bims-librar Biomed News
on Biomedical librarianship
Issue of 2024‒01‒07
23 papers selected by
Thomas Krichel, Open Library Society
  1. Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature.
  2. [Pitfalls of searching online: all symptoms, diseases and adverse events appear correlated].
  3. Development of search strategies for systematic reviews in health using ChatGPT: a critical analysis.
  4. Appraising systematic reviews: a comprehensive guide to ensuring validity and reliability.
  5. Machine Learning Methods for Systematic Reviews:: A Rapid Scoping Review.
  6. Utility of ChatGPT for Automated Creation of Patient Education Handouts: An Application in Neuro-Ophthalmology.
  7. Retrieval augmentation of large language models for lay language generation.
  8. Do ChatGPT and Google Differ in Answers to Commonly Asked Patient Questions Regarding Total Shoulder and Total Elbow Arthroplasty?
  9. Invited Commentary: "Consulting the Digital Doctor: Google Versus ChatGPT as Sources of Information on Breast Implant-Associated Anaplastic Large Cell Lymphoma and Breast Implant Illness".
  10. ChatGPT: Artificial Intelligence as a Potential Tool for Parents Seeking Information About Autism.
  11. Response to Letter Regarding: Assessing the Readability of Online Education Resources Related to Neophallus Reconstruction.
  12. A COMPARATIVE ANALYSIS OF AI-BASED CHATBOTS: ASSESSING DATA QUALITY IN ORTHOGNATHIC SURGERY RELATED PATIENT INFORMATION.
  13. Evaluation of the reliability and readability of ChatGPT-4 responses regarding hypothyroidism during pregnancy.
  14. Users' experience with health-related content on YouTube: an exploratory study.
  15. Bilibili, TikTok, and YouTube as sources of information on gastric cancer: assessment and analysis of the content and quality.
  16. Quality and educational content of Douyin and TikTok short videos on early screening of rectal cancer.
  17. How much information regarding gingival enlargement can we get from TikTok and YouTube?
  18. Youtube as a source of information vagal nerve stimulation: A quality analysis.
  19. Quality of Spine Surgery Information on Social Media: A DISCERN Analysis of TikTok Videos.
  20. Quality of Patient-Centered eHealth Information on Erosive Tooth Wear: Systematic Search and Evaluation of Websites and YouTube Videos.
  21. Assessment of Quality and Readability of Web-Based Arabic Knowledge About Cleft Lip and/or Palate: An Infodemiology Study.
  22. Health Information Seeking Behavior on Social Networking Sites and Self-Treatment: Pilot Survey Study.
  23. Internet Search Trends for Common Hand Surgery Diagnoses.
  1. Pac Symp Biocomput. 2024 ;29 8-23
    Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature.
    Alejandro Lozano, Scott L Fleming, Chia-Chun Chiang, Nigam Shah.
      The quickly-expanding nature of published medical literature makes it challenging for clinicians and researchers to keep up with and summarize recent, relevant findings in a timely manner. While several closed-source summarization tools based on large language models (LLMs) now exist, rigorous and systematic evaluations of their outputs are lacking. Furthermore, there is a paucity of high-quality datasets and appropriate benchmark tasks with which to evaluate these tools. We address these issues with four contributions: we release Clinfo.ai, an open-source WebApp that answers clinical questions based on dynamically retrieved scientific literature; we specify an information retrieval and abstractive summarization task to evaluate the performance of such retrieval-augmented LLM systems; we release a dataset of 200 questions and corresponding answers derived from published systematic reviews, which we name PubMed Retrieval and Synthesis (PubMedRS-200); and report benchmark results for Clinfo.ai and other publicly available OpenQA systems on PubMedRS-200.
  2. Ned Tijdschr Geneeskd. 2023 Nov 23. pii: D7753. [Epub ahead of print]167
    [Pitfalls of searching online: all symptoms, diseases and adverse events appear correlated].
    Thijs E van Mens, F A Klok, Marcel Levi.
      When confronted with an unexpected clinical observation, such as a remarkable symptom in a patient with an unrelated rare disease, clinicians increasingly apply online literature search to support the observed correlation. Against a background of an exponential rise in medical publications and the well-documented problem of publication bias, the easy access to literature carries the risk of suggesting spurious correlations. The current paper expounds on this phenomenon. Queries in medical search engines often provide a number of hits, regardless of the plausibility of the correlation searched for. To quantify this, we recently performed a study involving 30.000 automated queries in PubMed using completely random search terms drawn from lists of diseases, symptoms and medications. This provided a background rate of PubMed hits. The data support that several hits by no means automatically indicate a relevant correlation, and underline need for judicious critical appraisal when searching for a correlation observed in daily practice.
  3. J Transl Med. 2024 Jan 02. 22(1): 1
    Development of search strategies for systematic reviews in health using ChatGPT: a critical analysis.
    Observatory of Epidemiology, Nutrition, Health Research (OPENS)
      
    DOI:  https://doi.org/10.1186/s12967-023-04371-5
  4. Front Res Metr Anal. 2023 ;8 1268045
    Appraising systematic reviews: a comprehensive guide to ensuring validity and reliability.
    Nour Shaheen, Ahmed Shaheen, Alaa Ramadan, Mahmoud Tarek Hefnawy, Abdelraouf Ramadan, Ismail A Ibrahim, Maged Elsayed Hassanein, Mohamed E Ashour, Oliver Flouty.
