bims-librar Biomed News
on Biomedical librarianship
Issue of 2025–01–19
35 papers selected by
Thomas Krichel, Open Library Society
  1. Bridging the health information gap among undergraduate university students: The role of academic libraries.
  2. A Catalyst to Better Searching: Tackling Health Inequities with a Novel Interactive eResource.
  3. The role of information science within the clinical translational science ecosystem.
  4. Development and validation of a search strategy and an automated classifier for retrieving temporomandibular disorders studies.
  5. Validation of the eHealth literacy scales: comparison between the shorter and longer versions.
  6. Indexing of Journals and Indices of Publications.
  7. ChatGPT is an Unreliable Source of Peer-Reviewed Information for Common Total Knee and Hip Arthroplasty Patient Questions.
  8. Transformer-Based Tool for Automated Fact-Checking: A Pilot Study on Online Health Information.
  9. Title: Can ChatGPT 4.0 Reliably Answer Patient Frequently Asked Questions About Boxer's Fractures?
  10. Evaluation of ChatGPT-4 Performance in Answering Patients' Questions About the Management of Type 2 Diabetes.
  11. Comparative Performance of the Leading Large Language Models in Answering Complex Rhinoplasty Consultation Questions.
  12. Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19 Impacts in Pregnancy: A Cross-Sectional Pilot Study.
  13. Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.
  14. Use of generative large language models for patient education on common surgical conditions: a comparative analysis between ChatGPT and Google Gemini.
  15. A Study of Orthopedic Patient Leaflets and Readability of AI-Generated Text in Foot and Ankle Surgery (SOLE-AI).
  16. Pediatric Supracondylar Humerus and Diaphyseal Femur Fractures: A Comparative Analysis of Chat Generative Pretrained Transformer and Google Gemini Recommendations Versus American Academy of Orthopaedic Surgeons Clinical Practice Guidelines.
  17. Evaluating AI Chatbot Responses to Postkidney Transplant Inquiries.
  18. BiomedRAG: A retrieval augmented large language model for biomedicine.
  19. Jargon and Readability in Plain Language Summaries of Health Research: Cross-Sectional Observational Study.
  20. [Online resources for ankle sprains : A German language web analysis].
  21. Anterior Cruciate Ligament Injuries: A Review of Quality and Reliability of Online Information.
  22. Content and quality of consumer websites providing information about human papillomavirus infection in patients with systemic lupus erythematosus: An environmental scan.
  23. Are YouTube Videos Useful in Robot-Assisted Segmentectomy Education?
  24. Are YouTube™ and TikTok™ videos useful as educational tool for patients with cleft lip and palate?
  25. Evaluating the quality of Spanish-language information for patients with type 2 diabetes on YouTube and Facebook.
  26. Celiac Disease in Children and YouTube: Do the Videos Contain Accurate Information?
  27. The Association Between COVID-19 Vaccination Uptake and Information-Seeking Behaviors Using the Internet: Nationwide Cross-Sectional Study.
  28. Validation of a Cancer-Focused Information Seeking Experience (ISEE) Scale.
  29. How Patients With Cancer Use the Internet to Search for Health Information: Scenario-Based Think-Aloud Study.
  30. Linking multiple-channel information seeking and lifestyle among Chinese older adults: A moderation and mediation analysis.
  31. eHealth, digital information and technology use of men with prostate cancer.
  32. For Myself or for Others? The Influence of Family Communication Patterns on Family Health History Communication and Online Health Information Seeking.
  33. What are patients asking and reading online? An analysis of online patient searches about treatments for developmental dysplasia of the hip.
  34. Evaluating Online and Offline Health Information With the Patient Education Materials Assessment Tool: Protocol for a Systematic Review.
  35. Harnessing Internet Search Data as a Potential Tool for Medical Diagnosis: Literature Review.
  1. Health Info Libr J. 2025 Jan 13.
    Bridging the health information gap among undergraduate university students: The role of academic libraries.
    Paulina Nana Yaa Kwafoa, Christopher K Filson, Gloria Tachie-Donkor, Diana Atuase, Paul Nunekpeku.
       BACKGROUND: Although university students are young and seem generally healthy, they do have health information needs that affect their academic work. Some university healthcare services and academic libraries collaborated during the COVID-19 pandemic to provide health information to students.
    AIMS/OBJECTIVES: The study explored the health information gap among undergraduate students in universities in Ghana.
    METHODOLOGY: The study involved 382 students from the University of Cape Coast, the University of Ghana, and Kwame Nkrumah University of Science and Technology, including nine librarians and six university health professionals. Respondents for the study were chosen using stratified sampling and purposeful sampling techniques. A questionnaire and a semi-structured interview guide were used to collect the data.
    RESULTS: The study revealed limited access to health information for undergraduate students. Male and female students had similar high priorities (personal hygiene, disease prevention, healthy living, mental health) but reproductive health information was mostly a priority for female students.
    DISCUSSION: Inadequate access to health information among undergraduate students may pose a threat to avoidable health risks and academic productivity.
    CONCLUSION: Based on the findings, a functional Collaborative Health Information Model for Academic Libraries and University Healthcare Systems is proposed to address undergraduate students' health information needs.
    Keywords:  Africa, west; collaboration; health information needs; libraries, academic; students
    DOI:  https://doi.org/10.1111/hir.12563
  2. Med Ref Serv Q. 2025 Jan 12. 1-14
    A Catalyst to Better Searching: Tackling Health Inequities with a Novel Interactive eResource.
    Lauren E Robinson, B Reeder, S Henderson, C M Robinson.
      This paper describes a web-based resource that aims to improve health disparities research by providing guidance and tools for searching and evaluating information on vulnerable populations. The resource integrates electronic books on equity, diversity, and inclusion with interactive tutorials and modules teaching users to formulate research questions, select appropriate search terms, and appraise their searches. The resource also addresses the issue of biased and outdated searching terminology and offers alternative strategies for finding literature. The paper explains the rationale, design, and development process of the resource, as well as its potential benefits and challenges for health disparities researchers and educators.
    Keywords:  Health disparities; health equity; reducing bias in searching; teaching search skills
    DOI:  https://doi.org/10.1080/02763869.2024.2448344
  3. J Clin Transl Sci. 2025 ;8(1): e224
    The role of information science within the clinical translational science ecosystem.
    Bart Ragon, Anne Seymour, Elizabeth C Whipple, Alisa Surkis, Amanda Haberstroh, Jennifer Muilenburg, Melissa L Rethlefsen, Erinn E Aspinall, Jill Deaver, Nadine Dexter, Renae Barger, Nicole Contaxis, Emily J Glenn, Elizabeth Hinton, Barbara Kern, Micquel Little, Keith Pickett, Erika Sevetson, Donghua Tao, Megan von Isenburg, Debra A Werner, Terrie R Wheeler, Kristi Holmes.
      Academic health sciences libraries ("libraries") offer services that span the entire research lifecycle, positioning them as natural partners in advancing clinical and translational science. Many libraries enjoy active and productive collaborations with Clinical and Translational Science Award (CTSA) Program hubs and other translational initiatives like the IDeA Clinical & Translational Research Network. This article explores areas of potential partnership between libraries and Translational Science Hubs (TSH), highlighting areas where libraries can support the CTSA Program's five functional areas outlined in the Notice of Funding Opportunity. It serves as a primer for TSH and libraries to explore potential collaborations, demonstrating how libraries can connect researchers to services and resources that support the information needs of TSH.
    Keywords:  Clinical and Translational Science; Clinical and Translational Science Award Program Hubs; Health sciences libraries; collaboration; partnership
    DOI:  https://doi.org/10.1017/cts.2024.664
  4. J Oral Facial Pain Headache. 2024 Jun;38(2): 74-81
    Development and validation of a search strategy and an automated classifier for retrieving temporomandibular disorders studies.
    Vicente Wielandt, Juan Fernando Oyarzo, Manolis Jusakos, Giuliana Lunecke, Diana Biscay, Claudia Bosio, Paula Zambrano-Achig, Sebastián Pinto, Magdalena Bignon, Gabriel Rada, Francisca Verdugo-Paiva.
      The objective was to develop and evaluate a comprehensive search strategy (SS) and automated classifier (AC) for retrieving temporomandibular disorders (TMD) research articles. An initial version of SS and AC was created by compiling terms from various sources, including previous systematic reviews (SRs) and consulting with TMD specialists. Performance was assessed using the relative recall (RR) method against a sample of all the primary studies (PS) included in 100 TMD-related SRs, with RR calculated for both SS and AC based on their ability to capture/classify TMD PSs. Adjustments were made iteratively. A validation was performed against PSs included in all TMD-relevant SRs published from January to April 2023. The analysis included 1271 PSs from 100 SRs published between 2002-2022. The initial SS had a relative recall of 89.34%, while the AC detected 70.05% of the studies. After adjustments, the fifth version reached 99.5% and 89.5% relative recall, respectively. Validation with 28 SRs from 2023 showed a search strategy sensitivity of 99.67% and AC sensitivity of 88.04%. In conclusion, the proposed SS demonstrated excellent performance in retrieving TMD-related research articles, with only a small percentage not correctly classified by the AC. The SS can effectively support evidence synthesis related to TMD, while the AC can aid in creating an open-access, continuously updated digital repository for all relevant TMD evidence.
