bims-librar Biomed News
on Biomedical librarianship
Issue of 2026–01–11
29 papers selected by
Thomas Krichel, Open Library Society
  1. Data Dilemma: Evolving Roles and Skills for Medical Librarians.
  2. Creating an Indexing Scheme for Case Series Articles.
  3. Educational interventions for improving health-related literature searching skills of health professionals and students.
  4. Concerns About Use of Artificial Intelligence (AI) in Literature Searches, Scholarly Writing, and Manuscript Reviews.
  5. Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study.
  6. Letter to the Editor regarding: evaluation of Google and ChatGPT responses to common patient questions about scoliosis.
  7. Evaluating ChatGPT-4o and DeepSeek-R1 for Patient Education in Nasopharyngeal Carcinoma Radiotherapy: a Comparative Analysis.
  8. ChatGPT as a GLP-1 Agonists Information Source: Balancing Quality, Readability, and Patient Safety.
  9. Accuracy and Readability of Chat Generative Pre-Trained Transformer-4 Omni in Answering Ophthalmology Patient Questions.
  10. Readability and quality assessment of AI-powered chatbot responses to overactive bladder patient questions: a comparative study.
  11. Rothwell Classification of AI and Internet Search Results in Blepharoplasty Related Queries.
  12. Correction to 'ChatGPT as a patient education tool in colorectal cancer-An in-depth assessment of efficacy, quality and readability'.
  13. An Analysis of the Readability of Public-Facing Information Relating to Prevention of Infectious Diseases by Vaccination.
  14. A Cross-Sectional Analysis of the Quality and Readability of Online Resources for Alopecia Areata.
  15. Readability Analysis of Commonly Cited Patient-Reported Outcome Measures in the Orthopaedic Joint Literature.
  16. Review of the Quality and Reliability of Online Arabic Content on Diabetic Retinopathy: Infodemiological Study.
  17. Assessing the quality and reliability of YouTube™ content on dental cleaning over time.
  18. Evaluation of the reliability, informational content, and quality of YouTube videos on cervical disc herniation.
  19. Expression of Concern: Quality of information in gestational diabetes mellitus videos on TikTok: Cross-sectional study.
  20. Scroll, like, diagnose? Evaluating mast cell activation syndrome information on TikTok.
  21. Bilibili and TikTok as sources of medical information on osteonecrosis of the femoral head: A cross-platform content analysis.
  22. Evaluating the quality of educational TikTok videos on diabetic retinopathy: a cross-sectional study.
  23. The quality and reliability of herpes zoster information on TikTok and Bilibili: A cross-sectional study.
  24. "Let's see if that's true": Nurses' processes and dispositions in evaluating evidence for practice.
  25. Online Questions About Clubfoot Surgery: Content Analysis and Development of a Patient Education Resource.
  26. Online Health Information-Seeking Among Older Adults and Predictors of Use, Motivations, and Barriers in the Context of Healthy Aging: Cross-Sectional Study.
  27. Dataset on patient education and digital information quality in knee cartilage restoration with matrix-induced autologous chondrocyte implantation (MACI).
  28. Queryome: Orchestrating Retrieval, Reasoning, and Synthesis across Biomedical Literature.
  29. Towards advanced AI-based solutions for securing IoMT in smart health information systems.
  1. Med Ref Serv Q. 2026 Jan 06. 1-16
    Data Dilemma: Evolving Roles and Skills for Medical Librarians.
    Sunny Chung, Mimi Byun, Nina Exner.
      Recent results show that Health Sciences and Medical Librarians have increasingly been asked to support their institutions since the NIH data sharing guidance in the last decade. This study aims to assess health sciences librarians' data skills based on the conceptual framework developed by Federer and how hteya re able to solve any gaps in knowledge or training. In this cross-sectional survey, we are looking to determine if the health science libraries are adjusting to the demands of medical data preservation and sharing support and to determine whether health sciences librarians perceive there to be a need for increased assistance for these emerging responsibilties. This study will also examine what particular areas need support (i.e. data visualization, data preservation, or supporting an institutional respository).
    Keywords:  Academic Librarianship; Data Librarianship; Data management; Data preservation; Data visualization; Health Sciences Librarian
    DOI:  https://doi.org/10.1080/02763869.2025.2602018
  2. medRxiv. 2025 Dec 29. pii: 2025.12.19.25342712. [Epub ahead of print]
    Creating an Indexing Scheme for Case Series Articles.
    Andrew Shahidehpour, Arthur W Holt, Ang Michael Troy, Joe D Menke, Neil R Smalheiser.
       Objectives: Case reports and case series comprise a significant portion of the biomedical literature, yet unlike case reports, the National Library of Medicine does not index case series as a Publication Type. This hurts clinicians' and researchers' ability to retrieve, identify and analyze evidence from this type of study.
    Materials and Methods: PubMed articles mentioning "case series" in title or abstract were characterized to learn what are considered to be case series by the authors themselves. We then set aside articles better indexed as other standard publication types - case reports, cohort studies, reviews and clinical trials -- as well as those that discuss (rather than report the results of) case series studies, to create a corpus of typical case series articles. A random sample of these articles was evaluated by two annotators who confirmed that the great majority satisfy a formal definition of "case series".
    Results: The corpus was utilized in an automated transformer-based machine learning indexing model. Case series performance of this model on hold-out data was excellent (precision = 0.887, recall = 0.952, F1 = 0.918, PR-AUC = 0.941) and manual evaluation of 100 articles tagged as "case series" revealed that 88% satisfied a formal definition of case series.
    Discussion and Conclusion: This study demonstrates the feasibility of automatically indexing case series articles. Indexing should enhance their discoverability, and hence their medical value, for evidence synthesis groups as well as general users of the biomedical literature.
    DOI:  https://doi.org/10.64898/2025.12.19.25342712
  3. Cochrane Database Syst Rev. 2026 01 07. 1 CD016153
    Educational interventions for improving health-related literature searching skills of health professionals and students.
    Julian Hirt, Magdalena Vogt, Janine Vetsch, Martin N Dichter, Jasmin Eppel-Meichlinger, Hannah Ewald, Ralph Möhler, Martin Mueller, Anne C Rahn, Gabriele Meyer, Thomas Nordhausen.
