bims-librar Biomed News
on Biomedical librarianship
Issue of 2021‒01‒31
twenty-one papers selected by
Thomas Krichel
Open Library Society


  1. Nature. 2021 Jan;589(7843): 634
      
    Keywords:  Careers; Conservation biology; History
    DOI:  https://doi.org/10.1038/d41586-021-00179-9
  2. Syst Rev. 2021 Jan 26. 10(1): 39
      BACKGROUND: Literature searches underlie the foundations of systematic reviews and related review types. Yet, the literature searching component of systematic reviews and related review types is often poorly reported. Guidance for literature search reporting has been diverse, and, in many cases, does not offer enough detail to authors who need more specific information about reporting search methods and information sources in a clear, reproducible way. This document presents the PRISMA-S (Preferred Reporting Items for Systematic reviews and Meta-Analyses literature search extension) checklist, and explanation and elaboration.METHODS: The checklist was developed using a 3-stage Delphi survey process, followed by a consensus conference and public review process.
    RESULTS: The final checklist includes 16 reporting items, each of which is detailed with exemplar reporting and rationale.
    CONCLUSIONS: The intent of PRISMA-S is to complement the PRISMA Statement and its extensions by providing a checklist that could be used by interdisciplinary authors, editors, and peer reviewers to verify that each component of a search is completely reported and therefore reproducible.
    Keywords:  Information retrieval; Literature search; Reporting guidelines; Reproducibility; Search strategies; Systematic reviews
    DOI:  https://doi.org/10.1186/s13643-020-01542-z
  3. Syst Rev. 2021 Jan 23. 10(1): 38
      BACKGROUND: Systematic reviews involve searching multiple bibliographic databases to identify eligible studies. As this type of evidence synthesis is increasingly pursued, the use of various electronic platforms can help researchers improve the efficiency and quality of their research. We examined the accuracy and efficiency of commonly used electronic methods for flagging and removing duplicate references during this process.METHODS: A heterogeneous sample of references was obtained by conducting a similar topical search in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO databases. References were de-duplicated via manual abstraction to create a benchmark set. The default settings were then used in Ovid multifile search, EndNote desktop, Mendeley, Zotero, Covidence, and Rayyan to de-duplicate the sample of references independently. Using the benchmark set as reference, the number of false-negative and false-positive duplicate references for each method was identified, and accuracy, sensitivity, and specificity were determined.
    RESULTS: We found that the most accurate methods for identifying duplicate references were Ovid, Covidence, and Rayyan. Ovid and Covidence possessed the highest specificity for identifying duplicate references, while Rayyan demonstrated the highest sensitivity.
    CONCLUSION: This study reveals the strengths and weaknesses of commonly used de-duplication methods and provides strategies for improving their performance to avoid unintentionally removing eligible studies and introducing bias into systematic reviews. Along with availability, ease-of-use, functionality, and capability, these findings are important to consider when researchers are selecting database platforms and supporting software programs for conducting systematic reviews.
    Keywords:  Bibliographic databases; De-duplication; Duplicate references; Reference management software; Study design; Synthesis methods; Systematic review software; Systematic reviews
    DOI:  https://doi.org/10.1186/s13643-021-01583-y
  4. Ugeskr Laeger. 2021 Jan 11. pii: V09200645. [Epub ahead of print]183(2):
      In this review, we critically discuss the information distributed to patients and doctors regarding adverse drug reactions. A major concern is that frequencies reported in the summary of product characteristics are not adjusted for the occurrence of side effects observed in the placebo group. Previous research has found that the understanding of the health hazards related to pharmacotherapy can be significantly improved by providing information on the frequencies of adverse drug reactions in both the active- and the placebo group.
