bims-librar 2026-08-02 papers

bims-librar

Biomed News

on Biomedical librarianship

Issue of 2026–08–02
thirty papers selected by
Thomas Krichel, Open Library Society

Future medical libraries.
Literature horizon scan for new scientific data on plants, microorganisms and animals, and their products obtained by new genomic techniques (March 2026).
Consumer Health Information: A Narrative Review.
What information is available online for adults with distal radius fracture? Online literature search and synthesis using generative AI.
LLMs in Medical Education for Autism Caregivers: A Comparative Evaluation of Accuracy, Readability, Actionability, and Neurodiversity-Affirming Language.
The use of structured prompt to improve the readability, accuracy, and quality of ChatGPT responses on labor epidural analgesia: a brief report.
Mapping the Reliability-Readability Gap in the Education of Patients With Age-Related Macular Degeneration Across 6 Large Language Models: Comparative Evaluation Study.
Leveraging Large Language Models to Address Common Vaccination Myths and Misconceptions.
Comparative Evaluation of AI Chatbots for Testicular Cancer Education: Validity, Information Quality, and Readability.
Conversational Artificial Intelligence as a Source of Oral Health Information: A Cross-Sectional Study in a Romanian Population.
Evaluating the quality of artificial intelligence responses to common patient questions about peripheral nerve blocks.
Online removable complete denture postdelivery instructions: Concordance with American College of Prosthodontists denture care guidelines and health literacy benchmarks.
Evaluating the Readability of Patient-Facing Online Educational Materials for Pediatric Leukemia and Lymphoma.
Quality of Korean and English online health information on pediatric flatfoot retrieved from NAVER and Google using the EQIP tool: a cross-sectional study.
Quality of Web-Based Patient Education on Osteoporosis Lifestyle Changes.
A comparative analysis of readability, quality, and reliability in large language model outputs pertaining to knee osteoarthritis queries.
Exploring global variations in the quality of patient information videos for keratoplasty.
Large language models as sources of patient information on robotic knee arthroplasty: a comparative evaluation.
Evaluation of the Educational Quality and Reliability of Cardiopulmonary Resuscitation Training Videos on YouTube™.
Quality and Reliability of YouTube Videos on Earthquake Preparedness: A Cross-Sectional Analysis.
YouTube as a source of patient information on robot-assisted radical prostatectomy: a cross-sectional study of quality, reliability, transparency, and content gaps.
YouTube as a source for clavicle fracture education: a quality, comprehensibility, and reliability assessment.
[Septoplasty videos on YouTube and assessment of the IVORY evaluation system : Analysis of video quality].
Tubal Permanent Contraception on TikTok: Content Themes and Quality of Educational Videos.
Content quality and source credibility of fall prevention videos for older adults on Chinese short-video platforms: A cross-sectional content analysis.
Channel Effects on Online Health Information Seeking in the Age of AI: An Extension of the CMIS Framework.
Caregiver Health Information-Seeking Behavior During Pandemics, Disasters, and Emergencies Within Pediatric Advocacy and Health Care Networks.
Online Health Information Needs of Pregnant Women in Low- and Middle-Income Countries: A Systematic Scoping Review.
Nativity and Cancer Information-Seeking Behaviors Among Middle-Aged and Older-Adults in the United States.
A Google Trend analysis of online searches for stroke.

Postgrad Med J. 2026 Jul 31. pii: qgag110. [Epub ahead of print]

Future medical libraries.

Apichai Wattanapisit, Chirk Jenn Ng, Sanhapan Wattanapisit.

DOI: https://doi.org/10.1093/postmj/qgag110
EFSA J. 2026 Jul;24(7): e10230

Literature horizon scan for new scientific data on plants, microorganisms and animals, and their products obtained by new genomic techniques (March 2026).

European Food Safety Authority (EFSA)

  The European Food Safety Authority has issued several scientific opinions on plants, microorganisms and animals obtained through certain new genomic techniques (NGTs), following requests received by the European Commission. These scientific opinions provided considerations on the potential risks associated with NGTs, as compared to conventional breeding techniques and established genomic techniques (EGTs), and on the applicability of existing guidelines for the risk assessment of plants, microorganisms and animals obtained by NGTs and products thereof. Against this background, EFSA was asked by the European Commission 'to provide scientific and technical assistance for a regular horizon scanning to assess new scientific data on plants, microorganisms and animals, and products thereof obtained by new genomic techniques', to assess any new data and evidence emerging from these studies, and to consider whether it may have implications for EFSA's relevant scientific opinions. A critical assessment of the quality and relevance of these studies should also be conducted, and biannual reports delivered to the Commission. This report presents the outcome of the literature search on new scientific data on plants, microorganisms and animals and products thereof obtained by NGTs, performed as described in the protocol made available for public consultation in May-June 2025. The report describes search strategies and inclusion/exclusion criteria applied for literature review and presents the results of the assessment performed for new scientific data (published up to March 2026) on plants, microorganisms and animals and products thereof obtained by NGTs. The report discusses the limitations of the search and provides recommendations for improvement. EFSA concluded that none of the studies retrieved by the literature search contained new hazards or risks not previously considered in EFSA scientific opinions.

Keywords:  CRISPR; biotechnology; genetically modified organisms; genome editing; targeted mutagenesis

DOI:  https://doi.org/10.2903/j.efsa.2026.10230
Med J Islam Repub Iran. 2026 ;40 22

Consumer Health Information: A Narrative Review.

Mohammad Javad Dehnavi, Nooshin Peyman, Mohammad Javad Mansourzadeh, Paria Amiri, Seyed Hojjat Khatamifar, Fatemeh Sheikhshoaei.

   Background: Consumer Health Information (CHI) encompasses the dissemination of information and the cultivation of appropriate attitudes toward healthcare, as well as specific professional skills, aimed at altering behaviors and enhancing the health status of consumers. The aim of this study was to introduce the concept, features, and associated issues of CHI, provide an overview of current research, and examine the information-seeking behavior of health information consumers.
Methods: On February 28, 2025, the keywords "consumer health information," "health literacy," and their related terms were searched in PubMed, Web of Science, Google Scholar, and grey literature sources. Out of 1,058 retrieved records, 55 met the inclusion criteria and were analyzed to extract the relevant characteristics.
Results: The findings of this study indicate that consumer health information (CHI) is a dynamic concept that encompasses the provision of information and the enhancement of skills related to healthcare, with the aim of influencing behavior and improving consumers' health. A review of the existing literature demonstrates that the evaluation components of this concept encompass a range that includes comprehensiveness, credibility, readability, and usefulness. Furthermore, the Internet, social media, and artificial intelligence tools serve as the primary platforms for searching for and accessing such information. The results also suggest that challenges such as misinformation, information overload, and limitations in health literacy significantly influence information-seeking behavior, underscoring the necessity for increased attention to the role of librarians as trusted information intermediaries.
Conclusion: The necessity of disseminating accurate and reliable health information tailored to consumers' needs is underscored by the increasing trend of scientific output in this domain in recent years. It is essential to develop standard guidelines and regulations, as well as to create appropriate infrastructure for CHI at the macro level. Furthermore, conducting economic studies to evaluate the return on investment and utility of CHI can aid policymakers in their decision-making processes.

Keywords:  Consumer Health Information; Health Information Literacy; Internet; Narrative Review

DOI:  https://doi.org/10.47176/mjiri.40.22
Hand Ther. 2026 Jul 28. 17589983261472044

What information is available online for adults with distal radius fracture? Online literature search and synthesis using generative AI.

Daniel Ceh, Kalpesh R Vaghela, Lisa Newington.