       OBJECTIVES: This is a protocol for a Cochrane Review (methodology). The objectives are as follows: To evaluate the effects of educational interventions for improving health-related literature searching skills of health professionals and students.
    DOI:  https://doi.org/10.1002/14651858.CD016153
  4. Issues Ment Health Nurs. 2025 Dec;46(12): 1175-1177
    Concerns About Use of Artificial Intelligence (AI) in Literature Searches, Scholarly Writing, and Manuscript Reviews.
    Sandra P Thomas.
      
    DOI:  https://doi.org/10.1080/01612840.2025.2587574
  5. JMIR AI. 2026 Jan 06. 5 e72101
    Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study.
    Adriano Cypriano Faneli, Rafael Scherer, Rohit Muralidhar, Marcus Guerreiro-Filho, Luiz Beniz, Verônica Vilasboas-Campos, Douglas Costa, Alessandro A Jammal, Felipe A Medeiros.
       Background: Large language models (LLMs) have been shown to answer patient questions in ophthalmology similar to human experts. However, concerns remain regarding their use, particularly related to patient privacy and potential inaccuracies that could compromise patient safety.
    Objective: This study aimed to compare the performance of an LLM in answering frequently asked patient questions about glaucoma with that of a small language model (SLM) trained locally on ophthalmology-specific literature.
    Methods: We compiled 35 frequently asked questions on glaucoma, categorized into 6 domains, including pathogenesis, risk factors, clinical manifestations, diagnosis, treatment and prevention, and prognosis. Each question was posed to both a SLM using a retrieval-augmented generation framework, trained on ophthalmology-specific literature, and to a LLM (ChatGPT 4.0, OpenAI). Three glaucoma specialists from a single institution independently assessed the answers using a 3-tier accuracy rating scale: poor (score=1), borderline (score=2), and good (score=3). Each answer received a quality score ranging from 3 to 9 points based on the sum of ratings from the 3 graders. Readability grade level was assessed using 4 formulas, such as the Flesch-Kincaid Level, the Gunning Fog Index, the Coleman-Liau Index, and the Simple Measure of Gobbledygook Index.
    Results: The answers from the SLM demonstrated comparable quality with ChatGPT 4.0, scoring mean 7.9 (SD 1.2) and mean 7.4 (SD 1.5), respectively, out of a total of 9 points (P=.13). The accuracy rating was consistent overall and across all 6 glaucoma care domains. Both models provided answers considered unsuitable for health care-related information, as they were difficult for the average layperson to read.
    Conclusions: Both models generated accurate content, but the answers were considered challenging for the average layperson to understand, making them unsuitable for health care-related information. Given the specialized SLM's comparable performance to the LLM, its high customization potential, lower cost, and ability to operate locally, it presents a viable option for deploying natural language processing in real-world ophthalmology clinical settings.
    Keywords:  ChatGPT4.0; glaucoma; large language model; online health information; small language model
    DOI:  https://doi.org/10.2196/72101
  6. Spine Deform. 2026 Jan 09.
    Letter to the Editor regarding: evaluation of Google and ChatGPT responses to common patient questions about scoliosis.
    Irene Accossato, Emmanuel Pio Pastore.
      
    DOI:  https://doi.org/10.1007/s43390-025-01267-w
  7. J Cancer Educ. 2026 Jan 05.
    Evaluating ChatGPT-4o and DeepSeek-R1 for Patient Education in Nasopharyngeal Carcinoma Radiotherapy: a Comparative Analysis.
    Zhuting Tong, Jun Xing, Ning Zhu.
      Nasopharyngeal carcinoma (NPC) is one of the most common head and neck tumors and is particularly prevalent in certain geographical regions, especially Southeast Asia. Radiotherapy remains the cornerstone of treatment; however, patients often exhibit misconceptions due to limited health literacy, which may compromise treatment adherence and outcomes. Large language models (LLMs) provide a novel approach to patient education, yet their reliability and readability in the context of radiotherapy for NPC have not been systematically evaluated. In July 2025, we conducted a comparative evaluation of ChatGPT-4o and DeepSeek-R1 in addressing educational questions related to NPC radiotherapy. The DISCERN instrument was used to assess response quality and reliability, while text readability was measured using the Flesch-Kincaid Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), and Coleman-Liau Index (CLI). Statistical analyses were performed using RStudio (v4.2.2). Both models achieved overall DISCERN scores of 51-62, indicating a "good" quality rating, with strengths in relevance and neutrality. However, deficiencies were noted in the areas of evidence currency, guideline references, and long-term side effects. DeepSeek-R1 demonstrated significantly higher readability compared with ChatGPT-4o, with a 25.6% reduction in FKGL and a 27% decrease in mean sentence length, making it more accessible for populations with limited health literacy. LLMs show substantial potential in supporting patient education for NPC radiotherapy, particularly by enhancing readability. Nonetheless, current models remain limited in terms of source transparency and completeness of clinical details. Future development should incorporate multimodal educational formats, real-time guideline integration, and structured output templates to further improve information reliability and patient support.
    Keywords:  ChatGPT; DeepSeek; Nasopharyngeal carcinoma; Patient education
    DOI:  https://doi.org/10.1007/s13187-025-02815-8
  8. J Diabetes Sci Technol. 2026 Jan 05. 19322968251409205
    ChatGPT as a GLP-1 Agonists Information Source: Balancing Quality, Readability, and Patient Safety.
    Mustafa Turgut Yildizgoren, Ibrahim Karakaya, Fatih Bagcier, Cahit Ucar.
      
    Keywords:  ChatGPT; GLP-1 receptor agonists; artificial intelligence; health information quality; readability
    DOI:  https://doi.org/10.1177/19322968251409205
  9. Ophthalmol Sci. 2026 Feb;6(2): 101007
    Accuracy and Readability of Chat Generative Pre-Trained Transformer-4 Omni in Answering Ophthalmology Patient Questions.
    Nikoo Hamzeh, Alcina K Lidder, Robert S Feder, Emmanuel A Sarmiento, Rukhsana G Mirza, Avrey J Thau, Angelo P Tanna.
