bims-librar Biomed News
on Biomedical librarianship
Issue of 2021‒04‒25
twenty papers selected by
Thomas Krichel
Open Library Society

  1. Syst Rev. 2021 Apr 19. 10(1): 115
      BACKGROUND: Appropriate search strategies are essential to ensure the integrity and reproducibility of systematic and scoping reviews, as researchers seek to capture as many relevant resources as possible. In the case of Indigenous health reviews, researchers are met with the special challenge of creating a search strategy that can encompass this large, diverse population group with no universally agreed upon identification criteria.MAIN BODY: With an aim to promote improved review methodologies that uphold standards of justice, autonomy, and equity for Indigenous peoples and other heterogeneous populations, we describe critical gaps and approaches to close them. We report organizational and transparency issues around how Indigenous populations are indexed in several major databases, and draw on examples of published reviews and protocols to demonstrate the challenges inherent to creating a comprehensive search strategy.
    CONCLUSIONS: The conduct and communication of results from health literature research on global Indigenous populations are compromised by challenges of methodology that are rooted in the complexities inherent to defining Indigenous peoples. These challenges must be urgently addressed to improve this important field of inquiry moving forward.
    Keywords:  Academic databases; Ethics; Indigenous populations; Methods; Population health; Scoping reviews; Search terms; Social justice; Subject headings; Systematic reviews
  2. ATS Sch. 2020 Jun 29. 1(2): 186-193
      The emergence and worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused major disruptions to the healthcare system and medical education. In response, the scientific community has been acquiring, releasing, and publishing data at a remarkable pace. At the same time, medical practitioners are taxed with greater professional duties than ever before, making it challenging to stay current with the influx of medical literature.To address the above mismatch between data release and provider capacity and to support our colleagues, physicians at the Massachusetts General Hospital have engaged in an electronic collaborative effort focused on rapid literature appraisal and dissemination regarding SARS-CoV-2 with a focus on critical care.
    Members of the Division of Pulmonary and Critical Care, the Division of Cardiology, and the Department of Medicine at Massachusetts General Hospital established the Fast Literature Assessment and Review (FLARE) team. This group rapidly compiles, appraises, and synthesizes literature regarding SARS-CoV-2 as it pertains to critical care, relevant clinical questions, and anecdotal reports. Daily, FLARE produces and disseminates highly curated scientific reviews and opinion pieces, which are distributed to readers using an online newsletter platform.
    Interest in our work has escalated rapidly. FLARE was quickly shared with colleagues outside our division, and, in a short time, our audience has grown to include more than 4,000 readers across the globe.
    Creating a collaborative group with a variety of expertise represents a feasible and acceptable way of rapidly appraising, synthesizing, and communicating scientific evidence directly to frontline clinicians in this time of great need.
    Keywords:  COVID-19; coronavirus disease; critical care; review literature as topic
  3. Front Res Metr Anal. 2020 ;5 600382
      Subject categories of scholarly papers generally refer to the knowledge domain(s) to which the papers belong, examples being computer science or physics. Subject category classification is a prerequisite for bibliometric studies, organizing scientific publications for domain knowledge extraction, and facilitating faceted searches for digital library search engines. Unfortunately, many academic papers do not have such information as part of their metadata. Most existing methods for solving this task focus on unsupervised learning that often relies on citation networks. However, a complete list of papers citing the current paper may not be readily available. In particular, new papers that have few or no citations cannot be classified using such methods. Here, we propose a deep attentive neural network (DANN) that classifies scholarly papers using only their abstracts. The network is trained using nine million abstracts from Web of Science (WoS). We also use the WoS schema that covers 104 subject categories. The proposed network consists of two bi-directional recurrent neural networks followed by an attention layer. We compare our model against baselines by varying the architecture and text representation. Our best model achieves micro- F 1 measure of 0.76 with F 1 of individual subject categories ranging from 0.50 to 0.95. The results showed the importance of retraining word embedding models to maximize the vocabulary overlap and the effectiveness of the attention mechanism. The combination of word vectors with TFIDF outperforms character and sentence level embedding models. We discuss imbalanced samples and overlapping categories and suggest possible strategies for mitigation. We also determine the subject category distribution in CiteSeerX by classifying a random sample of one million academic papers.