      Systematic reviews play a crucial role in evidence-based practices as they consolidate research findings to inform decision-making. However, it is essential to assess the quality of systematic reviews to prevent biased or inaccurate conclusions. This paper underscores the importance of adhering to recognized guidelines, such as the PRISMA statement and Cochrane Handbook. These recommendations advocate for systematic approaches and emphasize the documentation of critical components, including the search strategy and study selection. A thorough evaluation of methodologies, research quality, and overall evidence strength is essential during the appraisal process. Identifying potential sources of bias and review limitations, such as selective reporting or trial heterogeneity, is facilitated by tools like the Cochrane Risk of Bias and the AMSTAR 2 checklist. The assessment of included studies emphasizes formulating clear research questions and employing appropriate search strategies to construct robust reviews. Relevance and bias reduction are ensured through meticulous selection of inclusion and exclusion criteria. Accurate data synthesis, including appropriate data extraction and analysis, is necessary for drawing reliable conclusions. Meta-analysis, a statistical method for aggregating trial findings, improves the precision of treatment impact estimates. Systematic reviews should consider crucial factors such as addressing biases, disclosing conflicts of interest, and acknowledging review and methodological limitations. This paper aims to enhance the reliability of systematic reviews, ultimately improving decision-making in healthcare, public policy, and other domains. It provides academics, practitioners, and policymakers with a comprehensive understanding of the evaluation process, empowering them to make well-informed decisions based on robust data.
    Keywords:  bias evaluation; quality assessment; systematic review; systematic review appraisal; systematic review methodology
    DOI:  https://doi.org/10.3389/frma.2023.1268045
  5. Dela J Public Health. 2023 Nov;9(4): 40-47
    Machine Learning Methods for Systematic Reviews:: A Rapid Scoping Review.
    Stephanie Roth, Alex Wermer-Colan.
      Objective: At the forefront of machine learning research since its inception has been natural language processing, also known as text mining, referring to a wide range of statistical processes for analyzing textual data and retrieving information. In medical fields, text mining has made valuable contributions in unexpected ways, not least by synthesizing data from disparate biomedical studies. This rapid scoping review examines how machine learning methods for text mining can be implemented at the intersection of these disparate fields to improve the workflow and process of conducting systematic reviews in medical research and related academic disciplines.Methods: The primary research question that this investigation asked, "what impact does the use of machine learning have on the methods used by systematic review teams to carry out the systematic review process, such as the precision of search strategies, unbiased article selection or data abstraction and/or analysis for systematic reviews and other comprehensive review types of similar methodology?" A literature search was conducted by a medical librarian utilizing multiple databases, a grey literature search and handsearching of the literature. The search was completed on December 4, 2020. Handsearching was done on an ongoing basis with an end date of April 14, 2023.
    Results: The search yielded 23,190 studies after duplicates were removed. As a result, 117 studies (1.70%) met eligibility criteria for inclusion in this rapid scoping review.
    Conclusions: There are several techniques and/or types of machine learning methods in development or that have already been fully developed to assist with the systematic review stages. Combined with human intelligence, these machine learning methods and tools provide promise for making the systematic review process more efficient, saving valuable time for systematic review authors, and increasing the speed in which evidence can be created and placed in the hands of decision makers and the public.
    DOI:  https://doi.org/10.32481/djph.2023.11.008
  6. J Neuroophthalmol. 2024 Jan 04.
    Utility of ChatGPT for Automated Creation of Patient Education Handouts: An Application in Neuro-Ophthalmology.
    Brendan K Tao, Armin Handzic, Nicholas J Hua, Amir R Vosoughi, Edward A Margolin, Jonathan A Micieli.
      BACKGROUND: Patient education in ophthalmology poses a challenge for physicians because of time and resource limitations. ChatGPT (OpenAI, San Francisco) may assist with automating production of patient handouts on common neuro-ophthalmic diseases.METHODS: We queried ChatGPT-3.5 to generate 51 patient education handouts across 17 conditions. We devised the "Quality of Generated Language Outputs for Patients" (QGLOP) tool to assess handouts on the domains of accuracy/comprehensiveness, bias, currency, and tone, each scored out of 4 for a total of 16. A fellowship-trained neuro-ophthalmologist scored each passage. Handout readability was assessed using the Simple Measure of Gobbledygook (SMOG), which estimates years of education required to understand a text.
    RESULTS: The QGLOP scores for accuracy, bias, currency, and tone were found to be 2.43, 3, 3.43, and 3.02 respectively. The mean QGLOP score was 11.9 [95% CI 8.98, 14.8] out of 16 points, indicating a performance of 74.4% [95% CI 56.1%, 92.5%]. The mean SMOG across responses as 10.9 [95% CI 9.36, 12.4] years of education.
    CONCLUSIONS: The mean QGLOP score suggests that a fellowship-trained ophthalmologist may have at-least a moderate level of satisfaction with the write-up quality conferred by ChatGPT. This still requires a final review and editing before dissemination. Comparatively, the rarer 5% of responses collectively on either extreme would require very mild or extensive revision. Also, the mean SMOG score exceeded the accepted upper limits of grade 8 reading level for health-related patient handouts. In its current iteration, ChatGPT should be used as an efficiency tool to generate an initial draft for the neuro-ophthalmologist, who may then refine the accuracy and readability for a lay readership.
