bims-librar Biomed News
on Biomedical librarianship
Issue of 2025–02–16
24 papers selected by
Thomas Krichel, Open Library Society
  1. The Intersection of Quality and Readability in Online Health Information: Implications for Patient Education-A Critical Perspective.
  2. ENQUIRE automatically reconstructs, expands, and drives enrichment analysis of gene and Mesh co-occurrence networks from context-specific biomedical literature.
  3. Is ChatGPT a Reliable Tool for Explaining Medical Terms?
  4. Laypeople's Use of and Attitudes Toward Large Language Models and Search Engines for Health Queries: Survey Study.
  5. Generative AI chatbots for reliable cancer information: Evaluating web-search, multilingual, and reference capabilities of emerging large language models.
  6. Performance of ChatGPT in Pediatric Audiology as Rated by Students and Experts.
  7. Evaluating the utility of ChatGPT in enhancing parental education and clinical support in hypospadias care.
  8. Association of Primary Care Access with Health-Related ChatGPT Use: A National Cross-Sectional Survey.
  9. Appropriateness and Consistency of an Online Artificial Intelligence System's Response to Common Questions Regarding Cervical Fusion.
  10. Evaluating ChatGPT's Ability to Address Frequently Asked Questions in Gender-Affirmation Surgery.
  11. Evaluating ChatGPT's Outputs to 16 Alzheimer's Disease Myths: Can ChatGPT 4.o Generate Reliable Results?
  12. Exploring the Utility of ChatGPT in Cleft Lip Repair Education.
  13. Evaluating the Quality and Readability of Information Provided by Generative Artificial Intelligence Chatbots on Clavicle Fracture Treatment Options.
  14. Assessing ChatGPT responses to frequently asked patient questions in reconstructive urology.
  15. A qualitative analysis of Arabic language websites about extraction of third molars.
  16. Readability of Patient Education Materials for Anterior Cervical Discectomy and Fusion.
  17. Readability and Quality of Microtia Online Information by Large Organizations in English and Spanish.
  18. Assessing the Quality of YouTube Content on Laryngoplasty: A Resource for Patient Education.
  19. Letter to the Editor: Quality and comprehensiveness of YouTube videos on back pain during pregnancy.
  20. The usefulness of a YouTube video on palliative care.
  21. Assessing quality, reliability and accuracy of polycystic ovary syndrome-related content on TikTok: A video-based cross-sectional analysis.
  22. Online Health Information Seeking and Cyberchondria Among Men at Risk of HIV Infection: A Moderated Mediation Model.
  23. Public interest in online searching of asthma information: insights from a Google trends analysis.
  24. Digital Health Literacy and Surgical Information - Seeking Behaviour: A Cross Sectional Survey.
  1. Dermatol Surg. 2025 Feb 12.
    The Intersection of Quality and Readability in Online Health Information: Implications for Patient Education-A Critical Perspective.
    Georgios Karamitros, Ioanna Karamitrou, Michael P Grant, Gregory A Lamaris.
      
    DOI:  https://doi.org/10.1097/DSS.0000000000004578
  2. PLoS Comput Biol. 2025 Feb 11. 21(2): e1012745
    ENQUIRE automatically reconstructs, expands, and drives enrichment analysis of gene and Mesh co-occurrence networks from context-specific biomedical literature.
    Luca Musella, Alejandro Afonso Castro, Xin Lai, Max Widmann, Julio Vera.
      The accelerating growth of scientific literature overwhelms our capacity to manually distil complex phenomena like molecular networks linked to diseases. Moreover, biases in biomedical research and database annotation limit our interpretation of facts and generation of hypotheses. ENQUIRE (Expanding Networks by Querying Unexpectedly Inter-Related Entities) offers a time- and resource-efficient alternative to manual literature curation and database mining. ENQUIRE reconstructs and expands co-occurrence networks of genes and biomedical ontologies from user-selected input corpora and network-inferred PubMed queries. Its modest resource usage and the integration of text mining, automatic querying, and network-based statistics mitigating literature biases makes ENQUIRE unique in its broad-scope applications. For example, ENQUIRE can generate co-occurrence gene networks that reflect high-confidence, functional networks. When tested on case studies spanning cancer, cell differentiation and immunity, ENQUIRE identified interlinked genes and enriched pathways unique to each topic, thereby preserving their underlying context specificity. ENQUIRE supports biomedical researchers by easing literature annotation, boosting hypothesis formulation, and facilitating the identification of molecular targets for subsequent experimentation.
    DOI:  https://doi.org/10.1371/journal.pcbi.1012745
  3. Cureus. 2025 Jan;17(1): e77258
    Is ChatGPT a Reliable Tool for Explaining Medical Terms?
    Ayse Dilara Oztermeli.
      Background The increasing reliance on the internet for health-related information has driven interest in artificial intelligence (AI) applications in healthcare. ChatGPT has demonstrated strong performance in medical exams, raising questions about its potential use in patient education. However, no prior study has evaluated the reliability of ChatGPT in explaining medical terms. This study investigates whether ChatGPT-4 is a reliable tool for translating frequently used medical terms into language that patients can understand. Methodology A total of 105 frequently used medical terms were selected from the University of San Diego's medical terminology list. Four groups - general practitioners, resident physicians, specialist physicians, and ChatGPT-4 - were tasked with defining these terms. Responses were classified as correct or incorrect. Statistical analyses, including chi-square and post-hoc tests, were conducted to compare accuracy rates across groups. Results ChatGPT-4 achieved a 100% accuracy rate, outperforming specialist physicians (98.1%), resident physicians (93.3%), and general practitioners (84.8%). The differences in accuracy rates between groups were statistically significant (χ²=25.99, p<0.00001). Post-hoc analyses confirmed significant pairwise differences, such as ChatGPT-4 vs. specialist physicians (p<0.001) and specialist physicians vs. resident physicians (p=0.02). Conclusions ChatGPT-4 demonstrated superior reliability in translating medical terms into understandable language, surpassing even highly experienced physicians. These findings suggest that ChatGPT could be a valuable auxiliary tool for improving patient comprehension of medical terminology. Nonetheless, the importance of consulting healthcare professionals for clinical decision-making remains crucial.
