Identifying strategies to support implementation of interprofessional primary care teams in Nova Scotia: Results of a survey and knowledge sharing event.

BACKGROUND: Interprofessional primary care teams (IPCTs) work together to enhance care. Despite evidence on the benefits of IPCTs, implementation remains challenging. This research aims to 1) identify and prioritize barriers and enablers, and 2) co-develop team-level strategies to support IPCT implementation in Nova Scotia, Canada. METHODS: Healthcare providers and staff of IPCTs were invited to complete an online survey to identify barriers and enablers, and the degree to which each item impacted the functioning of their team. Top ranked items were identified using the sum of frequency x impact for each response. A virtual knowledge sharing event was held to identify strategies to address local barriers and enablers that impact team functioning. RESULTS: IPCT members (n = 117), with a mix of clinic roles and experience, completed the survey. The top three enablers identified were access to technological tools to support their role, standardized processes for using the technological tools, and having a team manager to coordinate collaboration. The top three barriers were limited opportunity for daily team communication, lack of conflict resolution strategies, and lack of capacity building opportunities. IPCT members, administrators, and patients attended the knowledge sharing event (n = 33). Five strategies were identified including: 1) balancing patient needs and provider scope of practice, 2) holding regular and accessible meetings, 3) supporting team development opportunities, 4) supporting professional development, and 5) supporting involvement in non-clinical activities. INTERPRETATION: This research contextualized evidence to further understand local perspectives and experiences of barriers and enablers to the implementation of IPCTs. The knowledge exchange event identified actionable strategies that IPCTs and healthcare administrators can tailor to support teams and care for patients.

Difference in Rumor Dissemination and Debunking Before and After the Relaxation of COVID-19 Prevention and Control Measures in China: Infodemiology Study.

BACKGROUND: The information epidemic emerged along with the COVID-19 pandemic. While controlling the spread of COVID-19, the secondary harm of epidemic rumors to social order cannot be ignored. OBJECTIVE: The objective of this paper was to understand the characteristics of rumor dissemination before and after the pandemic and the corresponding rumor management and debunking mechanisms. This study aimed to provide a theoretical basis and effective methods for relevant departments to establish a sound mechanism for managing network rumors related to public health emergencies such as COVID-19. METHODS: This study collected data sets of epidemic rumors before and after the relaxation of the epidemic prevention and control measures, focusing on large-scale network rumors. Starting from 3 dimensions of rumor content construction, rumor propagation, and rumor-refuting response, the epidemic rumors were subdivided into 7 categories, namely, involved subjects, communication content, emotional expression, communication channels, communication forms, rumor-refuting subjects, and verification sources. Based on this framework, content coding and statistical analysis of epidemic rumors were carried out. RESULTS: The study found that the rumor information was primarily directed at a clear target audience. The main themes of rumor dissemination were related to the public's immediate interests in the COVID-19 field, with significant differences in emotional expression and mostly negative emotions. Rumors mostly spread through social media interactions, community dissemination, and circle dissemination, with text content as the main form, but they lack factual evidence. The preferences of debunking subjects showed differences, and the frequent occurrence of rumors reflected the unsmooth channels of debunking. The χ2 test of data before and after the pandemic showed that the P value was less than .05, indicating that the difference in rumor content before and after the pandemic had statistical significance. CONCLUSIONS: This study's results showed that the themes of rumors during the pandemic are closely related to the immediate interests of the public, and the emotions of the public accelerate the spread of these rumors, which are mostly disseminated through social networks. Therefore, to more effectively prevent and control the spread of rumors during the pandemic and to enhance the capability to respond to public health crises, relevant authorities should strengthen communication with the public, conduct emotional risk assessments, and establish a joint mechanism for debunking rumors.

News and misinformation consumption: A temporal comparison across European countries.

