Category Archives: Resource Highlights

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Learning How to Conduct a Systematic Review

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Thinking about embarking on a systematic review (SR) research project soon? Planning to host some summer trainees or incoming fellows who may be interested in learning more about how to conduct a systematic review?

Here’s a list of SR training resources available to you via the MSK Library:

Cochrane Interactive Learning

Cochrane Interactive Learning is an online introductory course on how to conduct a systematic review of interventions. To gain access to learning modules users will need to register first. Cochrane recommends that users register for an account onsite. When offsite, users may be prompted with a proxy message. Users will need to click the “Please click here first” link within the proxy message to complete registration. Additional instructions are available here.

Covidence SR project management software vendor training opportunities:

Covidence Academy
Find helpful tips and tools for getting started on your systematic review with Covidence.

Covidence Knowledgebase
Peruse Covidence’s library of FAQs and training articles.

Covidence vendor training
You can choose to register for a free weekly “live” in-person Covidence 101 class or listen to the recording of a recent session “On Demand”.

MSK Library classes

Introduction to Systematic Reviews (Online Webinar)
Getting started with a systematic review, but now sure where to start? In this 1-hour session, you’ll learn the basics of the systematic review process, plus key systematic review tools, resources, and guidelines.

Covidence
Covidence is a web-based software platform that streamlines the production of systematic reviews. This class provides an overview of the key systematic review project steps supported by Covidence.

Systematic Review Service LibGuide

LibGuide packed with links to helpful resources and information about collaborating with a MSK Research Informationist to publish your Systematic Review.

Questions? Ask Us at the MSK Library.

Race and Ethnicity-related 2022 MeSH changes

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Over the last year, many stakeholders involved in scholarly publishing have been revisiting the terminology used for reporting race and ethnicity in biomedical literature, for example:

Flanagin A, Frey T, Christiansen SL; AMA Manual of Style Committee. Updated Guidance on the Reporting of Race and Ethnicity in Medical and Science Journals. JAMA. 2021 Aug 17;326(7):621-627. 

Flanagin A, Frey T, Christiansen SL, Bauchner H. The Reporting of Race and Ethnicity in Medical and Science Journals: Comments Invited. JAMA. 2021 Mar 16;325(11):1049-1052. 

In 2022, the National Library of Medicine, producer of PubMed/MEDLINE, also made changes to the Medical Subject Headings (MeSH) related to race and ethnicity, replacing multiple headings with more up-to-date terminology that better matches with the latest United States Census terminology. Among the 24 changes to MeSH headings this year were:

African Continental Ancestry Group >>>> Blacks
American Natives  >>>>  American Indians or Alaska Natives
Asian Continental Ancestry Group  >>>>  Asians
Continental Population Groups   >>>>  Racial Groups
Ethnic Groups >>>>  Ethnicity
European Continental Ancestry Group >>>> Whites
Hispanic Americans  >>>>  Hispanic or Latino
Oceanic Ancestry Group  >>>>  Native Hawaiian or Other Pacific Islander

Below is a more detailed view of how the MeSH Tree Structures were affected by the changes. To compare, here is the Population Groups Tree from MeSH 2021:
2022 MeSH replacements:

“Ethnicity”[Mesh]

A group of people with a common cultural heritage that sets them apart from others in a variety of social relationships.

“Racial Groups”[Mesh]

Groups of individuals with similar physical appearances often reinforced by cultural, social and/or linguistic similarities.

 

 

 

 

 

 

 


2022 MeSH additions: (to MeSH trees other than “Population Groups”)

“Health Disparity, Minority and Vulnerable Populations”[Mesh] 

Groups of persons whose special characteristics make them a minority, vulnerable, and frequently subjected to conditions with limited levels of access to health care and other opportunities. (Most of the 2021 “Ethnic Groups” MeSH tree terms were moved here.) 

“Ethnic and Racial Minorities”[Mesh]

Socially constructed groups of people who differ in race, color or national, religious, or cultural origin from the dominant group and is often the majority population of the country in which they live. Ethnic minority groups generally share a common sense of identity and common characteristics such as language, religion, tribe, nationality, race, or a combination thereof.

 

 

 


The MeSH vocabulary is reviewed annually and revised on an “as needed” basis to best represent the latest subject matter appearing in the biomedical literature. It is not perfect and always a work in progress that grows and changes organically. Everyone is welcome to write to the NLM help desk to submit a request for a change or addition to the MeSH vocabulary.

Questions? Ask Us at the MSK Library.

Tools for Ranking Journals by Impact

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Many considerations should factor into a well-made decision about which journal(s) an author should target for manuscript submission. (For more info, see the MSK Library’s Support for Authors LibGuide.) 

As they explore their options, it’s often useful for authors to get a sense of how reputable a particular journal title is based on how this journal ranks – in terms of impact – versus other journals within the same discipline. In general, journal impact metrics are generated using a mathematical algorithm that is largely based on article citation counts over a pre-specified time period. Citation count data can provide some indication of a journal’s influence and reach, particularly when considered relative to other journals.

Below are three tools (two subscription databases available via the MSK Library and one free online search engine) that can be used to generate journal impact ranking information that can aid with the journal selection process.

Journal Impact FactorsTM – and the Journal Citation Reports (JCR) rankings that they lead to – are generated using two years-worth of article citation data compiled in Clarivate’s Web of Science database. This metric has been around for over 50 years, and was developed by the originator of the citation analysis concept, Eugene Garfield, who is often considered the grandfather of information science and scientometrics. 

See more details on how the Journal Impact FactorTM is calculated.

Elsevier generates it own impact metric, called the CiteScoreTM, by using the citations to articles, reviews, conference papers, book chapters and data papers published over a four-year publication window. Similar to Clarivate, Elsevier can generate these metrics because the data needed for the calculations is available from its flagship Scopus database.

See more details on how the CiteScoreTM is calculated.

Google Scholar, although not a structured database populated with records that have standard fields (as is the case in JCR and Elsevier’s Scopus Sources) still collects citation data that it compiles via the Google Scholar search crawler. It then uses citation data to generate an h-index type metric for the entire journal, as opposed to the usual use of the h-index to evaluate the productivity of an individual researcher. Google Scholar h5 metrics are calculations based on the citation count to published items from the last five complete calendar years.

See more details on how Google Scholar h-based metrics are calculated.

Be sure to check out the MSK Library’s Measuring Research Impact class and the Evaluating Journal Quality class if you have questions, or Ask Us!