   Introduction: Distal radius fractures (DRFs) are the most common adult fracture in the UK, and patients seek online information to support recovery. The quality of such information varies, including in artificial intelligence (AI) generated summaries. This study explored the use of a generative AI model (Gemini) for information searching and synthesis of patient information on DRF recovery.
Methods: Seven health information questions were co-developed with patients, hand therapists, and surgeons. Each question was searched in Google using three terms: 'distal radius fracture', 'wrist fracture', and 'broken wrist'. For each AI Overview, the summary and cited sources were exported. Citations were screened for relevance and checked for accurate representation in the AI summary. Trustworthiness was rated using a National Institutes of Health (NIH) framework. AI summaries were compared with four UK guidelines on DRF management and rehabilitation.
Results: Across all searches, 277 citations were identified; 37% were irrelevant. Of relevant citations, 57% (n = 99) were highly trustworthy, 40% (n = 70) moderately, and 3% (n = 6) low. Core messages aligned with UK guidelines, but AI summaries often gave fixed recovery timeframes.
Discussion: Google's AI Overview produced generally accurate, trustworthy DRF recovery information. However, variable source relevance, differing complexity by search term, and fixed timeframes highlight the need for clinicians to understand the online content patients encounter. Terminology influenced tone, 'distal radius fracture' yielded technical summaries, 'wrist fracture' mixed technical and practical advice, 'broken wrist' offered more lay-friendly guidance. Awareness of these differences can support personalised advice and bridge gaps between AI-generated content and evidence-based practice.

Keywords:  artificial intelligence; health information seeking behaviour; health literacy; radius fractures; rehabilitation

DOI:  https://doi.org/10.1177/17589983261472044
Healthcare (Basel). 2026 Jul 16. pii: 2137. [Epub ahead of print]14(14):

LLMs in Medical Education for Autism Caregivers: A Comparative Evaluation of Accuracy, Readability, Actionability, and Neurodiversity-Affirming Language.

Shahid Akhtar Akhund, Asma Alsaleh, Naheed Haroon Kazi, Bheemsain Rajpal, Shahmina Naz, Shoukat Ali Arain.

  Background: Family caregivers of children with autism spectrum disorder (ASD) increasingly utilize large language models (LLMs) for health information. This study presents a systematic comparative evaluation of three widely used LLMs as localized ASD health information tools in Saudi Arabia. Methods: Twenty-four clinically validated, caregiver-oriented questions were posed to Google Gemini 1.5 Pro, OpenAI ChatGPT (GPT-4o), and DeepSeek-V3 using a standardized prompt. Three expert raters independently evaluated responses across four dimensions: scientific accuracy, PEMAT-P understandability, PEMAT-P actionability, and neurodiversity (ND)-affirming language. Readability was assessed via Flesch-Kincaid Grade Level (FKGL) and SMOG indices. Non-parametric Kruskal-Wallis tests with post hoc Mann-Whitney U comparisons and one-sample t-tests were applied. Results: Gemini achieved the highest mean accuracy (2.96/3.00), significantly outperforming DeepSeek (p = 0.003, r = -0.37). Accuracy failures across all LLMs clustered on regional epidemiological, genetic risk, and financial inquiries. ChatGPT achieved significantly higher understandability than Gemini (p < 0.001, r = 0.55), while DeepSeek achieved significantly higher actionability than Gemini (p < 0.001, r = 0.59). However, all three LLM scores fell short of the Agency for Healthcare Research and Quality (AHRQ) 80% actionability benchmark (all p < 0.001). All LLMs exceeded patient education readability benchmarks (FKGL ≤ 6, SMOG ≤ 8; all p < 0.001); ChatGPT was the most readable (FKGL = 7.86; SMOG = 9.97) and Gemini the most complex. No model differed significantly on ND-affirming language, defaulting to a mixed medical-affirming register. Conclusions: Evaluated LLMs demonstrated distinct, specialized strengths: Gemini was the most accurate, ChatGPT the most readable, and DeepSeek the most actionable. Importantly, all models failed to meet established consumer education standards for readability and actionability. LLMs require extensive plain-language adaptation and cultural customization. Clinicians must guide families on navigating LLM outputs, particularly concerning country-specific epidemiological, economic, and healthcare service queries.

Keywords:  ChatGPT; DeepSeek; FKGL; Gemini; PEMAT-P; SMOG; Saudi Arabia; autism spectrum disorder; caregiver education; health literacy; large language models; neurodiversity-affirming language

DOI:  https://doi.org/10.3390/healthcare14142137
Int J Obstet Anesth. 2026 Jul 25. pii: S0959-289X(26)00415-2. [Epub ahead of print]68 105257

The use of structured prompt to improve the readability, accuracy, and quality of ChatGPT responses on labor epidural analgesia: a brief report.

C W Tan, R J K Sng, J C Y Chan, J J I Chan, S Nagarajan, B L Sng.

   BACKGROUND: Artificial intelligence chatbot responses to frequently asked questions on labor epidural analgesia reported poor readability with limited consideration on personalized context. We investigated whether a structured prompt based on Context, Role, Action, Format, Tone (CRAFT) framework could improve the readability and accuracy of these chatbot-generated responses.
METHODS: Twenty-nine questions on labor epidural analgesia covering patient preferences and clinical scenarios were evaluated in ChatGPT-5.2. Two sets of responses were produced: one generated with direct questions and the other using CRAFT-based prompt prior to the questions. Readability metrics were applied to each response and averaged, while accuracy was calculated as the proportion of correct statements. Quality was assessed using Patient Education Materials Assessment Tool for Print, with four obstetric and gynecological anesthesiologists independently evaluating understandability and actionability on top of accuracy.
RESULTS: Responses generated using CRAFT-based prompt had significantly better readability than those with direct questions only. The direct-question responses ranged from slightly difficult to professional (9th grade to college level), whereas the CRAFT-based prompt responses ranged from fairly easy to slightly difficult (6th to 9th grade). Accuracy was significantly higher in CRAFT-based prompt group than direct-question group (99.8% ± 0.2% vs. 99.0% ± 0.4%, P = 0.029). No significant differences were observed in understandability or actionability scores.
CONCLUSIONS: Incorporating CRAFT-based prompts could generate responses with high accuracy and quality on understandability and actionability. Patient education could involve customized prompts to improve readability and accuracy. This approach could thus improve access to reliable clinical information and support shared decision-making.

Keywords:  Artificial intelligence; Chatbots; Educational level; Labor epidural analgesia; Prompts

DOI:  https://doi.org/10.1016/j.ijoa.2026.105257
JMIR Med Inform. 2026 Jul 28. 14 e91016

Mapping the Reliability-Readability Gap in the Education of Patients With Age-Related Macular Degeneration Across 6 Large Language Models: Comparative Evaluation Study.

Zhili Lu, Haixing Cao, Cong Ma, Jin Zheng, Xiang Ma.

   Background: Artificial intelligence-generated health information is increasingly used by patients, but its reliability, visible transparency indicators, and readability remain uncertain in specialized ophthalmic conditions such as age-related macular degeneration (AMD).
Objective: This study aimed to evaluate and compare the informational reliability, visible transparency indicators, overall quality, and readability of responses generated by 6 publicly accessible large language models (LLMs) to AMD-related patient-facing prompts under a zero-shot, single-turn prompting scenario.
Methods: Thirty English-language AMD-related prompts were curated from Google Trends, the 2023 Chinese AMD guideline, and the 2025 American Academy of Ophthalmology Preferred Practice Pattern. Chinese guideline-derived prompts were translated and reviewed before model querying. Each finalized prompt was entered verbatim into ChatGPT-5.1-auto, DeepSeek-v3.2, Gemini-2.5-Flash-Thinking, Grok 4, Claude-Sonnet 4.5, and Qwen3-Max between October 10 and November 25, 2025. Two senior ophthalmologists (ZL and XM) blinded to model identity independently scored all responses using DISCERN, Ensuring Quality Information for Patients (EQIP), Global Quality Scale, and Journal of the American Medical Association benchmark criteria, with adjudication for disagreements. Readability was assessed using 6 standard formulas against a sixth-grade benchmark. Between-model differences were analyzed using Friedman tests with Holm-adjusted pairwise comparisons.
Results: A total of 180 responses were analyzed. Interrater agreement was substantial to near-perfect across reliability instruments (κ=0.72-0.97). No model met the recommended sixth-grade readability target. Grok 4 achieved the highest scores on reliability-related instruments, including DISCERN (mean 46.40, SD 7.43) and EQIP (mean 74.33, SD 9.07), whereas DeepSeek-v3.2 generated the most readable responses, with the highest Flesch Reading Ease Score (mean 48.23, SD 9.16) and lowest Flesch-Kincaid Grade Level (mean 9.95, SD 1.87). Significant between-model differences were observed across all reliability and readability metrics (all P<.001).
Conclusions: Under zero-shot, single-turn prompting conditions, the evaluated public LLMs showed substantial model-dependent differences in AMD-related patient education quality and readability. No model met the sixth-grade readability benchmark, including those with comparatively stronger reliability performance. These findings support clinician oversight, readability optimization, and further evaluation before LLM-generated AMD information is used directly in patient-facing settings.