The Internet and social media have transformed the information landscape, democratizing content access and production. While making information easily accessible, these platforms can also act as channels for spreading misinformation, posing crucial societal challenges. To address this, understanding news consumption patterns and unraveling the complexities of the online information environment are essential. Previous studies highlight polarization and misinformation in online discussions, but many focus on specific topics or contexts, often overlooking comprehensive cross-country and cross-topic analyses. However, the dynamics of debates, misinformation prevalence, and the efficacy of countermeasures are intrinsically tied to socio-cultural contexts. This work aims to bridge this gap by exploring information consumption patterns across four European countries over three years. Analyzing the Twitter activity of news outlets in France, Germany, Italy, and the UK, this study seeks to shed light on how topics of European significance resonate across these nations and the role played by misinformation sources. The results spotlight that while reliable sources predominantly shape the information landscape, unreliable content persists across all countries and topics. Though most users favor trustworthy sources, a small percentage predominantly consumes content from questionable sources, with even fewer maintaining a mixed information diet. The cross-country comparison unravels disparities in audience overlap among news sources, the prevalence of misinformation, and the proportion of users relying on questionable sources. Such distinctions surface not only across countries but also within various topics. These insights underscore the pressing need for tailored studies, crucial in designing targeted and effective countermeasures against misinformation and extreme polarization in the digital space.

Workflow for detecting biomedical articles with underlying open and restricted-access datasets.

To monitor the sharing of research data through repositories is increasingly of interest to institutions and funders, as well as from a meta-research perspective. Automated screening tools exist, but they are based on either narrow or vague definitions of open data. Where manual validation has been performed, it was based on a small article sample. At our biomedical research institution, we developed detailed criteria for such a screening, as well as a workflow which combines an automated and a manual step, and considers both fully open and restricted-access data. We use the results for an internal incentivization scheme, as well as for a monitoring in a dashboard. Here, we describe in detail our screening procedure and its validation, based on automated screening of 11035 biomedical research articles, of which 1381 articles with potential data sharing were subsequently screened manually. The screening results were highly reliable, as witnessed by inter-rater reliability values of ≥0.8 (Krippendorff's alpha) in two different validation samples. We also report the results of the screening, both for our institution and an independent sample from a meta-research study. In the largest of the three samples, the 2021 institutional sample, underlying data had been openly shared for 7.8% of research articles. For an additional 1.0% of articles, restricted-access data had been shared, resulting in 8.3% of articles overall having open and/or restricted-access data. The extraction workflow is then discussed with regard to its applicability in different contexts, limitations, possible variations, and future developments. In summary, we present a comprehensive, validated, semi-automated workflow for the detection of shared research data underlying biomedical article publications.

Sharing insect data through GBIF: novel monitoring methods, opportunities and standards.

Technological advancements in biological monitoring have facilitated the study of insect communities at unprecedented spatial scales. The progress allows more comprehensive coverage of the diversity within a given area while minimizing disturbance and reducing the need for extensive human labour. Compared with traditional methods, these novel technologies offer the opportunity to examine biological patterns that were previously beyond our reach. However, to address the pressing scientific inquiries of the future, data must be easily accessible, interoperable and reusable for the global research community. Biodiversity information standards and platforms provide the necessary infrastructure to standardize and share biodiversity data. This paper explores the possibilities and prerequisites of publishing insect data obtained through novel monitoring methods through GBIF, the most comprehensive global biodiversity data infrastructure. We describe the essential components of metadata standards and existing data standards for occurrence data on insects, including data extensions. By addressing the current opportunities, limitations, and future development of GBIF's publishing framework, we hope to encourage researchers to both share data and contribute to the further development of biodiversity data standards and publishing models. Wider commitments to open data initiatives will promote data interoperability and support cross-disciplinary scientific research and key policy indicators. This article is part of the theme issue 'Towards a toolkit for global insect biodiversity monitoring'.

Does Reader Engagement with Neurosurgery Journal Websites Correlate with the Number of Citations Received by Articles?

BACKGROUND: Medicine has begun adapting to new information-sharing paradigms in the hyper-connected social media era. In this milieu, the role of journal websites in the dissemination of clinical and research information needs to be reevaluated. OBJECTIVE: We sought to explore whether reader engagement with neurosurgical journal websites, reflected by the number of article views and downloads, correlated with the eventual number of citations received by the articles. METHODS: The websites of all Medline indexed neurosurgical journals were screened to identify those that provided information regarding the number of abstract and full text views and downloads. Articles published in these journals between July 2010 and June 2011 were included in this analysis. Various article attributes were identified and the number of citations per article was obtained from Google Scholar. The impact factors of the selected journals for the year 2010 were obtained from the Journal Citation Reports. RESULTS: Twenty-two journals that had published 2527 articles were finally included in this analysis. The number of abstract views, full-text views, and downloads all correlated strongly with the journal impact factors in 2010 as well as the eventual citations per article. The number of article downloads independently predicted the citations per article on multivariate analysis. Neurology India had significantly higher article views and downloads but lower citations per article than the other journals. CONCLUSIONS: Readers were found to engage significantly with neurosurgical journal websites and therefore, open access to articles would lead to increased visibility of articles, resulting in higher citation rates.