  5. Health Info Libr J. 2020 Dec;37 Suppl 1 84
      
    DOI:  https://doi.org/10.1111/hir.12355
  6. Health Info Libr J. 2020 Dec;37 Suppl 1 82-83
      
    DOI:  https://doi.org/10.1111/hir.12354
  7. J Med Internet Res. 2021 Jan 26. 23(1): e24594
      BACKGROUND: Interoperability and secondary use of data is a challenge in health care. Specifically, the reuse of clinical free text remains an unresolved problem. The Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) has become the universal language of health care and presents characteristics of a natural language. Its use to represent clinical free text could constitute a solution to improve interoperability.OBJECTIVE: Although the use of SNOMED and SNOMED CT has already been reviewed, its specific use in processing and representing unstructured data such as clinical free text has not. This review aims to better understand SNOMED CT's use for representing free text in medicine.
    METHODS: A scoping review was performed on the topic by searching MEDLINE, Embase, and Web of Science for publications featuring free-text processing and SNOMED CT. A recursive reference review was conducted to broaden the scope of research. The review covered the type of processed data, the targeted language, the goal of the terminology binding, the method used and, when appropriate, the specific software used.
    RESULTS: In total, 76 publications were selected for an extensive study. The language targeted by publications was 91% (n=69) English. The most frequent types of documents for which the terminology was used are complementary exam reports (n=18, 24%) and narrative notes (n=16, 21%). Mapping to SNOMED CT was the final goal of the research in 21% (n=16) of publications and a part of the final goal in 33% (n=25). The main objectives of mapping are information extraction (n=44, 39%), feature in a classification task (n=26, 23%), and data normalization (n=23, 20%). The method used was rule-based in 70% (n=53) of publications, hybrid in 11% (n=8), and machine learning in 5% (n=4). In total, 12 different software packages were used to map text to SNOMED CT concepts, the most frequent being Medtex, Mayo Clinic Vocabulary Server, and Medical Text Extraction Reasoning and Mapping System. Full terminology was used in 64% (n=49) of publications, whereas only a subset was used in 30% (n=23) of publications. Postcoordination was proposed in 17% (n=13) of publications, and only 5% (n=4) of publications specifically mentioned the use of the compositional grammar.
    CONCLUSIONS: SNOMED CT has been largely used to represent free-text data, most frequently with rule-based approaches, in English. However, currently, there is no easy solution for mapping free text to this terminology and to perform automatic postcoordination. Most solutions conceive SNOMED CT as a simple terminology rather than as a compositional bag of ontologies. Since 2012, the number of publications on this subject per year has decreased. However, the need for formal semantic representation of free text in health care is high, and automatic encoding into a compositional ontology could be a solution.
    Keywords:  SNOMED CT; natural language processing; scoping review; terminology
    DOI:  https://doi.org/10.2196/24594
  8. Bioinformatics. 2021 Jan 28. pii: btab042. [Epub ahead of print]
      SUMMARY: Named entity recognition (NER) is an important step in biomedical information extraction pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly accurate, and be robust towards variations in text genre and style. We present HunFlair, an NER tagger fulfilling these requirements. HunFlair is integrated into the widely-used NLP framework Flair, recognizes five biomedical entity types, reaches or overcomes state-of-the-art performance on a wide set of evaluation corpora, and is trained in a cross-corpus setting to avoid corpus-specific bias. Technically, it uses a character-level language model pretrained on roughly 24 million biomedical abstracts and three million full texts. It outperforms other off-the-shelf biomedical NER tools with an average gain of 7.26 pp over the next best tool in a cross-corpus setting and achieves on-par results with state-of-the-art research prototypes in in-corpus experiments. HunFlair can be installed with a single command and is applied with only four lines of code. Furthermore, it is accompanied by harmonized versions of 23 biomedical NER corpora.AVAILABILITY: HunFlair ist freely available through the Flair NLP framework (https://github.com/flairNLP/flair) under an MIT license and is compatible with all major operating systems.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btab042
  9. J Am Coll Emerg Physicians Open. 2021 Feb;2(1): e12356
      In the spring of 2020, emergency physicians found themselves in new, uncharted territory as there were few data available for understanding coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. In response, knowledge was being crowd sourced and shared across online platforms. The "wisdom of crowds" is an important vehicle for sharing information and expertise. In this article, we explore concepts related to the social psychology of group decisionmaking and knowledge translation. We then analyze a scenario in which the American College of Emergency Physicians (ACEP), a professional medical society, used the wisdom of crowds (via the EngagED platform) to disseminate clinically relevant information and create a useful resource called the "ACEP COVID-19 Field Guide." We also evaluate the crowd-sourced approach, content, and attributes of EngagED compared to other social media platforms. We conclude that professional organizations can play a more prominent role using the wisdom of crowds for augmenting pandemic response efforts.
