Arthur Ryan is a graduate student in clinical psychology at Emory University. His research focuses on understanding the etiology and neuropathology underlying severe mental illness.
Elaine Walker is a Professor of Psychology and Neuroscience in the Department of Psychology at Emory University and is the Director of the Development and Mental Health Research Program, which is supported by the National Institute of Mental Health. Her research is focused on child and adolescent development and the brain changes that are associated with adolescence. She is also a member of the AJOB Neuroscience editorial board.
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| Arthur Ryan, M.A. |
Over the past several decades, there has been a significant effort to minimize bias against individuals based on ethnicity and other demographic factors through the creation of seemingly impartial and objective criteria across a host of domains. For example, when the United States Federal Sentencing Guidelines were created in the 1980’s, one of their primary goals was to alleviate “...unwarranted disparity among offenders with similar characteristics convicted of similar criminal conduct” [1]. Unfortunately, even well-intentioned efforts such as this one can still have a disparate negative impact upon historically marginalized groups, such as the well-documented disproportionate sentencing of black individuals due to differing rules governing offenses committed with crack vs. powdered cocaine [2]. Concerns about such inadvertent bias are not limited to the legal domain. Agencies that fund clinical investigations are paying greater attention to demographic representativeness and access to participation in health-related research.
Let us consider a hypothetical example, drawn from the authors’ own field of research in a US context, of how seemingly objective research design choices can results in biases in access to research participation. There is increasing evidence that inflammatory factors may play an important role in the etiology of schizophrenia and other psychotic illnesses [3]. One thing researchers do when attempting to understand a complex system like the human brain is to minimize external sources of variance. One readily identifiable correlate of inflammatory markers is body mass index (BMI) [4]. Schizophrenia itself is also correlated with BMI, such that patients tend to have a higher BMI than healthy individuals [5]. So a hypothetical researcher might reasonably say to herself, “Let me compare inflammatory markers in individuals with and without schizophrenia who have a BMI below 25 (BMIs of 25 or greater are considered to be medically overweight). That way, if I find a difference between the groups, I can more strongly conclude that the difference has to do with schizophrenia’s underlying pathology and was not due to individuals with schizophrenia being medically overweight.”
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| Elaine Walker, Ph.D. |
Our hypothetical researcher’s experimental design choice is scientifically defensible and seemingly innocuous, but her decision may have unintended negative consequences. In a study of patients at the Grady Medical Clinic, an Atlanta primary care clinic serving inner city residents, 80% of black American women had a BMI of ≥ 25 [6]. Of particular note, the Grady Health System and its patients regularly participate in mental health research, including our own clinical studies, and the vast majority of those patients— around 85% [7]— are African American. So if our hypothetical researcher had unknowingly gone ahead with her BMI exclusion criterion and was recruiting from a similar population, she would effectively be excluding four out of five black American women from participating in her research, despite the disproportionately high number of black patients served. This would be more than a minor unfairness or lost opportunity for the individual women who could not participate: given the growing research literature showing that various biological and genetic risk markers have differential predictive utility across racial and ethnic groups, this hypothetical study might produce findings that are invalid for minority individuals. Because rates of schizophrenia seem to be similar across various racial groups and nationalities when measured by well-controlled studies, such an omission is not acceptable. If the study yielded results valid largely for one racial group, our hypothetical researcher would also be compromising one of her ethical obligations described under the Belmont Report, which requires that researchers avoid creating unjust patterns in the “...overall distribution of the burdens and benefits of research” [8]. The report explicitly extends this principle to research involving racial minorities and other historically exploited groups.
To reiterate, the preceding example was hypothetical and no such exclusionary criterion was employed in our own work. However, the possibility of research design choices having a discriminatory impact is no hypothetical hazard. In a 2006 review of randomized controlled drug trials, only 24% of participants were women [9], while a 2008 review of trials funded by the National Heart, Lung, and Blood Institute showed a mean female participation rate of 27% [10]. Even non-human females are underrepresented in research, with male-animal-only studies outnumbering female-animal-only studies at a roughly 5 : 1 ratio in neuroscience and pharmacology [11]. Such exclusion is even more notable considering that some conditions may be experienced at higher rates by those left out of such trials. For example, major depression affects women at an approximately 2:1 ratio [12]. So, theoretically, it would be particularly egregious to exclude women from antidepressant medication trials—and any research that sought to create a representative sample should include women at that same 2:1 ratio.
