bims-librar Biomed News
on Biomedical librarianship
Issue of 2019‒06‒02
ten papers selected by
Thomas Krichel
Open Library Society


  1. J Educ Health Promot. 2019 ;8 102
    Ashrafi-Rizi H, Shahrzadi L, Dehghani-Champiri Z.
      INTRODUCTION: Patients have different rights, one of which is their right to access health information. The aim of this study was to identify patients' rights to benefit from consumer health information services using a qualitative method.MATERIALS AND METHODS: The research method was qualitative using a Delphi technique. The statistical population consisted of 12 specialists in the field of medical library and information science and researchers and healthcare professionals. Eight dimensions and 42 items of patients' rights were identified and were approved by Delphi panel.
    RESULTS: Regarding patients' rights to benefit from consumer health information services, eight dimensions including the right to health knowledge, the right to access to health information, the professional behavior of medical librarians with patients, content richness, information seeking skills, awareness of new services and products, the ease of using health information centers, and the professional behavior of healthcare professionals with patients were identified and approved.
    CONCLUSION: Decreasing the gap between the health literacy of healthcare professionals and patients is one of the duties of medical librarians and health information professionals. Establishing of patient rights in the area of utilizing health information services is an important step in improving the quality of services received by patients.
    Keywords:  Code of ethics; consumer health information services; health information professionals; librarians; patients’ rights; professional ethics
    DOI:  https://doi.org/10.4103/jehp.jehp_18_19
  2. Int J Pediatr Endocrinol. 2019 ;2019 1
    Ernst MM, Chen D, Kennedy K, Jewell T, Sajwani A, Foley C, Sandberg DE, .
      Objectives: Consumers rely on online health information, particularly for unusual conditions. Disorders of Sex Development (DSD) are complex with some aspects of care controversial. Accurate web-based DSD information is essential for decision-making, but the quality has not been rigorously evaluated. The purpose of the present study was to assess the quality of online health information related to DSD presented by 12 pediatric institutions comprising the NIH-sponsored DSD-Translational Research Network (DSD-TRN).Methods: DSD-TRN sites identified team webpages, then we identified linked webpages. We also used each institution search engine to search common DSD terms. We assessed webpages using validated tools: the Simple Measure of Gobbledygook (SMOG) determined reading level, the Patient Education Materials Assessment Tool (PEMAT) evaluated content for understandability and actionability, and the DISCERN tool assessed treatment decision-making information (for hormone replacement and surgery). We developed a "Completeness" measure which assessed the presence of information on 25 DSD topics.
    Results: The SMOG reading level of webpages was at or above high-school grade level. Mean (SD) PEMAT understandability score for Team Pages and Team Links was 68% (6%); on average these pages met less than 70% of the understandability criteria. Mean (SD) PEMAT actionability score was 23% (20%); few patient actions were identified. The DISCERN tool determined that the quality of information related to hormone treatment and to surgery was poor. Sites' webpages covered 12-56% of the items on our Completeness measure.
    Conclusions: Quality of DSD online content was poor, and would be improved by using a variety of strategies, such as simplifying word choice, using visual aids, highlighting actions patients can take and acknowledging areas of uncertainty. For complex conditions such as DSD, high-quality web-based information is essential to empower patients (and caregiver proxies), particularly when aspects of care are controversial.
    Keywords:  Disorder of sex development; Health literacy; Internet health information
    DOI:  https://doi.org/10.1186/s13633-019-0065-x
  3. J Drugs Dermatol. 2019 May 01. pii: S1545961619P0484X. [Epub ahead of print]18(5): 484-487
    Kang R, Lipner S.
      Onychomycosis is a common and significant nail condition causing both physical and social impairment. Since patients often search for health information online, the accuracy of this information has become important. In this study, we sought to assess the reliability and comprehensibility of accessible internet information for patients searching for onychomycosis. We identified the top search engine hits, evaluating websites on several categories: Accountability, Quality of Medical Information, Readability, Display, Support Features, and Transparency/Disclosures. Utilizing a pro forma based on established internet codes of conduct, website readability scores, and peer-reviewed papers, we objectively analyzed and scored the most commonly-listed websites on onychomycosis. Fifty-one total websites were reviewed with a maximum possible overall score of 43. The mean overall score for all websites was 20 and 1/43 (range, 4-35) with varied Accountability (mean, 4.9/10; range, 0-10) and Quality (mean, 6.4/13; range,1-12/13). Readability was poor overall with only 1/3 of sites meeting the acceptable 7th grade reading level for patients. In addition, while sites such as the American Academy of Dermatology website were well-organized and highly readable (Readability score, 5/5), this may compromise the quality of medical information presented (Quality score, 6/13). Because online education materials set the expectations and concerns of patients with onychomycosis, the variability in website reliability necessitates more efficient and regulated methods of presenting health information.
  4. BMJ Open. 2019 May 30. 9(5): e023804
    Hanley B, Brown P, O'Neill S, Osborn M.
