Who is blocking access to PubMed? Educational 'Escape Room' for medical residents.

Teaching students how to conduct bibliographic searches in health sciences' databases is essential training. One of the challenges librarians face is how to motivate students during classroom learning. In this article, two hospital libraries, in Spain, used Escape rooms as a method of bringing creativity, teamwork, communication and critical thinking into bibliographic search instruction. Escape rooms are a series of puzzles that must be solved to exit the game. This article explores the methods used for integrating escape rooms into training programmes and evaluates the results. Escape Rooms are a useful tool that can be integrated into residents' training to support their instruction on bibliographic searches. This kind of learning stablishes competences like logical thinking and deductive approaching. These aspects aid participants to make their own decision and to develop social and intellectual skills.

Facilitating access to evidence: Primary Health Care Search Filter.

BACKGROUND: The evidence base developed by, and relevant to, primary health care (PHC) is rapidly increasing. With the wealth of literature available, searchers trying to find PHC-specific citations can feel overwhelmed. OBJECTIVES: Flinders Filters and the Primary Health Care Research & Information Service collaborated to develop a search filter enabling efficient and effective retrieval of relevant PHC literature. METHODS: Stage 1 involved developing a PHC Search Filter in the OvidSP Medline platform using a rigorous experimental methodology. The search filter was then translated for Web-based 'one-click searching' in PubMed during Stage 2. Stage 3 involved planning and implementing a mixed-methods evaluation. RESULTS: The search filter sensitivity was 77.0% with a post hoc relevance assessment of 78.3%. Four months after its launch, a mixed-methods study evaluated the PHC Search Filter. With 90 respondents, analysis of data from the online survey demonstrated overarching benefits, a positive response to the tool and directions for further refinement of the PHC Search Filter. DISCUSSION: Designing the PHC Search Filter followed an established method that ensures the tool offers a validated search strategy. Evaluation results suggest that the PHC Search Filter is a useful tool that is easy to navigate. Challenges for the Filter relate to access to full text articles, while challenges for the evaluation relate to the small sample size. CONCLUSIONS: The PHC Search Filter reduces the burden associated with literature searching, increases the value of the results that are received and provides a useful resource to improve the likelihood of incorporating relevant evidence into policy and practice.

Choropleth map legend design for visualizing the most influential areas in article citation disparities: A bibliometric study.

BACKGROUND: Disparities in health outcomes across countries/areas are a central concern in public health and epidemiology. However, few authors have discussed legends that can be complemental to choropleth maps (CMs) and merely linked differences in outcomes to other factors like density in areas. Thus, whether health outcome rates on CMs showing the geographical distribution can be applied to publication citations in bibliometric analyses requires further study. The legends for visualizing the most influential areas in article citation disparities should have sophisticated designs. This paper illustrates the use of cumulative frequency (CF) map legends along with Lorenz curves and Gini coefficients (GC) to characterize the disparity of article citations in areas on CMs, based on the quantile classification method for classes. METHODS: By searching the PubMed database (pubmed.com), we used the keyword "Medicine" [journal] and downloaded 7042 articles published from 1945 to 2016. A total number of 41,628 articles were cited in Pubmed Central (PMC). The publication outputs based on the author's x-index were applied to plot CM about research contributions. The approach uses two methods (i.e., quantiles and equal total values for each class) with CF legends, in order to highlight the difference in x-indices across geographical areas on CMs. GC was applied to observe the x-index disparities in areas. Microsoft Excel Visual Basic for Application (VBA) was used for creating the CMs. RESULTS: Results showed that the most productive and cited countries in Medicine (Baltimore) were China and the US. The most-cited states and cities were Maryland (the US) and Beijing (China). Taiwan (x-index = 24.38) ranked behind Maryland (25.97), but ahead of Beijing (16.9). China earned lower disparity (0.42) than the US (0.49) and the rest of the world (0.53) when the GCs were applied. CONCLUSION: CF legends, particularly using the quantile classification for classes, can be useful to complement CMs. They also contain more information than those in standard CM legends that are commonly used with other classification methods. The steps of creating CM legends are described and introduced. Bibliometric analysts on CM can be replicated in the future.

Technical development of PubMed interact: an improved interface for MEDLINE/PubMed searches.

