CORE and PubMed collaborate for further full text dissemination – Research

“CORE provides access to freely available full text papers which were previously  unavailable in PubMed to enhance the experience of PubMed users. This is delivered via the LinkOut service. 

PubMed is maintained by the US National Library of Medicine at the National Institutes of Health. It constitutes the largest citations database in health sciences and is one of the most widely used scholarly infrastructure services with millions of monthly active users.

We are happy to announce that hundreds of thousands of relevant articles hosted in CORE are now linked from PubMed, taking  more  available content directly to the researchers.   

Currently, many PubMed records offer metadata information and the full text may not be available. This development now enables PubMed users to access full text links to articles hosted in CORE via its LinkOut service, providing researchers with a direct route to the research. The linking of CORE papers directly from PubMed resources and other related databases further increases the discoverability of content aggregated by CORE, providing a valuable service to our repositories.  …”

A detailed open access model of the PubMed literature | Scientific Data

Abstract:  Portfolio analysis is a fundamental practice of organizational leadership and is a necessary precursor of strategic planning. Successful application requires a highly detailed model of research options. We have constructed a model, the first of its kind, that accurately characterizes these options for the biomedical literature. The model comprises over 18 million PubMed documents from 1996–2019. Document relatedness was measured using a hybrid citation analysis?+?text similarity approach. The resulting 606.6 million document-to-document links were used to create 28,743 document clusters and an associated visual map. Clusters are characterized using metadata (e.g., phrases, MeSH) and over 20 indicators (e.g., funding, patent activity). The map and cluster-level data are embedded in Tableau to provide an interactive model enabling in-depth exploration of a research portfolio. Two example usage cases are provided, one to identify specific research opportunities related to coronavirus, and the second to identify research strengths of a large cohort of African American and Native American researchers at the University of Michigan Medical School.

 

LitCovid – NCBI – NLM – NIH

“LitCovid is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus. It is the most comprehensive resource on the subject, providing a central access to 1121 (and growing) research articles in PubMed. The articles are updated daily and are further categorized by different research topics and geographic locations for improved access….”

LitCovid – NCBI – NLM – NIH

“LitCovid is a curated literature hub for tracking up-to-date scientific information about the 2019 novel Coronavirus. It is the most comprehensive resource on the subject, providing a central access to 1121 (and growing) research articles in PubMed. The articles are updated daily and are further categorized by different research topics and geographic locations for improved access….”

Keep up with the latest coronavirus research

“An open-resource literature hub known as LitCovid curates the most comprehensive collection of international research papers so far on the new coronavirus disease COVID-19 (see go.nature.com/3almd5p). Developed with the support of the US National Institutes of Health’s intramural research programme, LitCovid is updated daily with newly published articles. The aim is to provide timely insight from the scientific literature into the biology of the virus and the diagnosis and management of those who have been infected.

LitCovid has a more sophisticated search function than existing resources. It identifies roughly 35% more relevant articles than do conventional keyword-based searches for entries such as ‘COVID-19’ or ‘nCOV’. Furthermore, the articles are categorized by topic — overview, disease mechanism, transmission dynamics, treatment, case report and epidemic forecasting — as well as by geographic location for visualization on a world map…..”

Keep up with the latest coronavirus research

“An open-resource literature hub known as LitCovid curates the most comprehensive collection of international research papers so far on the new coronavirus disease COVID-19 (see go.nature.com/3almd5p). Developed with the support of the US National Institutes of Health’s intramural research programme, LitCovid is updated daily with newly published articles. The aim is to provide timely insight from the scientific literature into the biology of the virus and the diagnosis and management of those who have been infected.

LitCovid has a more sophisticated search function than existing resources. It identifies roughly 35% more relevant articles than do conventional keyword-based searches for entries such as ‘COVID-19’ or ‘nCOV’. Furthermore, the articles are categorized by topic — overview, disease mechanism, transmission dynamics, treatment, case report and epidemic forecasting — as well as by geographic location for visualization on a world map…..”

