Accurate and affirming messaging in research communications

5 minute read

Written by: Lauren Wolfe -

Recently the Women’s HIV Research Collaborative (WHRC) released a call to action for groups to commit to scientifically accurate and culturally affirming messaging about study populations in COVID-19 and HIV research. While the Coop does not publish on or conduct any research in these areas, a large portion of what we do is related to data and scientific communication. We feel that this call to action is important and relevant to our work so we have signed to show our commitment to this effort. This post will go into what actions the letter calls for and why we believe this effort is so important.

Finding humanity in data

Studies and datasets that have human participants require extra care. We often talk about that extra care in terms of privacy, HIPPA laws, and data governance. While these things are incredibly important the conversation needs to go further. When we only talk about participants in terms of the data that they provide to a study, it becomes easy to forget that each data point is representative of a human who’s personhood and identity extend far beyond the confines of whatever metrics we’ve captured. As Inioluwa Deborah Raji writes in her paper The Discomfort of Death Counts: Mourning Through the Distorted Lens of Reported COVID-19 Death Data:

It is disquieting to imagine these data points as anything other than a compact resource, one in which we as data scientists and dashboard builders feel entitled to package and expose, to harvest and exploit. But data are not bricks to be stacked, oil to be drilled, gold to be mined, opportunities to be harvested. Data are humans to be seen, maybe loved, hopefully, taken care of.

There is a lot of work to be done to bring a more humane approach to data science and research. Dr. Raji highlights one aspect of this - how filtering, aggregating, and analyzing COVID-19 death counts flattens and dehumanizes the people these numbers represent. She reminds us that data science is human subjects research and that we need to do better by the humans that our data is supposed to represent.

Accurate and affirming messaging

The WHRC letter aims to address a slightly different facet of how research and data science can dehumanize participants. Their focus is on how we communicate in our research papers and more mainstream media about participants that take part in a study.

In their statement, the WHRC highlights how this year’s groundbreaking news about a long-acting injectable drug for HIV prevention was communicated to the public. They note that in the hours after the initial announcement major press releases and media outlets referred to the participants in the study using a broad range of language. In the image below, they have indicated how to describe the study participants accurately and juxtapose this with some of the inaccurate descriptions found in the articles written on the study.

description of study participants

The WHRC writes:

The broad range of inaccurate and insensitive descriptions of these study populations signals a pervasive, systemic issue in research reporting that is certainly not limited to these two studies.

3 commitments

The Women’s HIV Research Collaborative’s statement invites you to join them by signing on to 3 commitments:

  1. Commit to scientific accuracy. When we fail to describe study populations with precision, we undermine the science. For example, when a study finds that a product works for cisgender men who have sex with men, it is inaccurate to say that it works for all men who have sex with men. When a study includes only cisgender women, it is inaccurate to say that its results apply to all women. Transgender women are women. Transgender men are men. We implore protocol teams to set the example; if you use precise language to describe the populations in your studies, others will follow. We urge reporters and community members to do your fact-checking; verify the study populations before you start writing or reporting. In the name of science, use the terms ‘cisgender’ and ‘transgender’ when describing study populations.
  2. Commit to affirming language. Language matters. It reveals the value we place on respecting people and how they want to be treated. There is a direct link between the respect we show for people and their participation in research. NIAID has released an HIV Language Guide that was developed with input from many community stakeholders. We invite you to commit to implementing this guidance in your own work. The British Columbia Centre for Disease Control released a COVID-19 Language Guide that we also endorse.
  3. Commit to equity in representation. Structural factors such as racism and misogyny continue to echo throughout clinical research, resulting in the underrepresentation of the most affected populations. When a study does not include cisgender women and/or transgender people, ask why. When a study in the US has no plan for engaging Black, Latinx, and Native participants, team up, and create one. When a COVID-19 study excludes people living with HIV with no scientific justification, demand an amendment–and win! We applaud the HPTN and advisory groups such as the HPTN Black Caucus for setting an example in HPTN 083, which set, met, and exceeded measurable goals for the recruitment of transgender women and African American participants. We celebrate the activists and advocates holding COVID-19 researchers accountable for equitable and ethical inclusion. We invite all of our colleagues to ensure that these examples are followed and improved upon.

Take action!

  • If this effort resonates with you or your group and is something you’ll implement in your work you can view the full document and sign on here.
  • For more information on bias-free and affirming language check out the APA Style Guide for Bias-Free Language and implement it in your life and work.
  • FHREE (Fred Hutch Rainbow Employees for Equity) LGBTQ+ Employee Resource Group is working on building out language guidance for researchers at the Hutch. This effort is currently seeking researchers/labs that would be willing to beta test the guidelines. If you’re interested in taking part in this please contact Anders McConachie for more information!