      OBJECTIVES: Hospital (consented) autopsy rates have dropped precipitously in recent decades. Online medical information is now a common resource used by the general public. Given clinician reluctance to request hospital postmortem examinations, we assessed whether healthcare users have access to high quality, readable autopsy information online.DESIGN: A cross-sectional analysis of 400 webpages. Readability was determined using the Flesch-Kincaid score, grade level and Coleman-Liau Index. Authorship, DISCERN score and Journal of the American Medical Association (JAMA) criteria were applied by two independent observers. Health on the net code of conduct (HON-code) certification was also assessed. Sixty-five webpages were included in the final analysis.
    RESULTS: The overall quality was poor (mean DISCERN=38.1/80, 28.8% did not fulfil a single JAMA criterion and only 10.6% were HON-code certified). Quality scores were significantly different across author types, with scientific and health-portal websites scoring highest by DISCERN (analysis of variance (ANOVA), F=5.447, p<0.001) and JAMA (Kruskal-Wallis, p<0.001) criteria. HON-code certified sites were associated with higher JAMA (Mann-Whitney U, p<0.001) and DISCERN (t-test, t=3.5, p=0.001) scores. The most frequent author type was government (27.3%) which performed lower than average on DISCERN scores (ANOVA, F=5.447, p<0.001). Just 5% (3/65) were at or below the recommended eight grade reading level (aged 13-15 years).
    CONCLUSIONS: Although there were occasional high quality web articles containing autopsy information, these were diluted by irrelevant and low quality sites, set at an inappropriately high reading level. Given the paucity of high quality articles, healthcare providers should familiarise themselves with the best resources and direct the public accordingly.
    Keywords:  DISCERN; autopsy; online information; post-mortem; quality; readability
    DOI:  https://doi.org/10.1136/bmjopen-2018-023804
  5. Acad Med. 2019 May 28.
    Widmer RJ, Mandrekar J, Ward A, Aase LA, Lanier WL, Timimi FK, Gerber TC.
      PURPOSE: To study the effect of a planned social media promotion strategy on access of online articles of an established academic medical journal.METHOD: This was a single-masked, randomized controlled trial using articles published in Mayo Clinic Proceedings, a large-circulation general/internal medicine journal. Articles published during the months of October, November, and December 2015 (n = 68) were randomized either to social media promotion (SoMe) using Twitter, Facebook, and LinkedIn or to no social media promotion (NoSoMe), for 30 days (beginning with the date of online article publication). Journal website visits and full-text article downloads were compared for 0-30 days and 31-60 days following online publication between SoMe versus NoSoMe using a Wilcoxon rank sum test.
    RESULTS: Website access of articles from 0-30 days was significantly higher in the SoMe group (n = 34) compared to the NoSoMe group (n = 34): 1,070 median downloads versus 265, P < 0.001. Similarly, full-text article downloads from 0 to 30 days were significantly higher in the SoMe group: 1,042 median downloads versus 142, P < .001. Compared to the NoSoMe articles, articles randomized to SoMe received a greater number of website visits via Twitter (90 vs. 1), Facebook (526 vs. 2.5), and LinkedIn (31.5 vs. 0)-all P < .001.
    CONCLUSIONS: Articles randomized to SoMe were more widely accessed compared to those without social media promotion. These findings show a possible role, benefit, and need for further study of a carefully planned social media promotion strategy in an academic medical journal.
    DOI:  https://doi.org/10.1097/ACM.0000000000002811
  6. J Clin Epidemiol. 2019 May 28. pii: S0895-4356(18)31128-4. [Epub ahead of print]
    Golder S, Peryer G, Loke YK.
      OBJECTIVE: Methodological research has been undertaken to investigate the many challenges in searching for adverse effects data. It is imperative that the search approach adopted in systematic reviews is based on the best available evidence. We provide a detailed summary of the results and implications of the current evidence base to assist future searches for adverse effects.STUDY DESIGN AND SETTING: This paper is a narrative review from the authors of the Cochrane Handbook chapter on adverse effects.
    RESULTS: The specified search strategy must be based on the PICO (Population, Intervention, Comparator, Outcome(s)) format for question formulation and appropriate study designs for adverse effects data. Search filters and suggested search terms are available for the adverse effects of drug, medical devices and surgical interventions. The use of generic adverse effects terms (such as harms, and complications) as textwords and indexing terms and specific adverse effects terms (such as rash and wound infection) are warranted. Searching databases beyond MEDLINE has proven useful, as well as the use of non-database sources.
    CONCLUSION: This paper provides the most up to date evidence-based guidance in identifying adverse effects data in the literature. It will support searchers and researchers evaluating the potential for harm of medical interventions in systematic reviews.
    Keywords:  Adverse effects; complications; information retrieval; literature searching; systematic reviews
    DOI:  https://doi.org/10.1016/j.jclinepi.2019.05.019
  7. Math Biosci Eng. 2019 Mar 08. 16(4): 1978-1991
    Wang XW, Zhang Y, Guo Z, Li J.