       Purpose: To assess the quality of Chat Generative Pre-Trained Transformer-4 Omni (ChatGPT-4o) responses to questions submitted by patients through Epic MyChart.
    Design: Retrospective cross-sectional study.
    Participants: One hundred sixty-five patients who submitted ophthalmology-related questions via Epic MyChart.
    Methods: Questions asked by ophthalmology clinic patients related to the subspecialties of glaucoma, retina, and cornea via the Epic MyChart at a single institution were evaluated. Nonclinical questions were excluded. Each question was submitted to ChatGPT-4o twice, first without limitations and then after priming the large language model (LLM) to respond at a sixth-grade reading level. The ChatGPT-4o output and subsequent conversations were graded by 2 independent ophthalmologist reviewers as "accurate and complete," "incomplete," or "unacceptable" with respect to the quality of the output. A third subspecialist reviewer provided adjudication in cases of disagreement. Readability of the ChatGPT-4o output was assessed using the Flesch-Kincaid Grade Level and other readability indices.
    Main Outcome Measures: Quality and readability of answers generated by ChatGPT-4o.
    Results: Two hundred eighty-five queries asked by 165 patients were analyzed. Overall, 220 (77%) responses were graded as accurate and complete, 49 (17%) as incomplete, and 16 (6%) as unacceptable. The initial 2 reviewers agreed in 87% of the responses generated by ChatGPT-4o. The overall mean Flesch-Kincaid reading grade level was 12.1 ± 2.1. When asked to respond at a sixth-grade reading level, 242 (85%) responses were graded as accurate and complete, 38 (13%) were incomplete, and 5 (2%) were graded as unacceptable.
    Conclusions: Chat Generative Pre-Trained Transformer-4 Omni usually provides accurate and complete answers to the questions posed by patients to their glaucoma, retina, and cornea subspecialists. A substantial proportion of the responses were, however, graded as incomplete or unacceptable. Chat Generative Pre-Trained Transformer-4 Omni responses required a 12th-grade education level as assessed by Flesch-Kincaid and other readability indices, which may make them difficult for many patients to understand; however, when prompted to do so, the LLM can generate responses at a sixth-grade reading level without a compromise in response quality. Chat Generative Pre-Trained Transformer-4 Omni can potentially be used to answer clinical ophthalmology questions posed by patients; however, additional refinement will be required prior to implementation of such an approach.
    Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
    Keywords:  Artificial intelligence; ChatGPT-4o; Ophthalmology; Patient questions; Readability
    DOI:  https://doi.org/10.1016/j.xops.2025.101007
  10. BMC Urol. 2026 Jan 08.
    Readability and quality assessment of AI-powered chatbot responses to overactive bladder patient questions: a comparative study.
    Mutlu Deger, Tunahan Ates, Ismail Onder Yilmaz, Mehmet Gurkan Arıkan, Ibrahim Halil Sukur, Fesih Ok, Nebil Akdogan, Volkan Izol.
       INTRODUCTION: Overactive bladder (OAB) is a common urological condition affecting millions of people worldwide, significantly reducing their quality of life. Patient compliance and active participation in disease management are critical to achieving successful outcomes. This study aims to understand the potential role of AI-assisted chatbots in educating patients with OAB and their impact on health literacy.
    METHODS: We compared responses from four AI chatbots (ChatGPT, DeepSeek, Claude, and Gemini) to 16 standardized questions from the AUA Overactive Bladder Patient Guide. Two board-certified urologists independently evaluated responses using Ensuring Quality Information for Patients (EQIP) tool and Google E-E-A-T principles.
    RESULTS: Inter-rater reliability was excellent (ICC = 0.97 for EQIP, κ = 0.89 for E-E-A-T). A significant difference was found between chatbots in terms of readability scores (Gunning Fox Index p = 0.008, Flesch-Kincaid Grade Level p < 0.001), with all responses requiring education levels above the recommended 6th-8th grade. However, significant differences emerged in information quality (EQIP, p < 0.001; E-E-A-T, p < 0.001). Gemini demonstrated superior performance in both EQIP (60.2 ± 6.92) and E-E-A-T scores (13.5) compared to all other chatbots.
    CONCLUSION: AI chatbots show potential for patient education but produce content with readability levels too complex for general audiences. Significant quality variations exist between models. These findings emphasize the need for collaboration between healthcare professionals and AI developers to create more accessible, reliable health information systems.
    Keywords:  AI; Chatbot; Large language model; Overactive bladder; Patient information
    DOI:  https://doi.org/10.1186/s12894-025-02033-w
  11. J Craniofac Surg. 2026 Jan 08.
    Rothwell Classification of AI and Internet Search Results in Blepharoplasty Related Queries.
    Alexandrea S Collins, Taylor E Kring, Mark Jessup, Rohan Mangal, Seth R Thaller.
      Patients increasingly turn to online search engines and artificial intelligence (AI) tools to gather information about blepharoplasty, yet the accuracy and reliability of these sources remain uncertain. In this study, ten blepharoplasty-related search terms were entered into Google Chrome using a standardized, depersonalized browser. For each term, the Google Gemini AI-generated response and the top 50 "People Also Ask" (PAA) questions were collected. Questions were categorized using the Rothwell classification system and subcategorized by topic. Most questions were fact-based (53%), with technical details (25.6%) and cost (18.6%) being the most frequent subtopics. The majority of linked webpages originated from single-surgeon or medical practice sites (39.0% and 24.7%), which demonstrated the lowest average JAMA scores (1.67 and 1.83). In contrast, peer-reviewed journals and academic sources achieved the highest JAMA scores but were rarely represented among results. Google Gemini responses predominantly referenced academic sources (60%) and achieved higher average JAMA scores (2.40) than webpages retrieved through PAA. Overall, online blepharoplasty information is highly variable and frequently falls short of established standards for authorship, attribution, and reliability. Although AI-generated responses demonstrated superior quality compared with traditional search results, inconsistencies in source citation remain a concern. These findings highlight the ongoing need for quality oversight of online medical content and suggest that, when properly regulated, AI tools may serve as valuable adjuncts in patient education.