Keywords:  age-related macular degeneration; health literacy; information quality; large language models; patient education

DOI:  https://doi.org/10.2196/91016
Vaccines (Basel). 2026 Jul 03. pii: 594. [Epub ahead of print]14(7):

Leveraging Large Language Models to Address Common Vaccination Myths and Misconceptions.

Florian Reis, Lea J Bayer, Claudius Malerczyk, Christian Lenz, Christof von Eiff.

  Background/Objectives: Large language models (LLMs) are increasingly used by the public to seek health information, yet their accuracy in addressing common vaccine myths remains unclear. Sycophantic LLM behavior, where models align with rather than correct user-stated beliefs, poses specific risks in health contexts. Methods: We conducted an exploratory multi-vendor evaluation of three LLMs (GPT-5, Gemini 2.5 Flash, Claude Sonnet 4) using officially curated vaccination myths from Germany's public health institution and two realistic user framings (curious skeptic, convinced believer). All model responses were independently evaluated by two blinded medical experts for misconception addressal (binary criterion applied to the response text), scientific accuracy, and communication clarity (5-point Likert scales). Additionally, blinded marketing experts ranked models for lay communication clarity. Flesch Reading Ease scores were computed for all outputs. Results: Across all myths, framings, and models (66 response items), both medical raters judged that all responses refuted the targeted misconception; no response affirmed or ignored a myth, including under the adversarial convinced believer framing. Scientific accuracy and clarity ratings were high and tightly clustered (median 4.0-4.5), with no combined score below 3 and substantial inter-rater agreement. Marketing experts independently ranked Gemini 2.5 Flash and GPT-5 highest for lay clarity. Readability analysis revealed generally low accessibility, particularly for the convinced believer framing and for Claude Sonnet 4 outputs. Conclusions: Our findings suggest that general-purpose LLMs can produce scientifically accurate, on-topic rebuttals to widely documented vaccine myths under realistic default conditions, although linguistic complexity and framing-sensitive style may limit accessibility. Whether such outputs change beliefs or behavior in hesitant individuals was not tested. With readability optimization, these outputs could serve as building blocks for myth-debunking tools, given prospective evaluation with behavioral endpoints.

Keywords:  health communication; health literacy; large language models; myth debunking; vaccine hesitancy; vaccine myths

DOI:  https://doi.org/10.3390/vaccines14070594
Ann Surg Oncol. 2026 Jul 28.

Comparative Evaluation of AI Chatbots for Testicular Cancer Education: Validity, Information Quality, and Readability.

Jiadong Zhao, Shuolei Sun, Anguo Zhao, Rui Liang, Lei Peng, Xiqi Peng, Rongkang Li.

   BACKGROUND: Large language models (LLMs) are increasingly used in health information seeking, but their performance in testicular cancer education remains unclear. This study evaluated the validity, reliability, and readability of responses generated by four widely used artificial intelligence (AI) chatbots.
METHODS: Four AI chatbots (ChatGPT 5.2, Copilot 2025, DeepSeek V3.2, and Gemini 2.5 Pro) were assessed. Structured clinical-knowledge accuracy was evaluated using 250 testicular cancer-related multiple choice questions across five domains, each administered to each model three times. The information quality of patient-facing responses was assessed using 12 patient-oriented questions derived from Google Trends queries and refined based on clinical experience, with responses rated using DISCERN, Ensuring Quality Information for Patients (EQIP), Global Quality Scale (GQS), and Journal of the American Medical Association (JAMA) benchmark criteria. Readability was measured using six standard readability indices and compared with the sixth-grade level recommended by the American Medical Association and the National Institutes of Health.
RESULTS: All four chatbots demonstrated high structured clinical-knowledge accuracy, with overall multiple choice question accuracy exceeding 96%. ChatGPT 5.2 achieved the highest accuracy (98.40%), followed by Gemini 2.5 Pro (97.20%), DeepSeek V3.2 (97.07%), and Copilot 2025 (96.93%). Overall accuracy differed significantly among models (p = 0.026), and only ChatGPT 5.2 significantly outperformed Gemini 2.5 Pro after Bonferroni correction. ChatGPT 5.2 also achieved the highest information-quality scores on DISCERN, EQIP, and GQS, whereas JAMA scores were uniformly low across all models. DeepSeek V3.2 generated the most readable responses overall. However, none of the chatbots met recommended readability thresholds, and all significantly deviated from sixth-grade readability benchmarks.
CONCLUSION: AI chatbots showed high validity in answering testicular cancer-related questions, but important differences remained in information quality and readability. ChatGPT 5.2 provided the most reliable responses, whereas DeepSeek V3.2 produced the most readable content. These tools may support patient education, but they cannot yet replace clinician-guided and evidence-based communication.

Keywords:  Artificial intelligence; Chatbots; Information quality; Readability; Testicular cancer

DOI:  https://doi.org/10.1245/s10434-026-20266-3
Dent J (Basel). 2026 Jul 10. pii: 424. [Epub ahead of print]14(7):

Conversational Artificial Intelligence as a Source of Oral Health Information: A Cross-Sectional Study in a Romanian Population.

Marina Antoneta Pop, Abel Emanuel Moca, Mihai Porumb, Anca Porumb.

  Background/Objectives: Large language models have created new pathways for patients to access health information, yet little is known about how the general population uses these conversational artificial intelligence (AI) tools for oral health concerns. This study investigated patterns of AI use as a source of oral health information, the nature of data shared with these systems, users' perceptions, and the impact on dental care-seeking behavior. Methods: A cross-sectional study was conducted among adults from Bihor County, Romania, using a structured 16-item online questionnaire distributed via social media, with eligibility restricted to individuals who had previously used conversational AI for oral health information. The final sample comprised 393 valid responses from this self-selected group of users. Fisher's exact test and Z-tests with Bonferroni correction were applied (α = 0.05). Results: Most participants were female (68.2%), university-educated (52.9%), and lived in an urban setting (88.3%). Significant differences in patterns of AI use for oral health information were identified according to age, sex, and living environment (p < 0.001). Younger participants used AI more frequently, while older individuals perceived the information as less clear. The vast majority used AI for informational or preliminary guidance purposes, with very few treating it as a substitute for professional opinion. A relevant subset shared visual data (intraoral photographs or radiographs) with AI systems, raising data privacy concerns. Rural participants more frequently delayed dental visits and less often discussed AI-derived information with their dentist compared to urban participants. Conclusions: When used by the public as a source of oral health information, AI is increasingly adopted, with adoption shaped by age, sex, and socioeconomic context. These findings concern only this informational use and do not extend to other applications of AI in dentistry, such as diagnostic support, image analysis, or clinical decision-making. Dental professionals should proactively engage patients about their use of AI for oral health information to ensure that digitally obtained content is appropriately contextualized.

Keywords:  artificial intelligence; dental behavior; large language models; oral health

DOI:  https://doi.org/10.3390/dj14070424
Can J Anaesth. 2026 Jul 31.

Evaluating the quality of artificial intelligence responses to common patient questions about peripheral nerve blocks.

Ekambir Saran, Vetri Thangavelu, Marc S Moreno, Ahtsham U Niazi.