    Keywords:  Automated classification; Evidence-based dentistry; Research methodology; Systematic review; Temporomandibular disorders
    DOI:  https://doi.org/10.22514/jofph.2024.015
  5. Inform Health Soc Care. 2025 Jan 17. 1-15
    Validation of the eHealth literacy scales: comparison between the shorter and longer versions.
    Areti Efthymiou, Argyroula Kalaitzaki, Michael Rovithis, Gregor Petrič.
      Digital service provision became necessary during and after the COVID-19 pandemic highlighting the technological disparity experienced by healthcare professionals and healthcare users. eHealth Literacy skills are mostly measured with the use of the eHeals, but recently more instruments have been developed to meet this need. The aim of the study was to validate and compare the two scales in Greek: the eHeals and the revised eHeals-Extended. In total, 401 participants replied to the eHeals, the revised eHeals-Extended, and the HLS-EU-Q16. The eHeals scales provided good psychometric properties. The validation of the eHeals confirmed the two dimensions with high internal consistency (total score α = .91, eHeals1 α = .88, eHeals2 α = .78). The revised eHeals-Extended exploratory analysis extracted five factors with satisfactory internal consistency (Cronbach's α = .62-.89): awareness and quality of resources online, understanding online information, smart on the net, accessing and validating online information and perceived efficiency. The use of the revised eHeals-Extended and eHeals validated in Greek, could be valuable tools in clinical and research settings. The eHeals could be used as an additional tool when eHealth Literacy is not the core concept measured and the revised eHeals-Extended can be used when researchers wish to measure eHealth Literacy concept more thoroughly.
    Keywords:  eHealth literacy; health information; health literacy; psychometric properties; validation
    DOI:  https://doi.org/10.1080/17538157.2025.2451427
  6. Indian J Radiol Imaging. 2025 Jan;35(Suppl 1): S148-S154
    Indexing of Journals and Indices of Publications.
    Biju Vasudevan, Manas Chatterjee, Vishal Sharma, Ravinder Sahdev.
      Journal indexes are indicators toward the quality of a journal. Authors, researchers, and the audience need some criteria to judge which literature they need to read or which journal they need to send their article to. Journal indexes help the respective groups to make this decision. From Index Medicus to Web of Science, journal indexes use different criteria to judge the quality of a journal or an article. Figures like impact factor and CiteScore also rank journals and articles based on various criteria so that the audience and authors can make their pick. Author indices like h-index and ResearchGate score aid in comparing scientific work done by authors and researchers. Indexes of journals, publications, and authors therefore offer a classification of medical literature from which the best can be chosen depending on the requirements in their respective fields.
    Keywords:  author; database; index; indexing; publication
    DOI:  https://doi.org/10.1055/s-0044-1800878
  7. Adv Orthop. 2025 ;2025 5534704
    ChatGPT is an Unreliable Source of Peer-Reviewed Information for Common Total Knee and Hip Arthroplasty Patient Questions.
    Jonathan D Schwartzman, M Kareem Shaath, Matthew S Kerr, Cody C Green, George J Haidukewych.
      Background: Advances in artificial intelligence (AI), machine learning, and publicly accessible language model tools such as ChatGPT-3.5 continue to shape the landscape of modern medicine and patient education. ChatGPT's open access (OA), instant, human-sounding interface capable of carrying discussion on myriad topics makes it a potentially useful resource for patients seeking medical advice. As it pertains to orthopedic surgery, ChatGPT may become a source to answer common preoperative questions regarding total knee arthroplasty (TKA) and total hip arthroplasty (THA). Since ChatGPT can utilize the peer-reviewed literature to source its responses, this study seeks to characterize the validity of its responses to common TKA and THA questions and characterize the peer-reviewed literature that it uses to formulate its responses. Methods: Preoperative TKA and THA questions were formulated by fellowship-trained adult reconstruction surgeons based on common questions posed by patients in the clinical setting. Questions were inputted into ChatGPT with the initial request of using solely the peer-reviewed literature to generate its responses. The validity of each response was rated on a Likert scale by the fellowship-trained surgeons, and the sources utilized were characterized in terms of accuracy of comparison to existing publications, publication date, study design, level of evidence, journal of publication, journal impact factor based on the clarivate analytics factor tool, journal OA status, and whether the journal is based in the United States. Results: A total of 109 sources were cited by ChatGPT in its answers to 17 questions regarding TKA procedures and 16 THA procedures. Thirty-nine sources (36%) were deemed accurate or able to be directly traced to an existing publication. Of these, seven (18%) were identified as duplicates, yielding a total of 32 unique sources that were identified as accurate and further characterized. The most common characteristics of these sources included dates of publication between 2011 and 2015 (10), publication in The Journal of Bone and Joint Surgery (13), journal impact factors between 5.1 and 10.0 (17), internationally based journals (17), and journals that are not OA (28). The most common study designs were retrospective cohort studies and case series (seven each). The level of evidence was broadly distributed between Levels I, III, and IV (seven each). The averages for the Likert scales for medical accuracy and completeness were 4.4/6 and 1.92/3, respectively. Conclusions: Investigation into ChatGPT's response quality and use of peer-reviewed sources when prompted with archetypal pre-TKA and pre-THA questions found ChatGPT to provide mostly reliable responses based on fellowship-trained orthopedic surgeon review of 4.4/6 for accuracy and 1.92/3 for completeness despite a 64.22% rate of citing inaccurate references. This study suggests that until ChatGPT is proven to be a reliable source of valid information and references, patients must exercise extreme caution in directing their pre-TKA and THA questions to this medium.
    DOI:  https://doi.org/10.1155/aort/5534704
  8. JMIR Infodemiology. 2024 Dec 24.
    Transformer-Based Tool for Automated Fact-Checking: A Pilot Study on Online Health Information.
    Azadeh Bayani, Alexandre Ayotte, Jean Noel Nikiema.
       BACKGROUND: Many people seek health-related information online. The significance of reliable information became particularly evident due to the potential dangers of misinformation. Therefore, discerning true and reliable information from false information has become increasingly challenging.
    OBJECTIVE: In the present pilot study, we introduced a novel approach to automate the fact-checking process, leveraging PubMed resources as a source of truth employing Natural Language Processing (NLP) transformer models to enhance the process.
    METHODS: A total of 538 health-related webpages, covering seven different disease subjects, were manually selected by Factually Health Company. The process included the following steps: i) using transformer models of Bidirectional Encoder Representations from Transformers (BERT) BioBERT and SciBERT and traditional models of random forests (RF) and support vector machines (SVM), to classify the contents of webpages into three thematic categories: semiology, epidemiology, and management, ii) for each category in the webpages, a PubMed query was automatically produced using a combination of the "WellcomeBertMesh" and "KeyBERT" models, iii) top 20 related literatures were automatically extracted from PubMed and finally, iv) the similarity checking techniques of Cosine similarity and Jaccard distance were applied to compare the content of extracted literature and webpages.
    RESULTS: The BERT model for categorization of webpages contents had a good performance with the F1-scores and recall of 93% and 94% for the semiology and epidemiology respectively and 96% of for both the recall and F1-score for management. For each of the three categories in a webpage, one PubMed query was generated and with each query, 20 most related, open access and within the category of systematic reviews and meta-analysis were extracted. Less than 10% of the extracted literature were irrelevant, which were deleted. For each webpage, an average number of 23% of the sentences found to be very similar to the literature. Moreover, during the evaluation, it was found that Cosine similarity outperformed the Jaccard Distance measure when comparing the similarity between sentences from web pages and academic papers vectorized by BERT. However, there was a significant issue with false positives in the retrieved sentences when compared to accurate similarities as some sentences had a similarity score exceeding 80%, but they could not be considered as similar sentences.
    CONCLUSIONS: In the present pilot study, we have proposed an approach to automate the fact-checking of health-related online information. Incorporating content from PubMed or other scientific article databases as trustworthy resources can automate the discovery of similarly credible information in the health domain.
    DOI:  https://doi.org/10.2196/56831
  9. Hand Surg Rehabil. 2025 Jan 09. pii: S2468-1229(25)00004-0. [Epub ahead of print] 102082
    Title: Can ChatGPT 4.0 Reliably Answer Patient Frequently Asked Questions About Boxer's Fractures?
    Christopher A White, Jamie L Kator, Hannah S Rhe, Thomas Boucher, Rachel Glenn, Amanda Walsh, Jaehon M Ki.
       BACKGROUND: Patients are increasingly turning to the internet, and recently artificial intelligence engines (e.g., ChatGPT), for answers to common medical questions. Regarding orthopedic hand surgery, recent literature has focused on ChatGPT's ability to answer patient frequently asked questions (FAQs) regarding subjects such as carpal tunnel syndrome, distal radius fractures, and more. The present study seeks to determine how accurately ChatGPT can answer patient FAQs surrounding simple fracture patterns such as fifth metacarpal neck fractures.
