bims-librar Biomed news
on Biomedical librarianship
Issue of 2019‒03‒31
fourteen papers selected by
Thomas Krichel
Open Library Society


  1. Nature. 2019 Mar;567(7749): 564
    Dawson R.
      
    DOI:  https://doi.org/10.1038/d41586-019-00905-4
  2. Health Info Libr J. 2019 Mar 25.
    Ayiku L, Levay P, Hudson T, Craven J, Finnegan A, Adams R, Barrett E.
      BACKGROUND: The authors developed a validated geographic search filter to retrieve research about the United Kingdom (UK) from OVID Embase. It was created to be used alongside their previously published OVID MEDLINE UK filter in systematic literature searches for context-sensitive topics.OBJECTIVES: To develop a validated geographic search filter to retrieve research about the UK from OVID Embase.
    METHODS: The Embase UK filter was translated from the MEDLINE UK filter. A gold standard set of references was generated using the relative recall method. The set contained references to publications about the UK that had informed National Institute for Health and Care Excellence (NICE) guidance and it was used to validate the filter. Recall, precision and number-needed-to-read (NNR) were calculated using a case study.
    RESULTS: The validated Embase UK filter demonstrated 99.8% recall against the references with UK identifiers in the gold standard set. In the case study, the Embase UK filter demonstrated 98.5% recall, 7.6% precision and a NNR of 13.
    CONCLUSION: The Embase UK filter can be used alongside the MEDLINE UK filter. The filters have the potential to save time and associated resource costs when they are used for context-sensitive topics that require research about UK settings.
    Keywords:  Embase; Great Britain; United Kingdom; database searching; information retrieval
    DOI:  https://doi.org/10.1111/hir.12252
  3. J Med Internet Res. 2019 Mar 27. 21(3): e10831
    Wong DK, Cheung MK.
      BACKGROUND: Previous studies have suggested that patients' online health information seeking affects their medical consultations and patient-doctor relationships. An up-to-date picture of patients' online health information-seeking behaviors can inform and prepare frontline health care professionals to collaborate, facilitate, or empower their patients to access and manage health information found online.OBJECTIVE: This study explores the prevalence, patterns, and predictors of online health information-seeking behaviors among primary care patients in Hong Kong, and the relations between online health information seeking and electronic health (eHealth) literacy.
    METHODS: Patients attending a university primary care clinic in Hong Kong were asked to complete a questionnaire survey on their demographic backgrounds; health status; frequency and pattern of online health information seeking; contents, sources, and reasons for online health information seeking; and their eHealth literacy. eHealth literacy was measured by the validated eHealth Literacy Scale (eHEALS). Regression analyses explored various demographic and behavioral predictors to online health information seeking, and predictors to eHealth literacy.
    RESULTS: In all, 97.32% (1162/1194) respondents used the internet, of which 87.44% (1016/1162) had used the internet to find health information. Most respondents (65.97%, 665/1008) searched once monthly or more. Few (26.88%, 271/1008) asked their doctor about health information found online, but most doctors (56.1%, 152/271) showed little or no interest at all. The most sought topic was symptom (81.59%, 829/1016), the top reason was noticing new symptoms or change in health (70.08%, 712/1016), the most popular source was online encyclopedia (69.98%, 711/1016), and the top reason for choosing a source was convenience (55.41%, 563/1016). Poisson regression analysis identified high eHEALS score, fair or poor self-rated health, having a chronic medical condition, and using the internet several times a day as significant predictors of online health information seeking. Multiple regression analysis identified lower age, better self-rated health, more frequent internet use, more frequent online health information seeking, and more types of health information sought as significant predictors to higher eHealth literacy.
    CONCLUSIONS: Online health information seeking is prevalent among primary care patients in Hong Kong, but only a minority shared the information with doctors. Websites were chosen more for convenience than for accuracy or authoritativeness. Doctors should recognize patients' online health information-seeking behavior, and facilitate and empower them to search for high-quality online health information.
    Keywords:  Hong Kong; eHealth literacy; online health information seeking; primary care
    DOI:  https://doi.org/10.2196/10831
  4. Women Birth. 2019 Mar 21. pii: S1871-5192(18)30620-6. [Epub ahead of print]
    Cannon S, Lastella M, Vincze L, Vandelanotte C, Hayman M.
      PROBLEM: Most pregnant women report using the internet to source health information during pregnancy. However, little is known about the information presented on the internet and whether it is consistent with current evidence-based guidelines.BACKGROUND: Pregnancy is considered a risk period for women as it is associated with poorer health behaviours including an inadequate diet, decreased physical activity and reduced sleep. As a result, pregnant women and their unborn child are at a greater risk of adverse health outcomes.