Keywords:  artificial intelligence; nerve blocks; patient education; regional anesthesia

DOI:  https://doi.org/10.1007/s12630-026-03164-w
J Prosthet Dent. 2026 Jul 29. pii: S0022-3913(26)00483-X. [Epub ahead of print]

Online removable complete denture postdelivery instructions: Concordance with American College of Prosthodontists denture care guidelines and health literacy benchmarks.

Carson Chou, Tara Boroumand, Mohammad A Sabeti, Sun Lim, Ambika Parti.

STATEMENT OF PROBLEM: The extent to which patient-directed, web-based removable complete denture postdelivery instructions are concordant with the American College of Prosthodontists (ACP) evidence-based guidelines for the care and maintenance of removable complete dentures and meet health literacy benchmarks is unclear.
PURPOSE: The purpose of this cross-sectional content analysis was to evaluate the concordance of online removable complete denture postdelivery instructions with ACP denture care guidelines and to assess readability, understandability, and actionability.
MATERIAL AND METHODS: A prosthodontist-informed Google search identified U.S. webpages with patient-directed, removable complete denture postdelivery instructions. Two calibrated reviewers scored ACP concordance with a 15-item checklist and assessed understandability and actionability using the Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P); interrater reliability was assessed with intraclass correlation coefficients. Readability was calculated as average grade level (AGL) from 4 indices. Benchmark comparisons used 1-sample t tests. Practice-type comparisons used Welch 2-sample t tests for ACP concordance, AGL, and PEMAT-P understandability and a Mann-Whitney U test for PEMAT-P actionability. Holm-Bonferroni adjustment was applied across 7 primary inferential tests (α=.05).
RESULTS: Fifty-four webpages met the inclusion criteria. Mean ACP concordance was 29.1 ±13.7% (95% CI, 25.4% to 32.9%) or 4.4 of 15 items. Wearing and follow-up recommendations were most frequently present, whereas adhesive-related items were rarely addressed (4.8%). Mean AGL was 9.3 ±1.1 (95% CI, 9.0 to 9.6), significantly above the sixth-grade benchmark (Holm-adjusted P<.001); no webpage met that benchmark (0/54, 0%; 95% CI, 0.0% to 6.6%). Mean PEMAT-P understandability and actionability were 59.8 ±11.3% (95% CI, 56.8% to 62.8%) and 56.9 ±11.5% (95% CI, 53.8% to 59.9%), both below the 70% benchmark (Holm-adjusted P<.001). Practice-type differences were not significant (Holm-adjusted P=.667 to >.999). Interrater reliability was excellent (ICC[2,2]=0.90 to 0.98).
CONCLUSIONS: Based on the findings of this cross-sectional content analysis, patient-directed online removable complete denture postdelivery instructions had a mean ACP guideline concordance of 29.1%, and 0%, 13.0%, and 7.4% met the readability, understandability, and actionability benchmarks, respectively. No statistically significant differences were detected between prosthodontic and nonprosthodontic practice webpages.

DOI: https://doi.org/10.1016/j.prosdent.2026.07.006
Pediatr Blood Cancer. 2026 Jul 30. e70602

Evaluating the Readability of Patient-Facing Online Educational Materials for Pediatric Leukemia and Lymphoma.

Chloe Strege, Simone Intriago Tito, Courtney Popp, William C Miller, Cindy Eide, Christen Ebens, Jakub Tolar.

   BACKGROUND: Together, leukemia and lymphoma account for 38.7% of newly diagnosed pediatric cancer cases in the United States each year. Many caregivers utilize online resources to inform medical health decisions. Understanding the readability of these materials is critical to ensuring comprehensible patient education. We sought to evaluate if the readability of online patient-facing educational materials concerning pediatric leukemia and lymphoma met the recommended sixth-grade reading level by the National Institute of Health (NIH) and the American Medical Association (AMA).
METHODS: The websites of the 72 National Cancer Institute (NCI) accredited cancer centers were accessed and the presence of a pediatric-specific informational page regarding leukemia, non-Hodgkin lymphoma, and Hodgkin lymphoma were recorded and analyzed using Flesch-Kinkaid, Coleman-Liau, and SMOG readability indices. The top 50 internet search results for pediatric leukemia, non-Hodgkin lymphoma, and Hodgkin lymphoma were also analyzed.
RESULTS: The average readability across disorders for the NCI-accredited Cancer Centers ranged from 8.62 to 10.20. A total of 95.6% of the Cancer Center materials did not meet the NIH and AMA guidelines. The average readability across disorders for the top 50 searches ranged from 10.52 to 11.01. A total of 98% of the search materials did not meet the guidelines.
CONCLUSIONS: The materials currently available online may be too complex for the average individual to understand, providing a potential barrier to making informed healthcare decisions. Correcting the readability of online materials, including those that are physician-recommended, is crucial to ensuring comprehensive patient education.

Keywords:  patient educational materials; pediatric Hodgkin lymphoma; pediatric leukemia; pediatric non‐Hodgkin lymphoma; readability

DOI:  https://doi.org/10.1002/1545-5017.70602
J Yeungnam Med Sci. 2026 ;43 50

Quality of Korean and English online health information on pediatric flatfoot retrieved from NAVER and Google using the EQIP tool: a cross-sectional study.

Yoon Ki Kim, Dong-Hwan Kim, Changsin Lee, Seung Hoo Lee.

   BACKGROUND: Parents increasingly rely on the internet for health-related information about their children; however, the quality of such information remains inconsistent. Pediatric flatfoot is a common parental concern in pediatric orthopedics. This study compared the quality of NAVER-retrieved Korean-language websites and Google-retrieved English-language websites on pediatric flatfoot using the Ensuring Quality Information for Patients (EQIP) tool.
METHODS: Websites related to pediatric flatfoot were searched using NAVER for Korean-language information and Google for English-language information. After applying the predefined exclusion criteria, 50 websites from each group were evaluated using the 36-item EQIP tool, which assesses content, identification, and structure. Total and domain scores were compared between the two groups and according to institution type.
RESULTS: Google-retrieved English-language websites had significantly higher total EQIP scores than NAVER-retrieved Korean-language websites (55.50±10.17 vs. 44.88±11.83, p<0.001), with higher content and structure scores but similar identification scores. Among NAVER-retrieved Korean-language websites, public institution websites had higher total EQIP scores than private websites (55.38±8.69 vs. 39.95±9.74, p<0.001), mainly owing to higher content scores. Among the top 10 search results in each group, Google-retrieved English-language websites had higher EQIP scores and included more public institution websites than NAVER-retrieved Korean-language websites.
CONCLUSION: In the selected search environment, Google-retrieved English-language websites had higher EQIP scores than NAVER-retrieved Korean-language websites. Among the NAVER-retrieved Korean-language websites, public institution websites provided higher-quality information than private websites, but their visibility in the NAVER search results was limited. Improving the quality and visibility of reliable Korean online resources may support informed parental decision-making.

Keywords:  Flatfoot; Foot; Internet; Patient education; Pediatrics

DOI:  https://doi.org/10.12701/jyms.2026.43.50
PRiMER. 2026 ;10 12

Quality of Web-Based Patient Education on Osteoporosis Lifestyle Changes.

Shaina Banh, Lynchi Nguyen, Michelle Kim, Alice Lee, John C Hagedorn, Namita Bhardwaj.

Introduction: Osteoporosis is a prevalent condition associated with reduced bone density and increased fracture risk, yet many patients rely on online health information to guide lifestyle management. This study aimed to evaluate the quality and accessibility of consumer health websites providing information on osteoporosis lifestyle modifications.
Methods: A systematic Google search identified the first 150 websites, with 85 websites eligible for inclusion. After review of several national guidelines, we established four lifestyle domains: calcium/vitamin D supplementation, fall prevention, exercise, and smoking cessation. Two independent reviewers assessed each website using the DISCERN instrument, which examines the quality of written consumer health information.
Results: The mean DISCERN score was 50.7±9.71 (out of 80). Of the 85 websites, 7 (8.2%) were rated as excellent, 41 (48.2%) as good, 31 (36.5%) as fair, 5 (5.9%) as poor, and 1 (1.2%) as very poor. Accessibility features were limited, with 7.8% offering translation and 31.8% incorporating multimedia content.
Conclusions: These findings demonstrate considerable variability in quality and highlight gaps in accessibility. Improvements in guideline-based recommendations, transparency, and reliability can support more equitable osteoporosis care.