    Keywords:  citeseerx; digital library; neural networks; scientific papers; subject category classification; text classification; text mining
  4. Artif Intell Med. 2021 04;pii: S0933-3657(21)00046-4. [Epub ahead of print]114 102053
      MOTIVATION: In the age of big data, the amount of scientific information available online dwarfs the ability of current tools to support researchers in locating and securing access to the necessary materials. Well-structured open data and the smart systems that make the appropriate use of it are invaluable and can help health researchers and professionals to find the appropriate information by, e.g., configuring the monitoring of information or refining a specific query on a disease.METHODS: We present an automated text classifier approach based on the MEDLINE/MeSH thesaurus, trained on the manual annotation of more than 26 million expert-annotated scientific abstracts. The classifier was developed tailor-fit to the public health and health research domain experts, in the light of their specific challenges and needs. We have applied the proposed methodology on three specific health domains: the Coronavirus, Mental Health and Diabetes, considering the pertinence of the first, and the known relations with the other two health topics.
    RESULTS: A classifier is trained on the MEDLINE dataset that can automatically annotate text, such as scientific articles, news articles or medical reports with relevant concepts from the MeSH thesaurus.
    CONCLUSIONS: The proposed text classifier shows promising results in the evaluation of health-related news. The application of the developed classifier enables the exploration of news and extraction of health-related insights, based on the MeSH thesaurus, through a similar workflow as in the usage of PubMed, with which most health researchers are familiar.
    Keywords:  Big data; COVID-19; Diabetes; Healthcare; MEDLINE; MeSH headings; Mental health; PubMed; Public health; Semantic technologies; Text mining
  5. Methods Mol Biol. 2021 ;2249 405-428
      The number of studies published in the biomedical literature has dramatically increased over the last few decades. This massive proliferation of literature makes clinical medicine increasingly complex, and information from multiple studies is often needed to inform a particular clinical decision. However, available studies often vary in their design, methodological quality, and population studied, and may define the research question of interest quite differently. This can make it challenging to synthesize the conclusions of multiple studies. In addition, since even highly cited trials may be challenged over time, clinical decision-making requires ongoing reconciliation of studies which provide different answers to the same question. Because it is often impractical for readers to track down and review all the primary studies, systematic reviews and meta-analyses are an important source of evidence on the diagnosis, prognosis and treatment of any given disease. This chapter summarizes methods for conducting and reading systematic reviews and meta-analyses, as well as describes potential advantages and disadvantages of these publications.
    Keywords:  Forest plot; Literature synthesis; Meta-analysis; Random effects; Systematic review
  6. Proc Natl Acad Sci U S A. 2021 Apr 13. pii: e1912436117. [Epub ahead of print]118(15):
      Science literacy is often held up as crucial for avoiding science-related misinformation and enabling more informed individual and collective decision-making. But research has not yet examined whether science literacy actually enables this, nor what skills it would need to encompass to do so. In this report, we address three questions to outline what it should mean to be science literate in today's world: 1) How should we conceptualize science literacy? 2) How can we achieve this science literacy? and 3) What can we expect science literacy's most important outcomes to be? If science literacy is to truly enable people to become and stay informed (and avoid being misinformed) on complex science issues, it requires skills that span the "lifecycle" of science information. This includes how the scientific community produces science information, how media repackage and share the information, and how individuals encounter and form opinions on this information. Science literacy, then, is best conceptualized as encompassing three dimensions of literacy spanning the lifecycle: Civic science literacy, digital media science literacy, and cognitive science literacy. Achieving such science literacy, particularly for adults, poses many challenges and will likely require a structural perspective. Digital divides, in particular, are a major structural barrier, and community literacy and building science literacy into media and science communication are promising opportunities. We end with a discussion of what some of the beneficial outcomes could be-and, as importantly, will likely not be-of science literacy that furthers informed and critical engagement with science in democratic society.