    Keywords:  Blepharoplasty; JAMA benchmark criteria; Rothwell classification; eyelid surgery
    DOI:  https://doi.org/10.1097/SCS.0000000000012365
  12. Colorectal Dis. 2026 Jan;28(1): e70367
    Correction to 'ChatGPT as a patient education tool in colorectal cancer-An in-depth assessment of efficacy, quality and readability'.
      
    DOI:  https://doi.org/10.1111/codi.70367
  13. Br J Biomed Sci. 2025 ;82 15435
    An Analysis of the Readability of Public-Facing Information Relating to Prevention of Infectious Diseases by Vaccination.
    Beverley C Millar, Callum Peters, John E Moore.
       Purpose: The readability of public-facing vaccine-related information is an important aspect of health literacy particularly regarding vaccine uptake. The aims of this study were to analyse the readability of such written literature and to provide recommendations, for improvement.
    Methods: Readability of vaccine-related information (ntotal = 240) from publicly available sources (n = 20 per category), including PubMed Abstracts, Expert Review of Vaccines (ERV) and Cochrane Reviews (CR), paired plain language and scientific abstracts, public health materials, clinical trial summaries and vaccine patient information leaflets, were assessed using the Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), SMOG and Gunning Fog readability metrics using the readability software tool readable.com.
    Results: Vaccine-related information for all sources had poor readability across all readability metrics with 90.8% and 94.6% not reaching the target FKGL (≤8) (mean 12 ± 3.2 sd) and FRE (≥60) (mean 34 ± 17 sd). Plain language summaries had improved readability, but did not reach reference targets. Scientific abstract and plain language scores for the CR were FRE (mean 25 ± 7.2 sd; median 25) versus (mean 37 ± 8.6 sd; median 36) p < 0.0001), respectively and for ERV FRE the scientific abstract (mean 18 ± 11 sd; median 17) versus the plain language score (mean 26 ± 11 sd; median 28) p = 0.002), respectively, indicating an improvement in readability scores for plain language summaries but again not reaching reference targets.
    Conclusion: The readability of public-facing vaccination materials is currently not optimum. The readability can be improved through the employment of readability calculators and ensuring, where possible, the use of mono-syllable words and less than fourteen words per sentence. The preparation of public-facing materials with improved readability scores will help aid in the promotion of health literacy and in turn promote vaccination uptake.
    Keywords:  immunisation; infectious diseases; lay stakeholders; lay writing; readability; scientific communication; vaccination; vaccine
    DOI:  https://doi.org/10.3389/bjbs.2025.15435
  14. J Cutan Med Surg. 2026 Jan 06. 12034754251410176
    A Cross-Sectional Analysis of the Quality and Readability of Online Resources for Alopecia Areata.
    Eric McMullen, Grace Xiong, Sana Gupta, Christopher Shenouda, Ashlyn Nguyen, Dea Metko, Shireen Dumont, Ilya Mukovozov, Jeffrey Donovan, Cathryn Sibbald.
      
    Keywords:  alopecia areata; online resources; readability
    DOI:  https://doi.org/10.1177/12034754251410176
  15. Arthroplast Today. 2026 Feb;37 101922
    Readability Analysis of Commonly Cited Patient-Reported Outcome Measures in the Orthopaedic Joint Literature.
    Harjot Uppal, Daniel Garcia, Kevin Rezzadeh, Nikhil Sahai, Andrew McGinniss, Arash Emami, Aiman Rifai.
       Background: Patient-reported outcome measures (PROMs) are vital for assessing surgical effectiveness and capturing patient perspectives on function, symptoms, and quality of life. To ensure patients can accurately complete these tools, readability is essential. The National Institutes of Health and American Medical Association recommend patient materials be written at or below a 6th-grade reading level. This study evaluated the readability of commonly cited PROMs in the orthopaedic joint literature to assess compliance with these standards.
    Methods: Thirty-five PROMs were analyzed using 2 validated readability metrics: the Flesch Reading Ease Score (FRES) and the Simple Measure of Gobbledygook (SMOG) Index. A FRES ≥80 or SMOG <7 indicated 6th-grade readability. Scores were calculated using an online readability calculator and compared to National Institutes of Health and American Medical Association guidelines.
    Results: The average FRES was 67 (range, 21-90), and the average SMOG Index was 8 (range, 6-12), indicating an overall 8th- to 9th-grade reading level. Only 6 PROMs (17%) met the readability threshold. Among the least readable were the University of California, Los Angeles Activity Score, Modified Cincinnati Knee Rating System, Hamilton Depression Rating Scale, Western Ontario and McMaster Universities Osteoarthritis Index, Kujala Score, International Knee Documentation Committee score, and Tampa Scale of Kinesiophobia.
    Conclusions: Most PROMs commonly cited in the orthopaedic joint literature are written above the recommended 6th-grade level, which may compromise patient understanding and data quality. Improving readability through revision or development of new tools may enhance patient accessibility and the accuracy of reported outcomes.
    Keywords:  Hip; Knee; Patient advocacy; Patient-reported outcome measures; Readability
    DOI:  https://doi.org/10.1016/j.artd.2025.101922
  16. JMIR Infodemiology. 2026 Jan 07. 6 e70514
    Review of the Quality and Reliability of Online Arabic Content on Diabetic Retinopathy: Infodemiological Study.
    Abdullah Ahmed Alabdrabulridha, Dalal Mahmoud Alabdulmohsen, Maryam Abdullah AlNajjar, Ibtisam Ahmed Algouf, Abdullah Mohammed Al-Omair, Omaima Muneer Alyahya, Mesa Ahmed Almahmudi, Abdulaziz Ahmed Al Taisan.
       Background: Diabetic retinopathy (DR) is a leading cause of vision loss, particularly in the Middle East. With the rise of online health information, many patients turn to the internet for knowledge about health conditions. However, the accuracy and quality of this information can be questionable, particularly in languages other than English.
    Objective: We sought to evaluate the quality and reliability of Arabic websites on DR to address this knowledge gap and improve patient care.
    Methods: The first 100 Arabic search results for DR were examined on Google, focusing on patient education websites in Arabic. Content was assessed using a 20-question model, quality was evaluated with the DISCERN instrument, and reliability was measured using the Journal of the American Medical Association (JAMA) benchmark. Two independent raters conducted evaluations, and data were analyzed with SPSS (IBM Corp). Descriptive statistics were used for website characteristics, and the first 10 Google web pages were compared to others using bivariate analysis with a significance level of P<.05.