DOI: https://doi.org/10.22454/PRiMER.2026.259063
PLoS One. 2026 ;21(7): e0353355

A comparative analysis of readability, quality, and reliability in large language model outputs pertaining to knee osteoarthritis queries.

Erdem Maraşlı, Erkan Ozduran, Volkan Hancı.

This study aims to comparatively examine the readability, accuracy, and quality of responses provided by artificial intelligence (AI)-based chatbots such as Perplexity, ChatGPT-5, and Gemini to questions about knee osteoarthritis (KOA), which accounts for approximately four-fifths of the global osteoarthritis (OA) burden. In this study, 8 keywords were determined by excluding repetitive, irrelevant or synonymous ones from the 25 most frequently used English keywords associated with KOA based on Google Trends data, and these terms were asked as questions to three different artificial intelligence-based chatbots. The study measured readability using formulas like Coleman-Liau Index (CLI), Automated Readability Index (ARI), and Linsear Write (LW). Reliability of the information was assessed using the Journal of the American Medical Association (JAMA) benchmarks along with the modified DISCERN instrument. To determine overall content quality, the Global Quality Score (GQS) and the Ensuring Quality Information for Patients (EQIP) scale were applied. Together, these tools provided a comprehensive assessment of how understandable, reliable, and high-quality each chatbot's responses were. The most frequently searched keywords related to OA were "osteoarthritis of knee," "knee pain," and "osteoarthritis knee pain." A readability analysis of responses from three different AI-based chat systems revealed that all platforms had text levels above the Grade 6 threshold, and this difference was statistically significant (p < 0.05). Comparisons demonstrated that ChatGPT-5 produced the most readable content (FRES:45, GFOG:11.9, FKGL:9.24, CLI:14.03, SMOG:8.37, ARI:11.37, LW:7.2). However, Perplexity achieved significantly higher scores than ChatGPT-5 across all quality and reliability assessments, yielding superior median scores (DISCERN: 4, JAMA: 2, GQS: 4, EQIP: 92.8). Perplexity also outperformed Gemini in the mDISCERN reliability assessment (p = 0.001), while no significant difference in quality or reliability was found between Gemini and ChatGPT-5. No statistically significant difference was found between Gemini and ChatGPT in reliability and quality surveys. This analysis of KOA highlights significant challenges regarding the potential of popular AI chatbots for patient information. When examining readability levels, responses from these tools consistently exceed the recommended comprehensibility threshold, making it difficult for patients to absorb critical information. Furthermore, the relatively low scores recorded in reliability and content quality assessments raise significant concerns about the scientific validity and integrity of the medical information presented. Given these findings, the sufficient quality, robustness, and appropriate levels of understandability of future AI-based tools can only be ensured by the establishment and operation of an effective oversight mechanism.

DOI: https://doi.org/10.1371/journal.pone.0353355
Oman J Ophthalmol. 2026 May-Aug;19(2):19(2): 217-222

Exploring global variations in the quality of patient information videos for keratoplasty.

David Luke Stanley, Jessica Westwood, Josh Li Saw Hee, Gibran F Butt.

   BACKGROUND: Healthcare information is easily accessible on YouTube; however, it is unregulated and the quality varies considerably. This study evaluates the causes for variation in the quality of corneal transplantation patient information videos on YouTube.
METHODS: YouTube was searched using "corneal transplant" and the variations for penetrating and lamellar transplants. The results were deduplicated and screened for inclusion by two independent reviewers. A modified DISCERN tool was used to evaluate the quality of each video by two observers independently. Differences in quality were assessed by production location and legality of direct-to-consumer (DTC) advertising.
RESULTS: Twenty-two videos were included in this study and the mean overall DISCERN score was 2.05 out of 5 (standard deviation = 1.09). Videos scored the highest in relevance to corneal transplant (mean 4.05) and lowest in explaining which patients are unsuitable (mean 1.00) and supporting shared decision-making (mean 1.05). The video with highest viewer engagement was created by McMaster University students. Videos produced in the United States (US) discussed uncertainty and risk less frequently (49% and 43% less, respectively [P < 0.05]) than videos released outside the US.
CONCLUSIONS: Quality of YouTube content is variable and the lack of clarity over corneal transplant subtypes can be confusing for patients. There is considerable scope to improve visuals within videos to supplement verbal information in clinic, alongside tailoring information to the relevant age demographic. Essential components frequently lacking include risk, especially where DTC advertising is legal. While videos may be a useful supplement they should not be relied on for comprehensive material.

Keywords:  Corneal transplantation; health videos; informed consent; patient information

DOI:  https://doi.org/10.4103/ojo.ojo_143_25
Knee. 2026 Jul 30. pii: S0968-0160(26)00261-9. [Epub ahead of print]62 104579

Large language models as sources of patient information on robotic knee arthroplasty: a comparative evaluation.

Mehmet Utku Ciftci, Ali Can Koluman, Ebru Aloğlu Çiftçi, Basar Burak Cakmur, Nezih Ziroğlu.

   BACKGROUND: Robotic-assisted total knee arthroplasty (rTKA) is increasingly used because of its surgical precision. However, inconsistent outcomes and high costs often lead patients to seek additional information from artificial intelligence (AI) tools. Large language models (LLMs) such as ChatGPT-4o, Gemini-2.5-Flash, and DeepSeek-V3 are commonly used, but their reliability and readability in orthopaedics remain unclear.
OBJECTIVES: To compare the reliability, usefulness, quality, and readability of responses to common patient questions about rTKA generated by leading LLMs.
METHODS: Three LLMs answered 20 frequently asked patient questions (n = 20) identified through Google Trends and expert validation. Three orthopaedic specialists (n = 3) evaluated reliability, usefulness, and overall quality using validated scales, while readability was assessed with standard indices.
RESULTS: Inter-rater reliability was good to excellent (ICC = 0.728-0.879). Gemini-2.5-Flash achieved significantly higher reliability and usefulness scores than ChatGPT-4o and DeepSeek-V3 (all p < 0.05). ChatGPT-4o and DeepSeek-V3 produced more readable but less accurate content, revealing an inverse relationship between reliability and readability.
CONCLUSIONS: Gemini-2.5-Flash provided the most reliable responses, highlighting the need for supervised integration of LLMs in patient education.

Keywords:  Artificial intelligence; Large language models; Patient education; Readability; Reliability; Robotic-assisted total knee arthroplasty

DOI:  https://doi.org/10.1016/j.knee.2026.104579
Br J Hosp Med (Lond). 2026 Jul 20. 87(7): 51256

Evaluation of the Educational Quality and Reliability of Cardiopulmonary Resuscitation Training Videos on YouTube™.

Süleyman Nogay, Turgut Dolanbay, Bilgehan Demir, Bilal Kartal, Asiye Özkan.