    Keywords:  digital literacy; misinformation; science communication; science knowledge; science literacy
  7. Front Res Metr Anal. 2019 ;4 2
    Keywords:  academic search; citation content analysis; computational linguistics; natural language processing; scientific papers; scientometrics; text mining
  8. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2021 Apr 21.
      Evidence-based health information is intended to empower people to make informed health decisions and include their personal goals and expectations by providing them with neutral and understandable content. To achieve this, a number of requirements must be followed in the production of health information, which are described in this article. These include, among other things, systematic research, a reasoned selection of appropriate evidence, and consideration of current evidence to communicate numbers, risks, and probabilities. Implementation must also take into account the issues, competencies and usage patterns of the groups for which the information is intended. A number of German-language information services demonstrate that implementation of these requirements is feasible for the general public.
    Keywords:  Empowerment; Health information; Health literacy; Informed decision; Quality
  9. PeerJ Comput Sci. 2020 ;6 e254
      Integrating data from multiple heterogeneous data sources entails dealing with data distributed among heterogeneous information sources, which can be structured, semi-structured or unstructured, and providing the user with a unified view of these data. Thus, in general, gathering information is challenging, and one of the main reasons is that data sources are designed to support specific applications. Very often their structure is unknown to the large part of users. Moreover, the stored data is often redundant, mixed with information only needed to support enterprise processes, and incomplete with respect to the business domain. Collecting, integrating, reconciling and efficiently extracting information from heterogeneous and autonomous data sources is regarded as a major challenge. In this paper, we present an approach for the semantic integration of heterogeneous data sources, DIF (Data Integration Framework), and a software prototype to support all aspects of a complex data integration process. The proposed approach is an ontology-based generalization of both Global-as-View and Local-as-View approaches. In particular, to overcome problems due to semantic heterogeneity and to support interoperability with external systems, ontologies are used as a conceptual schema to represent both data sources to be integrated and the global view.
    Keywords:  Data integration; Heterogeneous data sources; Ontologies; Semantic integration
  10. J Hand Microsurg. 2021 Apr;13(2): 65-68
      Introduction  The use of the internet for health-related information continues to increase. Because of its decentralized structure, information contained within the World Wide Web is not regulated. The purpose of the present study is to evaluate the type and quality of information on the internet regarding Kienböck's disease. We hypothesized that the information available on the World Wide Web would be of good informational value. Materials and Methods  The search phrase "Kienböck's disease" was entered into the five most commonly used internet search engines. The top 49 nonsponsored Web sites identified by each search engine were collected. Each unique Web site was evaluated for authorship and content, and an informational score ranging from 0 to 100 points was assigned. Each site was reviewed by two fellowship-trained hand surgeons. Results  The informational mean score for the sites was 45.5 out of a maximum of 100 points. Thirty-one (63%) of the Web sites evaluated were authored by an academic institution or a physician. Twelve (24%) of the sites were commercial sites or sold commercial products. The remaining 6 Web sites (12%) were noninformational, provided unconventional information, or had lay authorship. The average informational score on the academic or physician authored Web sites was 54 out of 100 points, compared with 38 out of 100 for the remainder of the sites. This difference was statistically significant. Conclusion  While the majority of the Web sites evaluated were authored by academic institutions or physicians, the informational value contained within is of limited completeness. More than one quarter of the Web sites were commercial in nature. There remains significant room for improvement in the completeness of information available for common hand conditions in the internet.
    Keywords:  Kienböck; content; information; internet; quality
  11. Urology. 2021 Apr 20. pii: S0090-4295(21)00330-7. [Epub ahead of print]
      OBJECTIVE: To compare the quality of robotic prostatectomy surgical videos on the popular website YouTube with more curated, professional sources using the Global Evaluative Assessment of Robotic Skills (GEARS) criteria.METHODS: A search was performed on YouTube for robotic prostatectomy. Results were sorted by views and the first ten that met inclusion criteria were selected for review. To represent curated sources five robotic prostatectomy videos were selected from the DaVinci Surgery Community (DVS) video repository and the AUA Surgical Video Library in order of publishing from present to past. Videos were edited to be deidentified. The videos were reviewed blindly in parallel and graded using the GEARS criteria. Concordance among reviewers was measured using Chronbach's alpha. Comparisons between groups were made using student t-test.