2019 Was Big for Academic Publishing. Here’s Our Year in Review | The Scientist Magazine®

“The global push to make the scholarly literature open access continued in 2019. Some publishers and libraries forged new licensing deals, while in other cases contract negotiations came to halt, and a radical open access plan made some adjustments. Here are some of the most notable developments in the publishing world in 2019:…”

How to add academic journal articles to PubMed: An overview for publishers

“If you work with journals in the biomedical or life sciences, getting the articles you publish added to PubMed to make them more discoverable is likely one of your top goals. But, you may be wondering how to go about it.

We caught up with PubMed Central (PMC) Program Manager Kathryn Funk to get answers to some of the most common questions that we hear from journal publishers about PubMed and the related literature databases at the National Library of Medicine (NLM), MEDLINE and PMC. Read on to learn more about how the PubMed database works and how to apply to have a journal included in MEDLINE or PMC in order to make its articles searchable via PubMed….”

Frequency and format of clinical trial results dissemination to patients: a survey of authors of trials indexed in PubMed

Abstract:  Objective Dissemination of research findings is central to research integrity and promoting discussion of new knowledge and its potential for translation into practice and policy. We investigated the frequency and format of dissemination to trial participants and patient groups. Design Survey of authors of clinical trials indexed in PubMed in 2014–2015. Results Questionnaire emailed to 19 321 authors; 3127 responses received (16%). Of these 3127 trials, 2690 had human participants and 1818 enrolled individual patients. Among the 1818, 498 authors (27%) reported having disseminated results to participants, 238 (13%) planned to do so, 600 (33%) did not plan to, 176 (10%) were unsure and 306 (17%) indicated ‘other’ or did not answer. Of the 498 authors who had disseminated, 198 (40%) shared academic reports, 252 (51%) shared lay reports, 111 (22%) shared both and 164 (33%) provided individualised study results. Of the 1818 trials, 577 authors (32%) shared/planned to share results with patients outside their trial by direct contact with charities/patient groups, 401 (22%) via patient communities, 845 (46%) via presentations at conferences with patient representation, 494 (27%) via mainstream media and 708 (39%) by online lay summaries. Relatively few of the 1818 authors reported dissemination was suggested by institutional bodies: 314 (17%) of funders reportedly suggested dissemination to trial participants, 252 (14%) to patient groups; 333 (18%) of ethical review boards reportedly suggested dissemination to trial participants, 148 (8%) to patient groups. Authors described many barriers to dissemination. Conclusion Fewer than half the respondents had disseminated to participants (or planned to) and only half of those who had disseminated shared lay reports. Motivation to disseminate results to participants appears to arise within research teams rather than being incentivised by institutional bodies. Multiple factors need to be considered and various steps taken to facilitate wide dissemination of research to participants.

Which Academic Search Systems are Suitable for Systematic Reviews or Meta?Analyses? Evaluating Retrieval Qualities of Google Scholar, PubMed and 26 other Resources – Gusenbauer – – Research Synthesis Methods – Wiley Online Library

Abstract:  Rigorous evidence identification is essential for systematic reviews and meta?analyses (evidence syntheses), because the sample selection of relevant studies determines a review’s outcome, validity, and explanatory power. Yet, the search systems allowing access to this evidence provide varying levels of precision, recall, and reproducibility and also demand different levels of effort. To date, it remains unclear which search systems are most appropriate for evidence synthesis and why. Advice on which search engines and bibliographic databases to choose for systematic searches is limited and lacking systematic, empirical performance assessments.

This study investigates and compares the systematic search qualities of 28 widely used academic search systems, including Google Scholar, PubMed and Web of Science. A novel, query?based method tests how well users are able to interact and retrieve records with each system. The study is the first to show the extent to which search systems can effectively and efficiently perform (Boolean) searches with regards to precision, recall and reproducibility. We found substantial differences in the performance of search systems, meaning that their usability in systematic searches varies. Indeed, only half of the search systems analysed and only a few Open Access databases can be recommended for evidence syntheses without adding substantial caveats. Particularly, our findings demonstrate why Google Scholar is inappropriate as principal search system.

We call for database owners to recognise the requirements of evidence synthesis, and for academic journals to re?assess quality requirements for systematic reviews. Our findings aim to support researchers in conducting better searches for better evidence synthesis.