By Amber Roguski
This is the second post in a two-part blog series- read Part 1, which explores funding body and institutional under-representation of Minority Ethnic individuals, here. The second part of this two-part series explores the under-representation of Minority Ethnic individuals as participants in biomedical research.
This blog is written within the context of United Kingdom (UK) institutions and research, though much can be applied to Global North biomedical research.
‘Minority Ethnic’ in this blog post describes individuals who do not identify as one of the majority White populations of the UK: English / Welsh / Scottish / Northern Irish / British.
Biomedical research is a broad term used to describe scientific enquiry into health and disease.
Part 2: Research Participants
Who is Participating in Biomedical Research?
In theory, anyone can participate in biomedical research and everyone should have equal access to research participation. In practice, and this will be familiar if you read the first part of this blog series, this is rarely the case, with White people 87% more likely to have taken part in UK medical research than people from a Minority Ethnic background [1].
To begin, all research studies involving humans will have strict ‘Inclusion and Exclusion Criteria’. These are a list of conditions which a person must meet to be eligible for study participation. Inclusion and exclusion criteria have a dual purpose: on the one hand, they protect the rights and wellbeing of the potential participant. One common inclusion criterion is ‘Capacity to give informed consent’, while exclusion criteria often specify health conditions which may put the individual at risk if they were to participate in the study.
The second purpose of the inclusion/exclusion criteria is to ensure that the integrity of the data collected is upheld. Exclusion criteria are used to disqualify people based on characteristics which may introduce unwanted factors into the data. For example, if you are interested in researching the effects of heart disease on sleep, you will want to exclude any people from your study who have sleeping problems (such as insomnia or sleep apnoea) as well as heart disease, as their sleep problems would mean you are not purely studying the impact of heart disease on sleep. Exclusion criteria can also be used to exclude people with whom data collection techniques may not be compatible. If you are investigating stress hormone levels in blood, you would want to exclude individuals with blood-clotting conditions or needle phobia from your study.
The problem with inclusion/exclusion criteria is that even though they are written with good intentions – to protect the participant and ensure data are of a high standard and therefore the participant’s involvement was worthwhile – they may disqualify people from one ethnic background more than another.
One such example of this is in electroencephalography (EEG) research, which uses electrodes placed on the scalp to monitor the brain’s electrical activity. As the electrical signals are very small, it is important to get close and strong contact between the scalp and the electrode. Several factors can affect this contact, including sweat, dead skin cells and hair. Specifically, hair types 3 (curly) and 4 (kinky), as described by the Andre Walker Hair Typing System [2], and some hairstyles (including locs and braids) can limit the connection between the scalp and electrode [3]. Therefore, researchers may actively discourage individuals with these hair types from participating in EEG research.
It is important to acknowledge that the primary driver of this discrimination is the EEG equipment, as researchers use equipment which has not been designed with these hair types in mind. Additionally, many researchers will have limited or no experience of working with these hair types and styles, due to a lack of formal training and historical disqualification of these hair types from their field. No matter the reason, this will disproportionately exclude individuals of African- or Oceanian-descent from taking part in EEG research.
Inclusion and exclusion criteria are rigid for a reason: they remove scientific ‘grey areas’ and ensure the scientific integrity of the data collected. Researchers need to be aware of the implications of these criteria in order to adapt their methodologies and create inclusive studies which yield representative data and generalisable conclusions.
Once it is decided who can or cannot take part in a research study, the study needs to be advertised to a suitable, diverse and large group of people. University researchers looking at fundamental processes and aspects of the human condition (usually psychological phenomena such as memory or emotional processing) will often recruit participants from the student population at their institution as it is quick, easy and often will require less stringent ethical review than if the study population were external to the university. The university student body across the UK is ~75% White (though Scotland, Wales and Northern Ireland universities have a considerably higher White student population than England) [4] and therefore recruiting from university student population has a strong potential to bias the research with a majority White participant population. The use of student populations in research is subject to much criticism within the scientific community [5], yet it remains precedent. Though the phenomena being investigated may be so universal and inherent to biological function (such as the fear response) it might be assumed that the population in which they are studied is irrelevant, it is naïve to think that personal experience (which certainly varies between ethnicities) does not influence the process in some way.