    Results: A Google search yielded 178,000 websites, and the first 100 were examined, with 29 meeting inclusion criteria. Most were hospital or medical center sites (n=20, 69%). The DISCERN assessment showed a low mean score of 36.59(SD 9.32) out of 80 points, with most rated "poor" or "very poor." The JAMA benchmarks indicated low reliability, with 62% (18/29) failing to meet any criteria.
    Conclusions: This study identified significant failings in the content, quality, and reliability of Arabic websites on diabetic retinopathy, highlighting the need for stronger evidence-based online resources focused on early disease prevention.
    Keywords:   JAMA ; Journal of the American Medical Association ; DISCERN; arabic content; diabetes; diabetic retinopathy; health education; internet; online; online health information; quality; reliability; retinopathy; website
    DOI:  https://doi.org/10.2196/70514
  17. Inform Health Soc Care. 2026 Jan 06. 1-11
    Assessing the quality and reliability of YouTube™ content on dental cleaning over time.
    Merve Akbaş, Nülüfer Demir, Beyza Bozoklu, Duygu Yaman.
       BACKGROUND: YouTube has become a major source of health information, including content on dental cleaning. However, reliability and quality of videos remain unclear. This study evaluated quality and reliability of YouTube videos related to dental cleaning by comparing two time periods: before and after the COVID-19 pandemic.
    METHODS: Google Trends identified "dental cleaning" as the most searched term related to non-surgical periodontal therapy. Two periodontists evaluated the 100 YouTube™ videos from 2019 and 2024 using VIQI, DISCERN, Modified DISCERN, GQS, and a customized content analysis. Statistical analyses were conducted using IBM SPSS 26.0.
    RESULTS: A total of 28 videos from 2019 and 34 videos from 2024 were included. GQS scores were significantly higher in 2019 compared to 2024 (p < .001). In both years, "useful" videos had longer durations, higher DISCERN (p < .05), Modified DISCERN (p < .05), GQS (p = .001), and VIQI scores (p < .001). Content Analysis scores were positively correlated with all quality indices (p < .001).
    CONCLUSION: Despite an increase in the number of useful videos according to Customized Content Index in 2024, the overall quality and reliability of YouTube™ videos on dental cleaning remain limited, highlighting the need for more accurate and professional content.
    Keywords:  COVID-19; Dental cleaning; YouTube; videos
    DOI:  https://doi.org/10.1080/17538157.2025.2606850
  18. J Back Musculoskelet Rehabil. 2026 Jan 06. 10538127251412592
    Evaluation of the reliability, informational content, and quality of YouTube videos on cervical disc herniation.
    Menekse Gok Simsek, Emine Isil Ustun, Banu Aydeniz, Turker Suleymanoglu, Sibel Caglar.
      BackgroundYouTube has become a widely used resource for patients and healthcare professionals seeking information on cervical disc herniation. However, the reliability and quality of online content show substantial variability.ObjectiveTo evaluate the reliability, informational content and quality of YouTube videos related to cervical disc herniation.MethodsThis cross-sectional study included YouTube videos related to cervical disc herniation, identified through searches using the terms "cervical disc herniation," "disc herniation of cervical spine," and "herniated cervical disc." Video characteristics such as duration, views, likes, comments, and content creator profiles were recorded. Reliability and quality were assessed using the DISCERN instrument, the Journal of the American Medical Association (JAMA) benchmark criteria, and the Global Quality Scale (GQS).ResultsA total of 300 videos (100 for each search term) were initially retrieved. After excluding duplicates, non-English, irrelevant, or very short videos, 104 unique videos were included in the study. Of the included videos, 41.3% were uploaded by physicians, 30.7% by non-physician healthcare professionals, 14.4% by medical channels, 8.7% by healthcare institutions, and 4.8% by patients. The mean DISCERN score was 35.3 ± 7.6, the mean JAMA score was 2.4 ± 0.6, and the mean GQS score was 3.5 ± 0.8, indicating generally poor to fair quality. The median (range) scores were 35.0 (17.0-58.0) for DISCERN, 2.0 (1.0-4.0) for JAMA, and 4.0 (1.0-5.0) for GQS. According to JAMA, 55.8% of the videos scored 2 points, reflecting low reliability, while only 2.9% achieved the maximum score of 4. In GQS, 52.9% were rated as high quality, 38.5% as moderate, and 8.6% as low. Correlation analyses showed that longer video duration was positively associated with higher DISCERN (r = 0.41-0.57, p < 0.001), JAMA (r = 0.36, p < 0.001), and GQS scores (r = 0.35, p < 0.001).ConclusionMost of the included YouTube videos on cervical disc herniation demonstrated low to moderate reliability. These findings emphasize the need for healthcare professionals and patients to critically appraise such content, and they highlight the importance of developing higher-quality, evidence-based online educational resources.
    Keywords:  DISCERN instrument; Global Quality Scale; JAMA benchmark criteria; YouTube videos; cervical disc herniation; reliability; video quality
    DOI:  https://doi.org/10.1177/10538127251412592
  19. PLoS One. 2026 ;21(1): e0340234
    Expression of Concern: Quality of information in gestational diabetes mellitus videos on TikTok: Cross-sectional study.
    PLOS One Editors
      
    DOI:  https://doi.org/10.1371/journal.pone.0340234
  20. Allergy Asthma Proc. 2026 Jan 01. 47(1): e1-e3
    Scroll, like, diagnose? Evaluating mast cell activation syndrome information on TikTok.
    Emily Gansert, Ricardo J Estrada-Mendizabal, Matthew M Farley, Dayne H Voelker, Alexei Gonzalez-Estrada.