Dacryocystorhinostomy videos on YouTube as a source of patient education.

BACKGROUND: To determine the quality and reliability of DCR YouTube videos as patient education resources and identify any associated factors predictive of video quality. METHODS: A YouTube search was conducted using the terms "Dacryocystorhinostomy, DCR, surgery" on 12th of January 2022, with the first 50 relevant videos selected for inclusion. For each video, the following was collected: video hyperlink, title, total views, months since the video was posted, video length, total likes/dislikes, authorship (i.e. surgeon, patient experience or media companies) and number of comments. The videos were graded independently by a resident, a registrar and an oculoplastic surgeon using three validated scoring systems: the Journal of the American Medical Association (JAMA), DISCERN, and Health on the Net (HON). RESULTS: The average number of video views was 22,992, with the mean length being 488.12 s and an average of 18 comments per video. The consensus JAMA, DISCERN and HON scores were 2.1 ± 0.6, 29.1 ± 8.8 and 2.7 ± 1.0, respectively. This indicated that the included videos were of a low quality, however, only DISCERN scores had good interobserver similarity. Videos posted by surgeons were superior to non-surgeons when considering mean JAMA and HON scores. No other factors were associated with the quality of educational content. CONCLUSION: The quality and reliability of DCR related content for patient education is relatively low. Based on this study's findings, patients should be encouraged to view videos created by surgeons or specialists in preference to other sources on YouTube.

Advancing data honesty in experimental biology.

The ease with which scientific data, particularly certain types of raw data in experimental biology, can be fabricated without trace begs urgent attention. This is thought to be a widespread problem across the academic world, where published results are the major currency, incentivizing publication of (usually positive) results at the cost of lax scientific rigor and even fraudulent data. Although solutions to improve data sharing and methodological transparency are increasingly being implemented, the inability to detect dishonesty within raw data remains an inherent flaw in the way in which we judge research. We therefore propose that one solution would be the development of a non-modifiable raw data format that could be published alongside scientific results; a format that would enable data authentication from the earliest stages of experimental data collection. A further extension of this tool could allow changes to the initial original version to be tracked, so every reviewer and reader could follow the logical footsteps of the author and detect unintentional errors or intentional manipulations of the data. Were such a tool to be developed, we would not advocate its use as a prerequisite for journal submission; rather, we envisage that authors would be given the option to provide such authentication. Only authors who did not manipulate or fabricate their data can provide the original data without risking discovery, so the mere choice to do so already increases their credibility (much like 'honest signaling' in animals). We strongly believe that such a tool would enhance data honesty and encourage more reliable science.

Agricultural education in Africa using YouTube multilingual animations: A retrospective feasibility study assessing costs to reach language-diverse populations.