    DOI:  https://doi.org/10.1097/WNO.0000000000002074
  7. J Biomed Inform. 2023 Dec 30. pii: S1532-0464(23)00301-5. [Epub ahead of print] 104580
    Retrieval augmentation of large language models for lay language generation.
    Yue Guo, Wei Qiu, Gondy Leroy, Sheng Wang, Trevor Cohen.
      The complex linguistic structures and specialized terminology of expert-authored content limit the accessibility of biomedical literature to the general public. Automated methods have the potential to render this literature more interpretable to readers with different educational backgrounds. Prior work has framed such lay language generation as a summarization or simplification task. However, adapting biomedical text for the lay public includes the additional and distinct task of background explanation: adding external content in the form of definitions, motivation, or examples to enhance comprehensibility. This task is especially challenging because the source document may not include the required background knowledge. Furthermore, background explanation capabilities have yet to be formally evaluated, and little is known about how best to enhance them. To address this problem, we introduce Retrieval-Augmented Lay Language (RALL) generation, which intuitively fits the need for external knowledge beyond that in expert-authored source documents. In addition, we introduce CELLS, the largest (63k pairs) and broadest-ranging (12 journals) parallel corpus for lay language generation. To evaluate RALL, we augmented state-of-the-art text generation models with information retrieval of either term definitions from the UMLS and Wikipedia, or embeddings of explanations from Wikipedia documents. Of these, embedding-based RALL models improved summary quality and simplicity while maintaining factual correctness, suggesting that Wikipedia is a helpful source for background explanation in this context. We also evaluated the ability of both open-soured Large Language Model (Llama 2) and closed-sourced Large Language Model (GPT-4) in background explanation, with and without retrieval augmentation. Results indicate that these LLMs can generate simplified content, but that the summary quality is not ideal. Taken together, this work presents the first comprehensive study of background explanation for lay language generation, paving the path for disseminating scientific knowledge to a broader audience. Our code and data are publicly available at: https://github.com/LinguisticAnomalies/pls_retrieval.
    Keywords:  Background explanation; Large language models; Lay language summary; Retrieval-augmented model; Text generation
    DOI:  https://doi.org/10.1016/j.jbi.2023.104580
  8. J Shoulder Elbow Surg. 2024 Jan 03. pii: S1058-2746(23)00899-6. [Epub ahead of print]
    Do ChatGPT and Google Differ in Answers to Commonly Asked Patient Questions Regarding Total Shoulder and Total Elbow Arthroplasty?
    Shebin Tharakan, Brandon Klein, Luke Bartlett, Aaron Atlas, Stephen A Parada, Randy M Cohn.
      BACKGROUND: Artificial intelligence (AI) and large language models (LLM) offer a new potential resource for patient education. The answers by ChatGPT, a LLM AI text bot, to frequently asked questions (FAQs) were compared to answers provided by a contemporary Google search to determine the reliability of information provided by these sources for patient education in upper extremity arthroplasty.METHODS: "Total shoulder arthroplasty" (TSA) and "total elbow arthroplasty" (TEA) were entered into Google Search and ChatGPT 3.0 to determine the ten most frequently asked questions (FAQs). On Google, the FAQs were obtained through the "people also ask" section, while ChatGPT was asked to provide the ten most FAQs. Each question, answer, and reference(s) cited were recorded. A modified version of the Rothwell system was used to categorize questions into 10 subtopics: special activities, timeline of recovery, restrictions, technical details, cost, indications/management, risks and complications, pain, longevity, and evaluation of surgery. Each reference was categorized into the following groups: commercial, academic, medical practice, single surgeon personal, or social media. Questions for TSA and TEA were combined for analysis and compared between Google and ChatGPT with a two sample Z-test for proportions.
    RESULTS: Overall, most questions were related to procedural indications or management (17.5%). There were no significant differences between Google and ChatGPT between question categories. The majority of references were from academic websites (65%). ChatGPT produced a greater number of academic references compared to Google (80% vs 50%; p=0.047), while Google more commonly provided medical practice references (25% vs 0%; p=0.017).
    CONCLUSION: In conjunction with patient-physician discussions, AI LLMs may provide a reliable resource for patients. By providing information based on academic references, these tools have the potential to improve health literacy and improved shared decision making for patients searching for information about TSA and TEA.
    CLINICAL SIGNIFICANCE: With the rising prevalence of AI programs, it is essential to understand how these applications affect patient education in medicine.
    Keywords:  ChatGPT; Google; Internet Analytics; Patient Education; Patient Information; Shoulder Arthroplasty; Total Elbow Arthroplasty
    DOI:  https://doi.org/10.1016/j.jse.2023.11.014
  9. Aesthetic Plast Surg. 2024 Jan 02.
    Invited Commentary: "Consulting the Digital Doctor: Google Versus ChatGPT as Sources of Information on Breast Implant-Associated Anaplastic Large Cell Lymphoma and Breast Implant Illness".
    Hilary Y Liu, Mario Alessandri Bonetti, Francesco M Egro.
      
    DOI:  https://doi.org/10.1007/s00266-023-03816-y
  10. Cyberpsychol Behav Soc Netw. 2024 Jan 05.
    ChatGPT: Artificial Intelligence as a Potential Tool for Parents Seeking Information About Autism.