    DOI:  https://doi.org/10.1002/emp2.12356
  10. J Med Internet Res. 2021 Jan 27. 23(1): e14088
      BACKGROUND: The internet has emerged as a main venue of health information delivery and health-related activities. However, few studies have examined how health literacy determines online health-related behavior.OBJECTIVE: The aim of this study was to investigate the current level of health-related information-seeking using the internet and how health literacy, access to technology, and sociodemographic characteristics impact health-related information-seeking behavior.
    METHODS: We conducted a cross-sectional study through a survey with Minnesotan adults (N=614) to examine their health literacy, access to technology, and health-related information-seeking internet use. We used multivariate regression analysis to assess the relationship between health-related information-seeking on the internet and health literacy and access to technology, controlling for sociodemographic characteristics.
    RESULTS: Better health literacy (β=.35, SE 0.12) and greater access to technological devices (eg, mobile phone and computer or tablet PC; β=.06, SE 0.19) were both associated with more health-related information-seeking behavior on the internet after adjusting for all other sociodemographic characteristics. Possession of a graduate degree (β=.28, SE 0.07), female gender (β=.15, SE 0.05), poor health (β=.22, SE 0.06), participation in social groups (β=.13, SE 0.05), and having an annual health exam (β=.35, SE 0.12) were all associated with online health-related information-seeking.
    CONCLUSIONS: Our findings indicate that access to online health-related information is not uniformly distributed throughout the population, which may exacerbate disparities in health and health care. Research, policy, and practice attention are needed to address the disparities in access to health information as well as to ensure the quality of the information and improve health literacy.
    Keywords:  access; digital divide; health literacy; internet; technology
    DOI:  https://doi.org/10.2196/14088
  11. BMC Med Inform Decis Mak. 2021 Jan 26. 21(1): 27
      BACKGROUND: Prescription medication (PM) misuse/abuse has emerged as a national crisis in the United States, and social media has been suggested as a potential resource for performing active monitoring. However, automating a social media-based monitoring system is challenging-requiring advanced natural language processing (NLP) and machine learning methods. In this paper, we describe the development and evaluation of automatic text classification models for detecting self-reports of PM abuse from Twitter.METHODS: We experimented with state-of-the-art bi-directional transformer-based language models, which utilize tweet-level representations that enable transfer learning (e.g., BERT, RoBERTa, XLNet, AlBERT, and DistilBERT), proposed fusion-based approaches, and compared the developed models with several traditional machine learning, including deep learning, approaches. Using a public dataset, we evaluated the performances of the classifiers on their abilities to classify the non-majority "abuse/misuse" class.
    RESULTS: Our proposed fusion-based model performs significantly better than the best traditional model (F1-score [95% CI]: 0.67 [0.64-0.69] vs. 0.45 [0.42-0.48]). We illustrate, via experimentation using varying training set sizes, that the transformer-based models are more stable and require less annotated data compared to the other models. The significant improvements achieved by our best-performing classification model over past approaches makes it suitable for automated continuous monitoring of nonmedical PM use from Twitter.