    METHODS: Internet queries were used to identify the ten most FAQs regarding boxer's fractures based on information from five trusted healthcare institutions. These ten questions were posed to ChatGPT 4.0, and the chatbot's responses were recorded. Two fellowship trained orthopedic hand surgeons and one orthopedic hand surgery fellow then graded ChatGPT's responses on an alphabetical grading scale (i.e., A-F); additional commentary was then provided for each response. Descriptive statistics were used to report question, grader, and overall ChatGPT response grades.
    RESULTS: ChatGPT achieved a cumulative grade of a B, indicating that the chatbot can provide adequate responses with only minor need for clarification when answering FAQs for boxer's fractures. Individual graders provided comparable overall grades of B, B, and B + respectively. ChatGPT deferred to a medical professional in 7/10 responses. General questions were graded at an A-. Management questions were graded at a C+.
    CONCLUSION: Overall, with a grade of B, ChatGPT 4.0 provides adequate-to- complete responses as it pertains to patient FAQs surrounding boxer's fractures.
    Keywords:  Boxer’s fracture; ChatGPT; artificial intelligence; fifth metacarpal; patient education
    DOI:  https://doi.org/10.1016/j.hansur.2025.102082
  10. Sisli Etfal Hastan Tip Bul. 2024 ;58(4): 483-490
    Evaluation of ChatGPT-4 Performance in Answering Patients' Questions About the Management of Type 2 Diabetes.
    Puren Gokbulut, Serife Mehlika Kuskonmaz, Cagatay Emir Onder, Isilay Taskaldiran, Gonul Koc.
       Objectives: Type 2 diabetes mellitus is a disease with a rising prevalence worldwide. Person-centered treatment factors, including comorbidities and treatment goals, should be considered in determining the pharmacological treatment of type 2 diabetes. ChatGPT-4 (Generative Pre-trained Transformer), a large language model, holds the potential performance in various fields, including medicine. We aimed to examine the reliability, quality, reproducibility, and readability of ChatGPT-4's responses to clinical scenarios about the medical treatment approach and management of type 2 diabetes patients.
    Methods: ChatGPT-4's responses to 24 questions were independently graded by two endocrinologists with clinical experience in endocrinology and resolved by a third reviewer based on the ADA(American Diabetes Association) 2023 guidelines. DISCERN (Quality Criteria for Consumer Health Information) Measurement Tool was used to evaluate the reliability and quality of information.
    Results: Responses to questions by ChatGPT-4 were fairly consistent in both sessions. No false or misleading information was found in any ChatGPT-4 responses. In terms of reliability, most of the answers showed good (87.5%), followed by excellent (12.5%) reliability. Reading Level was classified as fairly difficult to read (8.3%), difficult to read (50%), and very difficult to read (41.7%).
    Conclusion: ChatGPT-4 may have a role as an additional informative tool for type 2 diabetes patients for medical treatment approaches.
    Keywords:  Artificial intelligence; ChatGPT-4; medical treatment; type 2 diabetes mellitus
    DOI:  https://doi.org/10.14744/SEMB.2024.23697
  11. Facial Plast Surg Aesthet Med. 2025 Jan 15.
    Comparative Performance of the Leading Large Language Models in Answering Complex Rhinoplasty Consultation Questions.
    Khodayar Goshtasbi, Corliss Best, Bethany Powers, Harry Ching, Norman J Pastorek, Donald Altman, Peter Adamson, Mark Krugman, Brian J F Wong.
      Background: Various large language models (LLMs) can provide human-level medical discussions, but they have not been compared regarding rhinoplasty knowledge. Objective: To compare the leading LLMs in answering complex rhinoplasty consultation questions as evaluated by plastic surgeons. Methods: Ten open-ended rhinoplasty consultation questions were presented to ChatGPT-4o, Google Gemini, Claude, and Meta-AI LLMs. The responses were randomized and ranked by seven rhinoplasty-specializing plastic surgeons (1 = worst, 4 = best) considering their quality. Textual readability was analyzed via Flesch Reading Ease (FRE) and Flesch-Kincaid Grade (FKG). Results: Claude provided the top answers for seven questions while ChatGPT provided the top answers for three questions. In overall collective scoring, Claude provided the best answers with 224 points, followed by ChatGPT's 200, Meta's 138, and Gemini's 138 scores. Claude (mean score/question 3.20 ± 1.00) significantly outperformed all the other models (p < 0.05), while ChatGPT (mean score/question 2.86 ± 0.94) outperformed Meta and Gemini. Meta and Gemini performed similarly. Meta had a significantly lower FKG than Claude and ChatGPT and a significantly lower FRE than ChatGPT. Conclusion: According to ratings by seven rhinoplasty-specializing surgeons, Claude provided the best answers for a set of complex rhinoplasty consultation questions, followed by ChatGPT. Future studies are warranted to continue comparing these models as they evolve.
    DOI:  https://doi.org/10.1089/fpsam.2024.0206
  12. JMIR Form Res. 2025 Jan 09.
    Proficiency, Clarity, and Objectivity of Large Language Models Versus Specialists' Knowledge on COVID-19 Impacts in Pregnancy: A Cross-Sectional Pilot Study.
    Nicola Bragazzi, Michèle Buchinger, Hisham Atwan, Ruba Tuma, Francesco Chirico, Lukasz Szarpak, Raymond Farah, Rola Khamisy-Farah.
       BACKGROUND: The COVID-19 pandemic has significantly strained healthcare systems globally, leading to an overwhelming influx of patients and exacerbating resource limitations. Concurrently, an "infodemic" of misinformation, particularly prevalent in women's health, has emerged. This challenge has been pivotal for healthcare providers, especially gynecologists and obstetricians, in managing pregnant women's health. The pandemic heightened risks for pregnant women from COVID-19, necessitating balanced advice from specialists on vaccine safety versus known risks. Additionally, the advent of generative Artificial Intelligence (AI), such as large language models (LLMs), offers promising support in healthcare. However, they necessitate rigorous testing.
    OBJECTIVE: To assess LLMs' proficiency, clarity, and objectivity regarding COVID-19 impacts in pregnancy.
    METHODS: This study evaluates four major AI prototypes (ChatGPT-3.5, ChatGPT-4, Microsoft Copilot, and Google Bard) using zero-shot prompts in a questionnaire validated among 159 Israeli gynecologists and obstetricians. The questionnaire assesses proficiency in providing accurate information on COVID-19 in relation to pregnancy. Text-mining, sentiment analysis, and readability (Flesch-Kincaid grade level and Flesch Reading Ease Score) were also conducted.
    RESULTS: In terms of LLMs' knowledge, ChatGPT-4 and Microsoft Copilot each scored 97% (n=32/33), Google Bard 94% (n=31/33), and ChatGPT-3.5 82% (n=27/33). ChatGPT-4 incorrectly stated an increased risk of miscarriage due to COVID-19. Google Bard and Microsoft Copilot had minor inaccuracies concerning COVID-19 transmission and complications. At the sentiment analysis, Microsoft Copilot achieved the least negative score (-4), followed by ChatGPT-4 (-6) and Google Bard ( -7), while ChatGPT-3.5 obtained the most negative score (-12). Finally, concerning the readability analysis, Flesch-Kincaid Grade Level and Flesch Reading Ease Score showed that Microsoft Copilot was the most accessible at 9.9 and 49, followed by ChatGPT-4 at 12.4 and 37.1, while ChatGPT-3.5 (12.9 and 35.6) and Google Bard (12.9 and 35.8) generated particularly complex responses.
    CONCLUSIONS: The study highlights varying knowledge levels of LLMs in relation to COVID-19 and pregnancy. ChatGPT-3.5 showed the least knowledge and alignment with scientific evidence. Readability and complexity analyses suggest that each AI's approach was tailored to specific audiences, with ChatGPT versions being more suitable for specialized readers and Microsoft Copilot for the general public. Sentiment analysis revealed notable variations in the way LLMs communicated critical information, underscoring the essential role of neutral and objective healthcare communication in ensuring that pregnant women, particularly vulnerable during the COVID-19 pandemic, receive accurate and reassuring guidance. Overall, ChatGPT-4, Microsoft Copilot, and Google Bard generally provided accurate, updated information on COVID-19 and vaccines in maternal and fetal health, aligning with health guidelines. The study demonstrated the potential role of AI in supplementing healthcare knowledge, with a need for continuous updating and verification of AI knowledge bases. The choice of AI tool should consider the target audience and required information detail level.
    CLINICALTRIAL:
    DOI:  https://doi.org/10.2196/56126
  13. J Med Syst. 2025 Jan 17. 49(1): 11
    Assessing the Efficacy of ChatGPT Prompting Strategies in Enhancing Thyroid Cancer Patient Education: A Prospective Study.
    Qi Xu, Jing Wang, Xiaohui Chen, Jiale Wang, Hanzhi Li, Zheng Wang, Weihan Li, Jinliang Gao, Chen Chen, Yuwan Gao.
