed, including 88 from TikTok and 74 from Bilibili. TikTok videos demonstrated higher engagement and more certified uploaders, whereas Bilibili featured more diverse professional backgrounds. Bilibili emphasizing anatomy using PPT/class based, animation/ motion and television program/documentary styles. TikTok focusing on examination/diagnosis, and treatment delivered through solo narrative and Questions and Answers (Q&A). TikTok videos achieved higher scores across all quality assessment tools. Professionally generated content consistently outperformed nonprofessional content across most quality metrics, whereas no significant difference was observed for mDISCERN. Correlation analysis showed that engagement was strongly associated with VIQI on both platforms, with additional moderate associations for GQS and PEMAT only on TikTok, while mDISCERN showed no significant correlation.
Conclusions: TikTok favors high user engagement, whereas Bilibili provides more structured educational content. Professional involvement is essential to ensure information quality and effective medical communication.

Keywords:  Bilibili; TikTok; health science; information quality; knee arthroplasty; short video platforms

DOI:  https://doi.org/10.1177/20552076261421072
BMC Cardiovasc Disord. 2026 Feb 12.

The quality and reliability of short videos about pulmonary hypertension on Bilibili and TikTok: a cross-sectional study.

Yichao Zhu, Lan Cui, Tao Zhou, Hongyang Xu.



Keywords:  Digital health; Health information; Patient education; Pulmonary hypertension; Short-video platforms; Video quality

DOI:  https://doi.org/10.1186/s12872-026-05597-z
J Cancer Educ. 2026 Feb 11.

Comment on "Analysis of Quality, Reliability, and Content of Cervical Cancer-Related Chinese Videos on TikTok".

Peikai Sun, Zhipeng Fan, Lei Li.

DOI: https://doi.org/10.1007/s13187-026-02834-z
Health Commun. 2026 Feb 09. 1-10

"Google Didn't Get a Medical Degree": Understanding the Influence of Patient Online Health Information-Seeking on Shared Decision-Making.

Lili R Romann, Elizabeth A Hintz.

Patients are engaging in unprecedented levels of online health information-seeking (e.g., via TikTok, Google). Guided by shared decision-making (SDM) theorizing, this study illuminates health care workers' (HCWs) perspectives of patients' use of online health information in clinical encounters. We identify third-party health information (i.e., health information from beyond a clinical encounter) as a decision-making agent in the SDM process. Applying reflexive thematic analysis to analyze 17 interviews with HCWs, our findings revealed how online health information influences the SDM process by shifting perceptions of decision-making orientation and heightening patients' sense of agency. Our findings also reveal how HCWs navigate SDM when patients use online health information by praising the new-age information economy, promoting mediated health literacy to moderate patient health anxiety, and prioritizing and validating patients' lived experiences. We conclude by discussing implications for SDM and practical implications for HCWs.

DOI: https://doi.org/10.1080/10410236.2026.2625978
Digit Health. 2026 Jan-Dec;12:12 20552076261418908

Facilitators and barriers to health information-seeking behavior in cancer patients: A meta-synthesis.

Wenjie Wang, Yuxing Xie, Xu Liu, Han Yan, Yujing Chen, Li Wang, Li Ning.

   Objective: This study aimed to synthesize existing qualitative evidence to explore the complex facilitators of and barriers to health information-seeking behavior (HISB) among cancer patients.
Methods: Guided by the PRISMA framework, a systematic search was conducted across multiple English and Chinese databases, including Cochrane Library, PubMed, Embase, CINAHL, PsycINFO, Web of Science, CNKI, and Wanfang. Study quality was appraised using the Joanna Briggs Institute (JBI) critical appraisal tools. Evidence from 12 eligible qualitative studies involving 230 patients was integrated and synthesized using the JBI meta-aggregation approach.
Results: The synthesis revealed a multifaceted interplay of factors influencing HISB. Patients' behaviors are primarily driven by an internal psychological process, navigating a dynamic tension between acquiring knowledge to regain a sense of control and avoiding potentially distressing information to preserve hope. Furthermore, these behaviors are significantly shaped by external contexts, particularly the dynamics of patient-provider communication, family roles, and cultural beliefs, giving rise to a complementary "online preparatory search and offline verification" strategy. Ultimately, the ability to translate information-seeking intentions into effective action is closely tied to individual competencies, including health literacy, digital literacy, and accessible socioeconomic resources.
Conclusions: This review synthesizes the facilitators of and barriers to HISB, revealing a complex system shaped by internal states, external contexts, and personal capacities. Effective information support must therefore extend beyond mere information provision to incorporate dynamic, multi-level, and personalized strategies that are responsive to patients' psychological needs, cultural backgrounds, and resource realities. The findings provide a consolidated evidence base and a holistic understanding for developing patient-centered, contextually adapted, and digitally informed health information support practices.

Keywords:  Cancer patients; facilitators and barriers; health information-seeking behavior; meta-synthesis; qualitative research

DOI:  https://doi.org/10.1177/20552076261418908
PLOS Ment Health. 2024 ;1(4): e0000017

Impaired belief revision yet intact information seeking in positive schizotypy: A modified task of bias against disconfirmatory evidence.

Wanchen Zhao, Wisteria Deng, Tyrone Cannon.