So why do male-only studies still predominate? Because it is cheaper and easier to conduct male-only studies. With less variance among individuals, experimental effects are easier to detect. In addition, male hormones fluctuate less over time and including women in drug trials necessitates extra experimental protections to prevent harm should one of the participants become pregnant. Again, this practice is not simply an unfairness to the individual women who would otherwise want to participate in medical research. FDA studies have shown that drug concentrations in blood and tissue can vary by as much as 40% between men and women, with similar variations in side effect profiles [13]. This shouldn’t be surprising as gene expression may vary between males and females by more than 50% in liver, fat, and muscle tissue [14]. It is clear that such a systematic policy of excluding women from research, even if it lacked any conscious discriminatory intent, could have serious, even life-threatening, consequences for women receiving medical treatment for years to come.
There is no way to completely prevent unintentional discriminatory sequelae of research design choices. And it would be naïve to believe that there will never be genuine tradeoffs that need to be weighed when designing research studies. Sometimes researchers will need to decide between sample representativeness and experimental control. The important point here is that if researchers make their decisions in a reflective and intentional manner, always considering the downstream consequences of their study design choices, they are more likely to identify and mitigate secondary negative consequences of their work. In doing so, they are increasing the scientific value of their work, as well as fulfilling their ethical obligations to promote beneficence and justice with their research.
References
1. United States Sentencing Commission. An Overview of the United States Sentencing Commission.
2. NPR. High Court Rules on Drug Sentencing Disparities.
3. Miller, B. J., Buckley, P., Seabolt, W., Mellor, A. & Kirkpatrick, B. Meta-Analysis of Cytokine Alterations in Schizophrenia: Clinical Status and Antipsychotic Effects. Biol. Psychiatry 70, 663–671 (2011).
4. Festa, A. et al. The relation of body fat mass and distribution to markers of chronic inflammation. Int. J. Obes. 25, 1407–1415 (2001).
5. Homel, P., Casey, D. & Allison, D. B. Changes in body mass index for individuals with and without schizophrenia, 1987–1996. Schizophr. Res. 55, 277–284 (2002).
6. Jacobson, T. A., Morton, F., Jacobson, K. L., Sharma, S. & Garcia, D. C. An assessment of obesity among African-American women in an inner city primary care clinic. J. Natl. Med. Assoc. 94, 1049–1057 (2002).
7. Saunders, S. P. & Campbell, C. L. The Word on the Street: Performing the Scriptures in the Urban Context., (Wipf and Stock Publishers, pp.23, 2006).
8. The National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical principles and guidelines for the protection of human subjects of research. (1979)
9. Geller, S. E., Adams, M. G. & Carnes, M. Adherence to Federal Guidelines for Reporting of Sex and Race/Ethnicity in Clinical Trials. J. Womens Health 15, 1123–1131 (2006).
10. Kim, E. S. H., Carrigan, T. P. & Menon, V. Enrollment of Women in National Heart, Lung, and Blood Institute-Funded Cardiovascular Randomized Controlled Trials Fails to Meet Current Federal Mandates for Inclusion. J. Am. Coll. Cardiol. 52, 672–673 (2008).
11. Beery, A. K. & Zucker, I. Sex Bias in Neuroscience and Biomedical Research. Neurosci. Biobehav. Rev. 35, 565–572 (2011).
12. Kessler, R. C. Epidemiology of women and depression. J. Affect. Disord. 74, 5–13 (2003).
13. Anderson, G. D. Sex and racial differences in pharmacological response: where is the evidence? Pharmacogenetics, pharmacokinetics, and pharmacodynamics. J. Womens Health 2002 14, 19–29 (2005).
14. Yang, X. et al. Tissue-specific expression and regulation of sexually dimorphic genes in mice. Genome Res. 16, 995–1004 (2006).
Want to cite this post?
Ryan, A and Walker, E. (2015). Unintentional discrimination in clinical research: Why the small decisions matter. The Neuroethics Blog. Retrieved on , from http://www.theneuroethicsblog.com/2015/09/unintentional-discrimination-in.html.
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