      With the rise of AI platforms, patients increasingly use them for information, relying on advanced language models like ChatGPT for answers and advice. However, the effectiveness of ChatGPT in educating thyroid cancer patients remains unclear. We designed 50 questions covering key areas of thyroid cancer management and generated corresponding responses under four different prompt strategies. These answers were evaluated based on four dimensions: accuracy, comprehensiveness, human care, and satisfaction. Additionally, the readability of the responses was assessed using the Flesch-Kincaid grade level, Gunning Fog Index, Simple Measure of Gobbledygook, and Fry readability score. We also statistically analyzed the references in the responses generated by ChatGPT. The type of prompt significantly influences the quality of ChatGPT's responses. Notably, the "statistics and references" prompt yields the highest quality outcomes. Prompts tailored to a "6th-grade level" generated the most easily understandable text, whereas responses without specific prompts were the most complex. Additionally, the "statistics and references" prompt produced the longest responses while the "6th-grade level" prompt resulted in the shortest. Notably, 87.84% of citations referenced published medical literature, but 12.82% contained misinformation or errors. ChatGPT demonstrates considerable potential for enhancing the readability and quality of thyroid cancer patient education materials. By adjusting prompt strategies, ChatGPT can generate responses that cater to diverse patient needs, improving their understanding and management of the disease. However, AI-generated content must be carefully supervised to ensure that the information it provides is accurate.
    Keywords:  Artificial intelligence; ChatGPT; Patient education; Thyroid cancer
    DOI:  https://doi.org/10.1007/s10916-024-02129-0
  14. Updates Surg. 2025 Jan 15.
    Use of generative large language models for patient education on common surgical conditions: a comparative analysis between ChatGPT and Google Gemini.
    Omar Mahmoud ELSenbawy, Keval Bhavesh Patel, Randev Ayodhya Wannakuwatte, Akhila N Thota.
      There is a growing importance for patients to easily access information regarding their medical conditions to improve their understanding and participation in health care decisions. Artificial Intelligence (AI) has proven as a fast, efficient, and effective tool in educating patients regarding their health care conditions. The aim of the study is to compare the responses provided by AI tools, ChatGPT and Google Gemini, to assess for conciseness and understandability of information provided for the medical conditions Deep vein thrombosis, decubitus ulcers, and hemorrhoids. A cross-sectional original research design was conducted regarding the responses generated by ChatGPT and Google Gemini for the post-surgical complications of Deep vein thrombosis, decubitus ulcers, and hemorrhoids. Each response was evaluated by the Flesch-Kincaid calculator for total number of words, sentences, average words per sentence, average syllables per word, grade level, and ease score. Additionally, the similarity score was evaluated using QuillBot and reliability using a modified discern score. These results were then analyzed by the unpaired or two sample t-test to compare the averages between the two AI tools to conclude which one was superior. Chat GPT required a higher education level to understand as suggested by the higher grade levels and lower ease scores. The easiest brochure was for deep vein thrombosis which had the lowest ease score and highest grade level. ChatGPT displayed more similarity with information provided on the internet as calculated by the plagiarism calculator-Quill bot. The reliability score via the Modified Discern score showing both AI tools were similar. Although there is a difference in the various scores for each AI tool, based on the P values obtained there is not enough evidence to conclude the superiority of one AI tool over the other.
    Keywords:  Artificial intelligence; Chatgpt; Decubitus ulcer; Deep venous thrombosis; Education tool; Google Gemini; Hemorrhoids; Patient education; Surgery
    DOI:  https://doi.org/10.1007/s13304-025-02074-8
  15. Cureus. 2024 Dec;16(12): e75826
    A Study of Orthopedic Patient Leaflets and Readability of AI-Generated Text in Foot and Ankle Surgery (SOLE-AI).
    Alexander Jaques, Karim Abdelghafour, Oliver Perkins, Helen Nuttall, Omar Haidar, Karanjeev Johal.
      Introduction The internet age has broadened the horizons of modern medicine, and the ever-increasing scope of artificial intelligence (AI) has made information about healthcare, common pathologies, and available treatment options much more accessible to the wider population. Patient autonomy relies on clear, accurate, and user-friendly information to give informed consent to an intervention. Our paper aims to outline the quality, readability, and accuracy of readily available information produced by AI relating to common foot and ankle procedures. Materials and methods A retrospective qualitative analysis of procedure-specific information relating to three common foot and ankle orthopedic procedures: ankle arthroscopy, ankle arthrodesis/fusion, and a gastrocnemius lengthening procedure was undertaken. Patient information leaflets (PILs) created by The British Orthopaedic Foot and Ankle Society (BOFAS) were compared to ChatGPT responses for readability, quality, and accuracy of information. Four language tools were used to assess readability: the Flesch-Kincaid reading ease (FKRE) score, the Flesch-Kincaid grade level (FKGL), the Gunning fog score (GFS), and the simple measure of gobbledygook (SMOG) index. Quality and accuracy were determined by using the DISCERN tool by five independent assessors. Results PILs produced by AI had significantly lower FKRE scores when compared to BOFAS -40.4 (SD: ±7.69) compared to 91.9 (SD: ±2.24) (p ≤ 0.0001), indicating poor readability of AI-generated text. DISCERN scoring highlighted a statistically significant improvement in accuracy and quality of human-generated information across two PILs with a mean score of 55.06 compared to 46.8. FKGL scoring indicated that the required grade of students to understand AI responses was consistently higher than compared to information leaflets at 11.7 versus 1.1 (p ≤ 0.0001). The number of years spent in education required to understand the ChatGPT-produced PILs was significantly higher in both GFS (14.46 vs. 2.0 years) (p < 0.0001) and SMOG (11.0 vs. 3.06 years) (p < 0.0001). Conclusion Despite significant advances in the implementation of AI in surgery, AI-generated PILs for common foot and ankle surgical procedures currently lack sufficient quality, depth, and readability - this risks leaving patients misinformed regarding upcoming procedures. We conclude that information from trusted professional bodies should be used to complement a clinical consultation, as there currently lacks sufficient evidence to support the routine implementation of AI-generated information into the consent process.
    Keywords:  artificial intelligence (ai); elective foot and ankle surgery; orthopaedics surgery; patient information leaflet; readability analysis
    DOI:  https://doi.org/10.7759/cureus.75826
  16. J Pediatr Orthop. 2025 Jan 14.
    Pediatric Supracondylar Humerus and Diaphyseal Femur Fractures: A Comparative Analysis of Chat Generative Pretrained Transformer and Google Gemini Recommendations Versus American Academy of Orthopaedic Surgeons Clinical Practice Guidelines.
    Patrick P Nian, Amith Umesh, Shae K Simpson, Olivia C Tracey, Erikson Nichols, Stephanie Logterman, Shevaun M Doyle, Jessica H Heyer.
       OBJECTIVE: Artificial intelligence (AI) chatbots, including chat generative pretrained transformer (ChatGPT) and Google Gemini, have significantly increased access to medical information. However, in pediatric orthopaedics, no study has evaluated the accuracy of AI chatbots compared with evidence-based recommendations, including the American Academy of Orthopaedic Surgeons clinical practice guidelines (AAOS CPGs). The aims of this study were to compare responses by ChatGPT-4.0, ChatGPT-3.5, and Google Gemini with AAOS CPG recommendations on pediatric supracondylar humerus and diaphyseal femur fractures regarding accuracy, supplementary and incomplete response patterns, and readability.
    METHODS: ChatGPT-4.0, ChatGPT-3.5, and Google Gemini were prompted by questions created from 13 evidence-based recommendations (6 from the 2011 AAOS CPG on pediatric supracondylar humerus fractures; 7 from the 2020 AAOS CPG on pediatric diaphyseal femur fractures). Responses were anonymized and independently evaluated by 2 pediatric orthopaedic attending surgeons. Supplementary responses were, in addition, evaluated on whether no, some, or many modifications were necessary. Readability metrics (response length, Flesch-Kincaid reading level, Flesch Reading Ease, Gunning Fog Index) were compared. Cohen Kappa interrater reliability (κ) was calculated. χ2 analyses and single-factor analysis of variance were utilized to compare categorical and continuous variables, respectively. Statistical significance was set with P <0.05.
    RESULTS: ChatGPT-4.0, ChatGPT-3.5, and Google Gemini were accurate in 11/13, 9/13, and 11/13, supplementary in 13/13, 11/13, and 13/13, and incomplete in 3/13, 4/13, and 4/13 recommendations, respectively. Of 37 supplementary responses, 17 (45.9%), 19 (51.4%), and 1 (2.7%) required no, some, and many modifications, respectively. There were no significant differences in accuracy (P = 0.533), supplementary responses (P = 0.121), necessary modifications (P = 0.580), and incomplete responses (P = 0.881). Overall κ was moderate at 0.55. ChatGPT-3.5 provided shorter responses (P = 0.002), but Google Gemini was more readable in terms of Flesch-Kincaid Grade Level (P = 0.002), Flesch Reading Ease (P < 0.001), and Gunning Fog Index (P = 0.021).
    CONCLUSIONS: While AI chatbots provided responses with reasonable accuracy, most supplemental information required modification and had complex readability. Improvements are necessary before AI chatbots can be reliably used for patient education.
    LEVEL OF EVIDENCE: Level IV.
    DOI:  https://doi.org/10.1097/BPO.0000000000002890
  17. Transplant Proc. 2025 Jan 14. pii: S0041-1345(24)00682-1. [Epub ahead of print]
    Evaluating AI Chatbot Responses to Postkidney Transplant Inquiries.