      Background: One in five Americans turn to TikTok before calling their own physician. Objective: With social media on the rise as a source of health-related information, we aimed to investigate and evaluate popular content about mast cell activation syndrome (MCAS) on TikTok. Methods: Between June 14 and 16, 2024, four different MCAS-relevant phrases were searched on TikTok, and the top 50 most watched videos were analyzed independently by three subinvestigators. The global quality score (GQS) (range from 1 to 5) was applied to assess the value of the educational videos. The profession of the content creator, use of MCAS Vienna diagnostic criteria, association with postural orthostatic syndrome (POTS)/Ehlers Danlos syndrome (EDS), and information trends were also analyzed. Results: The 50 most watched MCAS-related videos collectively had > 6.5 million views, and the average number of views per video was 131,500. Most videos were created by health-care professionals (58%), including physicians (26%) and other health-care professionals (32%), whereas the minority were created by non-health-care professionals (42%). Only one video included the MCAS Vienna criteria (2%), and 12 videos associated MCAS with POTS and/or EDS (24%). The average GQS was 1.94 (SD 0.34). Common MCAS misinformation trends included the following: inaccuracy of symptoms, diagnostic criteria, triggers, and treatment options. Conclusion: Most MCAS videos on TikTok contained misinformation, did not include key diagnostic criteria, and had poor GQS. The most viewed videos were primarily created by health-care professionals. Patients and health-care providers need to be aware of the quality of health-care information on social media.
    DOI:  https://doi.org/10.2500/aap.2026.47.250090
  21. Digit Health. 2026 Jan-Dec;12:12 20552076251411032
    Bilibili and TikTok as sources of medical information on osteonecrosis of the femoral head: A cross-platform content analysis.
    Bingqi Wei, Liu Chen, Xinyue Zhang, Yijing Li, Jiarong Li, Xingyue Ren, Hang Li, Luwei Zhang, Yunfang Fan, Jiani Meng, Feiyang Chen, Zimeng Xie, Yifan Qi, Yueyang Chen, Shangzeng Wang.
       Background: Osteonecrosis of the femoral head is a disabling orthopedic condition often diagnosed late due to limited public awareness. Social media platforms such as Bilibili and TikTok have become key sources of health information, yet the quality of content varies widely.
    Methods: We searched Bilibili and TikTok on February 12, 2025, using the Chinese term "" (osteonecrosis of the femoral head), which serves as both the scientific and commonly used colloquial expression. A total of 162 videos were analyzed using the modified DISCERN (mDISCERN), Global Quality Score, Video Information and Quality Index (VIQI), and Patient Education Materials Assessment Tool evaluation tools. User engagement metrics and content quality scores were compared between platforms using the Mann-Whitney U test and the Chi-square test.
    Results: TikTok videos demonstrated significantly higher user engagement, reflected by greater numbers of likes, favorites and comments. However, Bilibili hosted a wider range of creators and provided more in-depth examination and diagnosis-oriented content. TikTok achieved higher scores in overall video quality (mDISCERN-sum and VIQI-sum), particularly in information flow，information accuracy and understandability, whereas Bilibili performed better in actionability, offering more detailed procedural or instructional guidance. Professional creators produced videos with higher scores in information flow and information accuracy, whereas non-professionals achieved higher actionability scores.
    Conclusion: TikTok and Bilibili serve complementary functions in osteonecrosis of the femoral head (ONFH) education: TikTok enhances awareness of early symptoms, while Bilibili supports deeper understanding of imaging, staging and treatment. Building on these strengths, future digital health efforts should integrate professional expertise, improve content governance and apply AI-assisted tools to deliver accurate, accessible and actionable ONFH information for earlier detection and better disease management.
    Keywords:  Bilibili; TikTok; health information quality; medical science; osteonecrosis of the femoral head; short video platform
    DOI:  https://doi.org/10.1177/20552076251411032
  22. Front Public Health. 2025 ;13 1718587
    Evaluating the quality of educational TikTok videos on diabetic retinopathy: a cross-sectional study.
    Ligang Jiang, Wencan Wu, Xin Jiang, Fangzheng Jiang.
       Background: Diabetic retinopathy (DR) is a leading cause of vision loss among working-age adults, and enhancing public health literacy through effective education is crucial for its prevention and management. With the rise of mobile internet and short video platforms such as TikTok, new opportunities have emerged for disseminating medical knowledge. However, concerns remain regarding the accuracy and quality of this content.
    Methods: A cross-sectional search was conducted on September 18, 2025. A total of 200 Mandarin-language TikTok videos directly relevant to DR were included after screening. Baseline characteristics, uploader type, and user engagement metrics were extracted. Video quality was assessed independently by two trained reviewers using the DISCERN tool and the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V). Content coverage was evaluated against the American Academy of Ophthalmology (AAO) Preferred Practice Pattern®. Inter-rater reliability was measured by intraclass correlation coefficients (ICCs). Group comparisons and correlation analyses were performed.
    Results: Significant differences were observed in quality scores across uploader categories (one-way ANOVA, p < 0.001). Non-profit organizations achieved the highest DISCERN scores (59.4 ± 8.2) and PEMAT-A/V understandability (88.5%), while for-profit accounts had the lowest DISCERN scores (23.0 ± 6.5; understandability 61.5%). Videos from non-profit sources also demonstrated balanced coverage across six core DR themes (14-20% per theme). Inter-rater reliability was excellent for all tools (ICC range 0.825-0.933). Engagement metrics were strongly correlated with DISCERN scores (likes r = 0.76, comments r = 0.64, favorites r = 0.73, shares r = 0.71; all p < 0.05), whereas video duration showed no significant correlation with quality (p > 0.05).
    Conclusion: The quality of DR-related educational short videos on TikTok varies widely, with the source of the video emerging as the key determinant. High-quality content from non-profit organizations and medical professional users not only demonstrates greater reliability but also fosters comprehensive health education. Strengthening professional participation, platform regulation, and evidence-informed communication strategies is essential to maximize the potential of short videos in DR health education and ultimately improve patient outcomes.
    Keywords:  TikTok; diabetic retinopathy; health education; social media; video quality
    DOI:  https://doi.org/10.3389/fpubh.2025.1718587
  23. Digit Health. 2026 Jan-Dec;12:12 20552076251412693
    The quality and reliability of herpes zoster information on TikTok and Bilibili: A cross-sectional study.
    Kaidi Zhao, Jiashu Liu.
       Objective: Herpes zoster (HZ) is a common viral skin disease. As short video platforms have become an important source of health information, evaluating the quality of HZ-related content is increasingly important.