   AIMS/BACKGROUND: Cardiac arrest is a leading cause of mortality worldwide, and early, high-quality cardiopulmonary resuscitation (CPR) is critical for survival. With increasing use of digital media, YouTube™ has become a common resource for CPR education. However, the educational quality and scientific reliability of these videos remain inconsistent. This study aimed to evaluate the educational quality, reliability, and technical adequacy of CPR training videos on YouTube™ using tools and an evaluation index.
METHODS: A total of 120 CPR-related YouTube™ videos were analyzed. Videos were assessed using four validated tools: Modified DISCERN Scale (MDS), Journal of the American Medical Association (JAMA) scoring system, Global Quality Scale (GQS), and a newly developed evaluation index [cardiopulmonary resuscitation-video evaluation index (CPR-VEI)]. Video duration, views, likes, and uploader type were recorded, and analyses used nonparametric tests and Spearman correlation.
RESULTS: Institutionally produced videos demonstrated significantly higher view counts (p = 0.008) as well as higher JAMA (p < 0.001), CPR-VEI (p = 0.020), and MDS (p = 0.031) scores compared with individually uploaded content. Intermediate-duration videos demonstrated significantly higher CPR-VEI, GQS, and MDS scores compared with short-duration videos, while long-duration videos showed higher numbers of likes. Correlation analysis revealed strong positive associations between CPR-VEI and GQS and MDS scores, and a moderate positive correlation with the JAMA score.
CONCLUSION: CPR training videos on YouTube™ exhibit substantial variability in educational quality and reliability. Institutionally produced videos demonstrated higher quality and reliability, while intermediate-duration videos showed higher educational scores and long-duration videos demonstrated greater engagement. However, popularity metrics such as views and likes did not reliably reflect educational quality. These findings support the role of guideline-based, technology-enhanced learning as an essential component of contemporary CPR education.

Keywords:  cardiopulmonary resuscitation; educational measurement; emergency medical services; health education; social media

DOI:  https://doi.org/10.31083/BJHM51256
J Community Health. 2026 Jul 25.

Quality and Reliability of YouTube Videos on Earthquake Preparedness: A Cross-Sectional Analysis.

Mehtap Kılıç Yıldız, Cüneyt Çalışkan.

  Earthquakes have caused devastating impacts throughout history, highlighting the growing importance of pre-disaster risk management. With the increasing use of digital technologies, social media platforms such as YouTube have become widely used sources of information on earthquake preparedness. However, the quality and reliability of such content remain questionable. This study aimed to evaluate the quality, reliability, and content of YouTube videos related to earthquake preparedness. In this cross-sectional study, the top 100 most-viewed videos for the keywords "earthquake preparedness" and "earthquake safety information" were analyzed on January 19, 2026. After applying eligibility criteria, 72 videos were included. Video quality and reliability were assessed using the Global Quality Scale (GQS) and modified DISCERN (mDISCERN), while popularity was measured through view rate and the Video Power Index (VPI). Content analysis and non-parametric statistical tests were performed. The findings showed that the overall quality and reliability of videos were low to moderate. Longer videos tended to have higher quality and reliability scores, whereas engagement metrics did not reflect content quality. These results indicate a need to improve the availability of accurate, evidence-based, and practical earthquake preparedness information on digital platforms.

Keywords:  Earthquake; Information quality; Preparedness; Reliability; Social media; YouTube

DOI:  https://doi.org/10.1007/s10900-026-01603-9
Ther Adv Urol. 2026 Jan-Dec;18:18 17562872261469665

YouTube as a source of patient information on robot-assisted radical prostatectomy: a cross-sectional study of quality, reliability, transparency, and content gaps.

Cem Tuğrul Gezmiş, Basri Çakıroğlu.

   Background: YouTube is widely used by patients seeking information about robot-assisted radical prostatectomy (RARP), but the reliability, transparency, and counseling coverage of RARP-related videos remain variable, particularly in a fragmented and search-driven digital environment.
Objectives: To evaluate the quality, reliability, transparency, and patient-oriented counseling coverage of YouTube videos on RARP and identify underrepresented topics relevant to shared decision-making.
Design: Cross-sectional observational study.
Methods: YouTube was searched on February 16, 2026, using "robotic radical prostatectomy," "RARP prostate," and "da Vinci prostatectomy" in incognito mode. After duplicate removal and eligibility assessment, 174 videos were included. Video characteristics, uploader type, target audience, and format were recorded. Educational quality, reliability, and transparency were assessed using the Global Quality Scale (GQS), modified DISCERN, and Journal of the American Medical Association (JAMA) benchmark criteria. Counseling-related coverage was assessed using a 15-item RARP-specific checklist designed to evaluate key patient-centered domains rather than stand-alone adequacy. Non-parametric tests and Spearman correlations were used.
Results: Among 174 videos, 93.7% targeted patients. Median duration was 3.09 min (interquartile range (IQR), 1.92-5.91), and median view count was 1658 (IQR, 371-9747). Educational quality and reliability were low to moderate (median GQS 2 (IQR, 2-3); modified DISCERN 2 (IQR, 2-3)). Transparency was limited (median JAMA 2 (IQR, 1-2)), with only 10.9% achieving JAMA ⩾3. Clinically important counseling topics were frequently underrepresented, including postoperative prostate-specific antigen follow-up (84.5%), complications/complication rates (55.2%), erectile dysfunction (40.8%), urinary continence outcomes (39.7%), and recovery timeline (31.6%). Transparency differed by uploader type (p < 0.001), whereas quality and counseling coverage did not differ by uploader source. Popularity metrics showed no meaningful correlation with GQS.
Conclusion: YouTube provides accessible and highly searchable information on RARP; however, the reliability, transparency, and coverage of key counseling-related topics vary considerably across videos. While short-form or highly specialized content may help address specific patient questions, important topics related to complications, functional outcomes, and postoperative follow-up are frequently underrepresented. Development of patient-centered and platform-adapted educational frameworks may improve the balance, transparency, and practical value of YouTube-based patient education in RARP.
Trial registration: Not applicable.

Keywords:  DISCERN; Global Quality Scale; RARP; YouTube; digital health information; patient education; prostate cancer; reliability; robot-assisted radical prostatectomy; transparency

DOI:  https://doi.org/10.1177/17562872261469665
JSES Rev Rep Tech. 2026 Nov;6(4): 100800

YouTube as a source for clavicle fracture education: a quality, comprehensibility, and reliability assessment.

Kirk Terada-Herzer, Ryan Nishi, Tyler Shimabukuro, Kyle Obana, Julian Rimm, Kyle Ishikawa, Matthew Nishimura, Joanna Kim, Lorrin Lee.

   Background: Clavicle fractures are common injuries, and patients frequently seek supplemental information online. YouTube is widely used for health-related content, but the quality and completeness of information related to clavicle fractures are not well defined. This study evaluated the reliability, comprehensibility, and educational completeness of clavicle fracture videos on YouTube.
Methods: A systematic search of YouTube was performed using 4 clavicle fracture-related terms. After screening for eligibility, the 50 most-viewed English-language videos were analyzed. Videos were categorized by source and content type. Reliability was assessed using the Journal of the American Medical Association (JAMA) Benchmark Criteria; comprehensibility was rated on a 4-point scale; and educational completeness was evaluated using an 18-point Clavicle Fracture Rating (CFR). Two independent reviewers scored all videos. Nonparametric analyses, including Kruskal-Wallis tests and Wilcoxon rank-sum tests with Holm correction, were applied.
Results: The median CFR score was 3 (Q1 = 1, Q3 = 6). The mean JAMA score was 1.4 and the mean comprehensibility score was 3.46. Physician-generated videos demonstrated significantly higher JAMA scores than patient-generated videos (P < .01), whereas patient-generated videos showed significantly higher comprehensibility (P < .01). YouTube "shorts" had significantly lower CFR scores (mean 0.8) than standard-length videos (mean 4.3; P < .01). Across all categories, essential elements of clavicle fracture evaluation and management were infrequently addressed.
Conclusion: YouTube videos related to clavicle fractures demonstrated low reliability and limited educational completeness, despite generally favorable comprehensibility. These findings suggest that commonly viewed online resources provide insufficient information for patient education.

Keywords:  Clavicle fracture; Educational quality; Orthopedic trauma; Patient information; Video reliability; YouTube

DOI:  https://doi.org/10.1016/j.xrrt.2026.100800
HNO. 2026 Jul 29.

[Septoplasty videos on YouTube and assessment of the IVORY evaluation system : Analysis of video quality].

Marcel Mayer, Sofia Kourou, Tarik Bugra Isik, Ina Evtimova, Yigit Kurnaz, Numan Kirca, Albert Wahl, Kevin Karl Hansen, Louis Jansen, Lisa Nachtsheim, Philipp Wolber, Jens Peter Klußmann, Sami Shabli.