    RESULTS: There was a high level of reliability of overall GEARS scores between reviewers for each video (α = 0.843). There was no significant difference between overall GEARS scores between the YouTube videos (mean 24.8, SDEV 1.85) and the AUA group (mean 24.3, SDEV 6.18) (p = 0.78). YouTube videos scored higher than the DVS videos (mean 22.1, SDEV 2.34) (p 0.03).
    CONCLUSIONS: Despite concerns about the quality of surgical videos on YouTube for education, the most viewed surgical videos for robot assisted laparoscopic prostatectomy score as well or better than more curated sources using the GEARS criteria. This may represent selection via crowd sourcing of the best videos amongst a much larger overall quantity.
    Keywords:  Robotic surgery; prostatectomy; social media; surgical education
  12. Health Inf Manag. 2021 Apr 04. 1833358321992683
      BACKGROUND: Social media is used in health communication by individuals, health professionals, disease centres and other health regulatory bodies. However, varying degrees of information quality are churned out daily on social media. This review is concerned with the quality of Social Media Health Information (SMHI).OBJECTIVE: The review sought to understand how SMHI quality issues have been framed and addressed in the literature. Health topics, users and social media platforms that have raised health information quality concerns are reviewed. The review also looked at the suitability of existing criteria and instruments used in evaluating SMHI and identified gaps for future research.
    METHOD: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the forward chaining strategy were used in the document search. Data were sourced according to inclusion criteria from five academic databases, namely Scopus, Web of Science, Cochrane Library, PubMed and MEDLINE.
    RESULTS: A total of 93 articles published between 2000 and 2019 were used in the review. The review revealed a worrying trend of health content and communication on social media, especially of cancer, dental care and diabetes information on YouTube. The review further discovered that the Journal of the American Medical Association, the DISCERN and the Health on the Net Foundation, which were designed before the advent of social media, continue to be used as quality evaluation instruments for SMHI, even though technical and user characteristics of social media differ from traditional portals such as websites.
    CONCLUSION: The study synthesises varied opinions on SMHI quality in the literature and recommends that future research proposes quality evaluation criteria and instruments specifically for SMHI.
    Keywords:  Social Media Health Information; consumer health information; data quality; e-health; health communication; misinformation; online health information quality; quality indicators; review; social media; social media health communication; systematic
  13. J Prev Interv Community. 2021 Apr 19. 1-9
      The uncertain and unprecedented nature of the COVID-19 pandemic is anxiety-provoking and some people are seeking information about this anxiety online. The purpose of this study was to assess the readability levels of online articles related to anxiety and COVID-19. The first 50 English language URLs to appear in a Google search in July 2020 were assessed for readability using A five-measure panel consisting of the Flesch-Kincaid Grade Level (FKGL), Gunning Fog Index, Coleman-Liau Index (CLI), the Simple Measure of Gobbledygook (SMOG) Grade Level, and Flesch-Kincaid Reading Ease (FRE) was used, and grade level scores were recoded as easy, average, and difficult readability. Websites were grouped as commercial vs. noncommercial sources bases on the URL. Of the 50 articles evaluated, the majority were found to be written at a difficult (>10th grade) reading level with four of the five measures employed which is well above the 7-8th grade reading level abilities of most Americans. Given the importance of access to mental health information during the pandemic, it is crucial that the resources available to the general public are written at a reading level that is comprehensible to ensure they are understood.
