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      Assessment of the quality, content, and reliability of YouTube® videos on diabetes mellitus and polycystic ovary syndrome: a systematic review with cross-sectional analysis comparing peer-reviewed videos

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          Abstract

          YouTube® is one of the leading platforms for health information. However, the lack of regulation of content and quality raises concerns about accuracy and reliability. CoMICs (Concise Medical Information Cines) are evidence-based short videos created by medical students and junior doctors and reviewed by experts to ensure clinical accuracy. We performed a systematic review to understand the impact of videos on knowledge and awareness about diabetes and PCOS. We then evaluated the quality of YouTube® videos about diabetes and PCOS using various validated quality assessment tools and compared these with CoMICs videos on the same topics. Quality assessment tools like DISCERN, JAMA benchmark criteria, and global quality scale (GQS) score were employed. Some of the authors of this study also co-authored the creation of some of the CoMICs evaluated. Our study revealed that while videos effectively improve understanding of diabetes and PCOS, there are notable differences in quality and reliability of the videos on YouTube®. For diabetes, CoMICs videos had higher DISCERN scores (CoMICs vs YouTube®: 2.4 vs 1.6), superior reliability ( P < 0.01), and treatment quality ( P < 0.01) and met JAMA criteria for authorship (100% vs 30.6%) and currency (100% vs 53.1%). For PCOS, CoMICs had higher DISCERN scores (2.9 vs 1.9), reliability ( P < 0.01), and treatment quality ( P < 0.01); met JAMA criteria for authorship (100% vs 34.0%) and currency (100% vs 54.0%); and had higher GQS scores (4.0 vs 3.0). In conclusion, CoMICs outperformed other similar sources on YouTube® in providing reliable evidence-based medical information which may be used for patient education.

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          DISCERN: an instrument for judging the quality of written consumer health information on treatment choices.

          To develop a short instrument, called DISCERN, which will enable patients and information providers to judge the quality of written information about treatment choices. DISCERN will also facilitate the production of new, high quality, evidence-based consumer health information. An expert panel, representing a range of expertise in consumer health information, generated criteria from a random sample of information for three medical conditions with varying degrees of evidence: myocardial infarction, endometriosis, and chronic fatigue syndrome. A graft instrument, based on this analysis, was tested by the panel on a random sample of new material for the same three conditions. The panel re-drafted the instrument to take account of the results of the test. The DISCERN instrument was finally tested by a national sample of 15 information providers and 13 self help group members on a random sample of leaflets from 19 major national self help organisations. Participants also completed an 8 item questionnaire concerning the face and content validity of the instrument. Chance corrected agreement (weighted kappa) for the overall quality rating was kappa = 0.53 (95% CI kappa = 0.48 to kappa = 0.59) among the expert panel, kappa = 0.40 (95% CI kappa = 0.36 to kappa = 0.43) among information providers, and kappa = 0.23 (95% CI kappa = 0.19 to kappa = 0.27) among self help group members. Higher agreement levels were associated with experience of using the instrument and with professional knowledge of consumer health information. Levels of agreement varied across individual items on the instrument, reflecting the need for subjectivity in rating certain criteria. The trends in levels of agreement were similar among all groups. The final instrument consisted of 15 questions plus an overall quality rating. Responses to the questionnaire after the final testing revealed the instrument to have good face and content validity and to be generally applicable. DISCERN is a reliable and valid instrument for judging the quality of written consumer health information. While some subjectivity is required for rating certain criteria, the findings demonstrate that the instrument can be applied by experienced users and providers of health information to discriminate between publications of high and low quality. The instrument will also be of benefit to patients, though its use will be improved by training.
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            Prevalence of Health Misinformation on Social Media: Systematic Review

            Background Although at present there is broad agreement among researchers, health professionals, and policy makers on the need to control and combat health misinformation, the magnitude of this problem is still unknown. Consequently, it is fundamental to discover both the most prevalent health topics and the social media platforms from which these topics are initially framed and subsequently disseminated. Objective This systematic review aimed to identify the main health misinformation topics and their prevalence on different social media platforms, focusing on methodological quality and the diverse solutions that are being implemented to address this public health concern. Methods We searched PubMed, MEDLINE, Scopus, and Web of Science for articles published in English before March 2019, with a focus on the study of health misinformation in social media. We defined health misinformation as a health-related claim that is based on anecdotal evidence, false, or misleading owing to the lack of existing scientific knowledge. We included (1) articles that focused on health misinformation in social media, including those in which the authors discussed the consequences or purposes of health misinformation and (2) studies that described empirical findings regarding the measurement of health misinformation on these platforms. Results A total of 69 studies were identified as eligible, and they covered a wide range of health topics and social media platforms. The topics were articulated around the following six principal categories: vaccines (32%), drugs or smoking (22%), noncommunicable diseases (19%), pandemics (10%), eating disorders (9%), and medical treatments (7%). Studies were mainly based on the following five methodological approaches: social network analysis (28%), evaluating content (26%), evaluating quality (24%), content/text analysis (16%), and sentiment analysis (6%). Health misinformation was most prevalent in studies related to smoking products and drugs such as opioids and marijuana. Posts with misinformation reached 87% in some studies. Health misinformation about vaccines was also very common (43%), with the human papilloma virus vaccine being the most affected. Health misinformation related to diets or pro–eating disorder arguments were moderate in comparison to the aforementioned topics (36%). Studies focused on diseases (ie, noncommunicable diseases and pandemics) also reported moderate misinformation rates (40%), especially in the case of cancer. Finally, the lowest levels of health misinformation were related to medical treatments (30%). Conclusions The prevalence of health misinformation was the highest on Twitter and on issues related to smoking products and drugs. However, misinformation on major public health issues, such as vaccines and diseases, was also high. Our study offers a comprehensive characterization of the dominant health misinformation topics and a comprehensive description of their prevalence on different social media platforms, which can guide future studies and help in the development of evidence-based digital policy action plans.
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              Assessing, Controlling, and Assuring the Quality of Medical Information on the Internet

                Author and article information

                Journal
                Endocr Connect
                Endocr Connect
                EC
                Endocrine Connections
                Bioscientifica Ltd (Bristol )
                2049-3614
                28 June 2024
                10 June 2024
                01 July 2024
                : 13
                : 7
                : e240059
                Affiliations
                [1 ]College of Medical and Dental Sciences , University of Birmingham, Birmingham, United Kingdom
                [2 ]Department of Surgery , Rama Medical College Hospital and Research Centre, Hapur, Uttar Pradesh, India
                [3 ]Institute of Applied Health Research , College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
                [4 ]Queen Elizabeth Hospital , University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
                Author notes
                Correspondence should be addressed to P Kempegowda: p.kempegowda@ 123456bham.ac.uk

                *(S Ali Baig and K Malhotra are joint first authors of this study)

                Author information
                http://orcid.org/0009-0002-9606-4473
                http://orcid.org/0000-0003-0954-6512
                Article
                EC-24-0059
                10.1530/EC-24-0059
                11227060
                38856005
                d9a34c4f-b1cd-45ee-adf2-70675c031aca
                © the author(s)

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 13 February 2024
                : 10 June 2024
                Categories
                Research
                EC-Metabolic-Syndrome-and-Diabetes, Metabolic Syndrome and Diabetes
                Custom metadata
                EC-Metabolic-Syndrome-and-Diabetes

                youtube,diabetes,polycystic ovary syndrome,digital health,online media,quality,evidence

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