    Keywords:  artificial intelligence; chatgpt; clinical decision support; medical terminology; patient education
    DOI:  https://doi.org/10.7759/cureus.77258
  4. J Med Internet Res. 2025 Feb 13. 27 e64290
    Laypeople's Use of and Attitudes Toward Large Language Models and Search Engines for Health Queries: Survey Study.
    Tamir Mendel, Nina Singh, Devin M Mann, Batia Wiesenfeld, Oded Nov.
       BACKGROUND: Laypeople have easy access to health information through large language models (LLMs), such as ChatGPT, and search engines, such as Google. Search engines transformed health information access, and LLMs offer a new avenue for answering laypeople's questions.
    OBJECTIVE: We aimed to compare the frequency of use and attitudes toward LLMs and search engines as well as their comparative relevance, usefulness, ease of use, and trustworthiness in responding to health queries.
    METHODS: We conducted a screening survey to compare the demographics of LLM users and nonusers seeking health information, analyzing results with logistic regression. LLM users from the screening survey were invited to a follow-up survey to report the types of health information they sought. We compared the frequency of use of LLMs and search engines using ANOVA and Tukey post hoc tests. Lastly, paired-sample Wilcoxon tests compared LLMs and search engines on perceived usefulness, ease of use, trustworthiness, feelings, bias, and anthropomorphism.
    RESULTS: In total, 2002 US participants recruited on Prolific participated in the screening survey about the use of LLMs and search engines. Of them, 52% (n=1045) of the participants were female, with a mean age of 39 (SD 13) years. Participants were 9.7% (n=194) Asian, 12.1% (n=242) Black, 73.3% (n=1467) White, 1.1% (n=22) Hispanic, and 3.8% (n=77) were of other races and ethnicities. Further, 1913 (95.6%) used search engines to look up health queries versus 642 (32.6%) for LLMs. Men had higher odds (odds ratio [OR] 1.63, 95% CI 1.34-1.99; P<.001) of using LLMs for health questions than women. Black (OR 1.90, 95% CI 1.42-2.54; P<.001) and Asian (OR 1.66, 95% CI 1.19-2.30; P<.01) individuals had higher odds than White individuals. Those with excellent perceived health (OR 1.46, 95% CI 1.1-1.93; P=.01) were more likely to use LLMs than those with good health. Higher technical proficiency increased the likelihood of LLM use (OR 1.26, 95% CI 1.14-1.39; P<.001). In a follow-up survey of 281 LLM users for health, most participants used search engines first (n=174, 62%) to answer health questions, but the second most common first source consulted was LLMs (n=39, 14%). LLMs were perceived as less useful (P<.01) and less relevant (P=.07), but elicited fewer negative feelings (P<.001), appeared more human (LLM: n=160, vs search: n=32), and were seen as less biased (P<.001). Trust (P=.56) and ease of use (P=.27) showed no differences.
    CONCLUSIONS: Search engines are the primary source of health information; yet, positive perceptions of LLMs suggest growing use. Future work could explore whether LLM trust and usefulness are enhanced by supplementing answers with external references and limiting persuasive language to curb overreliance. Collaboration with health organizations can help improve the quality of LLMs' health output.
    Keywords:  Google; LLMs; United States; artificial intelligence; internet; large language model; mobile phone; online health information; search engine; survey
    DOI:  https://doi.org/10.2196/64290
  5. Eur J Cancer. 2025 Feb 03. pii: S0959-8049(25)00055-3. [Epub ahead of print]218 115274
    Generative AI chatbots for reliable cancer information: Evaluating web-search, multilingual, and reference capabilities of emerging large language models.
    Bradley D Menz, Natansh D Modi, Ahmad Y Abuhelwa, Warit Ruanglertboon, Agnes Vitry, Yuan Gao, Lee X Li, Rakchha Chhetri, Bianca Chu, Stephen Bacchi, Ganessan Kichenadasse, Adel Shahnam, Andrew Rowland, Michael J Sorich, Ashley M Hopkins.
      Recent advancements in large language models (LLMs) enable real-time web search, improved referencing, and multilingual support, yet ensuring they provide safe health information remains crucial. This perspective evaluates seven publicly accessible LLMs-ChatGPT, Co-Pilot, Gemini, MetaAI, Claude, Grok, Perplexity-on three simple cancer-related queries across eight languages (336 responses: English, French, Chinese, Thai, Hindi, Nepali, Vietnamese, and Arabic). None of the 42 English responses contained clinically meaningful hallucinations, whereas 7 of 294 non-English responses did. 48 % (162/336) of responses included valid references, but 39 % of the English references were.com links reflecting quality concerns. English responses frequently exceeded an eighth-grade level, and many non-English outputs were also complex. These findings reflect substantial progress over the past 2-years but reveal persistent gaps in multilingual accuracy, reliable reference inclusion, referral practices, and readability. Ongoing benchmarking is essential to ensure LLMs safely support global health information dichotomy and meet online information standards.
    Keywords:  Artificial intelligence; Cancer enquiries; English; Health enquiries; Language; Large language model
    DOI:  https://doi.org/10.1016/j.ejca.2025.115274
  6. J Clin Med. 2025 Jan 28. pii: 875. [Epub ahead of print]14(3):
    Performance of ChatGPT in Pediatric Audiology as Rated by Students and Experts.
