Exchanging words: Engaging the challenges of sharing qualitative research data

James M. DuBois, Jessica Mozersky, Meredith Parsons, Heidi A. Walsh, Annie Friedrich, Amy Pienta

Research output: Contribution to journalArticlepeer-review

Abstract

In January 2023, a new NIH policy on data sharing went into effect. The policy applies to both quantitative and qualitative research (QR) data such as data from interviews or focus groups. QR data are often sensitive and difficult to deidentify, and thus have rarely been shared in the United States. Over the past 5 y, our research team has engaged stakeholders on QR data sharing, developed software to support data deidentification, produced guidance, and collaborated with the ICPSR data repository to pilot the deposit of 30 QR datasets. In this perspective article, we share important lessons learned by addressing eight clusters of questions on issues such as where, when, and what to share; how to deidentify data and support high-quality secondary use; budgeting for data sharing; and the permissions needed to share data. We also offer a brief assessment of the state of preparedness of data repositories, QR journals, and QR textbooks to support data sharing. While QR data sharing could yield important benefits to the research community, we quickly need to develop enforceable standards, expertise, and resources to support responsible QR data sharing. Absent these resources, we risk violating participant confidentiality and wasting a significant amount of time and funding on data that are not useful for either secondary use or data transparency and verification.

Original languageEnglish
Article numbere2206981120
JournalProceedings of the National Academy of Sciences of the United States of America
Volume120
Issue number43
DOIs
StatePublished - 2023

Keywords

  • data de-identification
  • data sharing
  • FAIR principles
  • qualitative research
  • research compliance

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