Research Impact Metrics

When demonstrating author productivity and impact the most common metric used is the H-Index. 

In order to help ensure more accurate metrics for themselves, authors would be wise to sign up for and use stable author identifier numbers like an ORCiD to help validate which publications are theirs, identify themselves uniquely among others with similar names, help track their own papers if they have had name changes, and improve the findability of other types of their outputs such as blog posts, conference papers, and posters.

Additionally, social media impact can be measured through ImpactStory.

Author profiles and identification numbers are the best way to disambiguate you and your citations from an author with a similar name. These profiles  are essential to calculating metrics like the H-Index and by signing up for and managing your authorial profiles you will ensure the accuracy of the citations attributed to you and the associated metric outputs.

First suggested in 2005 by Hirsch in his article Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National academy of Sciences, 102(46), 16569-16572.

The H-index is a metric representing the intersection of an author's productivity (publication count) and impact (citation count).The basic formula is that : h is the number of articles greater than h that have at least h citations. For example, an h-index of 5 means that there are 5 items that have 5 citations or more.

There are major caveats to using this metric:

• It will vary greatly for authors in different subject fields, as different fields have different publishing norms.
• It does not take author role/contribution into account (1st, 2nd, last author placement)
• There are statistical validity issues with the metric because h-index has a preference towards scholars who produce many moderately cited publications over those who prefer to produce a few high impact papers.
• It should not be the only metric you use to assess impact
• It should not be used to compare researchers except in very few instances - see the section below on Comparing Researchers for more information.

Further Reading on the H-Index

• Teixeira da Silva JA, Dobránszki J. Multiple versions of the h-index: Cautionary use for formal academic purposes. Scientometrics. 2018 May 1;115(2):1107-13
• Costas R, Franssen T. Reflections around 'the cautionary use' of the h-index: response to Teixeira da Silva and Dobránszki. Scientometrics. 2018;115(2):1125-1130.
• Bollen, J., Van de Sompel, H., Hagberg, A., & Chute, R. (2009). A Principal Component Analysis of 39 Scientific Impact Measures. PLoS ONE, 4(6). 

It is usually inappropriate to compare researchers to each other using the H-index.

Any kind of comparisons will have the best results only if the researchers compared are:

1. in the same field, in the same discipline (for example, a Toxicologist in the Biochemistry Department whose research focuses on environment toxicology should not be compared with an pharmaceutical toxicologist even though both are in the Biochemistry field.)
2. at the same stage of their career
3. have been tenured for a similar length of time
4. be published in similar journals

And always be aware that there are systemic reasons why two researchers may not have similar scholarly output: funding, family needs, career path, research topic choice, as well as the broader issues  and impacts of gender, racial, socio-economic, and class status.

There are three providers that calculate the H-index for authors (Scopus, Web of Science, and Google Scholar).  Each one will give a different number because each has different coverage , benefits, and limitations.

The key is to choose one source and be consistent because there is no one official H-index for a person.