There is a critical need for widespread information dissemination of agricultural best practices in Africa. Literacy, language and resource barriers often impede such information dissemination. Culturally and linguistically localized, computer-animated training videos placed on YouTube and promoted through paid advertising is a potential tool to help overcome these barriers. The goal of this study is to assess the feasibility of reaching language-diverse populations in Africa using this new type of information dissemination channel. As a case study, cost estimates were obtained for YouTube ad campaigns of a video to prevent post-harvest loss through safe food storage using sanitized jerrycan containers. Seventy-three video variants were created for the most common 16 languages in Ghana, 35 languages in Kenya, and 22 languages in Nigeria. Using these videos, campaigns were deployed country wide or focused on zones of influence that represent economically underdeveloped regions known to produce beans suitable for jerrycan storage. Using data collected from YouTube ad campaigns, language-specific models were created for each country to estimate how many viewers could be reached per US dollar spent. Separate models were created to estimate the number of viewers who watched 25% and 75% of the video (most of video without end credits), reflecting different levels of engagement. For language campaigns with both country wide and zone of influence areas of deployment, separate region-specific models were created. Models showed that the estimated number of viewers per dollar spent varied considerably amongst countries and languages. On average, the expected number of viewers per dollar spent were 1.8 (Range = 0.2-7.3) for 25% watched and 0.8 (Range = 0.1-3.2) for 75% watched in Ghana, 1.2 (0.2-4.8) for 25% watched and 0.5 (Range = 0.1-2.0) for 75% watched in Kenya, and 0.4 (Range = 0.2-1.3) for 25% watched and 0.2 (Range = 0.1-0.5) for 75% watched in Nigeria. English versions of the video were the most cost-effective in reaching viewers in Ghana and Nigeria. In Kenya, English language campaigns ranked 28 (country wide) and 36 (zones of influence) out of 37 analyzed campaigns. Results also showed that many local language campaigns performed well, opening the possibility that targeted knowledge dissemination on topics of importance to local populations, is potentially cost effective. In addition, such targeted information dissemination appears feasible, even during regional and global crises when in-person training may not be possible. In summary, leveraging multilingual computer-animations and digital platforms such as YouTube shows promise for conducting large-scale agricultural education campaigns. The findings of the current study provides the justification to pursue a more rigorous prospective study to verify the efficacy of knowledge exchange and societal impact through this form of information dissemination channel.

Data challenges for international health emergencies: lessons learned from ten international COVID-19 driver projects.

The COVID-19 pandemic highlighted the importance of international data sharing and access to improve health outcomes for all. The International COVID-19 Data Alliance (ICODA) programme enabled 12 exemplar or driver projects to use existing health-related data to address major research questions relating to the pandemic, and developed data science approaches that helped each research team to overcome challenges, accelerate the data research cycle, and produce rapid insights and outputs. These approaches also sought to address inequity in data access and use, test approaches to ethical health data use, and make summary datasets and outputs accessible to a wider group of researchers. This Health Policy paper focuses on the challenges and lessons learned from ten of the ICODA driver projects, involving researchers from 19 countries and a range of health-related datasets. The ICODA programme reviewed the time taken for each project to complete stages of the health data research cycle and identified common challenges in areas such as data sharing agreements and data curation. Solutions included provision of standard data sharing templates, additional data curation expertise at an early stage, and a trusted research environment that facilitated data sharing across national boundaries and reduced risk. These approaches enabled the driver projects to rapidly produce research outputs, including publications, shared code, dashboards, and innovative resources, which can all be accessed and used by other research teams to address global health challenges.

'Kindling the fire' of NHS patient data exploitations: The care.data controversy in news media discourses.

This paper explores news media discourse about care.data: an NHS England programme of work for amalgamating and sharing patient data from primary care for planning and research. It was scrapped in 2016 after three years of public outcry, delays and around 1.5 million opt-outs. I examine UK news media coverage of this programme through the 'fire object' metaphor, focusing upon the visions of purpose and value it inspired, the abrupt discontinuities, juxtapositions and transformations it performed, and the matters of concern that went unheeded. Findings suggest that, in care.data's pursuit of a societal consensus on NHS patient data exploitations, various visions for new and fluid data flows brought to presence narratives of transforming the NHS, saving lives, and growing the economy. Other realities and concerns that mattered for certain stakeholders, such as data ownership and commercialisation, public engagement and informed consent, commitment and leadership, operational capabilities, and NHS privatisation agendas, remained absent or unsettled. False dichotomies kept the controversy alive, sealing its fate. I conclude by arguing that such failed programmes can turn into phantom-like objects, haunting future patient data schemes of similar aspirations. The paper highlights the role news media can have in understanding such energetic public controversies.

Contents analysis of thyroid cancer-related information uploaded to YouTube by physicians in Korea: endorsing thyroid cancer screening, potentially leading to overdiagnosis.

