Diversified innovations in the health sciences: Proposal for a Diversity Minimal Item Set (DiMIS) Articles uri icon

publication date

  • June 2023

volume

  • 33

International Standard Serial Number (ISSN)

  • 2352-5541

abstract

  • Background: Science strives to provide high-quality evidence for all members of society, but there
    continues to be a considerable gender and diversity data gap, i.e., a systematic lack of data for
    traditionally underrepresented groups. Gender and other diversity domains are related to
    morbidity, mortality, and social and economic participation, yet measures as well as evidence
    regarding how these domains intersect are missing. We propose a brief, efficient Diversity Minimal Item Set (DiMIS) for routine data collection in empirical studies to contribute to closing the
    diversity and gender data gap. We focus on the example of health but consider the DiMIS
    applicable across scientific disciplines.
    Methods: To identify items for the DiMIS across diversity domains, we performed an extensive
    literature search and conducted semi-structured interviews with scientific experts and community
    stakeholders in nine diversity domains. Using this information, we created a minimal item set of
    self-report survey items for each domain.
    Findings: Items covering nine diversity domains as well as discrimination experiences were
    compiled from a variety of sources and modified as recommended by experts. The DiMIS focuses
    on an intersectional approach, i.e., studying gender, age, socioeconomic status, care responsibilities, sexual orientation, ethnicity, religion, disability, mental and physical health, and
    their intersections. It allows for data sets with comparable assessments of gender and diversity
    across multiple projects to be combined, creating samples large enough for meaningful analyses.
    Interpretation: In proposing the DiMIS, we hope to advance the conversation about closing the
    gender and diversity data gap in science.

subjects

  • Computer Science

keywords

  • diversity science; equity; health disparities; gendered innovation