    Yihua Zhan, Xutao Chen, Feihong Ye, Zhikai Wu, Muhammad Usman, Zhihan Yuan, Han Wu, Jian Huang, Hao Yu.
      This study evaluated the capability of three AI chatbots-ChatGPT 4.0, Claude 3.0, and Gemini Pro, as well as Google-in responding to common postkidney transplantation inquiries. We compiled a list of frequently asked postkidney transplant questions using Google and Bing. Response quality was rated on a 5-point Likert scale, while understandability and actionability were measured with the Patient Education Materials Assessment Tool (PEMAT). Readability was assessed using the Flesch Reading Ease and Flesch-Kincaid Grade Level metrics, with statistical analysis conducted via non-parametric tests, specifically the Kruskal-Wallis test, using SPSS. We gathered 127 questions, which were addressed by the chatbots and Google. The responses were of high quality (median Likert score: 4 [4,5]), good understandability (median PEMAT understandability score: 72.7% [62.5,77.8]), but poor actionability (median PEMAT operability score: 20% [0%-20%]). The readability was challenging (median Flesch Reading Ease score: 22.1 [8.7,34.8]), with a Flesch-Kincaid Grade Level akin to undergraduate-level text (median score: 14.7 [12.3,16.7]). Among the chatbots, Claude 3.0 provided the most reliable responses, though they required a higher reading level. ChatGPT 4.0 offered the most comprehensible responses. Moreover, Google did not outperform the chatbots in any of the scoring metrics.
    DOI:  https://doi.org/10.1016/j.transproceed.2024.12.028
  18. J Biomed Inform. 2025 Jan 13. pii: S1532-0464(24)00187-4. [Epub ahead of print] 104769
    BiomedRAG: A retrieval augmented large language model for biomedicine.
    Mingchen Li, Halil Kilicoglu, Hua Xu, Rui Zhang.
      Retrieval-augmented generation (RAG) involves a solution by retrieving knowledge from an established database to enhance the performance of large language models (LLM). , these models retrieve information at the sentence or paragraph level, potentially introducing noise and affecting the generation quality. To address these issues, we propose a novel BiomedRAG framework that directly feeds automatically retrieved chunk-based documents into the LLM. Our evaluation of BiomedRAG across four biomedical natural language processing tasks using eight datasets demonstrates that our proposed framework not only improves the performance by 9.95% on average, but also achieves state-of-the-art results, surpassing various baselines by 4.97%. BiomedRAG paves the way for more accurate and adaptable LLM applications in the biomedical domain.
    Keywords:  Automatically retrieve documents in chunks; Large language model; Retrieval-augmented generation
    DOI:  https://doi.org/10.1016/j.jbi.2024.104769
  19. J Med Internet Res. 2025 Jan 13. 27 e50862
    Jargon and Readability in Plain Language Summaries of Health Research: Cross-Sectional Observational Study.
    Iain A Lang, Angela King, Kate Boddy, Ken Stein, Lauren Asare, Jo Day, Kristin Liabo.
       BACKGROUND: The idea of making science more accessible to nonscientists has prompted health researchers to involve patients and the public more actively in their research. This sometimes involves writing a plain language summary (PLS), a short summary intended to make research findings accessible to nonspecialists. However, whether PLSs satisfy the basic requirements of accessible language is unclear.
    OBJECTIVE: We aimed to assess the readability and level of jargon in the PLSs of research funded by the largest national clinical research funder in Europe, the United Kingdom's National Institute for Health and Care Research (NIHR). We also aimed to assess whether readability and jargon were influenced by internal and external characteristics of research projects.
    METHODS: We downloaded the PLSs of all NIHR National Journals Library reports from mid-2014 to mid-2022 (N=1241) and analyzed them using the Flesch Reading Ease (FRE) formula and a jargon calculator (the De-Jargonizer). In our analysis, we included the following study characteristics of each PLS: research topic, funding program, project size, length, publication year, and readability and jargon scores of the original funding proposal.
    RESULTS: Readability scores ranged from 1.1 to 70.8, with an average FRE score of 39.0 (95% CI 38.4-39.7). Moreover, 2.8% (35/1241) of the PLSs had an FRE score classified as "plain English" or better; none had readability scores in line with the average reading age of the UK population. Jargon scores ranged from 76.4 to 99.3, with an average score of 91.7 (95% CI 91.5-91.9) and 21.7% (269/1241) of the PLSs had a jargon score suitable for general comprehension. Variables such as research topic, funding program, and project size significantly influenced readability and jargon scores. The biggest differences related to the original proposals: proposals with a PLS in their application that were in the 20% most readable were almost 3 times more likely to have a more readable final PLS (incidence rate ratio 2.88, 95% CI 1.86-4.45). Those with the 20% least jargon in the original application were more than 10 times as likely to have low levels of jargon in the final PLS (incidence rate ratio 13.87, 95% CI 5.17-37.2). There was no observable trend over time.
    CONCLUSIONS: Most of the PLSs published in the NIHR's National Journals Library have poor readability due to their complexity and use of jargon. None were readable at a level in keeping with the average reading age of the UK population. There were significant variations in readability and jargon scores depending on the research topic, funding program, and other factors. Notably, the readability of the original funding proposal seemed to significantly impact the final report's readability. Ways of improving the accessibility of PLSs are needed, as is greater clarity over who and what they are for.
    Keywords:  accessibility; health communication; health literacy; health research; jargon; open science; patient and public involvement; plain language summary; public understanding of science; readability; reading; science communication
    DOI:  https://doi.org/10.2196/50862
  20. Unfallchirurgie (Heidelb). 2025 Jan 16.
    [Online resources for ankle sprains : A German language web analysis].
    Sophie Maria Tengler, Mark Lenz, Gunther O Hofmann, Marianne Rosenthal, Klaus E Roth, Lena Mohr, Hazibullah Waizy, Kajetan Klos.
       BACKGROUND: With the Internet as the main source of information for health content, the quality of websites with medical information is of high importance.
    OBJECTIVE: This study analysed 250 websites on acute ankle sprain (ASD), one of the most common musculoskeletal disorders, for their quality and readability. Based on the results, a guide for patients was created.
    METHOD: The quality of the websites was assessed using a 25-item content score and the EQIP36 score for medical information material. The reading level could be determined using the Flesch-Kincaid index and the calculated readability. The best three websites were evaluated in a user survey.
    RESULTS: Of the 250 websites recorded 77 were included in the study. The quality of these varied significantly, with none achieving the maximum score. Sources in the healthcare system showed higher quality, while commercially influenced sites were below average in terms of completeness of content. Only 14% of the websites reached the recommended reading level. A significant negative correlation was found between completeness of content and readability. The user survey showed a mixed level of satisfaction and participants with previous medical knowledge were more critical than laypersons.
    CONCLUSION: Online resources about ASD are suboptimal and differ considerably. Deficiencies in content, readability and structure were identified, which limit the effective use by patients. Health information publishers should work harder to improve the comprehensibility and quality of the information provided.
    Keywords:  Ankle sprain; Quality; Readability; Web analysis; Websites
    DOI:  https://doi.org/10.1007/s00113-024-01526-x
  21. Cureus. 2024 Dec;16(12): e75776
    Anterior Cruciate Ligament Injuries: A Review of Quality and Reliability of Online Information.
    Ahmad W Mohamed, Matthieu Durand-Hill, Arpit Patel.
      Aim This study aims to evaluate the reliability and quality of online information on anterior cruciate ligament (ACL) injuries. Methods An internet search on the three top search engines, Google, Yahoo!, and Bing, was done using the keywords "anterior cruciate ligament injury". The search was carried out in June 2023, and 39 websites were selected. Exclusion criteria comprised video-only explanatory websites (such as YouTube) and access requiring payment or registration. Websites were categorised using the following scoring systems: (i) DISCERN score, (ii) Health-on-Net Foundation Code (HON code), (iii) Journal of the American Medical Association (JAMA) benchmark criteria, and (iv) ACL content score, which was specifically designed for this study. Results The majority of websites were commercial (n = 16 [41.0%]), followed by academic (n = 10 [25.6%]). None of the websites included had a HON code present. The mean DISCERN score was 52.1, the mean JAMA score was 2.62, and the mean ACL content score was 7.49. Conclusion There is a vast amount of information available on the internet with regard to the topic of ACL injuries, and this ranges from excellent to poor-quality information. In light of this, orthopaedic specialists and healthcare providers must guide patients to online resources that are reliable and trusted based on either their personal experience or resource type (academic/physician). In addition, we recommend that websites providing information seek HON-code certification as a seal of quality, as this has previously been noted in previous studies to be positively linked with the quality of information delivered.
    Keywords:  acl; acl injury; acl sprain; anterior cruciate ligament (acl) reconstruction; ortho; ortho surgery; sports surgery
    DOI:  https://doi.org/10.7759/cureus.75776
  22. Patient Educ Couns. 2025 Jan 09. pii: S0738-3991(25)00011-4. [Epub ahead of print]133 108644
    Content and quality of consumer websites providing information about human papillomavirus infection in patients with systemic lupus erythematosus: An environmental scan.
    Juan I Ruiz, Contessa Radabaugh, Yimin Geng, Maria E Suarez-Almazor.