BACKGROUND: Thyroid cancer overdiagnosis is a major public health issue in South Korea, which has the highest incidence rate. The accessibility of information through the Internet, particularly on YouTube, could potentially impact excessive screening. This study aimed to analyze the content of thyroid cancer-related YouTube videos, particularly those from 2016 onwards, to evaluate the potential spread of misinformation. METHODS: A total of 326 videos for analysis were collected using a video search protocol with the keyword "thyroid cancer" on YouTube. This study classified the selected YouTube videos as either provided by medical professionals or not and used topic clustering with LDA (latent dirichlet allocation), sentiment analysis with KoBERT (Korean bidirectional encoder representations from transformers), and reliability evaluation to analyze the content. The proportion of mentions of poor prognosis for thyroid cancer and the categorization of advertising content was also analyzed. RESULTS: Videos by medical professionals were categorized into 7 topics, with "Thyroid cancer is not a 'Good cancer'" being the most common. The number of videos opposing excessive thyroid cancer screening decreased gradually yearly. Videos advocating screening received more favorable comments from viewers than videos opposing excessive thyroid cancer screening. Patient experience videos were categorized into 6 topics, with the "Treatment process and after-treatment" being the most common. CONCLUSION: This study found that a significant proportion of videos uploaded by medical professionals on thyroid cancer endorse the practice, potentially leading to excessive treatments. The study highlights the need for medical professionals to provide high-quality and unbiased information on social media platforms to prevent the spread of medical misinformation and the need for criteria to judge the content and quality of online health information.

Assessing the Reliability of Facial Feminization Content on Social Media and Its Impact on the Dissemination of Misinformation.

BACKGROUND: The surge in social media usage has transformed the dissemination and consumption of healthcare information, notably impacting plastic surgery and cosmetic specialties. This study focuses on the influence of social media, particularly Instagram and TikTok, in shaping perceptions of individuals seeking facial feminization (FF) procedures. METHODS: Using the validated DISCERN scale, we assessed the reliability and accuracy of FF content on TikTok and Instagram. The study also analyzed the relationship between content reliability on engagement metrics (likes, comments, views) and the type of content shared (educational, testimonial, promotional). RESULTS: The analysis encompassed 225 TikTok videos and 75 Instagram posts. TikTok content showed 9.33% as "very poor," 66.2% as "poor," 22.6% as "fair," and only 1.33% as "excellent." Similarly, Instagram content demonstrated 14.67% as "very poor" and 69.33% as "poor," with no content rated as "good" or "excellent." Educational content received higher reliability scores on both platforms. TikTok engagement metrics showed lower reliability ratings correlating with more views, comments, and likes. CONCLUSION: The study underscores the critical role of social media in shaping patient perspectives on FF procedures. The prevalence of inaccurate information necessitates a focus on responsible engagement by healthcare professionals, aiming to provide accurate, educational content that aligns with patients' informational needs and ultimately enhances surgical outcomes.

A study on formalizing the knowledge of data curation activities across different fields.

In recent years, with the trend of open science, there have been many efforts to share research data on the internet. To promote research data sharing, data curation is essential to make the data interpretable and reusable. In research fields such as life sciences, earth sciences, and social sciences, tasks and procedures have been already developed to implement efficient data curation to meet the needs and customs of individual research fields. However, not only data sharing within research fields but also interdisciplinary data sharing is required to promote open science. For this purpose, knowledge of data curation across the research fields is surveyed, analyzed, and organized as an ontology in this paper. As the survey, existing vocabularies and procedures are collected and compared as well as interviews with the data curators in research institutes in different fields are conducted to clarify commonalities and differences in data curation across the research fields. It turned out that the granularity of tasks and procedures that constitute the building blocks of data curation is not formalized. Without a method to overcome this gap, it will be challenging to promote interdisciplinary reuse of research data. Based on the analysis above, the ontology for the data curation process is proposed to describe data curation processes in different fields universally. It is described by OWL and shown as valid and consistent from the logical viewpoint. The ontology successfully represents data curation activities as the processes in the different fields acquired by the interviews. It is also helpful to identify the functions of the systems to support the data curation process. This study contributes to building a knowledge framework for an interdisciplinary understanding of data curation activities in different fields.

Seek and you may (not) find: A multi-institutional analysis of where research data are shared.