    Anna Ratuszniak, Elzbieta Gos, Artur Lorens, Piotr Henryk Skarzynski, Henryk Skarzynski, W Wiktor Jedrzejczak.
      Background: Despite the growing popularity of artificial intelligence (AI)-based systems such as ChatGPT, there is still little evidence of their effectiveness in audiology, particularly in pediatric audiology. The present study aimed to verify the performance of ChatGPT in this field, as assessed by both students and professionals, and to compare its Polish and English versions. Methods: ChatGPT was presented with 20 questions, which were posed twice, first in Polish and then in English. A group of 20 students and 16 professionals in the field of audiology and otolaryngology rated the answers on a Likert scale of 1 to 5 in terms of correctness, relevance, completeness, and linguistic accuracy. Both groups were also asked to assess the usefulness of ChatGPT as a source of information for patients, in educational settings for students, and in professional work. Results: Both students and professionals generally rated ChatGPT's responses to be satisfactory. For most of the questions, ChatGPT's responses were rated somewhat higher by the students than the professionals, although statistically significant differences were only evident for completeness and linguistic accuracy. Those who rated ChatGPT's responses more highly also rated its usefulness more highly. Conclusions: ChatGPT can possibly be used for quick information retrieval, especially by non-experts, but it lacks the depth and reliability required by professionals. The different ratings given by students and professionals, and its language dependency, indicate it works best as a supplementary tool, not as a replacement for verifiable sources, particularly in a healthcare setting.
    Keywords:  ChatGPT; artificial intelligence; audiology; health information-seeking behavior; large language models in medicine; otorhinolaryngology
    DOI:  https://doi.org/10.3390/jcm14030875
  7. J Pediatr Urol. 2025 Jan 31. pii: S1477-5131(25)00028-2. [Epub ahead of print]
    Evaluating the utility of ChatGPT in enhancing parental education and clinical support in hypospadias care.
    Ihsan Azka Adriansyah, Irfan Wahyudi, Santiago Vallasciani, Yaser Elhout, Amilal Bhat, Shivam Priyadarshi, M S Ansari, Putu Angga Risky Raharja, Tariq O Abbas.
       INTRODUCTION: Hypospadias is a prevalent congenital anomaly that requires effective parental education. Current online resources often exceed recommended readability levels, potentially hindering understanding. This study evaluates the utility of ChatGPT in providing accurate, clear, and actionable information towards parental education about hypospadias.
    METHODS: A structured set of questions was posed to ChatGPT 4.0 covering diagnosis, treatment options, and postoperative care. Responses were quantitatively assessed using the Patient Education Material Assessment Tool for Printable Materials (PEMAT-P) to measure understandability and actionability. Qualitative evaluations were conducted by six pediatric urologists who rated the information for accuracy on a scale from 1 (completely accurate) to 4 (completely inaccurate). The Fleiss' Kappa statistic was calculated to assess inter-observer agreement among the urologists.
    RESULTS: The quantitative assessment yielded understandability scores between 84 % and 92 % (average 88 %), while actionability scores ranged from 37 % to 70 % (average 51 %). In the qualitative assessment, 41 % of responses were deemed completely accurate, with 35 % considered accurate but inadequate, and 24 % rated as inaccurate. The overall Kappa value was 0.607, indicating substantial agreement among reviewers regarding the accuracy of the information provided by ChatGPT.
    CONCLUSION: ChatGPT can effectively convey information about hypospadias, but enhancing the actionability of its responses is crucial. Inaccuracy is still a main concern in using AI-generated search engine. Future updates should include more accurate and reliable responses and visual aids addition may support parents in navigating their child's care.
    Keywords:  Artificial intelligence; ChatGPT; Hypospadias; Patient education
    DOI:  https://doi.org/10.1016/j.jpurol.2025.01.026
  8. J Gen Intern Med. 2025 Feb 10.
    Association of Primary Care Access with Health-Related ChatGPT Use: A National Cross-Sectional Survey.
    Oluwatobiloba Ayo-Ajibola, Catherine Julien, Matthew E Lin, Jeffrey Riddell, Naihua Duan, Richard L Kravitz.
       BACKGROUND: ChatGPT has quickly gained popularity as a source of online health information (OHI). However, it is unclear how having a usual source of primary care (USPC) is related to OHI-seeking.
    OBJECTIVE: Explore how having a USPC and other characteristics thought to affect access-to-care influence the use of ChatGPT and other OHI forms.
    DESIGN: Cross-sectional national survey.
    PARTICIPANTS: Adult members of ResearchMatch, a non-profit affiliate of the National Institutes of Health, between June and August 2023.
    MAIN MEASURES: The survey evaluated demographics, health characteristics, and OHI-seeking behaviors, including ChatGPT usage. OHI sources were categorized as "passive" (Google, Wikipedia, WebMD) and "interactive" (forums, Q&A sites, ChatGPT). Descriptive statistics, t-tests, and chi-square tests compared users by USPC status. Multiple logistic regression estimated adjusted effects on ChatGPT use.
    KEY RESULTS: Of 21,499 adults invited to participate in the survey, 2406 (11.2%) responded. Among respondents, 56% reported having a USPC. Those with a USPC, compared to those without, were older, spoke English as their primary language, had higher income, and had more formal education (all p<.001). Participants with a USPC were more likely to use passive OHI (OR 2.46, 95% CI 1.55-3.90, p<.001) and less likely to use interactive OHI (OR 0.73, 95% CI 0.60-0.89, p=.002) or ChatGPT (OR 0.56, 95% CI 0.44-0.71, p<.001). Age over 50 (OR 0.11, 95% CI 0.06-0.20, p<.001), non-White race (OR 0.51, 95% CI 0.38-0.70, p<.001), very good or better health (OR 0.71, 95% CI 0.55-0.92, p=.009), and college education (OR 0.61, 95% CI 0.39-0.97, p=.035) were inversely related to ChatGPT use.