       OBJECTIVE: We aimed to evaluate the content and quality of websites for consumers providing information about human papillomavirus (HPV) risks in patients with systemic lupus erythematosus (SLE).
    METHODS: We conducted an environmental scan of websites for patients and the general public with information about HPV and SLE. We searched Google from inception to June 2023, using the terms "HPV" and "lupus". We included websites with information about HPV and SLE. Two reviewers appraised the websites and collected website characteristics, and rated various attributes: completeness and comprehensiveness, accuracy, technical elements, design and aesthetics, usability, readability, and accessibility.
    RESULTS: We identified 16 websites for analysis. Ten (62.5 %) were commercial websites One website provided complete and comprehensive information about HPV risk, screening, and vaccination in patients with SLE; 7 (44 %) websites provided only information about the HPV vaccine. Eight websites included risk of HPV infection, cervical cancer screening, and cervical cancer risk in patients with SLE. Seventy-five percent provided information based on clinical guidelines, textbooks, peer-reviewed papers or scientific publications while the remaining were based on expert opinions. All websites were considered to have adequate design and aesthetics and were easy to navigate. Only 1 (6 %) website had a 6th-grade reading level and the other had reading levels higher than that (not appropriate for consumer websites). The overall quality scores ranged from 32 to 51 (maximum 69).
    CONCLUSION: Our findings showed that most websites for patients and the general public with information about HPV and SLE did not provide complete and comprehensive information about HPV.
    Keywords:  Environmental scan; Human papillomavirus; Patient education; Systemic lupus erythematosus; Websites
    DOI:  https://doi.org/10.1016/j.pec.2025.108644
  23. Thorac Cardiovasc Surg. 2025 Jan 10.
    Are YouTube Videos Useful in Robot-Assisted Segmentectomy Education?
    Tugba Cosgun, Talha Dogruyol, Cagatay Tezel.
       BACKGROUND: Segmentectomy operation became a preferable operation for small lesions due to the importance of saving lung parenchyma. Using robotic technology has too many advantages for segmentectomy operations. Websites such as YouTube have become educational tools for surgical trainees. The aim of our study is to analyze YouTube videos for accurate and up-to-date information about robotic segmentectomy operations.
    METHODS: The videos on www.youtube.com, which were reached on July 11, 2024, by using the keywords 'Robot segmentectomy' and 'Robotic segmentectomy lung', were evaluated in this research. The videos were evaluated by using the Journal of the American Medical Association (JAMA) scoring system, critical view of safety (CVS), and LAParoscopic surgery Video Educational GuidelineS (LAP-VEGaS).
    RESULTS: Eighty-one videos were included. Almost half of the videos (n = 42) were affiliated with university hospitals. Preoperative imaging was seen in 49% of all videos; however, the rates were 32% and 20.9% for patients' demographics and preoperative assessment information, respectively. Only 29.6% of the videos presented the placement of trocars during the presentation.
    CONCLUSIONS: It has become possible to record high-quality videos easily with developing technology. However, our results showed that many of the videos don't include the parameters, especially related to education. Therefore, we believe that those videos are inadequate for trainees.
    DOI:  https://doi.org/10.1055/a-2513-9522
  24. Dental Press J Orthod. 2025 ;pii: S2176-94512024000600306. [Epub ahead of print]29(6): e2424151
    Are YouTube™ and TikTok™ videos useful as educational tool for patients with cleft lip and palate?
    José Dilson Alves de Oliveira Júnior, Anna Vitória Mendes Viana Silva, Carina Cristina Montalvany-Antonucci, Gabriele Andrade Maia, Kamila Rodrigues Junqueira Carvalho, Soraia Macari.
       OBJECTIVE: To evaluate the quality of YouTube™ and TikTok™ videos as educational tools for patients with cleft lip and palate (CLP) as regards their care, and multidisciplinary treatment.
    METHODS: Videos were searched on YouTube™ and TikTok™ using four keywords. The reliability and quality of the first 60 videos for each keyword and platform were analyzed. The following variables were analyzed: the source, distribution, and purpose of the videos, the general and audiovisual quality of the videos, and their main subject. The study's covariates were cleft classification, dental treatment, pre-surgical orthopedic treatments, surgical and medical treatments.
    RESULTS: Of the 480 videos selected, 303 videos were evaluated (177 excluded due to the exclusion criteria). TikTok™ emerged as the most frequently accessed platform, recording a greater number of views and likes. YouTube™ stood out for its availability of longer and more comprehensive videos, in terms of content. On YouTube™ the majority of videos were produced by academic/health and medical organizations, predominantly aimed at educational purposes; whereas on TikTok™ prevailed the production of individual and personal content geared toward informational purposes. On both platforms, the videos proved to be of low quality. YouTube™ videos from individual sources and organizations were associated with medium and low quality, respectively. Additionally, YouTube™ videos of shorter duration were of lower quality. TikTok™ videos had lower overall quality, especially those produced individually, regardless of associations.
    CONCLUSIONS: YouTube™ and TikTok™ exhibited predominantly low-quality videos, suggesting they are not suitable as educational tools to guide patients with CLP for their multidisciplinary treatment.
    DOI:  https://doi.org/10.1590/2177-6709.29.6.e2424151.oar
  25. Health Informatics J. 2025 Jan-Mar;31(1):31(1): 14604582251315592
    Evaluating the quality of Spanish-language information for patients with type 2 diabetes on YouTube and Facebook.
    María Juliana Soto-Chávez, Candida Díaz-Brochero, Ana María Gómez-Medina, Diana Cristina Henao, Oscar Mauricio Muñoz.
      Introduction: Spanish speakers rely on social media for health information, with varying quality of its content. This study evaluates the reliability, completeness, and quality of type 2 diabetes (T2D) information available in Spanish-language videos on YouTube and Facebook. Methods: Analytical observational study that included Spanish-language videos on TD2 available on Facebook and YouTube. General characteristics, interaction and generating sources are described. Standardized tools were used to assess reliability, completeness and overall quality. Results: We included 172 videos, 90 from Youtube® and 82 from Facebook®. The median number of views was 1725 (IQR 213-10,000), with an average duration of 5.93 minutes (IQR 3.2-16.8) and an internet time of 834 days (IQR 407-1477). Most videos were uploaded by independent users (58.72%). Reliability (evaluated with DISCERN tool) had a median of 3 (IQR 2-3), completeness (content score) had a median of 2 (IQR 1-3), and overall quality, evaluated with the Global Quality Score (GQS) tool had a median of 3 (IQR 3-4). Using a global classification of "subjective reliability" 92.4% of the videos were considered reliable. Better completeness was observed in Facebook videos (p < .001). Reliability was better for videos from government or news organizations. Conclusion: Our results suggest that videos about T2D in Spanish on social media such as YouTube and Facebook have good reliability and quality, with greater exhaustiveness in content in Facebook videos and greater reliability for videos from government or news organizations.
    Keywords:  information sources; internet; social media; type 2 diabetes
    DOI:  https://doi.org/10.1177/14604582251315592
  26. Turk Arch Pediatr. 2025 Jan 02. 60(1): 71-77
    Celiac Disease in Children and YouTube: Do the Videos Contain Accurate Information?
    Abdulkerim Elmas, Mustafa Akcam.
      Objective: Celiac disease (CD) is a gluten-associated enteropathy whose incidence has been increasing in recent years. Parents whose children are diagnosed with CD search for information about the disease via the internet. YouTube is one of the most frequently used platforms to access information due to the number of users and ease of access. This study aims to investigate how much quality and reliable information the most frequently viewed videos contain for families seeking information about celiac disease in children via YouTube. Materials and Methods: On November 13, 2023, a global search for "Celiac in Children" was conducted on YouTube. The first 150 videos were evaluated using the most frequently watched video filter, and 86 eligible videos were included in the study. Journal of the American Medical Association (JAMA), Global Quality Scale (GQS), and modified DISCERN (ModDISCERN) scoring were performed for quality and reliability of the videos. Results: Thirty-five of the videos (40.7%) were related to childhood CD. When analyzed according to the upload source, 67 (77.9%) were created by healthcare professionals (doctors, nurses, dietitians, etc.) and 19 (22.1%) by independent users. Of all videos, 62% were of very poor and poor quality (1 and 2 points). Videos created by healthcare professionals had higher JAMA scores, GQS scores, and ModDISCERN scores (P = < .001/P =< .001/P =< .001/P =< .001/P =< .001/P =< .001, respectively). Conclusion: The quality and reliability of the most frequently watched YouTube videos about CD in children were generally low. At this point, analyzing videos on medical topics by experts and adding them to the search algorithm according to the scores will help users access reliable information.
    DOI:  https://doi.org/10.5152/TurkArchPediatr.2025.24235
  27. J Med Internet Res. 2025 Jan 14. 27 e59352
    The Association Between COVID-19 Vaccination Uptake and Information-Seeking Behaviors Using the Internet: Nationwide Cross-Sectional Study.
    Kazuya Taira, Misa Shiomi, Takayo Nakabe, Yuichi Imanaka.