Research data sharing has become an expected component of scientific research and scholarly publishing practice over the last few decades, due in part to requirements for federally funded research. As part of a larger effort to better understand the workflows and costs of public access to research data, this project conducted a high-level analysis of where academic research data is most frequently shared. To do this, we leveraged the DataCite and Crossref application programming interfaces (APIs) in search of Publisher field elements demonstrating which data repositories were utilized by researchers from six academic research institutions between 2012-2022. In addition, we also ran a preliminary analysis of the quality of the metadata associated with these published datasets, comparing the extent to which information was missing from metadata fields deemed important for public access to research data. Results show that the top 10 publishers accounted for 89.0% to 99.8% of the datasets connected with the institutions in our study. Known data repositories, including institutional data repositories hosted by those institutions, were initially lacking from our sample due to varying metadata standards and practices. We conclude that the metadata quality landscape for published research datasets is uneven; key information, such as author affiliation, is often incomplete or missing from source data repositories and aggregators. To enhance the findability, interoperability, accessibility, and reusability (FAIRness) of research data, we provide a set of concrete recommendations that repositories and data authors can take to improve scholarly metadata associated with shared datasets.

Now Is the Time to Strengthen Government-Academic Data Infrastructures to Jump-Start Future Public Health Crisis Response.

During public health crises, the significance of rapid data sharing cannot be overstated. In attempts to accelerate COVID-19 pandemic responses, discussions within society and scholarly research have focused on data sharing among health care providers, across government departments at different levels, and on an international scale. A lesser-addressed yet equally important approach to sharing data during the COVID-19 pandemic and other crises involves cross-sector collaboration between government entities and academic researchers. Specifically, this refers to dedicated projects in which a government entity shares public health data with an academic research team for data analysis to receive data insights to inform policy. In this viewpoint, we identify and outline documented data sharing challenges in the context of COVID-19 and other public health crises, as well as broader crisis scenarios encompassing natural disasters and humanitarian emergencies. We then argue that government-academic data collaborations have the potential to alleviate these challenges, which should place them at the forefront of future research attention. In particular, for researchers, data collaborations with government entities should be considered part of the social infrastructure that bolsters their research efforts toward public health crisis response. Looking ahead, we propose a shift from ad hoc, intermittent collaborations to cultivating robust and enduring partnerships. Thus, we need to move beyond viewing government-academic data interactions as 1-time sharing events. Additionally, given the scarcity of scholarly exploration in this domain, we advocate for further investigation into the real-world practices and experiences related to sharing data from government sources with researchers during public health crises.

The Costs of Anonymization: Case Study Using Clinical Data.

BACKGROUND: Sharing data from clinical studies can accelerate scientific progress, improve transparency, and increase the potential for innovation and collaboration. However, privacy concerns remain a barrier to data sharing. Certain concerns, such as reidentification risk, can be addressed through the application of anonymization algorithms, whereby data are altered so that it is no longer reasonably related to a person. Yet, such alterations have the potential to influence the data set's statistical properties, such that the privacy-utility trade-off must be considered. This has been studied in theory, but evidence based on real-world individual-level clinical data is rare, and anonymization has not broadly been adopted in clinical practice. OBJECTIVE: The goal of this study is to contribute to a better understanding of anonymization in the real world by comprehensively evaluating the privacy-utility trade-off of differently anonymized data using data and scientific results from the German Chronic Kidney Disease (GCKD) study. METHODS: The GCKD data set extracted for this study consists of 5217 records and 70 variables. A 2-step procedure was followed to determine which variables constituted reidentification risks. To capture a large portion of the risk-utility space, we decided on risk thresholds ranging from 0.02 to 1. The data were then transformed via generalization and suppression, and the anonymization process was varied using a generic and a use case-specific configuration. To assess the utility of the anonymized GCKD data, general-purpose metrics (ie, data granularity and entropy), as well as use case-specific metrics (ie, reproducibility), were applied. Reproducibility was assessed by measuring the overlap of the 95% CI lengths between anonymized and original results. RESULTS: Reproducibility measured by 95% CI overlap was higher than utility obtained from general-purpose metrics. For example, granularity varied between 68.2% and 87.6%, and entropy varied between 25.5% and 46.2%, whereas the average 95% CI overlap was above 90% for all risk thresholds applied. A nonoverlapping 95% CI was detected in 6 estimates across all analyses, but the overwhelming majority of estimates exhibited an overlap over 50%. The use case-specific configuration outperformed the generic one in terms of actual utility (ie, reproducibility) at the same level of privacy. CONCLUSIONS: Our results illustrate the challenges that anonymization faces when aiming to support multiple likely and possibly competing uses, while use case-specific anonymization can provide greater utility. This aspect should be taken into account when evaluating the associated costs of anonymized data and attempting to maintain sufficiently high levels of privacy for anonymized data. TRIAL REGISTRATION: German Clinical Trials Register DRKS00003971; https://drks.de/search/en/trial/DRKS00003971. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1093/ndt/gfr456.