    CONCLUSIONS: In this national survey of patients participating in a clinical research matching service, those with regular primary care access relied less on ChatGPT, suggesting that a personal primary care relationship may attenuate the need or motivation to use AI-derived OHI.
    Keywords:  artificial intelligence; chatGPT; online health information; patient information seeking; primary care
    DOI:  https://doi.org/10.1007/s11606-025-09406-9
  9. Clin Spine Surg. 2025 Feb 10.
    Appropriateness and Consistency of an Online Artificial Intelligence System's Response to Common Questions Regarding Cervical Fusion.
    Mark Miller, William T DiCiurcio, Matthew Meade, Levi Buchan, Jeffrey Gleimer, Barrett Woods, Christopher Kepler.
       STUDY DESIGN: Prospective survey study.
    OBJECTIVE: To address a gap that exists concerning ChatGPT's ability to respond to various types of questions regarding cervical surgery.
    SUMMARY OF BACKGROUND DATA: Artificial Intelligence (AI) and machine learning have been creating great change in the landscape of scientific research. Chat Generative Pre-trained Transformer(ChatGPT), an online AI language model, has emerged as a powerful tool in clinical medicine and surgery. Previous studies have demonstrated appropriate and reliable responses from ChatGPT concerning patient questions regarding total joint arthroplasty, distal radius fractures, and lumbar laminectomy. However, there is a gap that exists in examining how accurate and reliable ChatGPT responses are to common questions related to cervical surgery.
    MATERIALS AND METHODS: Twenty questions regarding cervical surgery were presented to the online ChatGPT-3.5 web application 3 separate times, creating 60 responses. Responses were then analyzed by 3 fellowship-trained spine surgeons across 2 institutions using a modified Global Quality Scale (1-5 rating) to evaluate accuracy and utility. Descriptive statistics were reported based on responses, and intraclass correlation coefficients were then calculated to assess the consistency of response quality.
    RESULTS: Out of all questions proposed to the AI platform, the average score was 3.17 (95% CI, 2.92, 3.42), with 66.7% of responses being recorded to be of at least "moderate" quality by 1 reviewer. Nine (45%) questions yielded responses that were graded at least "moderate" quality by all 3 reviewers. The test-retest reliability was poor with the intraclass correlation coefficient (ICC) calculated as 0.0941 (-0.222, 0.135).
    CONCLUSION: This study demonstrated that ChatGPT can answer common patient questions concerning cervical surgery with moderate quality during the majority of responses. Further research within AI is necessary to increase response.
    DOI:  https://doi.org/10.1097/BSD.0000000000001768
  10. J Homosex. 2025 Feb 13. 1-12
    Evaluating ChatGPT's Ability to Address Frequently Asked Questions in Gender-Affirmation Surgery.
    Evan Rothchild, Geena Jung, Joseph A Ricci.
      ChatGPT has significantly influenced healthcare, yet its impact on patient education regarding gender-affirmation surgery (GAS) remains underexplored. This study aimed to evaluate ChatGPT's utility in providing medical information to patients seeking GAS. In the first part of the study, we collected questions from the "Ask a Surgeon" forum hosted by the American Society of Plastic Surgery and compared responses from verified physicians on the forum to those generated by ChatGPT. We found that ChatGPT's responses were significantly more complex across five readability metrics but had significantly higher DISCERN and PEMAT scores compared to physician responses, indicating superior reliability, quality, and understandability. In the second part of our study, ChatGPT was queried using ten frequently asked questions to simulate a patient's experience seeking treatment information. ChatGPT's responses were generally detailed and on-topic, emphasized the importance of consulting a healthcare provider, and highlighted the psychological and emotional factors associated with GAS. Overall, ChatGPT showed promise as an effective tool for patient education in GAS. It provides clear, private information, correctly emphasizes the psychosocial needs of this patient population, and consistently advises consultation with healthcare professionals. However, its high reading level and lack of transparent references raise concerns about its implementation.
    Keywords:  ChatGPT; artificial intelligence; gender-affirmation surgery; patient education
    DOI:  https://doi.org/10.1080/00918369.2025.2466712
  11. J Am Med Dir Assoc. 2025 Feb 08. pii: S1525-8610(25)00003-9. [Epub ahead of print] 105486
    Evaluating ChatGPT's Outputs to 16 Alzheimer's Disease Myths: Can ChatGPT 4.o Generate Reliable Results?
    Huai Cheng.
      
    DOI:  https://doi.org/10.1016/j.jamda.2025.105486
  12. J Clin Med. 2025 Feb 04. pii: 993. [Epub ahead of print]14(3):
    Exploring the Utility of ChatGPT in Cleft Lip Repair Education.
    Monali Mahedia, Rachel N Rohrich, Kaiser O'Sahil Sadiq, Lauren Bailey, Lucas M Harrison, Rami R Hallac.