    Tyler C McFayden, Stephanie Bristol, Orla Putnam, Clare Harrop.
      Autism Spectrum Disorder has seen a drastic increase in prevalence over the past two decades, along with discourse rife with debates and misinformation. This discourse has primarily taken place online, the main source of information for parents seeking information about autism. One potential tool for navigating information is ChatGPT-4, an artificial intelligence question and answer-style communication program. Although ChatGPT shows great promise, no empirical work has evaluated its viability as a tool for providing information about autism to caregivers. The current study evaluated answers provided by ChatGPT, including basic information about autism, myths/misconceptions, and resources. Our results suggested that ChatGPT was largely correct, concise, and clear, but did not provide much actionable advice, which was further limited by inaccurate references and hyperlinks. The authors conclude that ChatGPT-4 is a viable tool for parents seeking accurate information about autism, with opportunities for improvement in actionability and reference accuracy.
    Keywords:  ChatGPT; artificial intelligence; autism spectrum disorder; misinformation
    DOI:  https://doi.org/10.1089/cyber.2023.0202
  11. J Surg Res. 2024 Jan 02. pii: S0022-4804(23)00565-6. [Epub ahead of print]
    Response to Letter Regarding: Assessing the Readability of Online Education Resources Related to Neophallus Reconstruction.
    Praneet Paidisetty, Sairandri Sathyanarayanan, Leonard Kuan-Pei Wang, Kristen Slaughter, Daniel Freet, Matthew Greives, Wendy Chen.
      
    DOI:  https://doi.org/10.1016/j.jss.2023.11.003
  12. J Stomatol Oral Maxillofac Surg. 2023 Dec 27. pii: S2468-7855(23)00377-4. [Epub ahead of print] 101757
    A COMPARATIVE ANALYSIS OF AI-BASED CHATBOTS: ASSESSING DATA QUALITY IN ORTHOGNATHIC SURGERY RELATED PATIENT INFORMATION.
    Ebru Yurdakurban, Kübra Gülnur Topsakal, Gökhan Serhat Duran.
      INTRODUCTION: The aim of the current study is to evaluate the quality, reliability, readability, and similarity of data provided by different AI-based chatbots in the field of orthognathic surgery.MATERIALS AND METHODS: Guidelines on orthognathic surgery were reviewed, and a list of questions for patients to ask chatbots was produced by two reasearchers. The questions were categorized into 'General Information and Procedure' and 'Results and Recovery', with 30 questions in each category. Five different scoring criteria were used to evaluate the chatbot responses to 60 questions: Ensuring Quality Information for Patients (EQIP) tool, Reliability Scoring System (adapted from DISCERN), Global Quality Scale (GQS), Simple Measure of Gobbledygook (SMOG) and Similarity Index.
    RESULTS: The highest mean values were observed in OpenEvidence for EQIP tool, SMOG, and Similarity Index, while for Reliability and GQS assessment criteria, MediSearch showed the highest values. When evaluated in terms of reliability and quality, all three AI-based chatbots demonstrated high reliability and good quality; however, they required at least a college-level education for readability based on the SMOG index. Additionally, upon assessment of similarity, ChatGPT-4 displayed high originality, while OpenEvidence exhibited a high degree of similarity.
    CONCLUSION: AI-based chatbots with a variety of features have usually provided answers with high quality, reliability, and difficult readability to questions. Although the medical information in the field of orthognathic surgery provided through chatbots is of higher quality, it is recommended that individuals consult their healthcare professionals on this issue.
    Keywords:  Artificial intelligence; natural language processing; orthognathic surgery
    DOI:  https://doi.org/10.1016/j.jormas.2023.101757
  13. Sci Rep. 2024 01 02. 14(1): 243
    Evaluation of the reliability and readability of ChatGPT-4 responses regarding hypothyroidism during pregnancy.
    C E Onder, G Koc, P Gokbulut, I Taskaldiran, S M Kuskonmaz.
      Hypothyroidism is characterized by thyroid hormone deficiency and has adverse effects on both pregnancy and fetal health. Chat Generative Pre-trained Transformer (ChatGPT) is a large language model trained with a very large database from many sources. Our study was aimed to evaluate the reliability and readability of ChatGPT-4 answers about hypothyroidism in pregnancy. A total of 19 questions were created in line with the recommendations in the latest guideline of the American Thyroid Association (ATA) on hypothyroidism in pregnancy and were asked to ChatGPT-4. The reliability and quality of the responses were scored by two independent researchers using the global quality scale (GQS) and modified DISCERN tools. The readability of ChatGPT was assessed used Flesch Reading Ease (FRE) Score, Flesch-Kincaid grade level (FKGL), Gunning Fog Index (GFI), Coleman-Liau Index (CLI), and Simple Measure of Gobbledygook (SMOG) tools. No misleading information was found in any of the answers. The mean mDISCERN score of the responses was 30.26 ± 3.14; the median GQS score was 4 (2-4). In terms of reliability, most of the answers showed moderate (78.9%) followed by good (21.1%) reliability. In the readability analysis, the median FRE was 32.20 (13.00-37.10). The years of education required to read the answers were mostly found at the university level [9 (47.3%)]. Although ChatGPT-4 has significant potential, it can be used as an auxiliary information source for counseling by creating a bridge between patients and clinicians about hypothyroidism in pregnancy. Efforts should be made to improve the reliability and readability of ChatGPT.