    CONCLUSIONS: BERT, BERT-like and fusion-based models outperform traditional machine learning and deep learning models, achieving substantial improvements over many years of past research on the topic of prescription medication misuse/abuse classification from social media, which had been shown to be a complex task due to the unique ways in which information about nonmedical use is presented. Several challenges associated with the lack of context and the nature of social media language need to be overcome to further improve BERT and BERT-like models. These experimental driven challenges are represented as potential future research directions.
    Keywords:  Machine learning; Natural language processing; Prescription medication misuse; Social media
    DOI:  https://doi.org/10.1186/s12911-021-01394-0
  12. Am J Med Genet C Semin Med Genet. 2021 Jan 27.
      Parents use the internet to connect with their peers and access information about a multitude of health topics, including newborn screening (NBS). As the NBS system evolves, education about NBS must be evaluated and updated to remain accessible and beneficial to parents. In this article, we aim to describe parents' current NBS educational needs and highlight areas to improve newborn screening education by detailing an analysis of NBS posts on an online parenting discussion platform. We analyzed a total of 317 discussion posts on BabyCenter®, finding that parents had questions about and desired support around many aspects of NBS including processes, results, and follow-up. As a result of this analysis, three recommendations to improve NBS education were developed. Through collaboration and by leveraging technology, we can provide parents with accessible, timely, and desired NBS informational and social support.
    Keywords:  health information; internet; newborn screening; online discussion boards; parent education
    DOI:  https://doi.org/10.1002/ajmg.c.31884
  13. J Cancer Educ. 2021 Jan 26.
      The aim of this study is to assess the Internet usage pattern amongst glioma patients and to characterize its impact in their decision-making and clinical interactions. Glioma patients attending a tertiary cancer center between June and December 2019 were invited to participate in this study. A 26-item survey consisting of closed and open-ended questions was distributed with a unique identifier. Quantitative data were analyzed with descriptive statistics using SPSS Statistical package, and qualitative data with grounded theory approach. Thirty-two patients completed the survey. Demographics varied in age, time since diagnosis, glioma type, and level of education. Eighty-one percent were identified as "Internet users" who sought online glioma information. Google was the most popular search engine (96%), with "glioma" being the most frequent search term. The selection of websites often relied on perceived credibility and top search hits. The most searched topic was prognosis (73%). The majority of patients found that online information was easy to understand, and this did not vary significantly amongst age groups. Website quality was always assessed by 60% of patients. Only 62% patients found the Internet a useful resource, and 70% patients found it facilitated their understanding. Most patients discussed their Internet findings with a physician, largely regarding concerns about reliability. There is variable glioma information available online. Patients with glioma use the Internet as a resource, with variable impact on their interactions and decision-making. This information can be used by physicians, educators, and website developers to support glioma patients' needs.
    Keywords:  Glioma; Internet information; Online resources; Patient education; Web resources
    DOI:  https://doi.org/10.1007/s13187-021-01960-0
  14. Ann Glob Health. 2021 Jan 06. 87(1): 6
      Background: Occupational Safety and Health (OSH) professionals must base their advice and interventions on evidence from science, in balance with their expertise, and with workers' and other stakeholders' values and preferences. Evidence-based professional practice is one of the remedies against misinformation creating confusion and distrust in the society.Objectives: To present, for OSH professionals, an overview and critical considerations about concepts, strategies, and tools needed for an accurate search for evidence-based information.
    Methods: Information sources have been collected and discussed as a base for a documented vision on knowledge questions, online information sources, search engines, databases, and tools.
    Results: Every search should start with a carefully phrased question. To help finding a reliable answer, potential evidence-based online sources are presented. Systematic reviews and original scientific articles are regarded as primary sources. Secondary and tertiary sources are discussed, such as practice guidelines, point-of-care summaries, advisory reports, quality websites or apps, Wikipedia, quality videos, and e-lessons. To find sources, adequate use of search engines and databases is required. Examples are discussed briefly, such as PubMed/MEDLINE, Virtual Health Library, NICE, Cochrane Library, Cochrane Work, Google (Scholar), and YouTube.