    Methods: This cross-sectional study analyzed 186 HZ-related videos collected from the Chinese short video platforms TikTok (n = 96) and Bilibili (n = 90) from 12 to 16 July 2025. Video characteristics (duration, likes, shares, comments, and collections), content domains (etiology, clinical manifestations, diagnosis, treatment, and prognosis), and uploader identity were recorded. Quality was evaluated using the Global Quality Score (GQS) and modified DISCERN (mDISCERN).
    Results: TikTok videos had shorter durations (47.5 vs.196.0 seconds) but significantly higher engagement metrics, including likes (481.5 vs. 29.5), comments (20.5 vs. 3.5), and shares (152.5 vs. 19.0). Most videos were uploaded by pain medicine specialists (31.72%), followed by traditional Chinese medicine physicians (27.96%) and dermatologists (19.35%). Treatment was the most frequently addressed topic (67.74%), whereas prognosis was least discussed (18.28%). The median GQS was 2.00 (interquartile range (IQR): 1.00-3.00) and the mDISCERN score was 3.00 (IQR 1.00-3.00). Dermatologists achieved higher GQS and mDISCERN scores than patients and traditional Chinese medicine physicians (p < 0.05). No significant correlations were observed between engagement metrics and GQS scores (p > 0.05).
    Conclusions: HZ-related videos on short video platforms are of moderate quality and skewed toward treatment. Dermatologists involvement and better content regulation are needed. More emphasis should be placed on prognosis education to enhance public understanding.
    Keywords:  Bilibili; HZ; TikTok; health communication; video quality assessment
    DOI:  https://doi.org/10.1177/20552076251412693
  24. Nurs Outlook. 2026 Jan 03. pii: S0029-6554(25)00314-8. [Epub ahead of print]74(2): 102661
    "Let's see if that's true": Nurses' processes and dispositions in evaluating evidence for practice.
    Elizabeth Betsy S Hopkins, Brandon Patterson, Anne R Diekema, Nena Schvaneveldt.
       BACKGROUND: Evaluation of information is central to successful evidence-based practice, especially today when nurses are exposed to many information sources.
    PURPOSE: Here, we report on the processes and dispositions nurses display when evaluating information, along with additional observations relevant to evidence-based practice.
    METHODS: Our data comes from the qualitative portion of a mixed-methods study. We conducted 18 semi-structured interviews with nurses from a variety of specialties.
    DISCUSSION: The processes nurses used included fact-checking, examining criteria, looking for cited references, and group decision-making. Nurses demonstrated dispositions of trusting or distrusting source provenance, organizations, and credentials or role.
    CONCLUSION: While nurses are showing some positive evaluation behaviors, other findings are quite concerning. In particular, blindly trusting or mistrusting sources and relying only on existing knowledge to assess the information could lead nurses to incorrect evaluation judgments and prevent new research findings from being integrated into practice.
    Keywords:  Evidence-based practice; Information appraisal; Information evaluation; Nurses
    DOI:  https://doi.org/10.1016/j.outlook.2025.102661
  25. J Pediatr Soc North Am. 2026 Feb;14 100296
    Online Questions About Clubfoot Surgery: Content Analysis and Development of a Patient Education Resource.
    Camila Vicioso, Julian Javier, Jonathan J Huang, Rodnell B Torres, Uma Balachandran, Katrina Nietsch, Auston R Locke, Niklas H Koehne, Renee Ren, Nicholas Tully, Sheena C Ranade.
       Background: Clubfoot affects approximately 2 in 1,000 newborns globally. The Ponseti Method, the standard method of casting and bracing, often ends with Achilles tenotomy. More invasive procedures, such as posteromedial release, are typically reserved for complex or recurrent cases. Prior studies indicate that parents frequently turn to the internet to understand clubfoot treatments, though no studies have examined specific questions or the credibility of websites. This study identifies the most common online questions about clubfoot surgeries, assesses the credibility and types of sources answering them, and offers a handout of suggested resources.
    Methods: We extracted 1,207 question-website pairs from Google's "People Also Ask" feature using keywords on clubfoot surgeries. Questions were categorized using Rothwell's Classification System. Websites were evaluated for credibility using the Journal of the American Medical Association (JAMA) Benchmark Criteria.
    Results: A total of 992 question-website pairs were included for analysis. Most questions were fact-based (68.1%), focusing on technical details (49.2%), risks (13.2%), and recovery (10.3%). Academic websites were most frequent (55.9%). Sources were moderately credible (mean JAMA score = 1.79). Private medical practices, often linked to queries about percutaneous options, displayed the lowest credibility (mean JAMA score = 0.5).
    Conclusion: Most online queries about clubfoot surgery focus on procedural details, risks, and recovery, reflecting the specific concerns that families seek to address when considering treatment. The high repetition of websites lacking high credibility and showing limited diversity of search results suggests a gap in accessible, comprehensive online resources. Our findings emphasize the need for clinician awareness of this digital landscape and for proactive educational strategies. To help address this, we developed a curated, patient-facing handout that can be used to link families to credible sources, support informed decision-making, and enhance communication between parents and pediatric orthopaedic surgeons.
    Key Concepts: (1)Parents frequently search online for information about clubfoot surgeries, with questions most often focused on procedural details, risks, and recovery.(2)The majority of responses come from academic websites, though overall online credibility is variable, with important differences across source types.(3)Queries about posteromedial release emphasize technical details, while percutaneous procedures prompt more questions about risks, recovery, and outcomes.(4)The limited diversity and variable credibility of commonly accessed online resources highlight the need for more accessible, trustworthy educational content for families.(5)A curated, patient-facing handout linking families to reliable resources can support informed decision-making and enhance communication between caregivers and pediatric orthopaedic surgeons.
    Level of Evidence: IV.
    Keywords:  Clubfoot; Clubfoot surgery; Google search; Online health information; Patient education; Pediatric orthopaedics
    DOI:  https://doi.org/10.1016/j.jposna.2025.100296
  26. Online J Public Health Inform. 2026 Jan 06. 18 e77557
    Online Health Information-Seeking Among Older Adults and Predictors of Use, Motivations, and Barriers in the Context of Healthy Aging: Cross-Sectional Study.
    Yves Bachofner, Alexander Seifert, Samin Sepahniya, Carlo Fabian.