    AIM: The purpose of this study was to review pregnancy related information about nutrition, physical activity and sleep provided on Australian government and leading industry body websites, and to compare this information to current evidence-based guidelines.
    METHODS: A systematic online search was conducted to identify Australian Government, and leading industry websites that provided information on nutrition, physical activity, or sleep during pregnancy. The content of each website was reviewed and compared against current nutrition, physical activity and sleep guidelines.
    FINDINGS: 27 government and leading industry websites were included in this study. 18 websites included nutritional information, none of which aligned 100% with guidelines. Nine websites included physical activity information, only one of which was 100% in accordance with guidelines. Two websites included information on sleep during pregnancy, however neither were in accordance with guidelines.
    CONCLUSION: Women are accessing information via the internet that is not in accordance with current evidence-based guidelines. These results call to attention the need for government and leading industry websites to review and update their website information in accordance with current evidence-based guidelines.
    Keywords:  Exercise; Nutrition; Pregnancy; Recommendations; Sleep
    DOI:  https://doi.org/10.1016/j.wombi.2018.12.007
  5. Asian Pac J Cancer Prev. 2019 Mar 26. 20(3): 951-960
    G P, Lakshmanan L, Ramanathan L.
      Objective: In recent years, citation analysis tools provide many devices for finding or computing the citation score or impact factor for journals. It is important for the researchers to identify good journals for collecting research ideas discussed. A journal with a good impact factor value is preferably referred to by many researchers. In this research work, the author proposes a system for ranking journals on the basis of ideas and results cited in other papers. Methods: The work involves the cited content extractor for extracting the descriptive features mentioned about the cited paper. The cited content refers to the content in the article written by a citing paper and relating to the cited paper. The ranking system uses a citation score estimator for computing the overall weight of the descriptive cited content relating to a specific paper in the citing papers. The journal ranking system performs classification of the citation content with the evaluation of a citation score. The work that involves the citation content is classified under different categories as positively cited, negatively cited or neutral and unrelated. Results: Then the computed citation score is used for ranking the dealing with research on cancer research journals. The results of the ranking journals indicate that the particular ranked journal has been cited in the literature of many journals with a good descriptive content. Journal ranking system can be considered as a well-organized tool for ranking the cancer research scientific journal based on citation content and citation counting. Conclusion: This experimental cancer journal ranking method increases accuracy and effectiveness by using the citation content when compared with PageRank and HITS.
    Keywords:  Opining mining; citation ranking; citation classification; cancer research journal; Information retrieval
  6. Health Info Libr J. 2019 Mar 27.
    Popoola BO.
      BACKGROUND: The Goal 3 (SDG-3) of the United Nations' Sustainable Development Goals (SDG) incorporates 13 targets that cut across pressing health concerns globally. Health literacy has however been linked to achieving good health in the society, and its improvement in developing economies could aid the achievement of SDG-3.OBJECTIVE: The review focused on identifying actions that can be implemented by libraries to enhance health literacy and access to information among health care practitioners and consumers to support the achievement of SDG-3 in developing countries, especially Nigeria.
    METHOD: A literature search was conducted on reputable academic databases, namely sciencedirect, doaj, google scholar, pubmed and jstor. Similar keyword combinations were used to obtain articles, with filters set to search the keywords in article titles or abstract. Relevant criteria were used to screen the literature.
    RESULTS: Results from the literature searching were grouped under six themes that emerged from the literature. The value of libraries in health care was discussed, and suggestions were made for implementation in libraries.
    CONCLUSION: It was concluded that libraries in developing economies have to take actions to improve users' health literacy in order to become prominent stakeholders in the process of achieving SDG-3.
    Keywords:  Africa, West; consumer health information; developing economies; health science; libraries; literature; review
    DOI:  https://doi.org/10.1111/hir.12255
  7. Health Info Libr J. 2017 Sep;34(3): 258-262
    Tran A.
      Public Health England plays a vital role in ensuring the health of the nation. The Knowledge and Library Service (KLS) is a key part of the organisation's evidence supply chain. KLS staff handle over 200 requests for literature searches per annum, and this number is increasing exponentially year on year. Searches are often complex and require specialist public health knowledge to complete effectively. Library staff who are new to the area of public health require support and training. In this article, Anh Tran, Knowledge and Evidence Specialist for Public Health England, discusses a peer supported literature search training course that has been developed in-house for the benefit of new library staff, and to increase the Knowledge and Library Service's literature searching capacity at Public Health England. H. S.
    Keywords:  education and training; information retrieval; information services; instructional design; literature searching; public health
    DOI:  https://doi.org/10.1111/hir.12189
  8. J Med Internet Res. 2019 Mar 26. 21(3): e12235
    Cheng Q, Yom-Tov E.
