NIH and its peer reviewers take research integrity very seriously, particularly the topics of confidentiality and plagiarism in research applications, as they are integral to the review process. Borrowing text from a colleague’s previously submitted application without permission and proper attribution not only undermines the peer review process but also risks negatively impacting funding decisions, harming patients in clinical studies, and jeopardizing public trust in scientific research.
As a case in point, NIH Deputy Director for Extramural Research Dr. Michael Lauer brings attention to a relevant scenario in his Open Mike blog post “Case Study in Research Integrity: This Application Feels Familiar,” in which he discusses how NIH investigates plagiarism in the grant application process and reminds the research community about the importance of Maintaining Confidentiality within the peer review process.
As the case study describes:
While serving as a peer reviewer, Dr. ABC found themselves assigned to an application containing research that looked very similar to their own application submitted several years prior. The current project identifies Dr. XYZ as the project’s lead, who also serves as principal investigator on other NIH awards. Dr. ABC contacted the NIH scientific review officer (SRO) overseeing the study section, the SRO relayed the concern to NIH’s Office of Extramural Research (OER), and OER began an investigation of Dr. XYZ’s application.
Upon inspection, the Procedures and Data Collection sections in Dr. ABC’s application and Dr. XYZ’s applications were too similar to be coincidental. As it turns out, Dr. XYZ gained access to Dr. ABC’s application through a collaborator who served previously as a peer reviewer. NIH doesn’t just consider pulling information from another application without permission and attribution to be plagiarism—peer reviewers are prohibited from using and sharing materials from a confidential peer review meeting, and doing so constitutes a serious breach of confidentiality.
Read the blog post linked above to find out what actions NIH and Dr. XYZ’s institution took next.
Generative AI Tools Merit Caution
You may be thinking of using artificial intelligence (AI) tools such as ChatGPT to help write your next grant application. If you choose to do so, be aware: AI tools may plagiarize, falsify, or fabricate information. You, as an applicant, share responsibility for ensuring integrity in the scientific review process, and we will hold you accountable even if AI technology is the source of noncompliance.
Peer reviewers, however, are prohibited from using AI generators for peer review of applications due to confidentiality concerns, as outlined in NIH’s Guide notice The Use of Generative Artificial Intelligence Technologies Is Prohibited for the NIH Peer Review Process.
Resources
Read NIH’s page on Research Misconduct—Overview and the Confidentiality Agreement that peer reviewers must certify and sign before serving in a review meeting. Additionally, read NIH’s Guide notice on Maintaining Security and Confidentiality in NIH Peer Review: Rules, Responsibilities and Possible Consequences.
To detect scientific overlap in applications, NIH’s eRA system uses text-mining software to flag when two applications appear to be redundant. NIH staff then manually review the issue and consider potential overlap on a case-by-case basis. Learn more about that related topic in our article “Don’t Overlook the Three Types of Overlap.”