      Background/Objectives: The evolving capabilities of large language models, such as generative pre-trained transformers (ChatGPT), offer new avenues for disseminating health information online. These models, trained on extensive datasets, are designed to deliver customized responses to user queries. However, as these outputs are unsupervised, understanding their quality and accuracy is essential to gauge their reliability for potential applications in healthcare. This study evaluates responses generated by ChatGPT addressing common patient concerns and questions about cleft lip repair. Methods: Ten commonly asked questions about cleft lip repair procedures were selected from the American Society of Plastic Surgeons' patient information resources. These questions were input as ChatGPT prompts and five board-certified plastic surgeons assessed the generated responses on quality of content, clarity, relevance, and trustworthiness, using a 4-point Likert scale. Readability was evaluated using the Flesch reading ease score (FRES) and the Flesch-Kincaid grade level (FKGL). Results: ChatGPT responses scored an aggregated mean rating of 2.9 out of 4 across all evaluation criteria. Clarity and content quality received the highest ratings (3.1 ± 0.6), while trustworthiness had the lowest rating (2.7 ± 0.6). Readability metrics revealed a mean FRES of 44.35 and a FKGL of 10.87, corresponding to approximately a 10th-grade literacy standard. None of the responses contained grossly inaccurate or potentially harmful medical information but lacked citations. Conclusions: ChatGPT demonstrates potential as a supplementary tool for patient education in cleft lip management by delivering generally accurate, relevant, and understandable information. Despite the value that AI-powered tools can provide to clinicians and patients, the lack of human oversight underscores the importance of user awareness regarding its limitations.
    Keywords:  ChatGPT; cleft lip repair; generative artificial intelligence; healthcare information quality; large language model; patient education
    DOI:  https://doi.org/10.3390/jcm14030993
  13. Cureus. 2025 Jan;17(1): e77200
    Evaluating the Quality and Readability of Information Provided by Generative Artificial Intelligence Chatbots on Clavicle Fracture Treatment Options.
    Peter A Giammanco, Christopher E Collins, Jason Zimmerman, Mikayla Kricfalusi, Richard C Rice, Michael Trumbo, Bradley A Carlson, Rebecca A Rajfer, Brian A Schneiderman, Joseph G Elsissy.
      Introduction Generative artificial intelligence (AI) chatbots, like ChatGPT, have become more competent and prevalent, making their role in patient education more salient. This study aimed to compare the educational utility of six AI chatbots by quantifying the readability and quality of their answers to common patient questions about clavicle fracture management. Methods ChatGPT 4, ChatGPT 4o, Gemini 1.0, Gemini 1.5 Pro, Microsoft Copilot, and Perplexity were used with no prior training. Ten representative patient questions about clavicle fractures were posed to each model. The readability of AI responses was measured using Flesch-Kincaid Reading Grade Level, Gunning Fog, and Simple Measure of Gobbledygook (SMOG). Six orthopedists blindly graded the response quality of each model using the DISCERN criteria. Both metrics were analyzed via the Kruskal-Wallis test. Results No statistically significant difference was found among the readability of the six models. Microsoft Copilot (70.33±7.74) and Perplexity (71.83±7.57) demonstrated statistically significant higher DISCERN scores than ChatGPT 4 (56.67±7.15) and Gemini 1.5 Pro (51.00±8.94) with similar findings seen between Gemini 1.0 (68.00±6.42) and Gemini 1.5 Pro. The mean overall quality (question 16, DISCERN) of each model was rated at or above average (range, 3-4.4). Conclusion The findings suggest generative AI models have the capability to serve as supplementary patient education materials. With equal readability and overall high quality, Microsoft Copilot and Perplexity may be implicated as chatbots with the most educational utility regarding surgical intervention for clavicle fractures.
    Keywords:  artificial intelligence; chatbot; chatgpt; clavicle fracture; patient education
    DOI:  https://doi.org/10.7759/cureus.77200
  14. Urol Pract. 2025 Feb 12. 101097UPJ0000000000000792
    Assessing ChatGPT responses to frequently asked patient questions in reconstructive urology.
    Mark N Alshak, Johanna Cecelic, Isabella Florissi, Ridwan Alam, Andrew J Cohen.
       INTRODUCTION: Artificial intelligence (such as ChatGPT) augments patient education on medical topics, including reconstructive surgery. Herein we assess the information, misinformation, and readability of ChatGPT responses to reconstructive urology questions. We also evaluate prompt engineering to optimize responses.
    METHODS: 125 questions were presented to ChatGPT (version 4o, OpenAI) and were divided into 6 domains: stress urinary continence, neurogenic bladder, urethral stricture, ureteral stricture, impotence, and Peyronie's disease. Quality of health information was assessed using DISCERN (1 [low] to 5 [high]). Understandability and actionability were assessed using Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P), (0 [low] -100% [high]). Misinformation was scored from 1 [no misinformation] to 5 [high misinformation]. Grade and reading level were calculated using the Flesch-Kincaid scale [5 (easy) to 16 (difficult), and 100-90 (5th grade level) to 10-0 (professional level), respectively].
    RESULTS: Mean and median DISCERN scores were 3.63 and 5. PEMAT-P understandability was 85.3% but only 37.2% on actionability. There was little misinformation (mean, range: 1.23, 1-4). Responses were at a college graduate reading level.Using prompt engineering in the incontinence domain, scores for DISCERN (3.57 to 4.75, p=0.007), PEMAT-P understandability (89.6% to 96.2%, p<0.001), actionability (38.3% to 93.5%, p<0.001), and reading level (grade 12.4 to 5.4, p<001) all improved significantly while misinformation and word count did not change significantly.
    CONCLUSION: ChatGPT-4o's responses are high quality and understandability with little misinformation. Limitations include actionability and advanced reading level. Using prompt engineering, these deficiencies were addressed without increasing misinformation. ChatGPT-4o's can help augment reconstructive urology.
    Keywords:  Artificial intelligence; ChatGPT; Reconstructive urology
    DOI:  https://doi.org/10.1097/UPJ.0000000000000792
  15. Digit Health. 2025 Jan-Dec;11:11 20552076251321053
    A qualitative analysis of Arabic language websites about extraction of third molars.