   OBJECTIVE: The current study aims to analyze the educational quality of septoplasty videos on YouTube and to investigate the Instructional Videos in Otorhinolaryngology by YO-IFOS grading system (IVORY-GS), the first otorhinolaryngologic video evaluation system based on the IVORY guidelines.
METHODS: In March 2023, a YouTube search for the terms "septoplasty," "closed septoplasty," and "deviated nasal septum surgery" was performed. Videos of operations on patients and cadaver dissections were included. The IVORY-GS was adapted for septoplasty and used to evaluate the quality of videos in terms of ethical considerations, technical aspects, case presentation, surgical procedure, and organ-specific elements. Descriptive data on the videos were collected, including views, likes, video duration, and time since publication. Statistical tests were applied to identify correlations between the characteristics of the videos and the overall IVORY-GS score.
RESULTS: A total of 105 septoplasty videos were included. While 40% showed a Cottle technique, 53% observed the Killian technique. The average overall IVORY-GS score for septoplasty videos was 25.3 (maximally 48.0). In only 10% of the videos was the training quality evaluated as moderate/high. In comparison to macroscopic videos and videos published within the past 50 months, endoscopic videos received significantly higher overall scores (both p < 0.01). There was a significant correlation between the overall IVORY-GS score and the number of likes (p = 0.02). A higher overall score was a significant predictor of the number of likes (p = 0.02).
CONCLUSION: The analysis shows that only a small proportion of the septoplasty videos available on YouTube are suitable for surgical education. The IVORY-GS is useful for evaluating the training quality of videos in otorhinolaryngology and could be helpful for creation of a dedicated online platform for high-quality ENT surgical videos.

Keywords:  Educational videos; IVORY assessment system; IVORY guidelines; Septoplasty; YouTube

DOI:  https://doi.org/10.1007/s00106-026-01795-5
Contraception. 2026 Jul 29. pii: S0010-7824(26)00206-4. [Epub ahead of print] 111569

Tubal Permanent Contraception on TikTok: Content Themes and Quality of Educational Videos.

Jayne Caron, Kevin Petersen, Olivia Bruyn, Erica Cahill.

   OBJECTIVES: This study describes the content of TikTok videos related to tubal permanent contraception and evaluates the quality, understandability and actionability of the educational videos on tubal permanent contraception on TikTok by creator type.
STUDY DESIGN: A TikTok Data webscraper tool was used to download and extract information of the top 500 videos on TikTok videos with hashtags related to tubal permanent contraception. After qualitative descriptive analysis, videos classified as educational were further evaluated using the mDISCERN, PEMAT and GQS scoring systems.
RESULTS: Healthcare providers (HCP) created videos with higher mDISCERN scores, with an overall difference in score between the two groups of 1.79 (95% CI 1.36- 2.23, p-value<0.001). The four major recurring themes in the content of videos included pregnancy after permanent contraception, access to permanent contraception, types of procedures, and childfree by choice content. Subthemes included experiences with providers including barriers to access and coercion.
CONCLUSIONS: Healthcare providers (HCP) created higher quality and more understandable videos on permanent contraception, highlighting the importance of HCPs as a source of health information on social media.

Keywords:  Female sterilization; Permanent contraception; Social media

DOI:  https://doi.org/10.1016/j.contraception.2026.111569
Geriatr Nurs. 2026 Jul 30. pii: S0197-4572(26)00432-5. [Epub ahead of print]72 104227

Content quality and source credibility of fall prevention videos for older adults on Chinese short-video platforms: A cross-sectional content analysis.

Peng Liu, Wenjing Wang, Fuzhi Wang, Changzheng Yang.

   BACKGROUND: Falls constitute a leading cause of injury-related mortality among older adults globally. Chinese short-video platforms collectively reach over 900 million users, presenting unprecedented opportunities for health education, but the quality of fall prevention content and its relationship with user engagement have not been systematically evaluated.
OBJECTIVE: To evaluate fall prevention video quality across major Chinese short-video platforms, identify content creator characteristics associated with higher-quality information, and examine whether user engagement metrics correlate with video quality.
METHODS: We conducted a cross-sectional analysis of 216 fall prevention videos from five platforms (Douyin, Kuaishou, Bilibili, Xiaohongshu, Xigua Video) during October-November 2025. Two independent medical-school graduates with formal medical education and research expertise in medical informatics assessed video quality using the modified DISCERN instrument (mDISCERN; range 5-25) and Global Quality Scale (GQS; range 1-5). Interrater agreement was quantified using both intraclass correlation coefficients (ICC) and Cohen's weighted κ. User engagement metrics were extracted and analyzed using both Pearson and Spearman correlations.
RESULTS: Interrater reliability was excellent for mDISCERN (ICC=0.890; weighted κ=0.890) and good for GQS (ICC=0.723; weighted κ=0.722). Mean mDISCERN score was 17.61 (SD 2.87), with 48.1% achieving high quality. Uploader type demonstrated the strongest quality association (ε²=0.64): healthcare professionals substantially outperformed self-media creators (Cohen d=3.42). Platform verification strongly predicted quality (88.7% vs 9.1% high-quality; φ=0.79). Engagement metrics showed weak association with quality in this sample (Spearman ρ=0.149 for likes, explaining only 2.2% of variance), with detection power constrained by severe right-skewness and floor effects (e.g., 30.1% of videos had zero comments).
CONCLUSIONS: Content creator credentials and platform verification effectively discriminate video quality, while engagement metrics show only weak association in this sample. These findings support platform policies prioritizing verified professional content and indicate that engagement-based metrics, despite their algorithmic prominence, do not reliably signal health information quality in this dataset.

Keywords:  Fall prevention; Health information quality; Older adults; Short-video platforms

DOI:  https://doi.org/10.1016/j.gerinurse.2026.104227
Behav Sci (Basel). 2026 Jul 07. pii: 1137. [Epub ahead of print]16(7):

Channel Effects on Online Health Information Seeking in the Age of AI: An Extension of the CMIS Framework.

Heyang Zhang, Kexin Tai, Yueqin Hu.

  The rapid expansion of online health information channels, particularly emerging artificial intelligence (AI) platforms, is transforming how individuals access and evaluate health information. Drawing on an extended Comprehensive Model of Information Seeking (CMIS), this research examined how different channel types (AI-based, short-video, and text-based) influence online health information-seeking behavior (OHISB) through a pilot validation (N = 258), a cross-sectional survey (Study 1; N = 300), and a between-subjects experiment (Study 2; N = 300). Study 1 tested an extended CMIS model incorporating channel type, source credibility, information credibility, and perceived usefulness, while Study 2 examined the causal effects of channel exposure. Structural equation modeling in Studies 1 and 2 consistently showed that source and information credibility predicted OHISB indirectly through perceived usefulness. AI channels showed no advantage in Study 1, whereas Study 2 found that participants perceived AI sources as more credible and useful, which indirectly predicted stronger intentions for SAMC and information seeking through the credibility-usefulness pathway. This change may reflect methodological differences between self-report recall-based and direct exposure designs, and the public's growing familiarity with AI technologies. By integrating channel characteristics and credibility perceptions, this study extends the CMIS framework and provides evidence for AI's enhanced perceived credibility in health information contexts, offering insights for improving AI-driven health communication.

Keywords:  artificial intelligence (AI); information channels; online health information-seeking behavior; short-video; source credibility

DOI:  https://doi.org/10.3390/bs16071137
Pediatr Emerg Care. 2026 Jul 27.

Caregiver Health Information-Seeking Behavior During Pandemics, Disasters, and Emergencies Within Pediatric Advocacy and Health Care Networks.

Eury Hong, Marc Auerbach, Danielle Lee, Jennifer Talley, Sarah Ronis.