      BACKGROUND: Search engines display helpline notices when people query for suicide-related information.OBJECTIVE: In this study, we aimed to examine if these notices and other information displayed in response to suicide-related queries are correlated with subsequent searches for suicide prevention rather than harmful information.
    METHODS: Anonymous suicide-related searches made on Bing and Google in the United States, the United Kingdom, Hong Kong, and Taiwan in a span of 10 months were extracted. Descriptive analyses and regression models were fit to the data to assess the correlation with observed behaviors.
    RESULTS: Display of helpline notices was not associated with an observed change in the likelihood of or future suicide searches (P=.42). No statistically significant differences were observed in the likelihood of people making future suicide queries (both generally and specific types of suicide queries) when comparing search engines in locations that display helpline notices versus ones that do not. Pages with higher rank, being neutral to suicide, and those shown among more antisuicide pages were more likely to be clicked on. Having more antisuicide Web pages displayed was the only factor associated with further searches for suicide prevention information (hazard=1.18, P=.002).
    CONCLUSIONS: Helpline notices are not associated with harm. If they cause positive change in search behavior, it is small. This is possibly because of the variability in intent of users seeking suicide-related information. Nonetheless, helpline notice should be displayed, but more efforts should be made to improve the visibility and ranking of suicide prevention Web pages.
    Keywords:  search engines; suicide
    DOI:  https://doi.org/10.2196/12235
  9. Methods Inf Med. 2019 Mar 27.
    Gülkesen KH, Haux R.
      OBJECTIVES:  To identify major research subjects and trends in medical informatics research based on the current set of core medical informatics journals.METHODS:  Analyzing journals in the Web of Science (WoS) medical informatics category together with related categories from the years 2013 to 2017 by using a smart local moving algorithm as a clustering method for identifying the core set of journals. Text mining analysis with binary counting of abstracts from these journals published in the years 2006 to 2017 for identifying major research subjects. Building clusters based on these terms for the complete time period as well as for the periods 2006-2008, 2009-2011, 2012-2014, and 2015-2017 for identifying trends.
    RESULTS:  The identified cluster includes 17 core medical informatics journals. By text mining of these journals, 224,992 different terms in 14,414 articles were identified covering 550 specific key terms. Based on these key terms five clusters were identified: "Biomedical Data Analysis," "Clinical Informatics," "EHR and Knowledge Representation," "Mobile Health," and "Organizational Aspects of Health Information Systems." No shifts in the clusters were observed between the first two 3-year periods. In the third period, some terms like "mobile phone," "mobile apps," and "message" appear. Also, in the third period, a "Clinical Informatics" cluster appears and persists in the fourth period. In the fourth period, a rearrangement of clusters was observed.
    CONCLUSIONS:  Beside classical subjects of medical informatics on organizing, representing, and analyzing data, we observed new developments in the context of mobile health and clinical informatics. These subjects tended to grow over the past years, and we can expect this trend to continue.
    DOI:  https://doi.org/10.1055/s-0039-1681107
  10. Langenbecks Arch Surg. 2019 Mar 29.
    Reinisch A, Schröder SR, Ulrich F, Padberg W, Liese J.
      PURPOSE: Social media, especially Twitter®, is becoming increasingly important for medical topics. Systematic analyses of the content of these tweets are rare. To date, no analysis of the reception of antibiotic/non-operative-treated acute appendicitis on Twitter® has been performed.METHODS: Tweets with the content "appendicitis," "appendix," and "appendectomy" from December 31, 2010, to September 27, 2017, were recorded. Further analysis was performed by secondary search strings related to antibiotic-treated acute appendicitis. Subsequent systematic analysis of content, author groups, and followers was performed.
    RESULTS: Out of 22,962 analyzed tweets, 3400 were applicable on all search strings, and 349 dealt meaningfully with antibiotic-treated acute appendicitis. 47.9% of the tweets were published by individuals, of which non-surgical consultants comprised the largest group. The tweets published by organizations and institutions were mostly published by publishing platforms. Half of the tweets were neutral, with an overall positive trend for antibiotic-treated acute appendicitis, but significant differences were noted among the authors. The number of followers showed a wide range, with an considerable numeric impact.
    CONCLUSION: The scientific discussion of antibiotic-treated acute appendicitis is reflected on Twitter®. Overall, antibiotic-treated acute appendicitis is presented in a neutral and differentiated manner on Twitter®, but this picture is exclusively derived from assessment of a variety of tweets. Individual tweets are partially undifferentiated in content and misrepresent antibiotic-treated acute appendicitis. In addition, content and intentions are significantly author dependent. Scientists should therefore use Twitter® to make sound medical information heard. If this policy is not implemented, the importance of inadequate and incorrect information transfer is indirectly increased.