Researchers looking to study disease and healthcare outcomes will likely recruit from the healthcare system, utilising hospital departments and GP practices to identify potential participants with healthcare conditions relevant to the study. The majority of BAME individuals live in cities [6], and therefore healthcare research conducted in urban areas are more likely to have an ethnically diverse population of potential participants. However, even in areas with the highest populations of Minority Ethnic groups this does not automatically correspond with equal engagement in healthcare services. For many complex reasons, including difficulty in accessing healthcare services [7], low patient experience satisfaction [8], discriminatory and racist practices [9], unsuitable service-user communication methods [9] and cultural attitudes [10], BAME individuals are more likely to be disengaged from healthcare services and therefore simply might not be contacted regarding research participation opportunities. Different Minority Ethnic groups are subject to different combinations of the above factors and therefore recruitment of BAME participants might also be biased towards certain Minority Ethnic groups over others.
In both instances of participant recruitment, whether from a student population or from a healthcare service, researchers in the UK face the challenge of ensuring their study population are representative and inclusive of Minority Ethnic groups despite being faced with a majority White general population. It is difficult to definitively say when a study population is sufficiently representative and there are no real guidelines beyond the sentiment that research should be as inclusive as possible, where possible. Researchers must decide whether the ethnicity demographics of the study population should be determined by the demographics of the general population, local population or prevalence/incidence of the disease in question [11], though often they may not have the awareness nor data to inform such a decision.
Distrust of medical professionals by Minority Ethnic groups has often been cited as a reason for low research participation rates. This is a phenomenon usually framed within the context of the US [12], which has a history of unethical research studies using African American people as unwilling research subjects [12] [13] [14]. However, there is little evidence to suggest this sentiment exists amongst UK BAME groups [15], and instead willingness to participate in research and likelihood of engagement is far more dependent on awareness of ongoing research studies, clear and culturally-aware communication of the research, relevance to the community [16] and the health status of the individual [1]. It is therefore paramount that researchers ensure their recruitment methods are far-reaching, community-focused and presented to potential participants in an accessible way.
Conclusion
At every ‘level’ in biomedical research, from funding to research participation, there is racial bias and exclusion of Minority Ethnic individuals. The overarching cause of this is institutional racism which drives under-representation of Minority Ethnic researchers and subsequently research conducted with a White lens. Confound this situation with disengagement of Minority Ethnic populations from research participation and our understanding of health and disease becomes skewed to represent White people as the default, when in fact White ethnic groups are the minority in the global context. This has far-reaching implications for the generalisability of research results and healthcare experience and outcomes of Minority Ethnic individuals.
Humans as a species are genetically near-identical. 99.9% of all human genes are the same, with 15% of that variable 0.1% being population-specific (i.e. unique to a particular region or group of people) [17]. Genetics certainly influences health and our likelihood of developing certain diseases, but what arguably plays a larger role are ‘social determinants of health’. These are factors related to the conditions under which we are born, grow, live and age, and they underpin the health inequalities we see affecting BAME groups. Health equity is dependent on recognising and respecting how genetic and environmental factors result in differences between people. The only way we can achieve health equity is to truly understand what causes illness, and to do that we need representation of Minority Ethnic groups in biomedical research.
BAME Health Matters will play a part in this. We are working on resources to support funders, researchers and BAME study participants in order to improve Minority Ethnic group representation at every level of biomedical research, and actively promote the efforts of other organisations in this area. We also aim to conduct research into this area and provide training workshops for researchers to educate in inclusive research practices. To keep up to date with our work, sign up for our newsletter and check out our ongoing projects.