    DOI:  https://doi.org/10.1038/s41598-023-50884-w
  14. BMC Public Health. 2024 Jan 03. 24(1): 86
    Users' experience with health-related content on YouTube: an exploratory study.
    Fatma Mohamed, Abdulhadi Shoufan.
      BACKGROUND: This study focuses on health-related content (HRC) on YouTube and addresses the issue of misinformation on this platform. While previous research centered on content evaluations by experts, this study takes a user-centered approach and aims to explore users' experiences with and perceptions of HRC videos and to establish links between these perceptions and some socio-demographic characteristics including age, gender, profession, and educational level.METHODS: A quantitative research design was used in the study. 3,000 YouTube users responded to a 35-item anonymous questionnaire to collect information about the content they watch toward decision-making, their perceptions of the usefulness and bias of this content, what they identify as quality indicators for HRC, and what they recommend to improve the quality of such content on YouTube. The data were analyzed using descriptive statistics, frequency, and correlation analyses.
    RESULTS: The results reveal that 87.6 percent (n=2630) of the participants watch HRC on YouTube, and 84.7 percent (n=2542) make decisions based on what they watch. Exercise and bodybuilding videos are the most popular, with over half of the participants watching them. 40 percent of the users watch YouTube videos to decide whether to consult a doctor or adopt specific health-related practices. In contrast to evaluations by experts in previous studies, most respondents perceive HRC videos on YouTube as useful and do not find connections between video quality and surface features like the number of views and likes. Weak or no correlations were observed between the perceived usefulness of HRC videos and age, gender, profession, or educational level. Participants' recommendations for enhancing HRC quality align with previous research findings.
    CONCLUSIONS: Users turn to YouTube not only for health information but also as a decision-making tool. Combined with their generally positive attitudes towards content quality on this platform, this can have significant consequences for their health. Follow-up studies are needed to get more insights into decision-making behaviors and how users assess their decisions in retrospect.
    Keywords:  Content quality; Decision-making; Health-related videos; Medical videos; YouTube
    DOI:  https://doi.org/10.1186/s12889-023-17585-5
  15. BMC Public Health. 2024 Jan 02. 24(1): 57
    Bilibili, TikTok, and YouTube as sources of information on gastric cancer: assessment and analysis of the content and quality.
    Menghui Wang, Nan Yao, Jianming Wang, Wenjuan Chen, Yaobin Ouyang, Chuan Xie.
      BACKGROUND: Gastric cancer has attracted widespread attention on social media due to its high incidence and severity. The Bilibili, TikTok, and YouTube video-sharing platforms have received considerable interest among general health consumers. Nevertheless, it remains unclear whether the information in videos on these platforms is of satisfactory content and quality.METHODS: A total of 300 eligible videos related to gastric cancer were screened from three video-sharing platforms, Bilibili, TikTok, and YouTube, for assessment and analysis. First, the basic information presented in the videos was recorded. Next, we identified the source and content type of each video. Then, the Global Quality Scale (GQS), Journal of the American Medical Association (JAMA), and Modified DISCERN were used to assess the educational content and quality of each video. A comparative analysis was undertaken of the videos procured from these three sources.
    RESULTS: We identified six categories of uploaders of the 300 videos: 159 videos (53%) were uploaded by health professionals, 21 videos (7%) by users in science communications, 29 videos (9.67%) by general users, 27 videos (9%) from news agencies, 63 videos (12%) by nonprofit organizations, and one video (0.33%) by a for-profit organization. In terms of the content types of the 300 videos, we identified five distinct categories. There were 48 videos (16%) on early signals, 12 videos (4%) on late symptoms, 40 videos (13.33%) on etiologies and causations, 160 videos (53.33%) on scientific introductions, and 40 videos (13.33%) on treatment methods. The overall quality of the videos was evaluated by the GQS, JAMA, and Modified DISCERN and was found to be medium, with scores of 2.6/5, 2.41/4, and 2.71/5 points, respectively.
    CONCLUSIONS: This innovative study demonstrates that videos on social media platforms can help the public learn about early signals, late symptoms, treatment methods, etiologies and causations, and scientific introductions of gastric cancer. However, both the content and quality of uploaded recordings are inadequate currently. More efforts should be made to enhance the content and quality of videos on gastric cancer and to increase public awareness.
    Keywords:  Gastric cancer; Online video; Quality; Social media; The public
    DOI:  https://doi.org/10.1186/s12889-023-17323-x
  16. JGH Open. 2023 Dec;7(12): 936-941
    Quality and educational content of Douyin and TikTok short videos on early screening of rectal cancer.
    Lian-Shuo Li, Xiao-Juan Luo, Xin-Peng Shu, Zi-Wei Li, Fei Liu, Xu-Rui Liu, Yue Tong, Quan Lv, Xiao-Yu Liu, Wei Zhang, Dong Peng.