BACKGROUND: The project aims to create an alternative search interface for MEDLINE/PubMed that may provide assistance to the novice user and added convenience to the advanced user. An earlier version of the project was the 'Slider Interface for MEDLINE/PubMed searches' (SLIM) which provided JavaScript slider bars to control search parameters. In this new version, recent developments in Web-based technologies were implemented. These changes may prove to be even more valuable in enhancing user interactivity through client-side manipulation and management of results. RESULTS: PubMed Interact is a Web-based MEDLINE/PubMed search application built with HTML, JavaScript and PHP. It is implemented on a Windows Server 2003 with Apache 2.0.52, PHP 4.4.1 and MySQL 4.1.18. PHP scripts provide the backend engine that connects with E-Utilities and parses XML files. JavaScript manages client-side functionalities and converts Web pages into interactive platforms using dynamic HTML (DHTML), Document Object Model (DOM) tree manipulation and Ajax methods. With PubMed Interact, users can limit searches with JavaScript slider bars, preview result counts, delete citations from the list, display and add related articles and create relevance lists. Many interactive features occur at client-side, which allow instant feedback without reloading or refreshing the page resulting in a more efficient user experience. CONCLUSION: PubMed Interact is a highly interactive Web-based search application for MEDLINE/PubMed that explores recent trends in Web technologies like DOM tree manipulation and Ajax. It may become a valuable technical development for online medical search applications.

Development and evaluation of evidence-based nursing (EBN) filters and related databases.

OBJECTIVES: Difficulties encountered in the retrieval of evidence-based nursing (EBN) literature and recognition of terminology, research focus, and design differences between evidence-based medicine and nursing led to the realization that nursing needs its own filter strategies for evidence-based practice. This article describes the development and evaluation of filters that facilitate evidence-based nursing searches. METHODS: An inductive, multistep methodology was employed. A sleep search strategy was developed for uniform application to all filters for filter development and evaluation purposes. An EBN matrix was next developed as a framework to illustrate conceptually the placement of nursing-sensitive filters along two axes: horizontally, an adapted nursing process, and vertically, levels of evidence. Nursing diagnosis, patient outcomes, and primary data filters were developed recursively. Through an interface with the PubMed search engine, the EBN matrix filters were inserted into a database that executes filter searches, retrieves citations, and stores and updates retrieved citations sets hourly. For evaluation purposes, the filters were subjected to sensitivity and specificity analyses and retrieval set comparisons. Once the evaluation was complete, hyperlinks providing access to any one or a combination of completed filters to the EBN matrix were created. Subject searches on any topic may be applied to the filters, which interface with PubMed. RESULTS: Sensitivity and specificity for the combined nursing diagnosis and primary data filter were 64% and 99%, respectively; for the patient outcomes filter, the results were 75% and 71%, respectively. Comparisons were made between the EBN matrix filters (nursing diagnosis and primary data) and PubMed's Clinical Queries (diagnosis and sensitivity) filters. Additional comparisons examined publication types and indexing differences. Review articles accounted for the majority of the publication type differences, because "review" was accepted by the CQ but was "NOT'd" by the EBN filter. Indexing comparisons revealed that although the term "nursing diagnosis" is in Medical Subject Headings (MeSH), the nursing diagnoses themselves (e.g., sleep deprivation, disturbed sleep pattern) are not indexed as nursing diagnoses. As a result, abstracts deemed to be appropriate nursing diagnosis by the EBN filter were not accepted by the CQ diagnosis filter. CONCLUSIONS: The EBN filter capture of desired articles may be enhanced by further refinement to achieve a greater degree of filter sensitivity. Retrieval set comparisons revealed publication type differences and indexing issues. The EBN matrix filter "NOT'd" out "review," while the CQ filter did not. Indexing issues were identified that explained the retrieval of articles deemed appropriate by the EBN filter matrix but not included in the CQ retrieval. These results have MeSH definition and indexing implications as well as implications for clinical decision support in nursing practice.

Research methodology search filters: are they effective for locating research for evidence-based veterinary medicine in PubMed?

OBJECTIVE: The study examined the effectiveness of research methodology search filters developed by Haynes and colleagues and utilized by the Clinical Query feature of PubMed for locating literature for evidence-based veterinary medicine (EBVM). METHODS: A manual review of articles published in 6 commonly read veterinary journals was conducted. Articles were classified by format (original study, review, general article, conference report, decision analysis, and case report) and purpose category (etiology, prognosis, diagnosis, and treatment). Search strategies listed in PubMed's Clinical Query feature were then tested and compared to the manually reviewed data to calculate sensitivity, specificity, and precision. RESULTS: The author manually reviewed 914 articles to identify 702 original studies. Search #1 included terms determined to have the highest sensitivity and returned acceptable sensitivities over 75% for diagnosis and treatment. Search #2 included terms identified as providing the highest specificity and returned results with specificities over 75% for etiology, prognosis, and treatment. DISCUSSION: The low precision for each search prompts the question: Are research methodology search filters practical for locating literature for the practice of EBVM? A study examining terms related to appropriate research methodologies for advanced clinical veterinary research is necessary to develop filters designed to locate literature for EBVM.