       BACKGROUND: The COVID-19 pandemic, declared in March 2020, profoundly affected global health, societal, and economic frameworks. Vaccination became a crucial tactic in combating the virus. Simultaneously, the pandemic likely underscored the internet's role as a vital resource for seeking health information. The proliferation of misinformation on social media was observed, potentially influencing vaccination decisions and timing.
    OBJECTIVE: This study aimed to explore the relationship between COVID-19 vaccination rates, including the timing of vaccination, and reliance on internet-based information sources in Japan.
    METHODS: Using a cross-sectional study design using a subset of panel data, this nationwide survey was conducted in 7 waves. A total of 10,000 participants were randomly selected through an internet survey firm, narrowing down to 8724 after applying inclusion and exclusion criteria. The primary outcome was the COVID-19 vaccination date, divided into vaccinated versus unvaccinated and early versus late vaccination groups. The main exposure variable was the use of internet-based information sources. Control variables included gender, family structure, education level, employment status, household income, eligibility for priority COVID-19 vaccination due to pre-existing medical conditions, and a health literacy scale score. Two regression analyses using generalized estimating equations accounted for prefecture-specific correlations, focusing on vaccination status and timing. In addition, chi-square tests assessed the relationship between each information source and vaccination rates.
    RESULTS: Representing a cross-section of the Japanese population, the regression analysis found a significant association between internet information seeking and higher vaccination rates (adjusted odds ratio [aOR] 1.42 for those younger than 65 years; aOR 1.66 for those aged 65 years and older). However, no significant link was found regarding vaccination timing. Chi-square tests showed positive associations with vaccination for television, government web pages, and web news, whereas blogs and some social networking sites were negatively correlated.
    CONCLUSIONS: Internet-based information seeking is positively linked to COVID-19 vaccination rates in Japan, underscoring the significant influence of online information on public health decisions. Nonetheless, certain online information sources, including blogs and some social networks, negatively affected vaccination rates, warranting caution in their use and recognition. The study highlights the critical role of credible online sources in public health communication and the challenge of combating misinformation on less regulated platforms. This research sheds light on how the digital information landscape influences health behaviors, stressing the importance of accurate and trustworthy health information amidst global health emergencies.
    Keywords:  COVID-19; COVID-19 vaccines; Japan; adult; behavior; chi-square test; epidemiology; health informatics; information seeking behavior; internet use; longitudinal; panel study; regression analysis; survey; vaccine
    DOI:  https://doi.org/10.2196/59352
  28. J Health Commun. 2025 Jan 10. 1-9
    Validation of a Cancer-Focused Information Seeking Experience (ISEE) Scale.
    Ashley B Murray, Neha Trivedi, Roxanne E Jensen, Gordon Willis, Richard P Moser, Kelly D Blake.
       BACKGROUND: Searching for health information is critical for maintaining one's health and reducing risk of disease, including cancer. However, some people are more likely to experience challenges in finding and comprehending health information; therefore, it is important to measure health information-seeking behavior. In order to add to prior research conducted with the scale, this study provides the first formal evaluation of the validity and reliability of the four-item, cancer-focused Information Seeking Experience (ISEE) scale in a cross-sectional, nationally representative health survey of U.S. adults.
    RESULTS: Results indicated that the four ISEE scale items were within limits of normality (skew range = -.44-.11; kurtosis range = -1.07 - -.71), exhibited medium to strong pairwise correlations (r's = .54-.72), and indicated a strong internal consistency (Cronbach's α = .85). The scale was unidimensional (CFI = .997, TLI = .992, SRMR = .012), and the scale demonstrated construct validity with known sociodemographic characteristics. As predicted, the ISEE scale had relatively weak relationships with the Patient Health Questionnaire for Depression and Anxiety, Patient-Centered Communication Scale, and the Patient-Reported Outcomes Measurement Information System (PROMIS) Instrumental Support 4a, demonstrating discriminant validity.
    CONCLUSIONS: Tracking information-seeking experience in the population is critical, especially to inform efforts that ensure individuals have accessible, understandable, and reliable information about cancer. The ISEE scale was found to assess various aspects of cancer information-seeking in a reliable and valid manner and may be used in future surveys to track information support needs of those who seek health and cancer information.
    Keywords:  Cancer information-seeking; cancer communication; construct validity; health communication; health information-seeking; scale validation
    DOI:  https://doi.org/10.1080/10810730.2025.2449972
  29. JMIR Infodemiology. 2025 Jan 16. 5 e59625
    How Patients With Cancer Use the Internet to Search for Health Information: Scenario-Based Think-Aloud Study.
    Fiorella Huijgens, Pascale Kwakman, Marij Hillen, Julia van Weert, Monique Jaspers, Ellen Smets, Annemiek Linn.
       BACKGROUND: Patients with cancer increasingly use the internet to seek health information. However, thus far, research treats web-based health information seeking (WHIS) behavior in a rather dichotomous manner (ie, approaching or avoiding) and fails to capture the dynamic nature and evolving motivations that patients experience when engaging in WHIS throughout their disease trajectory. Insights can be used to support effective patient-provider communication about WHIS and can lead to better designed web-based health platforms.
    OBJECTIVE: This study explored patterns of motivations and emotions behind the web-based information seeking of patients with cancer at various stages of their disease trajectory, as well as the cognitive and emotional responses evoked by WHIS via a scenario-based, think-aloud approach.
    METHODS: In total, 15 analog patients were recruited, representing patients with cancer, survivors, and informal caregivers. Imagining themselves in 3 scenarios-prediagnosis phase (5/15, 33%), treatment phase (5/15, 33%), and survivor phase (5/15, 33%)-patients were asked to search for web-based health information while being prompted to verbalize their thoughts. In total, 2 researchers independently coded the sessions, categorizing the codes into broader themes to comprehend analog patients' experiences during WHIS.
    RESULTS: Overarching motives for WHIS included reducing uncertainty, seeking reassurance, and gaining empowerment. At the beginning of the disease trajectory, patients mainly showed cognitive needs, whereas this shifted more toward affective needs in the subsequent disease stages. Analog patients' WHIS approaches varied from exploratory to focused or a combination of both. They adapted their search strategy when faced with challenging cognitive or emotional content. WHIS triggered diverse emotions, fluctuating throughout the search. Complex, confrontational, and unexpected information mainly induced negative emotions.
    CONCLUSIONS: This study provides valuable insights into the motivations of patients with cancer underlying WHIS and the emotions experienced at various stages of the disease trajectory. Understanding patients' search patterns is pivotal in optimizing web-based health platforms to cater to specific needs. In addition, these findings can guide clinicians in accommodating patients' specific needs and directing patients toward reliable sources of web-based health information.
    Keywords:  cancer; caregiver; cognitive; emotional; health information; information seeking; internet; interview; men; motivation; patient; patient evaluation; pattern; response; scenario; scenario based; survivor; think aloud; web-based health information seeking; web-based information; women
    DOI:  https://doi.org/10.2196/59625
  30. Digit Health. 2025 Jan-Dec;11:11 20552076241305481
    Linking multiple-channel information seeking and lifestyle among Chinese older adults: A moderation and mediation analysis.
    Qingrui Li, Yifang Wu, Xinshu Zhao.
       Background: Healthy lifestyle improvement of older Chinese adults has drawn a lot of attention due to an exceeding ageing population in mainland China. The current study aims to investigate the beneficial functions of the multi-channel health information seeking on elders' lifestyle self-management.
    Objective: We conducted a mediation analysis to test the association between multi-channel information seeking behavior and lifestyle self-management, which mediates by perceived self-management competence. Meanwhile, we also test the moderation effect of perceived self-management competence on lifestyle management with motivation for health promotion and prevention as the moderator.
    Methods: To examine this mediation and moderation effects, we conducted a quota sampling online survey in mainland China from June 11 to October 12, 2023. The final sample size was 898 Chinese respondents aged 60 or above, with 54.5% male.
    Results: Health information seeking using the mHealth app (bp  = .03, 95% CI: [.005, .055]) and social media (bp  = .06, 95% CI: [.031, .086]) is positively associated with lifestyle self-management through perceived self-management competence. While broadcast media (bp  = .01, 95% CI: [-.015, .040]), print media (bp  = .01, 95% CI: [-.015, .026]), and search engine (bp  = .02, 95% CI: [-.006, .043]) show no significant impact on lifestyle management. Furthermore, health promotion and prevention motivation shows a positive moderation effect on perceived self-management competence and lifestyle management.
    Conclusions: Our findings show evidence supporting a cognitive mechanism of moderated mediation that links seeking health information to improve LSM in older Chinese adults. It is essential for health self-education and health promotion among older Chinese adults.
    Keywords:  Lifestyle; digital health; health information-seeking behavior; information foraging; motivation
    DOI:  https://doi.org/10.1177/20552076241305481
  31. Digit Health. 2025 Jan-Dec;11:11 20552076241309214
    eHealth, digital information and technology use of men with prostate cancer.
    Stuart R Jackson, Paul Yu, Steven Sowter, Stefano Occhipinti, Suzanne Chambers, Scott Leslie, Manish I Patel.
       Background: The investigation of digital information sources and technologies specifically used by men with prostate cancer is scarce. This study seeks to address current gaps in the literature by investigating prostate cancer-specific internet and technology use by men with prostate cancer and factors associated with this use.