      Background and Aim: The aim of this study was to assess the quality and content of videos on Douyin and TikTok for their educational role on early screening of rectal cancer (RC).Methods: We conducted a search for videos related to RC on the Douyin and TikTok applications on 20 April 2023. The search was conducted in Chinese on Douyin and in English and Japanese on TikTok. A sample of the first 100 videos recommended by the software was selected for each language group. The content of the videos was evaluated using a content scorecard, while the quality of the videos was assessed using DISCERN. Subsequently, we conducted two partial correlations: one between the DISCERN score and the number of likes, and another between the video content score and the number of likes.
    Results: This study encompassed a total of 89 Chinese, 54 English, and 51 Japanese videos. After selection, 78 Chinese, 38 English, and 25 Japanese videos were identified to contain content related to early screening for RC, prompting further quality assessment. Notably, videos in the Chinese language showed the highest DISCERN score (P < 0.05). In terms of partial correlation analysis, it was observed that both the content score and DISCERN score did not show a significant correlation with the number of likes (P > 0.05).
    Conclusion: In terms of quality score and content score, the Chinese videos on Douyin show superiority over the English and Japanese videos on TikTok. However, there is potential for improving the overall appeal of the Chinese videos.
    Keywords:  public health; rectal cancer; short video; social media
    DOI:  https://doi.org/10.1002/jgh3.13005
  17. Spec Care Dentist. 2024 Jan 04.
    How much information regarding gingival enlargement can we get from TikTok and YouTube?
    Vahdi Umut Bengi, Özlem Saraç Atagün, Seval Ceylan Şen, Erkan Özcan, Tuğçe Paksoy, Özlem Şebnem Güler.
      AIMS: This study aimed to evaluate and compare the reliability and quality of the information about gingival enlargements on YouTube and TikTok.METHODS: Two popular video sites, YouTube and TikTok, were searched for gingival enlargement and gingival hyperplasia. The reliability and quality of the first 300 videos for each search term, which is 1200 videos in total, were evaluated by social media video content evaluation tools: Global Quality Score (GQS) for quality and modified DISCERN for reliability.
    RESULTS: Health professionals uploaded 68.6% of the videos on YouTube and 54.5% on TikTok. It was observed that 50% of TikTok videos and 65.9% of YouTube videos were educational. In terms of quality, 2.7% of the videos on YouTube are of excellent quality, while in TikTok there are no videos of perfect quality. TikTok videos had considerably more views, likes, viewing rates, and interaction index scores than YouTube videos (P < 0.01).
    CONCLUSIONS: The videos and pieces of information on YouTube are more reliable and accurate in terms of gingival enlargement when compared to TikTok. Nevertheless, it was discovered that videos on both platforms were of poor reliability and quality in general.
    Keywords:  Global Quality Score (GQS); TikTok; YouTube; gingival enlargement; oral health; social media
    DOI:  https://doi.org/10.1111/scd.12957
  18. Epilepsy Behav. 2024 Jan 04. pii: S1525-5050(23)00516-4. [Epub ahead of print]151 109597
    Youtube as a source of information vagal nerve stimulation: A quality analysis.
    Aysima Özçelik, Cansu Özbaş, Ebru Arhan.
      PURPOSE: To evaluate the quality of available information on Youtube videos about VNS as a "source of health information" for patients with drug resistant epilepsy.METHODS: Youtube videos were searched and screened using the terms "VNS for seizures," and "VNS surgery," "VNS epilepsy" in May 2023. The quality of the videos was evaluated the Quality Criteria for Consumer Health Information (DISCERN) and Global Quality Scale (GQS). The videos were analyzed in terms of content, accuracy, reliability, and quality.
    RESULTS: A total of 104 videos were searched. After excluding duplicate or inappropriate videos, 51 videos were analyzed. Youtube videos about vagal nerve stimulation are mostly on general information, surgical procedures, patient experiences and magnet use. When video sources are examined according to the quality, according to GQS, 75 % of high quality videos were narrated by physicians, all intermediate quality videos were narrated by physicians, and low quality ones narrated by physicians were 47.4 % and 28.9 % by the patients. All of the videos narrated by the patients were of low quality. There was a significant and strong correlation between GQS and Discern score (r = 0.807, p < 0.001). Only GQS scores of videos with different content were found to be statistically significant (p < 0.05). Two pediatric neurologists independently reviewed the videos and classified the videos as useful or misleading according to the GQS, DISCERN scala. The overall κ value for interobserver consistency according to Global Quality Scale was 0.781 (p < 0.001). (95 % confidence interval), indicating a very good level of agreement.
    CONCLUSION: Youtube videos may provide a worthful source for patients and parents seeking to find more information about VNS However incorrect information could easily be disseminated by high number of views of videos with low quality. High skilled and experienced professionals should create videos on Youtube to ensure that patients and parents can access more useful, high-quality, and accurate information on VNS.
    Keywords:  Quality; Vagal nerve stimulation; Youtube videos
    DOI:  https://doi.org/10.1016/j.yebeh.2023.109597
  19. Neurospine. 2023 Dec;20(4): 1443-1449
    Quality of Spine Surgery Information on Social Media: A DISCERN Analysis of TikTok Videos.
    Tejas Subramanian, Kasra Araghi, Izzet Akosman, Olivia Tuma, Amier Hassan, Ali Lahooti, Anthony Pajak, Pratyush Shahi, Robert Merrill, Omri Maayan, Evan Sheha, James Dowdell, Sravisht Iyer, Sheeraz Qureshi.