    Muath Saad Alassaf, Mohannad Mohammed Abu Aof, Osama Ayidh Alharbi, Abdulrahman Turkustani, Moataz Ibrahim Karbouji, Nebras Althagafi, Ahmed Mohammed Almghamsi, Ghayda Yousof Zolaly, Shadia Elsayed.
       Aim: The study aimed to evaluate the quality and readability of Arabic-language web-based online information regarding surgical third molar extraction.
    Methods: In this observational web-based analytical study, the top 150 Arabic search results for surgical wisdom tooth extraction were collected from Google, Yahoo, and Bing. The quality of the websites was evaluated using the DISCERN tool and the Journal of American Medical Association (JAMA) guidelines for online content analysis. Readability was measured using the Flesch-Reading Ease (FRE) scale, the Flesch-Kincaid Grade Level (FKGL) scale, and the Simplified- Measure of Gobbledygook (SMOG).
    Results: A total of 450 websites related to the extraction of wisdom teeth were initially identified. 146 websites were included in the final analysis after exclusion according to specific exclusion criteria. Significant difference was observed in the domain of treatment alternatives and the quality of information provided, according to the DISCERN criteria. The median scores for reliability-related questions ranged from 1.5 to 4.5. The overall quality rating had a median score of 2.5 (IQR = 0.5). There were significant differences in the number of achieved JAMA items per webpage between the groups (P-value = 0.000). However, there was no significant difference in the DISCERN quality evaluations between the affiliations (P-value = 0.450).
    Conclusion: the study results indicating a broad spectrum in the explicitness and relevance of information with moderate quality across the evaluated websites and the investigation revealed significant variations in the content quality and readability provided by websites belonging to various affiliations, with non-profit websites generally achieving higher scores in JAMA criteria and readability measures.
    Keywords:  Web-based; extraction; impacted teeth; knowledge; wisdom tooth
    DOI:  https://doi.org/10.1177/20552076251321053
  16. Clin Spine Surg. 2025 Feb 13.
    Readability of Patient Education Materials for Anterior Cervical Discectomy and Fusion.
    Anil Sedani, Eric Kholodovsky, Justin Trapana, Evan Trapana.
       STUDY DESIGN: Descriptive study.
    SUMMARY OF BACKGROUND DATA: Patients commonly use online patient education materials (PEM) to learn about anterior cervical discectomy and fusion (ACDF).
    OBJECTIVE: The purpose of this study is to evaluate the readability of patient education materials on anterior cervical discectomy and fusion.
    METHODS: The Google search engine was queried using the term "Anterior Cervical Discectomy and Fusion patient information." The first 25 websites meeting inclusion criteria for this term were evaluated. Readability scores were automatically calculated by transferring the texts to http://www.readabilityformulas.com. Descriptive statistics were calculated for each measure using SPSS version 28.0.0.
    RESULTS: The mean average reading level was 9.2±2.4. The mean readability score out of 100 for the FK Reading Ease Score was 55.2±8.6. The remaining scores were: Gunning Fog, 12.7±2.2; FK Grade Level, 8.9±2.0; The Coleman Liau Index, 11.0±1.7; SMOG Index, 48.1±197.0; Automated Readability Index, 8.1±3.11; Linsear Write Formula, 9.8±2.1. Only 2 of the PEMs were written at or below a sixth grade level and only 7 were written at or below an eighth grade reading level.
    CONCLUSION: Patient readability is an important component of patient care and the current readability level of ACDF PEMs is insufficient. At their current state, PEMs may not allow a significant portion of the population to understand the nature of their condition and procedure properly.
    LEVEL OF EVIDENCE: Level III.
    DOI:  https://doi.org/10.1097/BSD.0000000000001769
  17. Laryngoscope. 2025 Feb 14.
    Readability and Quality of Microtia Online Information by Large Organizations in English and Spanish.
    Adriana I Báez Berríos, Stefania Goncalves, Enrique Perez.
       OBJECTIVE: To evaluate the readability and quality of microtia website health information in both Spanish and English.
    METHODS: The term "microtia" was searched using three Internet search engines, and the top 50 English and Spanish websites were short-listed. Readability was evaluated using online tools: the Flesch Reading Ease score for English and the Fernandez-Huerta Formula for Spanish sites. The quality of information was analyzed using the DISCERN quality instrument, and two bilingual neurotologists independently reviewed the websites to assess their quality.
    RESULTS: Forty-four English and 19 Spanish microtia health information websites were included. English websites were written at a higher reading level (mean = 47.63 SD = 11.86) than Spanish websites (mean = 62.37, SD = 8.92) (p < 0.001). English websites correlated to the reading level of a college student; Spanish websites correlated to the reading level of an 8th-9th grade student. The average DISCERN score was 41.93 (SD = 12.88) for English websites and 32.53 (SD = 11.06) for Spanish websites (p = 0.0054). No correlation was identified between the readability and quality of the examined websites.
    CONCLUSION: Both English and Spanish microtia websites exceed the recommended reading levels set by the American Medical Association (6th grade) and National Institutes of Health (8th grade). Additionally, the quality of information, especially on Spanish sites, is low. Given that parents rely on these resources to make treatment decisions, physicians should be aware of the variability in readability and quality of online microtia information across different languages.
    LEVEL OF EVIDENCE: N/A Laryngoscope, 2025.
    Keywords:  health disparity; health literacy; microtia; quality; readability
    DOI:  https://doi.org/10.1002/lary.32059
  18. J Voice. 2025 Feb 10. pii: S0892-1997(25)00020-7. [Epub ahead of print]
    Assessing the Quality of YouTube Content on Laryngoplasty: A Resource for Patient Education.
    Cristiano Frattesi Bernardes, Natalie Weiss, Amy Rutt.
