Addressing health inequalities: REP-EQUITY toolkit aims for fairer research representation

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In a recent study published in Nature Medicine, researchers created the REP-EQUITY toolbox for capturing an equitable and representative sample for health research studies.

Study: A toolkit for capturing a representative and equitable sample in health research. Image Credit: Hooppe/Shutterstock.com
Study: A toolkit for capturing a representative and equitable sample in health research. Image Credit: Hooppe/Shutterstock.com

Background

Research participants are often underrepresented in the general population, limiting generalizability and perpetuating health inequities. The coronavirus disease 2019 (COVID-19) has highlighted the need to apply findings to underserved populations, such as minorities, and understanding structural disparities and using evidence-based measures is crucial to increase research representativeness.

About the study

The present study researchers developed the REP-EQUITY toolbox to obtain an equitable and representative sample for health-related research.

The team developed the toolset through a comprehensive data search and consensus workshop, including researchers, NIHR Birmingham Biomedical Research Centre (BRC) topic leads, and patient as well as public participation and engagement (PPIE) panel members.

The team reviewed health-related articles, recommendations, toolkits, and approaches for obtaining representative sample populations, including underprivileged communities, from various databases, including Google Scholar, BASE, Trip, and National Grey Literature. Two researchers reviewed the data and handled inconsistencies by consensus.

The researchers excluded existing guidelines and reports on a particular area of research, only publishing abstracts, identifying underrepresented groups, emphasizing the requirement for additional research, and describing frameworks developed to enhance the involvement of neglected groups in research activities but not in sample selection.

The PPIE panel supervised the study, defining the scope and objectives of the project, choosing search terms for gray literature, incorporating the public in the workshop, and developing main messages for distribution. The toolbox sought to identify health research-related methods and frameworks to obtain a sample representative of the population, including underprivileged communities.

The researchers adjusted search keywords and phrases iteratively with search professionals and PPIE members. They retrieved data from eligible papers using a custom-designed predetermined form. The team built the draft toolkit on a framework designed in line with the research proposal development stages. They organized data from systematic reviews into framework phases, structured into a sequence of methodological procedures, and presented descriptively.

The toolkit was improved through a consensus workshop, a retrospective study, and a logical quick analysis technique. The usability of the toolkit was also investigated, with a preliminary coding framework created to refine its presentation and ensure its effectiveness.

Results

The team designed the REP-EQUITY toolbox with the help of four patients and general public members from various backgrounds. It emphasizes the involvement of underrepresented populations in research, emphasizing equity rather than equality. Four studies were created in Australia, one in the Republic of Ireland, two in the United Kingdom, and four in the United States after searching 2,209 studies. Four publications propose frameworks and strategies to capture a population-representative sample that includes underprivileged populations, three of which have an equity focus. The patient and public panel recommended the format and location of the workshop on November 14, 2022.

The prototype REP-EQUITY toolbox, divided into seven sections, reflected the study design route, identifying relevant groups, goals, sample needs, recruitment goal considerations, external factor management, assessment, and legacy. The content and applicability of the toolkit in informing the selection of representative research samples were generally agreed upon by workshop participants.

Reviewing current data, acquiring additional expertise, assessing potential research locations and sites of interest, and finding the proportion of persons with underserved characteristics can help determine whether underprivileged populations are crucial to a study issue.

Researchers must decide if the objective of equity and representativeness is testing hypotheses regarding potential differences based on underserved characteristics, generating hypotheses regarding probable differences based on neglected factors, or guaranteeing an equitable and just delivery of the hazards and advantages of research participation.

Using published literature or health data sources, the researchers could define sample proportions based on groups with a particular clinical indication or illness, the percentage of underrepresented populations (institutionally, locally, or nationally), or by regulating the prevalence and mortality rates of diseases, as needed, using published data or sources of health information.

The sampling strategy is crucial in cases where recruiting objectives are undetermined by sample size estimates. Researchers may examine cross-study comparison, generalization, and equity using transparent reporting. Efforts to obtain an accurate and fair sample can result in long-term outcomes that encourage best practices and inform future research regarding establishing advisory groups, participant registries, and connections with communities during research activities, besides adding to the body of evidence after study completion.

Based on the findings, the toolbox, produced through a systematic review and consensus workshop with 24 participants, is a guide for fostering representational and equitable participation in research. It includes seven processes for investigators to consider when selecting a representative sample, such as defining underrepresented populations, aiming for equality, calculating sample percentage, setting recruiting objectives, controlling external influences, evaluating representation, and acknowledging toolkit legacy.

Journal reference:
Pooja Toshniwal Paharia

Written by

Pooja Toshniwal Paharia

Dr. based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

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