      OBJECTIVE: The use of social media applications to disseminate information has substantially risen in recent decades. Spine and back pain-related hashtags have garnered several billion views on TikTok. As such, these videos, which share experiences, offer entertainment, and educate users about spinal surgery, have become increasingly influential. Herein, we assess the quality of spine surgery content TikTok from providers and patients.METHODS: Fifty hashtags encompassing spine surgery ("#spinalfusion," "#scoliosissurgery," and "#spinaldecompression") were searched using TikTok's algorithm and included. Two independent reviewers rated the quality of each video via the DISCERN questionnaire. Video metadata (likes, shares, comments, views, length) were all collected; type of content creator (musculoskeletal, layperson) and content category (educational, patient experience, entertainment) were determined.
    RESULTS: The overall DISCERN score was, on average, 24.4. #Spinalfusion videos demonstrated greater engagement, higher average likes (p = 0.02), and more comments (p < 0.001) compared to #spinaldecompression and #scoliosissurgery. #Spinaldecompression had the highest DISCERN score (p < 0.001), likely explained by the higher percentage of videos that were educational (p < 0.001) and created by musculoskeletal (MSK) professionals (p < 0.001). Compared to laypersons, MSK professionals had significantly higher quality videos (p < 0.001). Similarly, the educational category demonstrated higher quality videos (p < 0.001). Video interaction trended lower with MSK videos and educational videos had the lowest interaction of the content categories (likes: p = 0.023, comments: p = 0.005).
    CONCLUSION: The quality of spine surgery videos on TikTok is low. As the influence of the new social media landscape governs how the average person consumes information, MSK providers should participate in disseminating high-quality content.
    Keywords:  DISCERN; Quality; Social media; Spine surgery; TikTok
    DOI:  https://doi.org/10.14245/ns.2346700.350
  20. J Med Internet Res. 2024 Jan 03.
    Quality of Patient-Centered eHealth Information on Erosive Tooth Wear: Systematic Search and Evaluation of Websites and YouTube Videos.
    Lena Holland, Amelie Friederike Kanzow, Annette Wiegand, Philipp Kanzow.
      BACKGROUND: Due to declining prevalence of dental caries, non-carious tooth defects such as erosive tooth wear gained increased attention over the past decades. While patients more frequently search the internet for health-related information, quality of patient-centered online health information on erosive tooth wear is currently unknown.OBJECTIVE: This study aimed to assess the quality of patient-centered online health information (websites and YouTube videos) on erosive tooth wear.
    METHODS: German-speaking websites were systematically identified through 3 electronic search engines (google.de, bing.de/yahoo.de, duckduckgo.com) in September 2021. Eligible websites were independently assessed for (1) technically and functional aspects via LIDA instrument, (2) readability via Flesch reading-ease score test, (3) comprehensiveness of information via a structured checklist, and (4) generic quality and risk of bias via DISCERN instrument by 2 reviewers. An overall quality score (ie, higher scores being favored) generated from all 4 domains was used as primary outcome. Quality scores from each domain were separately analyzed as secondary outcomes and compared by Friedman test followed by Dunn-Bonferroni post-hoc tests. The effect of practice-specific variables on quality scores of websites from private dental offices was assessed using generalized linear modelling (GLM). Eligible YouTube videos were judged based on (1) comprehensiveness of information, (2) viewers' interaction, and (3) viewing rate. Comprehensiveness of information was compared between websites and YouTube videos using Wilcoxon rank-sum test.
    RESULTS: A total of 231 eligible websites and 7 YouTube videos was identified and assessed. The median overall quality of the websites was 33.6% (IQR 29.8%-39.2%). Secondary outcome scores amounted to 64.3% (IQR 59.8%-69.0%) for technical and functional aspects, 40.0% (IQR 34.0%-49.0%) for readability, 11.5% (IQR 3.9%-26.9%) for comprehensiveness of information, and 16.7% (IQR 8.3%-23.3%) for generic quality. While comprehensiveness of information and generic quality received low scores, technical and functional aspects as well as readability resulted in higher scores (both Padjusted<.001/Friedman test). Regarding practice-specific variables, websites from private dental offices outside Germany (P=.04/GLM, B=-6.64, 95% CI -12.85 to -0.42) or from dentists being a dental society member (P=.049/GLM, B=-3.55, 95% CI -7.09 to -0.01) resulted in lower readability scores (ie, were more difficult to read), while a shorter time since dentists' examination resulted in higher readability scores (P=.01/GLM, B=0.24 per year, 95% CI 0.05 to 0.43). The comprehensiveness of information of YouTube videos was 34.6% (IQR 13.5%-38.5%). However, comprehensiveness of information did not vary between websites and YouTube videos (P=.09/Wilcoxon rank-sum test). Also, viewers' interaction (1.7%, IQR 0.7%-3.4%) and viewing rates (101.0%, IQR 54.6%-112.6%) were low.
    CONCLUSIONS: The quality of German-speaking patient-centered online information on erosive tooth wear was limited. Especially, comprehensiveness and trustworthiness of the available information was insufficient. Online information on erosive tooth wear requires improvement to inform patients comprehensively and reliably.
    CLINICALTRIAL:
    DOI:  https://doi.org/10.2196/49514
  21. Cleft Palate Craniofac J. 2023 Dec 29. 10556656231223861
    Assessment of Quality and Readability of Web-Based Arabic Knowledge About Cleft Lip and/or Palate: An Infodemiology Study.