       OBJECTIVES: With increasing reliance on online platforms for health information, ensuring the accuracy, accessibility, and reliability of content is essential. To date, no studies have evaluated the quality of laryngoplasty content on YouTube. Assessing quality will (1) Reveal deficits in existing content to help providers facilitate patient education prior to laryngoplasty and (2) Provide a framework for institutions to produce better laryngoplasty content in the future.
    METHODS: A search of YouTube videos was performed using the keyword "laryngoplasty." The first three pages of results were filtered for videos from hospitals and universities under 20 minutes long. Transcripts were created based on YouTube's autogenerated transcripts that were edited by one author (N Weiss). Content was assessed with the DISCERN instrument, Flesch Readability Ease Score (FRES), and Flesch-Kincaid Grade Level (FKGL). Videos were grouped by DISCERN scores: good (DISCERN > 3), moderate (DISCERN = 3), and poor (DISCERN < 3). Engagement metrics were collected. Variables were summarized using mean and standard deviation.
    RESULTS: Eleven videos met inclusion criteria. Good videos (36.3%) scored 4.25 (0.5) on DISCERN, 10.97 (1.54) on FKGL, and 51.94 (7.37) on FRES. Engagement averaged 114.25 likes and 16 325 views. Duration averaged 3:05 minutes. Moderate videos (36.3%) scored 3 (0) on DISCERN, 7.61 (1.79) on FKGL, and 66.36 (5.29) on FRES. Engagement averaged 389 likes and 269 107 views. Duration averaged 1:44 minutes. Poor videos (27.2%) scored 1.33 (0.58) on DISCERN, 7.54 (0.64) on FKGL, and 69.11 (3.78) on FRES. Engagement averaged 294.3 likes and 59 621 views. Duration averaged 13:52 minutes.
    CONCLUSION: Good videos exhibited high FKGL (10.97) and low FRES (51.94), indicating that they are difficult for patients to understand. Moderate/poor videos had higher engagement (269 107 and 59 621 views, respectively) than good videos (16 325 views), indicating that patients are more often watching lower-quality content. Disparities seen in these data underscore the importance of providing thorough patient education in preparation for laryngoplasty and reveal a need to develop higher-quality, accessible laryngoplasty education on YouTube.
    EDUCATIONAL OBJECTIVES: 1-Provide information for institutions to create accessible and reliable laryngoplasty videos 2-Evaluate the accuracy and quality of information available on YouTube 3-Facilitate patient cooperation and education for laryngoplasty procedure.
    Keywords:  Laryngoplasty—YouTube—Patient education—Discern—Flesch-kincaid
    DOI:  https://doi.org/10.1016/j.jvoice.2025.01.020
  19. Int J Gynaecol Obstet. 2025 Feb 14.
    Letter to the Editor: Quality and comprehensiveness of YouTube videos on back pain during pregnancy.
    Levent Karataş.
      
    DOI:  https://doi.org/10.1002/ijgo.70021
  20. Int Psychogeriatr. 2025 Jan;pii: S1041-6102(24)00012-7. [Epub ahead of print]37(1): 100011
    The usefulness of a YouTube video on palliative care.
    Benjamin K P Woo, Jamie O P Chung, Sara Shu.
      
    DOI:  https://doi.org/10.1016/j.inpsyc.2024.100011
  21. Int J Gynaecol Obstet. 2025 Feb 10.
    Assessing quality, reliability and accuracy of polycystic ovary syndrome-related content on TikTok: A video-based cross-sectional analysis.
    Gaetano Riemma, Raffaela Maria Carotenuto, Camilla Casolari, Carlo Ronsini, Luigi Della Corte, Marco La Verde, Vittorio Unfer, Pasquale De Franciscis, Antonio Simone Laganà, Andrea Etrusco.
       OBJECTIVE: Social networks share medical content with no peer-review or fact-checking. In the present study we aimed to assess the quality, reliability, and level of misinformation in TikTok videos about polycystic ovary syndrome (PCOS).
    METHODS: We performed a cross-sectional analysis of TikTok videos retrieved using "PCOS" as the search term and analyzed using patient education materials assessment tool for audio-visual content (PEMAT A/V), modified DISCERN (mDISCERN), global quality scale (GQS), video information and quality index (VIQI) and misinformation assessment were employed.
    RESULTS: A total of 180 videos were included. Most videos were partially accurate (containing 25%-50% of false information) or uninformative (more than 50%) (56.7% and 6.6%, respectively) with a significantly higher proportion of inaccurate or uninformative videos from PCOS-patients than healthcare professionals (14.4% vs. 0%; P < 0.001) as well as for partially accurate videos (78.4% vs. 37.5%; P < 0.001). PEMAT A/V scores for understandability and actionability were 50% (interquartile range [IQR]: 33%-58%) and 25% (IQR: 25%-50%), respectively with significantly higher understandability for healthcare professionals (54% [IQR: 42%-71%] vs. 33% [IQR: 25%-50%], P < 0.001). Median mDISCERN was 2 (IQR: 1-3) (low degree of reliability), with videos by healthcare professionals scoring significantly higher than those by patients (2 [IQR: 2-3] vs. 1 [IQR: 0-2]; P = 0.001). Intermediate-low overall video quality was reported in VIQI with median score of 12 (IQR: 10-15) and significantly lower scores for patients (9 [IQR: 5-12] vs. 13 [IQR: 12-17]; P < 0.001). Similarly, median GQS score was overall intermediate for degree of usefulness (median 3 [IQR: 2-4]), but patient-created videos were of significantly lower quality (median 2 [IQR: 2-3] vs. 4 [IQR: 3-4]; P < 0.001).