       Background: Considering the rapid digital transformation, older adults are increasingly relying on online health information-seeking (OHIS) to support healthy aging. However, disparities in their digital competence levels (the ability to effectively use digital tools) and health literacy (the ability to access, understand, appraise, and apply health information) may influence engagement in OHIS.
    Objective: This paper examines the prevalence of OHIS among older adults in Switzerland and identifies their motivations, barriers, and predictors of use. The objective is to determine key factors that promote or hinder OHIS use among older internet users.
    Methods: A cross-sectional survey was conducted with 1261 internet users aged 60 years and older living in Switzerland (mean age 70.1, SD 7.3 years; 539/1261, 42.7% female). Descriptive analyses and hierarchical binary logistic regression models were used.
    Results: Overall, 77.6% (969/1248) of participants engaged in OHIS in their everyday lives. Subjective health status, internet use frequency, trust in online health information (OHI), and digital competence level significantly influenced OHIS use. Participants reporting good to very good health were less likely to engage in OHIS compared to those in poorer health (odds ratio [OR] 0.496, 95% CI 0.307-0.801; P=.004). Higher likelihood of OHIS use was associated with (almost) daily versus less frequent internet use (OR 1.550, 95% CI 1.011-2.376; P=.04), general trust versus distrust in OHI (OR 5.784, 95% CI 4.044-8.272; P<.001), and advanced versus low digital competence (OR 3.108, 95% CI 1.385-6.975; P=.006); health literacy was not a significant predictor of OHIS use (OR 0.912, 95% CI 0.393-2.117; P=.83, excellent vs deficient [reference]). Among OHIS users (n=969), the most common frequently indicated motivation for use (672/969, 69.3%) was to gain a better understanding of health conditions. Among nonusers (n=279), the most frequently indicated barriers were difficulties in assessing the credibility of information (159/279, 57%), distrust in the effectiveness of information provided (129/279, 46.2%), and concerns about dubious providers or spam (93/279, 33.3%).
    Conclusions: Digital competence, frequent internet use, and trust in OHI are critical for OHIS engagement among older adults. Programs to strengthen digital competencies in later life and initiatives to enhance the credibility of online health resources are essential to reduce digital disparities and support healthy aging. Notably, health literacy did not emerge as a significant factor in OHIS use, but digital competence did, suggesting that digital competence is most critical to OHIS use.
    Keywords:  Switzerland; aging; cross-sectional study; digital competence; health literacy; healthy aging; internet; older adults; online health information seeking
    DOI:  https://doi.org/10.2196/77557
  27. Data Brief. 2026 Feb;64 112353
    Dataset on patient education and digital information quality in knee cartilage restoration with matrix-induced autologous chondrocyte implantation (MACI).
    Camila Vicioso, Hannah L Terry, Ava G Neijna, Sabrina M Strickland.
      This dataset provides a comprehensive collection and classification of publicly available online questions and linked websites related to matrix-induced autologous chondrocyte implantation (MACI), an implant that can be utilized by orthopaedic surgeons for patients requiring knee cartilage restoration. Eight MACI-related search terms were entered individually into a history-cleared Google Chrome browser in incognito mode to minimize personalization bias. For each term, the "People Also Ask" feature was expanded to retrieve approximately 200 question-website pairs, yielding a total of 1620 entries that were compiled and screened for relevance. The final dataset includes 1107 unique, relevant question-website pairs organized in a spreadsheet containing variables for search term, question text, linked website, website source type, Rothwell classification (Fact, Policy, or Value) and subcategories, JAMA Benchmark Criteria component scores, total JAMA credibility score, and thematic grouping based on question content and author consensus. Each entry was rated independently by two reviewers, with discrepancies resolved by the primary author using an Excel-based verification process. Descriptive statistics and logistic regression were performed in Python (statsmodels, SciPy). The dataset is accompanied by materials outlining classification frameworks, frequently repeated questions, and commonly linked websites. By documenting how patients search for and encounter information on a popular cartilage restoration option, this dataset provides a model for evaluating digital health resources and developing accurate, accessible educational content for patients and clinicians across medical disciplines.
    Keywords:  Digital health literacy; Health communication; Healthcare educational content development; Online health resources; Orthopaedic surgery; Orthopaedic surgery education; Patient engagement; Search engine analysis
    DOI:  https://doi.org/10.1016/j.dib.2025.112353
  28. bioRxiv. 2025 Dec 24. pii: 2025.12.22.696019. [Epub ahead of print]
    Queryome: Orchestrating Retrieval, Reasoning, and Synthesis across Biomedical Literature.
    Pranav Punuru, Nabil Ibtehaz, Swagarika Giri, Harsha Srirangam, Emilia Tugolukova, Daisuke Kihara.
      The rapid expansion of biomedical literature has made comprehensive manual synthesis increasingly difficult to perform effectively, creating a pressing need for AI systems capable of reasoning across verified evidence rather than merely retrieving it. However, existing retrieval-augmented generation (RAG) methods often fall short when faced with complex biomedical questions that require iterative reasoning and multi-step synthesis. Here, we developed Queryome, a deep research system consisting of specialized large language model (LLM) agents that can adapt their orchestration dynamically to a wide range of queries. Using a hybrid semantic-lexical retrieval engine spanning 28.3 million PubMed abstracts, it performs iterative, evidence-grounded synthesis. On the MIRAGE benchmark, Queryome achieved 88.98 % accuracy, surpassing prior systems by up to 14 points, and improved reasoning accuracy on the biomedical Human's Last Exam (HLE) subset from 15.8% to 19.3%. Moreover, in a task for constructing a review article, it earned the highest composite score in comparison with Deep Research from OpenAI, Google, Perplexity, and Scite.AI, reflecting its strong literature retrieval and synthesis capabilities.
    DOI:  https://doi.org/10.64898/2025.12.22.696019
  29. Sci Rep. 2026 Jan 07.
    Towards advanced AI-based solutions for securing IoMT in smart health information systems.
    Xin Liu.
      
    Keywords:  Bidirectional gated recurrent unit; Cybersecurity; Internet of medical things; Refined black-winged kite algorithm; Smart health information systems
    DOI:  https://doi.org/10.1038/s41598-025-31850-0
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