    Muath S Alassaf, Saad M Hasubah, Shadan H Sharbib, Reem Alhammad, Ahmad A Othman, Mahmoud A Alsulaimani, Ahmad A Qazali.
      OBJECTIVE: The aim of this study is to evaluate the quality and readability of the Arabic web-based information about cleft lip and/or palate (CL/P).Materials and Method: Searching in three engines and checking eligibility for the first 300 websites. The quality of the included websites (72) was assessed using the DISCERN questionnaire, JAMA benchmarks, and HON code. The readability of the websites was assessed using three readability tests: FKGL, SMOG, and FRE. Then, data analysis was done.RESULTS: All checked websites were partly related to CL/P and contained medical facts. The affiliation of most of the websites was commercial 33 (45.8%). The mean overall DISCERN score was 2.87 (± 1.61). The maximum score was not achieved by any website, and only one (1.4%) website had the minimum score. For JAMA benchmarks, the currency was the most achieved item in 39 (54.2%) websites, and none of the websites achieved the four items. Only one website had the HON code. Based on the FRE scale, the level was very easy for most of the websites 57 (79.2%).
    CONCLUSION: The available content about CL/P is readable but with moderate to poor quality and trustfulness. Undoubtedly, there is a serious need to increase and improve the quality of the web-based Arabic population's knowledge about CL/P, especially by governmental institutions and universities. Establishing specialized websites for CL/P is also needed.
    Keywords:  cleft lip; cleft lip and palate; cleft palate; quality improvement; team care
    DOI:  https://doi.org/10.1177/10556656231223861
  22. Online J Public Health Inform. 2023 ;15 e51984
    Health Information Seeking Behavior on Social Networking Sites and Self-Treatment: Pilot Survey Study.
    Reginald A Silver, Chandrika Johnson.
      Background: Social networking site use and social network-based health information seeking behavior have proliferated to the point that the lines between seeking health information from credible social network-based sources and the decision to seek medical care or attempt to treat oneself have become blurred.Objective: We contribute to emerging research on health information seeking behavior by investigating demographic factors, social media use for health information seeking purposes, and the relationship between health information seeking and occurrences of self-treatment.
    Methods: Data were collected from an online survey in which participants were asked to describe sociodemographic factors about themselves, social media use patterns, perceptions about their motivations for health information seeking on social media platforms, and whether or not they attempted self-treatment after their social media-related health information seeking. We conducted a binomial logistic regression with self-treatment as a dichotomous categorical dependent variable.
    Results: Results indicate that significant predictors of self-treatment based on information obtained from social networking sites include race, exercise frequency, and degree of trust in the health-related information received.
    Conclusions: With an understanding of how sociodemographic factors might influence the decision to self-treat based on information obtained from social networking sites, health care providers can assist patients by educating them on credible social network-based sources of health information and discussing the importance of seeking medical advice from a health care provider.
    Keywords:  community survey; health care seeking behavior; logistic regression; online social networking; self-treatment; sociodemographic factors
    DOI:  https://doi.org/10.2196/51984
  23. Cureus. 2023 Nov;15(11): e49755
    Internet Search Trends for Common Hand Surgery Diagnoses.
    William Kilgallen, Brandon Earp, Dafang Zhang.
      PURPOSE: The internet is a common resource for patients seeking health information. Trends in internet search interests for common hand surgery diagnoses and their seasonal variations have not been previously studied. The objectives of this study were (1) to describe the temporal trends in internet search interest for common hand surgery diagnoses in the recent five-year time period and (2) to assess seasonal variations in search term interest.METHODS: An internet-based study of internet search term interest of 10 common hand surgery diagnoses was performed using Google Trends (Google, Inc., Mountain View, CA) from January 2017 to December 2021. The 10 diagnoses were "carpal tunnel syndrome," "trigger finger," "thumb arthritis," "ganglion cyst," "de Quervain's tenosynovitis," "lateral epicondylitis," "Dupuytren disease," "distal radius fracture," "finger fracture," and "scaphoid fracture." Analysis of variance (ANOVA) was used to assess for seasonal differences in search interest, and temporal trends were assessed using the two-tailed Mann-Kendall trend test.
    RESULTS: During the study period, there was an increasing trend for search interest for "carpal tunnel syndrome," "trigger finger," "thumb arthritis," "Dupuytren disease," and "finger fracture," both in the United States and worldwide. There was no significant temporal trend for "ganglion cyst," "de Quervain's tenosynovitis," "lateral epicondylitis," and "distal radius fracture." There were no significant temporal trend for "scaphoid fracture" in the United States and a decreasing trend worldwide. There was significant seasonal variation in search term interest for "finger fracture" in the United States, "finger fracture" worldwide, and "scaphoid fracture" in the United States, with popularity peaking in the fall.
    CONCLUSIONS: Despite growth in global internet usage, internet search interest has remained stagnant for many common hand surgery conditions, which may represent a shifting preference for patients to obtain health information from other resources. Internet search interest for traumatic hand conditions corresponds to seasonal variations in fracture epidemiology and peaks in the fall season.
    Keywords:  hand surgery; health literacy; internet; online; seasonal variation
    DOI:  https://doi.org/10.7759/cureus.49755
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