Myopia information on TikTok: analysis factors that impact video quality and audience engagement.

BACKGROUND: TikTok is emerging as a vital platform for health information dissemination. Despite myopia being a global public health issue, the high-quality myopia information shared by health educators often fails to go viral. It is imperative to analyze the factors influencing video quality and popularity, especially from diverse perspectives of researchers, health educators, and audiences. METHODS: TikTok myopia-related videos were retrieved using TikTok's default comprehensive search (DCS) and most liked search (MLS) strategies. Venn diagrams were employed to illustrate the relationships and commonalities between the two strategies across four sample sizes (top 200, 150, 100, and 50). Video metadata, including details such as creator information, production properties, upload time, video duration, and viewer engagement, were collected. Video quality was assessed using the DISCERN tool. Video content covering six aspects of myopia were evaluated. The impact of search strategies, video sample sizes, production properties, and myopia content on video quality and audience engagement was analyzed through single-factor or multi-factor analysis. RESULTS: DCS and MLS retrieval strategies, as well as varying sample sizes, resulted in differences in audience engagement for myopia videos (P < 0.039), while The DISCERN quality scores remained comparable (P > 0.221). Videos published by healthcare professionals (HCPs) and non-profit organizations (NPOs) were associated with high-quality (P ≤ 0.014) but comparatively lower popularity (P < 0.033). Videos that reported contents of risk factors, management, and outcomes showed high popularity (P < 0.018), while longer video duration (> 60s) exhibited the opposite trend (P < 0.032). Content on myopia evaluation (P ≤ 0.001) and management (P ≤ 0.022) and video duration were positively correlated with higher DISCERN quality. CONCLUSION: Videos created by HCPs and NPOs deserve greater attention. Rather than pursuing entertaining effects, professional educators should emphasize producing concise, and high-quality myopia content that readily resonates with the audience and has the potential to go viral on the platform.

A quality assessment of YouTube as an information resource for tonsillectomy.

PURPOSE: Online resources are increasingly being utilised by patients to guide their clinical decision making, as an alternative or supplement to the traditional clinical-patient relationship. YouTube is an online repository of user and community generated videos, which is one of the most popular websites globally. We undertook a study to examine the quality of information presented in YouTube videos related to tonsillectomy. METHODS: We completed a systematic search of YouTube in May 2023 and identified 88 videos for inclusion in our study. Videos were published in the English language, focussing on tonsillectomy and tonsillectomy recovery, and were greater than 2 min in length. We recorded video quality metrics and two authors independently analysed the quality of information using three validated quality assessment tools described in the literature including the modified DISCERN, Global Quality Score, and the JAMA Benchmark Criteria. RESULTS: The overall quality of the information was low with mean quality scores of Modified DISCERN (1.8 ± 1.3), GQS (2.6 ± 1.2), and JAMA Benchmark Criteria (1.6 ± 0.7). Information published by medical sources including medical professionals, healthcare organisations, and medical education channels scored significantly higher compared to non-medical sources across all quality measures and were of moderate overall quality and usefulness: Modified DISCERN (2.5 ± 1.1 vs 0.8 ± 0.9, z = -6.0, p < 0.001), GQS (3.2 ± 1.0 vs 1.7 ± 0.9, z = -5.7, p < 0.001), and JAMA (1.9 ± 0.8 vs 1.1 ± 0.3, z = -5.2, p < 0.001). Videos published during or after 2018 scored higher on Modified DISCERN (z = -3.2,p = 0.001) but not on GQS or JAMA. Video quality metrics such as total view count, likes, and comments, and channel subscriber count, did not correlate with higher video quality. However, amongst videos published by authoritative medical sources, total view count correlated positively with higher Modified DISCERN quality scores (p = 0.037). CONCLUSION: The overall quality and usefulness of YouTube videos on tonsillectomy is of low quality, but information published by authoritative medical sources score significantly higher. Clinicians should be mindful of increasing use of online information sources such as YouTube when counselling patients. Further research is needed in the medical community to create engaging, high-quality content to provide guidance for patients.