    CONCLUSION: PCOS-related videos on TikTok were mostly misinformative and of low quality and reliability. Healthcare professionals' videos were more informative with had higher quality compared to patient-created content. Identifying and addressing low-quality content is crucial for guiding future public health initiatives and improving the dissemination of trustworthy medical information on social networks.
    Keywords:  PCOS; TikTok; adolescents; misinformation; quality assessment; social network
    DOI:  https://doi.org/10.1002/ijgo.70007
  22. Int J Sex Health. 2025 ;37(1): 102-115
    Online Health Information Seeking and Cyberchondria Among Men at Risk of HIV Infection: A Moderated Mediation Model.
    Yu Guo, Yuxuan Wang, Yiwei Li.
       Objectives: This study investigates the relationship between HIV/AIDS-related online health information seeking (OHIS) and cyberchondria among Chinese men who have engaged in high-risk sexual behaviors. It proposes a moderated mediation model to explore the role of query escalation as a mediator and intolerance of uncertainty (IU) as a moderator in this relationship.
    Method: A survey was conducted with 227 men from an online community focused on HIV/AIDS-related fear in China. Participants reported their frequency of OHIS, levels of query escalation and IU, and experiences of cyberchondria. The study employed the PROCESS macro to examine the proposed moderated mediation model.
    Results: The findings indicated that frequent OHIS significantly predicts cyberchondria, with query escalation mediating this relationship. Additionally, IU moderates the mediation pathway, weakening the effect of query escalation on cyberchondria when IU is high. This suggests that individuals with high IU are less likely to experience escalating health inquiries and, consequently, cyberchondria.
    Conclusions: The study highlights the complex interaction between OHIS, query escalation, and IU in predicting cyberchondria among high-risk groups. These insights are crucial for designing effective interventions to mitigate cyberchondria by addressing the escalation of health information seeking and managing uncertainty intolerance in this population.
    Keywords:  HIV infection; cyberchondria; high-risk sexual behavior; intolerance of uncertainty; online health information seeking; query escalation
    DOI:  https://doi.org/10.1080/19317611.2024.2444590
  23. BMC Pulm Med. 2025 Feb 13. 25(1): 76
    Public interest in online searching of asthma information: insights from a Google trends analysis.
    Marsa Gholamzadeh, Mehrnaz Asadi Gharabaghi, Hamidreza Abtahi.
       BACKGROUND: Google Trends (GT) is a free tool that provides insights into the public's interest and information-seeking behavior on specific topics. In this study, we utilized GT data on patients' search history to better understand their questions and information needs regarding asthma.
    METHODS: We extracted the relative GT search volume (RSV) for keywords associated with asthma to explore information-seeking behaviors and assess internet search patterns regarding asthma disease from 2004 to 2024 in both English and Persian languages. In addition, a correlation analysis was conducted to assess terms correlated with asthma searches. Then, the AutoRegressive predictive models were developed to estimate future patterns of asthma-related searches and the information needs of individuals with asthma.
    RESULTS: The analysis revealed that the mean total RSV for asthma-related keywords over the 20-year period was 41.79 ± 6.07. The researchers found that while asthma-related search volume has shown a consistent upward trend in Persian-speaking countries over the last decade, English-speaking countries have experienced less variability in such searches except for a spike during the COVID-19 pandemic. The correlation analysis of related subjects showed that "air pollution", "infection", and "insomnia" have a positive correlation with asthma. Developing AutoRegressive predictive models on retrieved Google Trends data revealed a seasonal pattern in global asthma-related search interest. In contrast, the models forecasted a growing increase in information-seeking behaviors regarding asthma among Persian-speaking patients over the coming decades.
    CONCLUSIONS: There are significant differences in how people search for and access asthma information based on their language and regional context. In English-speaking countries, searches tend to focus on broader asthma-related topics like pollution and infections, likely due to the availability of comprehensive asthma resources. In contrast, Persian speakers prioritize understanding specific aspects of asthma-like symptoms, medications, and complementary treatments. To address these divergent information needs, health organizations should tailor content to these divergent needs.
    Keywords:  Asthma; Google trend; Public interest; Relative search volume; Time series analysis
    DOI:  https://doi.org/10.1186/s12890-025-03545-9
  24. J Pharm Bioallied Sci. 2024 Dec;16(Suppl 4): S3718-S3720
    Digital Health Literacy and Surgical Information - Seeking Behaviour: A Cross Sectional Survey.
    Mayank Asmit, Bhartendu Kumar, Tauseef Kibria, Soofia Firdaus, Md Khalid Tanweer, Sadaf Kibria.
       Background: In an era marked by technological advancements and increased digital information accessibility, digital health literacy has emerged as a pivotal factor in healthcare decision-making.
    Methods: A cross-sectional survey involving 400 participants was conducted. Digital health literacy, information sources, frequency of surgical information seeking, and factors influencing information-seeking behavior were assessed. Data analysis included descriptive statistics and inferential tests.
    Results: The study found diverse digital health literacy levels, with 45% in the moderate category. Social media (60%) and healthcare websites (70%) were primary information sources. A significant portion (30%) frequently sought surgical information online. Trust in online information (mean = 3.85), perceived usefulness (mean = 4.12), and access barriers (mean = 2.95) played crucial roles. Digital health literacy influenced information seeking, with moderate literacy individuals (60%) being the most engaged.
    Conclusion: Understanding digital health literacy and information-seeking behavior is vital for patient empowerment and healthcare decision-making. Tailored interventions should target trust-building, perceived usefulness, and access barriers.
    Keywords:  Access barriers; Bihar; Muzaffarpur; digital health literacy; healthcare communication; healthcare decision-making; patient empowerment; surgical information-seeking; trust in online information
    DOI:  https://doi.org/10.4103/jpbs.jpbs_1084_24
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