The importance of NOT being Other: Time to address the invisibility of nuanced gender and sexuality in clinical trials

Adam D. N. Williams, Kerenza Hood, Karen Bracken, Gillian W. Shorter

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
39 Downloads (Pure)

Abstract

Background
Representation of all members of society within research, especially those typically underserved, is needed to ensure that trial evidence applies to the relevant population, and that effective interventions are available to all. The lack of appropriate and representative options in demographic questions around sex, gender and sexuality may result in the exclusion of LGBTQIA + people from health research.

Main body
Sex and gender are not the same, yet this is rarely recognised in trial data collection, with the terms sex and gender often being used interchangeably. Sex or gender is often used as a stratification factor at randomisation and/or to define sub-groups at the time of data analysis, so correct data collection is essential for producing high-quality science. Sexuality also suffers from ‘othering’ with identities not being acknowledged but simply provided as an alternative to the perceived main identities. When collecting sexuality information, it is important to consider the purposes of collecting this data.

Conclusion
We call on those involved in trials to consider how sex, gender and sexuality data are collected, with an active consideration of inclusivity. Through the description of all non-straight, non-cisgender people as ‘other’ you may be ignoring the needs of these populations and doing science, yourself, and them a disservice. Inclusivity may require small but important changes to ensure your research findings are inclusive and develop the evidence base for often overlooked populations.
Original languageEnglish
Article number242
JournalTrials
Volume24
DOIs
Publication statusPublished - 30 Mar 2023

Bibliographical note

Open science - yes

Keywords

  • sex
  • gender
  • sexuality
  • trial recruitment
  • trial data collection
  • meta analysis
  • randomised control trial
  • randomized control trial
  • INCLUDE

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