    Conclusions: Evidence-based practice in OSH must be stimulated, relying mainly on trusted online sources. The breadth of appropriate information sources is wider than described in most publications. Search engines facilitate the finding of quality reports, videos, e-courses, and websites. Such sources can be explored by well-trained professionals to complement the use of scientific articles, reviews, point-of-care summaries, and guidelines. Adequate use of online information sources requires awareness, motivation, and skills in professionals and educators. To date, the quality of skills in searching is low, thus a more adequate education is crucial. The quality of sources, search engines, and databases will be considered more thoroughly in another study. International collaboration is profitable and needs new drivers.
    DOI:  https://doi.org/10.5334/aogh.3131
  15. BMC Med Inform Decis Mak. 2021 Jan 28. 21(1): 31
      BACKGROUND: The Elderly and their caregivers need credible health information to manage elderly chronic diseases and help them to be involved in health decision making. In this regard, health websites are considered as a potential source of information for elderlies as well as their caregivers. Nevertheless, the credibility of these websites has not been identified yet. Thus, this study aimed to evaluate the credibility of the health websites on the most prevalent chronic diseases of the elderly.METHODS: The terms "Chronic obstructive pulmonary disease", "Alzheimer's", "Ischemic heart disease", and "Stroke" were searched using the three popular search engines. A total of 216 unique websites were eligible for evaluation. The study was carried out using the HONcode of conduct. The chi-square test was carried out to determine the difference between conforming and nonconforming websites with HONcode principles and website categories.
    RESULTS: The findings showed that half of the evaluated websites had fully considered the HONcode principles. Furthermore, there was a significant difference between websites category and compliance with HONcode principles (p value < .05).
    CONCLUSION: Regarding the poor credibility of most prevalent elderly diseases' websites, the potential online health information users should be aware of the low credibility of such websites, which may seriously threaten their health. Furthermore, educating the elderly and their caregivers to evaluate the credibility of websites by the use of popular tools such as HONcode of conducts before utilizing their information seems to be necessary.
    Keywords:  E-health; Geriatric diseases; Health information; Health portals; Health websites; Patient education; Website evaluation
    DOI:  https://doi.org/10.1186/s12911-021-01397-x
  16. J Am Acad Orthop Surg Glob Res Rev. 2021 Jan 22. 5(1): 1-7
      INTRODUCTION: This study aimed to assess the quality of online resources pertaining to cannabidiol (CBD) for the nonoperative management of hip and knee arthritis.METHODS: Websites were identified on the three most popular global search engines using terms relevant to CBD, hip or knee pain, and arthritis. Websites were scored based on a 25-point scale regarding diagnosis, evaluation, and treatment of hip and knee pathologies.
    RESULTS: The initial search yielded 287 results, and 94 websites were analyzed after meeting inclusion criteria. The average Flesch-Kincaid reading level was 48, corresponding to a college education level. Mean website score was poor at 7.46 (SD 3.51) of 25 (29.8%). Websites published by physicians had statistically higher scores (P = 0.03).
    CONCLUSIONS: Many online resources regarding CBD use for hip and knee arthritis are available; however, the readability is more advanced than recommended by the National Institutes of Health. Very few resources are sponsored by physicians or professional organizations, and many are overtly sales oriented. Patients should be counseled that the information available online on this topic is generally unreliable. Surgeons and professional health organizations should play a stronger role in providing balanced resources to patients regarding CBD use for hip and knee arthritis.