   OBJECTIVES: Many caregivers of children face significant challenges accessing reliable health information during pandemics, disasters, and emergencies, which exacerbates health disparities. This study aimed to understand caregivers' information-seeking behaviors during emergencies, pandemics/disasters and explore their preferences to improve information dissemination during such events.
METHODS: An explanatory sequential mixed-methods approach was used to examine caregivers' information-seeking behaviors during pandemics, large-scale disasters, and/or individual medical emergencies. Recruitment (1/1/24 to 6/30/24) was through the Pediatric Pandemic Network (PPN), EMSC Family Advocacy Network (FAN), and Family Voices Affiliate Organizations (FVAOs). A 21-item survey assessed time spent seeking information, sources used, preferred sources, and barriers during past disasters and emergencies. A subset of respondents were invited to complete a qualitative phase involving semistructured interviews exploring caregivers' personal experiences navigating emergency situations and experience during COVID involving the children in their care. Interviews were recorded, transcribed, and inductive qualitative coding processes were followed iteratively until no new emerging themes, codes, nor discrepancies arose.
RESULTS: A total of 285 responses where received to the quantitative survey (144 male, 138 female; 48 rural; 33 states; 88% with at least one child with special health care needs) with 73 screened and 40 completing interviews. Caregivers spent an average of 3.38 hours/week seeking health information. The most common sources were professional and institutional sources (relational) (30.2%) and personal and social networks (relational) (29.6%). A significant gap exists between current usage and preferred sources, particularly for professional and institutional sources (asynchronous) (+45.7%) and media and online learning sources (online relational) (+55.4%). Availability (13.0%, 10.8%) and cost (14.5%, 10.6%) were primary barriers for personal and professional relational sources, respectively. In contrast, those using the most preferred resources report fewer barriers: availability (4.9%), cost (5.6%), time (4.0%), and internet access (2.3%).
CONCLUSION: During emergencies, pandemic, and disasters caregivers from established networks with a high representation of children with special health care needs often depend on real time, relational support for immediate needs. These caregivers strongly prefer professional and institutional sources (asynchronous) and media and online learning sources (online relational) for flexibility and reliability. A hybrid approach combining real-time professional access with asynchronous resources can more effectively meet these caregivers' diverse needs.

Keywords:  disaster; emergency; information seeking; medical complexity; pandeic; pediatric

DOI:  https://doi.org/10.1097/PEC.0000000000003665
Med J Islam Repub Iran. 2026 ;40 40

Online Health Information Needs of Pregnant Women in Low- and Middle-Income Countries: A Systematic Scoping Review.

Mohammad Zarei, Vahideh Zarea Gavgani, Atefeh Zarei, Firoozeh Zare-Farashbandi.

   Background: Pregnant women in low- and middle-income countries (LMICs) often face significant barriers in obtaining timely, accurate, and culturally appropriate health information, which can adversely affect pregnancy outcomes, maternal knowledge, and subsequently child health. The purpose of this research is to identify the online health information needs of pregnant women in LMICs.
Methods: This scoping review was conducted to identify the information needs of pregnant women in LMICs. Web of Science, PubMed, Scopus, and Proquest databases were searched to identify related studies. After removing duplicates and screening, studies from a total of retrieved studies were selected for data extraction. Two independent reviewers were involved in screening, selecting, and extracting data, which were synthesized using thematic analysis. All of the studies had good methodological quality.
Results: After removing duplicates and screening, 11 qualitative and quantitative studies from a total of 3907 retrieved studies were selected for data extraction. In total, 48 items were identified as online health information needs of pregnant women in LMICs. The information needs of pregnant women were divided into four themes: nutrition, information about the fetus, information about the pregnancy, and maternal health and medication management.
Conclusion: Pregnant women in LMICs have distinct online health information needs. Despite access to various information sources, there are still gaps in the availability and adequacy of culturally appropriate, reliable, and timely health information tailored to pregnant women's needs in these settings. The importance of improving access to high-quality online health information to support maternal and fetal well-being is evident, suggesting a need for health interventions and policies that address these specific informational gaps to leverage digital platforms effectively.

Keywords:  Information Needs; Information-seeking Behavior; Low-income Countries; Middle-income Countries; Pregnancy; Pregnant Women

DOI:  https://doi.org/10.47176/mjiri.40.40
J Racial Ethn Health Disparities. 2026 Jul 29.

Nativity and Cancer Information-Seeking Behaviors Among Middle-Aged and Older-Adults in the United States.

Sapna Anne Kedia, Shreya Sirohi, Coree Entwistle, Hyunmin Kim, Alexandria M Boykins, Asos Mahmood.

  Foreign-born U.S. residents experience disparities across the cancer continuum, including lower rates of colorectal, breast, and cervical cancer screening compared to U.S.-born adults. Language discordance, cultural differences, and challenges navigating the healthcare system contribute to these inequities. Because cancer information-seeking behaviors influence cancer screening and treatment decision-making, this study examines the association between nativity and cancer information-seeking among middle-aged and older in the U.S. We utilized pooled data from the U.S. National Cancer Institute's Health Information National Trends Survey (HINTS4, Cycle 4 [2014] and HINTS5, Cycles 1 & 2 [2017 & 2018]) for a sample of 5,311 respondents (aged ≥ 50 years) who sought health and medical information from any source. We investigated associations between U.S.- and foreign-born status and cancer information-seeking behavior by fitting a weighted multivariable logistic regression to generate adjusted odds ratios (aORs) and associated 95% confidence intervals (CIs). About 530 (10.5%) respondents were foreign-born. Respondents were primarily aged 50-64 years (n = 2,751; 63.2%), female (n = 3,054; 53.7%), had ≥ 1 chronic medical condition (n = 4,084; 72.6%), and had a regular health provider (n = 4,245; 79.2%). More than half (n = 3,070; 55.7%) ever sought cancer information from any source. Compared to the U.S.-born, foreign-born respondents had lower odds of cancer information-seeking (aOR = 0.68; 95% CI: 0.47-0.96). The findings demonstrate that middle-aged and older foreign-born adults were less likely to engage in cancer information-seeking compared to U.S.-born respondents. Tailored interventions that are responsive to the diverse needs of foreign-born populations may encourage cancer information-seeking and enhance their knowledge of cancer, preventive care, and cancer treatment options.

Keywords:  Cancer information-seeking; Cancer prevention; Disparities; Foreign-born; Health information; Middle-aged and older adults; U.S.-born

DOI:  https://doi.org/10.1007/s40615-026-03141-5
Contemp Nurse. 2026 Jul 28. 1-15

A Google Trend analysis of online searches for stroke.

Danny Kinsella, Caleb Ferguson, Gordon Bingham, Sabine Allida.

   BACKGROUND: In recent decades, Australia has embraced the digital revolution. Search engines, including Google, form a critical infrastructure for accessing health-related educational information. Examining how the Australian public searches for stroke health-related information online can provide valuable insights into trends, behaviours and priorities.
AIM: To investigate the patterns and trends of public online interest in stroke-related content in Australia during 2020-2025.
METHODS: A Google Trends analysis using the search term 'Stroke' between 4th June 2020 and 4th June 2025, restricted to Australia and categorised under 'Health' was conducted. Results are presented as relative normalised search volume or query index, that are expressed from 0 (minimum) to 100 (maximum).
RESULTS: Annual median search interest over the five-year study period were compared with weekly query index scores. The median search interest for stroke in Australia held a query index of 80.5, with fluctuations ranging from a low of 49 (last week of December 2021) to 100 query index (first week of May 2023). Search interest by geographical location, revealed South Australia had the highest query index of 100, while the Australian Capital Territory reported lowest query index of 78. Australian's top 10 'related topics' and 'related queries' with associated growth volumes highlighted searches on stroke causes, initial treatments, symptom presentation and emergency response escalation. The results also identified Australians search for information about public figures with a reported stroke diagnosis.
CONCLUSION: The Australian public searches online for specific stroke-specific health information. We observed associated influence of celebrity and media on public interest for stroke health information.

Keywords:  Google Trends; digital health; health literacy; infodemiology; nursing; stroke

DOI:  https://doi.org/10.1080/10376178.2026.2706779