    Keywords:  Anxiety; COVID-19 pandemic; health information; mental health; readability; seeking
  14. Can J Gastroenterol Hepatol. 2021 ;2021 7532905
      Introduction: Due to the ubiquity and ease of access of Internet, patients are able to access online health information more easily than ever. The American Medical Association recommends that patient education materials be targeted at or below the 6th grade level in order to accommodate a wider audience. In this study, we evaluate the difficulty of educational materials pertaining to common GI procedures; we analyze on the readability of online education materials for colonoscopy, flexible sigmoidoscopy, and esophagogastroduodenoscopy (EGD).Methods: Google search was performed using keywords of "colonoscopy," "sigmoidoscopy," and "EGD" with "patient information" at the end of each search term. The texts from a total of 18 studies, 6 for each of the procedures, were then saved. Each study was also subdivided into "Introduction," "Preparation," "Complications," and if available, "Alternatives." Furthermore, medical terminology that was properly explained, proper nouns, medication names, and other copyright text were removed in order to prevent inflation of the difficulty. Five validated readability tests were used to analyze each study and subsections: Coleman-Liau, New Dale-Chall, Flesch-Kincaid, Gunning Fog, SMOG.
    Results: Studies on colonoscopy, flexible sigmoidoscopy, and EGD had median readability grades of 9.7, 10.2, and 11.0, respectively. Analysis of the subsections revealed that the "Alternative" subsection was the most difficult to comprehend with a readability score of 11.4, whereas the "Introduction" subsection was the easiest to comprehend with a readability score of 9.5.
    Conclusion: Despite modifications to the studies that improved the readability scores, patient education materials were still significantly above the recommended 6th grade level across all websites. This study emphasizes that clear and simple language is warranted in order to create information that is suitable for most patients.
  15. Int J Med Inform. 2021 Apr 15. pii: S1386-5056(21)00091-5. [Epub ahead of print]150 104465
      BACKGROUND: The plethora of information in the contemporary digital age is enormous and beyond the capability of the average person to process all the information received. During the COVID-19 pandemic outbreak, huge amount of information is increasingly available in digital information sources and overwhelms the average person. The purpose of this research was to investigate public's information seeking behavior on COVID-19 in Greece.METHOD: The study was conducted through a web-based survey, facilitated by the use of questionnaire posted on the Google Forms platform. The questionnaire consisted of closed-ended, 7-point Likert scale questions and multiple choice questions and was distributed to all over Greek Regions to almost 3.000 recipients, during the implementation of restrictive measures against the COVID-19 outbreak in Spring 2020. The data collected were subjected to a descriptive statistical analysis. The median was used to present the results. In order to perform analysis between genders, as well as age groups, the non-parametric criteria Mann-Whitney U and Kruskal-Wallis were applied to determine the existence of differences in participants' beliefs.
    RESULTS: Responses by 776 individuals were obtained. Individuals dedicated up to 2 h per day to be informed on COVID-19. Television, electronic press and news websites were reported by the participants as more reliable than social media, in obtaining information on COVID-19. Respondents paid attention to official sources of information (Ministry of Health, Civil Protection etc.). Family and friends played an additional role in the participants' information on COVID-19, while the personal doctor, other health workers and pharmacists did not appear to be most preferred sources of information on COVID-19. Participants' most common information seeking strategy in digital environment was keyword searching. Unreliable information, fake news and information overload were the most common difficulties that the participants encountered seeking information on COVID-19. The respondents' views seemed to differ significantly among age groups. The older the participants, the more often they were informed by television (p < 0.001) and the less often by the internet (p < 0.001). Females appear to use more frequently internet (p < 0.001) and social media (p = 0.001) out of habit and visit more often the Ministry of Health (p < 0.001) and the Civil Protection (p=0.005) websites, compared to males. Most of the participants seemed to worry about the fake news phenomenon and agreed that fake news on COVID-19 is being spread in the media and especially social networks.
    CONCLUSION: The study revealed that, during the COVID-19 pandemic in Greece, participants obtained information about the disease mainly by television, electronic press and news websites. On the contrary, the limited use of social media demonstrates the participants awareness of the spread of fake news on social media. This observed information seeking behavior might has contributed to individuals' acceptance of the necessary behavioral changes that had led to the Greek success story in preventing spread of the disease.