    DOI:  https://doi.org/e20.00241
  17. Clin Neurol Neurosurg. 2021 Jan 12. pii: S0303-8467(21)00010-X. [Epub ahead of print]202 106483
      OBJECTIVES: Now that the internet is more accessible to an increasing number of populations worldwide, many rely on the internet for their information about their daily lives. This includes people concerned about their health to students to sometimes also doctors. Since YouTube is the second most visited website, our aim was to evaluate the content-quality of YouTube videos relating to meningitis.METHODS: We chose the first 30 videos for four different search phrases: meningitis, bacterial meningitis, viral meningitis, fungal meningitis and meningitis signs. The validated DISCERN scoring criteria was used to assess the videos by two raters independently. Qualitative data, quantitative data and the source of upload of each video were analyzed for video quality and audience engagement.
    RESULTS: Out of 150 videos, 84 videos met the inclusion criteria. The mean DISCERN score was 34.6 ± 9.76 (out of a total 75), which indicates that the quality of YouTube videos on meningitis is poor. There is an excellent reliability between the two raters. Videos had a higher audience engagement via a greater number of daily views and comments when they included the definition, symptoms, prognosis, animation, diagrams, and an anatomical explanation of the meninges (P < 0.0001 for all).
    CONCLUSION: The quality of YouTube videos on meningitis is poor, however, we have listed the videos which may be most effective for patient education for reference. Our quality and engagement analysis may help content creators make better health content on meningitis.
    Keywords:  DISCERN scores; Health information; Internet; Meningitis; YouTube
    DOI:  https://doi.org/10.1016/j.clineuro.2021.106483
  18. Health Commun. 2021 Jan 25. 1-8
      This study examined how frequently men who have sex with men (MSM) used a selection of sources, including news media, social media, health organizations, and dating/hookup apps, for HIV information. Additionally, the study explored the extent to which MSM's efficacy beliefs about pre-exposure prophylaxis (PrEP) and perceptions of condom importance could be predicted by the sources they used. A sample of MSM (N= 969) were surveyed online. Results showed that respondents obtained information about HIV most often from HIV organizations, LGBT organizations, and dating/hookup apps, particularly the apps Growlr, Scruff, and Grindr. Use of the app Scruff was the strongest source-based predictor of beliefs about both PrEP and condoms. Implications for health promotion are discussed.
    DOI:  https://doi.org/10.1080/10410236.2021.1876323
  19. J Am Med Inform Assoc. 2021 Jan 26. pii: ocaa340. [Epub ahead of print]
      OBJECTIVE: Data quality (DQ) must be consistently defined in context. The attributes, metadata, and context of longitudinal real-world data (RWD) have not been formalized for quality improvement across the data production and curation life cycle. We sought to complete a literature review on DQ assessment frameworks, indicators and tools for research, public health, service, and quality improvement across the data life cycle.MATERIALS AND METHODS: The review followed PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Databases from health, physical and social sciences were used: Cinahl, Embase, Scopus, ProQuest, Emcare, PsycINFO, Compendex, and Inspec. Embase was used instead of PubMed (an interface to search MEDLINE) because it includes all MeSH (Medical Subject Headings) terms used and journals in MEDLINE as well as additional unique journals and conference abstracts. A combined data life cycle and quality framework guided the search of published and gray literature for DQ frameworks, indicators, and tools. At least 2 authors independently identified articles for inclusion and extracted and categorized DQ concepts and constructs. All authors discussed findings iteratively until consensus was reached.
    RESULTS: The 120 included articles yielded concepts related to contextual (data source, custodian, and user) and technical (interoperability) factors across the data life cycle. Contextual DQ subcategories included relevance, usability, accessibility, timeliness, and trust. Well-tested computable DQ indicators and assessment tools were also found.
    CONCLUSIONS: A DQ assessment framework that covers intrinsic, technical, and contextual categories across the data life cycle enables assessment and management of RWD repositories to ensure fitness for purpose. Balancing security, privacy, and FAIR principles requires trust and reciprocity, transparent governance, and organizational cultures that value good documentation.
    Keywords:  DQ assessment tools; DQ indicators; DQ measures; data custodianship; data quality; data stewardship; literature review
    DOI:  https://doi.org/10.1093/jamia/ocaa340