      Automatically identifying semantic concepts from medical images provides multimodal insights for clinical research. To study the effectiveness of concept detection on large scale medical images, we reconstructed over 230,000 medical image-concepts pairs collected from the ImageCLEFcaption 2018 evaluation task. A transfer learning-based multi-label classification model was used to predict multiple high-frequency concepts for medical images. Semantically relevant concepts of visually similar medical images were identified by the image retrieval-based topic model. The results showed that the transfer learning method achieved F1 score of 0.1298, which was comparable with the state of art methods in the ImageCLEFcaption tasks. The image retrieval-based method contributed to the recall performance but reduced the overall F1 score, since the retrieval results of the search engine introduced irrelevant concepts. Although our proposed method achieved second-best performance in the concept detection subtask of ImageCLEFcaption 2018, there will be plenty of further work to improve the concept detection with better understanding the medical images.
    Keywords:   LDA ; concept detection ; medical image retrieval ; multi-label classification ; transfer learning
    DOI:  https://doi.org/10.3934/mbe.2019097
  8. J Dent. 2019 May 26. pii: S0300-5712(19)30112-5. [Epub ahead of print]
    Faggion CM, Hagenfeld D.
      OBJECTIVE: This study aimed to evaluate comprehensiveness and reproducibility of reviews that support consensus guidelines in periodontology.METHODS: We included the reviews that support consensus guidelines from three workshops in periodontology, which were overseen by the two most important organisations in the field: the European Federation of Periodontology and the American Academy of Periodontology. We independently evaluated the comprehensiveness of literature searches by determining whether authors had searched reference lists, journals, registries and grey literature and whether the searches were limited to only one or a few languages. We evaluated whether review authors reported the eligibility criteria, the search strategies, and the list of included/excluded articles. We tested whether the search and selection of articles in one major database was reproducible.
    RESULTS: Twenty-nine reviews were evaluated. Two (7%) reviews reported grey literature searches, and more than two-thirds of the reviews did not report hand-searching. Almost half of the reviews did not report whether there was language restriction for the literature searches. Two-thirds of the reviews reported the use of keywords only (without Boolean operators). One-fourth of the reviews reported the presence of a list of excluded articles after the full-text assessment. None of the reviews reported a full list of excluded articles after screening of titles/abstracts. None of the reviews reported enough information to allow reproduction of the findings of the PubMed search.
    CONCLUSIONS: There is a room to improve the reporting of the methodologies that are used for reviews that support periodontology consensus guidelines, although heterogeneity in reporting was found across all the reviews.
    Keywords:  Consensus development conference; guidelines; methods; periodontics; review
    DOI:  https://doi.org/10.1016/j.jdent.2019.05.029
  9. Int J Environ Res Public Health. 2019 May 20. pii: E1780. [Epub ahead of print]16(10):
    Lenstra N, Carlos J.
      Public libraries constitute a ubiquitous social infrastructure found in nearly every community in the United States and Canada. The hypothesis of this study is that public libraries can be understood as important supports of walking in neighborhoods, not only as walkable destinations, but also as providers of programs that increase walking in communities. Recent work by public health scholars has analyzed how libraries contribute to community health. This particular topic has not previously been researched. As such, a qualitative, exploratory approach guides this study. Grounded theory techniques are used in a content analysis of a corpus of 94 online articles documenting this phenomenon. Results show that across North America public librarians endeavor to support walking through programs oriented around stories, books, and local history, as well as through walking groups and community partnerships. While this exploratory study has many limitations, it does set the stage for future, more rigorous research on the contributions public libraries and public librarians make to walking in neighborhoods. The principal conclusion of this study is that additional research is needed to comprehensively understand the intersection between public librarianship and public health.
    Keywords:  librarianship; library and information science; public health partnerships; public libraries; public programming; walking programs
    DOI:  https://doi.org/10.3390/ijerph16101780
  10. BMC Bioinformatics. 2019 May 29. 20(Suppl 10): 249
    Yoon W, So CH, Lee J, Kang J.
      BACKGROUND: Finding biomedical named entities is one of the most essential tasks in biomedical text mining. Recently, deep learning-based approaches have been applied to biomedical named entity recognition (BioNER) and showed promising results. However, as deep learning approaches need an abundant amount of training data, a lack of data can hinder performance. BioNER datasets are scarce resources and each dataset covers only a small subset of entity types. Furthermore, many bio entities are polysemous, which is one of the major obstacles in named entity recognition.RESULTS: To address the lack of data and the entity type misclassification problem, we propose CollaboNet which utilizes a combination of multiple NER models. In CollaboNet, models trained on a different dataset are connected to each other so that a target model obtains information from other collaborator models to reduce false positives. Every model is an expert on their target entity type and takes turns serving as a target and a collaborator model during training time. The experimental results show that CollaboNet can be used to greatly reduce the number of false positives and misclassified entities including polysemous words. CollaboNet achieved state-of-the-art performance in terms of precision, recall and F1 score.
    CONCLUSIONS: We demonstrated the benefits of combining multiple models for BioNER. Our model has successfully reduced the number of misclassified entities and improved the performance by leveraging multiple datasets annotated for different entity types. Given the state-of-the-art performance of our model, we believe that CollaboNet can improve the accuracy of downstream biomedical text mining applications such as bio-entity relation extraction.
    Keywords:  Deep learning; NER; Named entity recognition; Text mining
    DOI:  https://doi.org/10.1186/s12859-019-2813-6