    Keywords:  COVID-19; Fake news; Information seeking behavior; Information sources; Misinformation; Pandemic
  16. Sci Data. 2021 Apr 20. 8(1): 113
      ODFM is a data management system that integrates comprehensive omics information for microorganisms associated with various fermented foods, additive ingredients, and seasonings (e.g. kimchi, Korean fermented vegetables, fermented seafood, solar salt, soybean paste, vinegar, beer, cheese, sake, and yogurt). The ODFM archives genome, metagenome, metataxonome, and (meta)transcriptome sequences of fermented food-associated bacteria, archaea, eukaryotic microorganisms, and viruses; 131 bacterial, 38 archaeal, and 28 eukaryotic genomes are now available to users. The ODFM provides both the Basic Local Alignment Search Tool search-based local alignment function as well as average nucleotide identity-based genetic relatedness measurement, enabling gene diversity and taxonomic analyses of an input query against the database. Genome sequences and annotation results of microorganisms are directly downloadable, and the microbial strains registered in the archive library will be available from our culture collection of fermented food-associated microorganisms. The ODFM is a comprehensive database that covers the genomes of an entire microbiome within a specific food ecosystem, providing basic information to evaluate microbial isolates as candidate fermentation starters for fermented food production.
  17. J Med Internet Res. 2021 Apr 17.
      BACKGROUND: The rapid outbreak of coronavirus disease 2019 (COVID-19) around the world has adversely affected the mental health of the public. The prevalence of anxiety among the public increased dramatically during the COVID-19 pandemic. However, there are few studies on the effects of positive psychological responses and information seeking behaviors on WeChat users' anxiety during the COVID-19 pandemic.OBJECTIVE: This study evaluated the prevalence of anxiety and its associated factors among the WeChat users in mainland China during the early stages of the COVID-19 pandemic.
    METHODS: From February 10 to February 24, 2020, a nationwide cross-sectional survey was carried out online using convenience sampling in mainland China. Levels of anxiety, positive psychological responses, and information seeking behaviors were measured. Questionnaires were distributed to WeChat users via the WeChat smart phone platform. Chi-square tests and multivariable logistic regression analyses were applied to examine the factors associated with anxiety.
    RESULTS: This study found that the prevalence of anxiety (GAD-7 score ≥7) among WeChat users in China was 446/2,483 (17.96%) during the early stages of the COVID-19 pandemic. Cannot stop searching for information on COVID-19, concerned about the COVID-19 pandemic, and spending more than 1 hour consuming information about the COVID-19 pandemic were observed to be associated with increased levels of anxiety according to the results of multivariable logistic regression. Additionally, participants who chose social media and commercial media as the primary sources of information about the COVID-19 pandemic were found more likely to report anxiety in this study. Conversely, it was observed that participants who were confident or rational about the COVID-19 pandemic were less likely to report anxiety.
    CONCLUSIONS: This study found that positive psychological responses and information seeking behaviors were closely associated with anxiety among WeChat users during the COVID-19 pandemic in China. It might be paramount to enhance mental well-being by helping people respond to the COVID-19 pandemic more rationally and positively in order to decrease symptoms of anxiety.
  18. PeerJ Comput Sci. 2021 ;7 e425
      The popularity of the internet, smartphones, and social networks has contributed to the proliferation of misleading information like fake news and fake reviews on news blogs, online newspapers, and e-commerce applications. Fake news has a worldwide impact and potential to change political scenarios, deceive people into increasing product sales, defaming politicians or celebrities, and misguiding visitors to stop visiting a place or country. Therefore, it is vital to find automatic methods to detect fake news online. In several past studies, the focus was the English language, but the resource-poor languages have been completely ignored because of the scarcity of labeled corpus. In this study, we investigate this issue in the Urdu language. Our contribution is threefold. First, we design an annotated corpus of Urdu news articles for the fake news detection tasks. Second, we explore three individual machine learning models to detect fake news. Third, we use five ensemble learning methods to ensemble the base-predictors' predictions to improve the fake news detection system's overall performance. Our experiment results on two Urdu news corpora show the superiority of ensemble models over individual machine learning models. Three performance metrics balanced accuracy, the area under the curve, and mean absolute error used to find that Ensemble Selection and Vote models outperform the other machine learning and ensemble learning models.
    Keywords:  Ensemble learning models; Machine learning methods; Social media; Urdu language