References
[1] Smart, A., & Harrison, E. (2017). The under-representation of minority ethnic groups in UK medical research. Ethnicity and Health. https://doi.org/10.1080/13557858.2016.1182126
[3] Etienne, A., Laroia, T., Weigle, H., Afelin, A., Kelly, S. K., Krishnan, A., & Grover, P. (2020). Novel Electrodes for Reliable EEG Recordings on Coarse and Curly Hair. https://doi.org/10.1101/2020.02.26.965202
[4] Higher Education Student Statistics: UK 2018/19- Student numbers and characteristics. Higher Educastion Statistics Agency (HESA), January 2020. https://www.hesa.ac.uk/news/16-01-2020/sb255-higher-education-student-statistics/numbers. Accessed 24.09.20
[5] Hanel, P. H., & Vione, K. C. (2016). Do Student Samples Provide an Accurate Estimate of the General Public?. PloS one, 11(12), e0168354. https://doi.org/10.1371/journal.pone.0168354
[6] Regional Ethnic Diversity (England and Wales 2011 Census). UK Government, August 2018.
https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/regional-ethnic-diversity/latest. Accessed 24.09.20
[7] BME people and access to health and wellbeing services in Sunderland: A report from BME engagement events. Healthwatch Sunderland, May 2014. http://www.healthwatchsunderland.com/sites/default/files/uploads/BME_people_and_access_to_health_and_wellbeing_services_in_Sunderland.pdf. Accessed 24.09.20
[8] Patient Experience of Primary Care: GP Services (NHS Outcomes Framework). UK Government, March 2019. https://www.ethnicity-facts-figures.service.gov.uk/health/patient-experience/patient-experience-of-primary-care-gp-services/latest. Acceseed 24.09.20
[9] Older BAME people's experiences of health and social care in Greater Manchester. Harries B, Harris S, Hall N and Cotterell N, February 2019. http://www.oldham-council.co.uk/jsna/wp-content/uploads/2018/11/BAME-peoples-experiences-of-health-and-social-care.pdf. Accessed 24.09.20
[10] Marlow, L. A., Wardle, J., & Waller, J. (2015). Understanding cervical screening non-attendance among ethnic minority women in England. British journal of cancer, 113(5), 833–839. https://doi.org/10.1038/bjc.2015.248
[11] Rathore, S. S., & Krumholz, H. M. (2003). Race, ethnic group, and clinical research. BMJ (Clinical research ed.), 327(7418), 763–764. https://doi.org/10.1136/bmj.327.7418.763
[12] Scharff, D. P., Mathews, K. J., Jackson, P., Hoffsuemmer, J., Martin, E., & Edwards, D. (2010). More than Tuskegee: understanding mistrust about research participation. Journal of health care for the poor and underserved, 21(3), 879–897. https://doi.org/10.1353/hpu.0.0323
[13] Ojanuga, D. (1993). The medical ethics of the “father of gynaecology”, Dr J Marion Sims. Journal of Medical Ethics. https://doi.org/10.1136/jme.19.1.28
[14] Beskow, L. M. (2016). Lessons from HeLa Cells: The Ethics and Policy of Biospecimens. Annual Review of Genomics and Human Genetics. https://doi.org/10.1146/annurev-genom-083115-022536
[15] Marlow, L. A., Wardle, J., & Waller, J. (2015). Understanding cervical screening non-attendance among ethnic minority women in England. British journal of cancer, 113(5), 833–839. https://doi.org/10.1038/bjc.2015.248
[16] Redwood, S., & Gill, P. S. (2013). Under-representation of minority ethnic groups in research--call for action. The British journal of general practice : the journal of the Royal College of General Practitioners, 63(612), 342–343. https://doi.org/10.3399/bjgp13X668456
[17] Huang, T., Shu, Y. & Cai, Y. Genetic differences among ethnic groups. BMC Genomics 16, 1093 (2015). https://doi.org/10.1186/s12864-015-2328-0