    Methods: Cross-sectional surveys were conducted in three Australian urology clinics (local in Sydney, Western Sydney and Murrumbidgee) in 2023. Data analysis included descriptive and bivariate analysis. Chi square tests of independence, Mann-Whitney U tests and Fischer exact tests were used to assess demographic, prostate cancer-specific and psychometric variables with prostate cancer-specific usage of each website, social media and technology type.
    Results: A total of 349 men responded. Mean age of respondents was 69.6 years (SD 7.8). 74.5% (n = 260) had undergone radical prostatectomy, while 10% (n = 35) reported locally advanced/metastatic disease. Information websites were used by 77.7% (n = 271) of men. Social media was used by 37% (n = 129), and total internet use was 79.1% (n = 276). Younger age, higher education and higher income were commonly associated with a greater extent of use of information source and technology types. High variability in usage and factor association was demonstrated between and within analysed group categories.
    Conclusions: Men with prostate cancer use a broad variety of digital information sources and technologies to access prostate cancer information at a higher rate than ever before. This work stresses the significant variability in the extent of use which men demonstrate among these resources and the factors which may play a role in this behaviour.
    Keywords:  Internet; cancer; digital; eHealth; information; prostate; social; technology
    DOI:  https://doi.org/10.1177/20552076241309214
  32. J Health Commun. 2025 Jan 13. 1-10
    For Myself or for Others? The Influence of Family Communication Patterns on Family Health History Communication and Online Health Information Seeking.
    Yulei Feng.
      With innovations in health information technology, there are increasing opportunities to search for health information online, with the potential to reduce health care costs and improve health outcomes for the family. This study aims to investigate how family communication processes influence online health information seeking for oneself (self OHIS) and for another person (surrogate OHIS). An online survey was conducted among 325 adults in China. The results showed that family conversation orientation was positively related to family health history (FHH) communication intentions, whereas family conformity orientation was negatively related to FHH communication intentions. Family conversation orientation was positively related to self and surrogate OHIS through the partial and masking mediation effects of FHH communication intentions, respectively. Family conformity orientation was negatively related to self OHIS through the full mediating effect of FHH communication intentions, while FHH communication intentions played a masking mediating role between conformity orientation and surrogate OHIS. Implications for extending family communication patterns research to health communication and cultural forces on OHIS are discussed.
    Keywords:  Online health information seeking; family communication patterns; family conversation; family health history communication;  family conformity,
    DOI:  https://doi.org/10.1080/10810730.2025.2450617
  33. J Child Orthop. 2025 Jan 11. 18632521241310318
    What are patients asking and reading online? An analysis of online patient searches about treatments for developmental dysplasia of the hip.
    Uma Balachandran, Renee Ren, Camila Vicioso, Jiwoo Park, Katrina S Nietsch, Brittany Sacks, Rodnell Busigo Torres, Sheena C Ranade.
       Purpose: We aimed to analyze frequently searched questions through Google's "People Also Ask" feature related to four common treatments for developmental dysplasia of the hip (DDH): the Pavlik harness, rhino brace, closed reduction surgery and open reduction surgery.
    Methods: Search terms for each treatment were entered into Google Web Search using a clean-install Google Chrome browser. The top frequently asked questions and associated websites were extracted. Questions were categorized using the Rothwell classification model. Websites were evaluated using the JAMA Benchmark Criteria. Chi-square tests were performed.
    Results: The initial search yielded 828 questions. Of 479 included questions, the most popular topics were specific activities that patients with DDH can/cannot do (32.8%), technical details about treatments (30.9%) and indications for treatments (18.2%). Websites were commonly academic (59.3%), commercial (40.5%) and governmental (12.3%). There were statistically significant more specific activity questions about Pavlik harnesses than about rhino braces (χ 2 = 7.1, p = 0.008), closed reduction (χ 2 = 56.5, p < 0.001) and open reduction (χ 2 = 14.7, p < 0.001). There were statistically significant more technical details questions about Pavlik harnesses than about closed reduction (χ 2 = 4.1, p = 0.04).
    Conclusions: This study provides insights into common concerns that parents have about their children's DDH treatment, enabling orthopaedic surgeons to provide more effective and targeted consultations. This is particularly important for DDH because affected patients are often diagnosed within the first few months of life, leaving parents overwhelmed by caring for a newborn child and simultaneously coping with this diagnosis.
    Keywords:  Developmental dysplasia of the hip; Pavlik harness; abduction brace; closed reduction surgery; open reduction surgery
    DOI:  https://doi.org/10.1177/18632521241310318
  34. JMIR Res Protoc. 2025 Jan 15. 14 e63489
    Evaluating Online and Offline Health Information With the Patient Education Materials Assessment Tool: Protocol for a Systematic Review.
    Emi Furukawa, Tsuyoshi Okuhara, Mingxin Liu, Hiroko Okada, Takahiro Kiuchi.
       BACKGROUND: The Patient Education Materials Assessment Tool (PEMAT) is a reliable and validated instrument for assessing the understandability and actionability of patient education materials. It has been applied across diverse cultural and linguistic contexts, enabling cross-field and cross-national material quality comparisons. Accumulated evidence from studies using the PEMAT over the past decade underscores its potential impact on patient and public action.
    OBJECTIVE: This systematic review aims to investigate how the quality of patient education materials has been assessed using the PEMAT.
    METHODS: This review protocol follows PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols) guidelines. PubMed, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL), APA PsycInfo, and Web of Science Core Collection will be searched systematically for articles published since September 2014. Two independent reviewers will conduct the search to yield a list of relevant studies based on the inclusion and exclusion criteria. Rayyan QCRI software will be used for screening and data extraction.
    RESULTS: The results will be included in the full systematic review, which is expected to start in September 2024 and be completed to be submitted for publication by early 2025.
    CONCLUSIONS: The findings are expected to identify the quality of materials evaluated by the PEMAT and the areas under evaluation. This review can also highlight gaps that exist in research and practice for improving the understandability and actionability of the materials, offering deeper insights into how existing materials can facilitate patient and public action.
    INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/63489.
    Keywords:  PEMAT; actionability Patient Education Materials Assessment Tool; behavior change; health communication; health information; health literacy; medical information; patient education; patient education materials; understandability
    DOI:  https://doi.org/10.2196/63489
  35. JMIR Ment Health. 2024 Dec 26.
    Harnessing Internet Search Data as a Potential Tool for Medical Diagnosis: Literature Review.
    Gregory J Downing, Lucas M Tramontozzi, Jackson Garcia, Emma Villanueva.
       BACKGROUND: Access to accurate medical diagnosis has been hindered by socioeconomic disparities, limited availability of specialized medical professionals, and lack of patient education, among other factors. Inequities in access to high-quality healthcare services exacerbate these challenges, often leading to disparities in health outcomes. Missed or inaccurate diagnoses can lead to delayed or unnecessary treatments, risking worsening of the condition. The historical reliance on direct patient-doctor interactions for diagnosis has often failed to bridge these gaps. The emergence of the internet and digital data in the latter part of the 20th century began to alter this landscape. Early research highlighted the early potential of the internet in patient education, setting the stage for an ever-increasing reliance on online health information, but questions remain regarding information accuracy, access and benefits, and privacy. Internet search data represent one of the largest sources of health data people seek. As of mid-2023, Google's daily search volume was over 8.5 billion queries. Around 5% of Google Searches are health related, and about 77% of persons with a new diagnosis use search engines. These and other data have prompted a series of research projects to address the feasibility and utility of using internet search data for seeking health services. Although the use of patient search data represents just one facet of technology being explored to help obtain more timely and accurate data about patient conditions, this paper focuses only on research studies that use internet search data.
    OBJECTIVE: To explore the potential and challenges of utilizing internet search data in medical diagnosis, focusing on ethical, technical, and policy considerations by assessing the current state of research, identifying gaps and limitations, and proposing future research directions to advance this emerging field.
    METHODS: A comprehensive analysis of peer-reviewed literature was conducted to examine the landscape of internet search data utilization in medical research. Searchers were performed for published peer-reviewed literature in PubMED (October to December 2023).
    RESULTS: Systematic selection according to predefined criteria resulted in the inclusion of 40 articles of the 2,499 identified citations. The analysis reveals a nascent domain of internet search data research in medical diagnosis, characterized by advancements in analytics and data integration. However, significant challenges such as bias, data privacy, and infrastructure limitations hinder its widespread adoption. Emerging initiatives may offer the transformative potential to reshape data collection methodologies and privacy safeguards.
    CONCLUSIONS: Signals correlating with diagnostic considerations have been identified in certain diseases and conditions, indicating the potential for such data to enhance clinical diagnostic capabilities. However, leveraging internet search data for improved early diagnosis and healthcare outcomes necessitates addressing ethical, technical, and policy challenges effectively. By fostering interdisciplinary collaboration, advancing infrastructure development, and prioritizing patient engagement and consent, researchers can unlock the transformative potential of internet search data in medical diagnosis, ultimately enhancing patient care and advancing healthcare practice and policy.
    CLINICALTRIAL:
    DOI:  https://doi.org/10.2196/63149
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