Cognitive models of delusions emphasize the role of bias against disconfirmatory evidence (BADE) in maintaining false beliefs, but sources of this tendency remain elusive. While impaired information integration could be an explanation for this tendency, the lack of information seeking motive could also result in disregard for new evidence once a (false) belief is formed. The role of information seeking in the association between psychosis-proneness and belief inflexibility has not been investigated in the context of a social interpretation task. In this study, we modified the Interpretation Inflexibility Task (IIT), which assess bias against disconfirmatory evidence in interpersonal contexts, to permit assessment of information seeking by allowing participants to skip seeing increasingly disambiguating information (in the form of pictures at varying degrees of degradation). A robust regression analysis was conducted to examine whether increasing severity of positive schizotypy is associated with more frequent skipping of later trial stages, to examine information seeking. Controlling for the number of pictures seen by participants, a robust mixed effects analysis was conducted to investigate the associations of positive schizotypy, trait anxiety, and the emotional valence of the scenario with a measure of belief revision. Participants higher in positive schizotypy did not opt out of seeing disambiguating information more frequently, p = 0.65, ß = 0.04; despite this, they still exhibited heightened belief inflexibility by rating the lures and true explanations as equally plausible, p < 0.001, ß = -0.32. These results suggest that bias against disconfirmatory evidence in positive schizotypy is unlikely a result of reduced information seeking, leaving impaired information integration as a more likely source.

DOI: https://doi.org/10.1371/journal.pmen.0000017
PLoS One. 2026 ;21(2): e0341314

"I Still Need Your Help": Online information seeking behavior of International Students in the United States on Reddit.

Sangpil Youm, Chaeeun Han, Hojeong Yoo, Sou Hyun Jang, Bonnie J Dorr.

This study examines the online information-seeking behavior of international students in the United States. Following the onset of COVID-19, their need for timely and relevant information becomes critical. Despite greater challenges than domestic students, limited research explores how international students use online platforms to meet their unique information needs. With online communities being essential sources of information and bridges for online social capital, our study analyzes the r/f1visa subreddit to examine international students' information-seeking patterns before and during the COVID-19 pandemic. Additionally, we identify unmet information needs through members' interactions and recurring questions. Our analysis reveals a shift in topics, with pandemic discussions focusing on travel, financial difficulties, and entry concerns, while pre-pandemic conversations primarily about employment. The increased similarity among recurring questions during the pandemic suggests a convergence of shared struggles that fosters solidarity and emotional support, even as many informational needs remain inadequately addressed. By examining international students' information needs through the theoretical lens of online social capital, this study contributes to understanding how crisis conditions reshape the dynamics of online communities, blurring traditional distinctions between bonding and bridging capital. The findings can inform universities, policymakers, and online community designers in developing more responsive and inclusive information environments that recognize both the instrumental and emotional support functions of digital platforms for international students.

DOI: https://doi.org/10.1371/journal.pone.0341314
Vet Rec. 2026 Feb 14. 198(4): 172-174

Avian influenza: how well is relevant biosecurity information communicated via online resources?

Rachael Tarlinton.

DOI: https://doi.org/10.1002/vetr.70426
Front Public Health. 2026 ;14 1749036

From awareness to action: exploring health information seeking behavior in coronary heart disease patients: a cross-sectional study.

Yunyu Guo, Panpan Tang, Meijuan Lan, Yuping Zhang, Xueqing Wang, Yueying Jiang, Yue Zhao, Maidiniguli Maitikuerban, Manjun Wang, Jing Shao, Dandan Chen, Zhihong Ye, Leiwen Tang.

   Introduction: Coronary heart disease (CHD) is a major global health burden requiring long-term management. Despite the essential role of health information seeking behavior (HISB) in disease self-management, current levels among CHD patients remain low, and research on its influencing factors is limited.
Objectives: This study aimed to explore HISB among patients with CHD and to identify factors associated with variations in HISB using the Risk Perception Attitude (RPA) framework.
Methods: A cross-sectional study of 330 CHD patients was conducted in China, using convenience sampling method. Data were collected through validated questionnaires assessing sociodemographic and clinical characteristics, HISB, risk perception, and self-efficacy. K-means clustering based on the RPA framework was employed to empirically identify distinct patient subgroups. Multivariate linear regression identified factors associated with of HISB within each subgroup.
Results: Four distinct subgroups were identified based on risk perception and self-efficacy: Responsive (6.7%), Proactive (41.2%), Indifference (8.2%), and Avoidance (43.9%). Multivariate regression revealed subgroup-specific factors: for Responsive, physical diagnosis and treatment risk was significant [β = 2.049, 95%CI (0.528,3.570)]; For Proactive, higher education [β = 4.725, 95%CI (2.272,7.178)], per capita monthly household income and self-efficacy were positively associated, while type of medical insurance [β = -5.814, 95%CI (-8.800, -2.828)], number of other diseases, and economic risk were negative predictors; For Indifference, only type of medical insurance was significant [β = -6.447, 95%CI (-12.503, -0.391)]; For Avoidance, older age was linked to lower HISB [β = -4.757, 95%CI (-8.525, -0.989)], whereas higher education increased it [β = 5.432, 95%CI (2.353, 8.511)].
Conclusions: This study validates the heterogeneity of CHD patients through RPA-based subgrouping, revealing that health information seeking behaviors are driven by distinct psychological and socioeconomic mechanisms across different groups. These findings underscore the limitation of uniform health education approaches and highlight the necessity of implementing subgroup-tailored strategies. By aligning clinical and public health interventions with the specific psychographic profiles of patient groups, healthcare providers can significantly enhance the precision and effectiveness of chronic disease management.
Registration: www.chictr.org.cn, identifier: ChiCTR2300069238.

Keywords:  coronary heart disease; health information seeking; risk perception; risk perception attitude framework; self-efficacy

DOI:  https://doi.org/10.3389/fpubh.2026.1749036