    Keywords:  Antibiotics; Appendicitis; Social media; Twitter®
    DOI:  https://doi.org/10.1007/s00423-019-01777-y
  11. BMC Bioinformatics. 2019 Mar 27. 20(1): 156
    Karadeniz İ, Özgür A.
      BACKGROUND: Although there is an enormous number of textual resources in the biomedical domain, currently, manually curated resources cover only a small part of the existing knowledge. The vast majority of these information is in unstructured form which contain nonstandard naming conventions. The task of named entity recognition, which is the identification of entity names from text, is not adequate without a standardization step. Linking each identified entity mention in text to an ontology/dictionary concept is an essential task to make sense of the identified entities. This paper presents an unsupervised approach for the linking of named entities to concepts in an ontology/dictionary. We propose an approach for the normalization of biomedical entities through an ontology/dictionary by using word embeddings to represent semantic spaces, and a syntactic parser to give higher weight to the most informative word in the named entity mentions.RESULTS: We applied the proposed method to two different normalization tasks: the normalization of bacteria biotope entities through the Onto-Biotope ontology and the normalization of adverse drug reaction entities through the Medical Dictionary for Regulatory Activities (MedDRA). The proposed method achieved a precision score of 65.9%, which is 2.9 percentage points above the state-of-the-art result on the BioNLP Shared Task 2016 Bacteria Biotope test data and a macro-averaged precision score of 68.7% on the Text Analysis Conference 2017 Adverse Drug Reaction test data.
    CONCLUSIONS: The core contribution of this paper is a syntax-based way of combining the individual word vectors to form vectors for the named entity mentions and ontology concepts, which can then be used to measure the similarity between them. The proposed approach is unsupervised and does not require labeled data, making it easily applicable to different domains.
    Keywords:  Adverse drug reactions; Bacteria biotopes; Entity categorization; Entity linking; Named entity normalization; Natural language processing; Text mining; Word embeddings
    DOI:  https://doi.org/10.1186/s12859-019-2678-8
  12. Int J Med Inform. 2019 May;pii: S1386-5056(18)31378-9. [Epub ahead of print]125 37-46
    Dreisbach C, Koleck TA, Bourne PE, Bakken S.
      OBJECTIVE: In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT).MATERIALS AND METHODS: A comprehensive literature search of 1964 articles from PubMed and EMBASE was narrowed to 21 eligible articles. Data related to purpose, text source, number of users and/or posts, evaluation metrics, and quality indicators were recorded.
    RESULTS: Pain (n = 18) and fatigue and sleep disturbance (n = 18) were the most frequently evaluated symptom clinical content categories. Studies accessed ePAT from sources such as Twitter and online community forums or patient portals focused on diseases, including diabetes, cancer, and depression. Fifteen studies used NLP as a primary methodology. Studies reported evaluation metrics including the precision, recall, and F-measure for symptom-specific research questions.
    DISCUSSION: NLP and text mining have been used to extract and analyze patient-authored symptom data in a wide variety of online communities. Though there are computational challenges with accessing ePAT, the depth of information provided directly from patients offers new horizons for precision medicine, characterization of sub-clinical symptoms, and the creation of personal health libraries as outlined by the National Library of Medicine.
    CONCLUSION: Future research should consider the needs of patients expressed through ePAT and its relevance to symptom science. Understanding the role that ePAT plays in health communication and real-time assessment of symptoms, through the use of NLP and text mining, is critical to a patient-centered health system.
    Keywords:  Electronic patient-authored text; Natural language processing; Review; Signs and symptoms
    DOI:  https://doi.org/10.1016/j.ijmedinf.2019.02.008
  13. Food Microbiol. 2019 Aug;pii: S0740-0020(17)31063-8. [Epub ahead of print]81 63-75
    Chaix E, Deléger L, Bossy R, Nédellec C.
      Information on food microbial diversity is scattered across millions of scientific papers. Researchers need tools to assist their bibliographic search in such large collections. Text mining and knowledge engineering methods are useful to automatically and efficiently find relevant information in Life Science. This work describes how the Alvis text mining platform has been applied to a large collection of PubMed abstracts of scientific papers in the food microbiology domain. The information targeted by our work is microorganisms, their habitats and phenotypes. Two knowledge resources, the NCBI taxonomy and the OntoBiotope ontology were used to detect this information in texts. The result of the text mining process was indexed and is presented through the AlvisIR Food on-line semantic search engine. In this paper, we also show through two illustrative examples the great potential of this new tool to assist in studies on ecological diversity and the origin of microbial presence in food.
    Keywords:  Food spoilage; Information extraction; Microbial biodiversity; Text mining
    DOI:  https://doi.org/10.1016/j.fm.2018.04.011