As an engaged and interdisciplinary research institute at The Ohio State University, the Kirwan Institute for the Study of Race and Ethnicity is a national leader in research into how implicit biases can unconsciously shape individuals’ cognition, attitudes, and even behaviors.  Through our annual publication, State of the Science: Implicit Bias Review, we work to deepen society’s understanding of how implicit bias operates across various sectors of society, including health care, criminal justice, employment, and education.  Indeed, a large body of social science evidence has shown that unconscious, automatically activated, and pervasive cognitive associations related to race, ethnicity, gender, age, and other identities can impact decision-making and judgments without our awareness.


These research findings have serious, far-reaching implications for individuals in a wide range of sectors. For instance, research suggests that implicit bias may skew teachers’ perceptions of student behavior [1-5], as well as their perceptions of students’ potential for academic achievement [6]. Similarly, there’s evidence demonstrating the multitude of ways in which implicit bias may impede on all aspects of the employment process for even the most well-meaning institution [7-10].  Bias has also been found to impact the health care realm by influencing clinical decision-making  [11, 12] and impacting the patients’ overall experience [13] and perceptions of care [14].


The reality is, all moments of human decision-making are susceptible to the influence of implicit bias; whether positive or negative, those biases have grave affects on outcomes in all sectors of our society.


Given the widespread affects of implicit bias, it is easy to see why understanding and mitigating implicit bias matters. Moreover, if health care providers are to embody the altruistic values expressed in the Hippocratic Oath, working to mitigating implicit bias is imperative.


Implicit Bias in Health Care:


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[1] Schubert Center for Child Studies, Play, Implicit Bias and Discrimination in Early Childhood: Implications for Childhood Development C.W.R. University, Editor. 2014: Cleveland, OH. p. 1-6.

[2] Okonofua, J.A. and J.L. Eberhardt, Two Strikes: Race and the Disciplining of Young Students. Psychological Science, 2015. 26(5): p. 617-624.

[3] Staats, C. and D. Contractor, Race and Discipline in Ohio Schools: What the Data Say, The Kirwan Institute, Editor. 2014, The Ohio State University

[4] Capatosto, K., Ohio discipline data: An analysis of ability and race, The Kirwan Institute, Editor. 2015, The Ohio State University

[5] Wright, R. A., Black Girls Matter, Too: A Gender and Race Examination of Implicit Bias in Ohio School Discipline Disparities. 2016, The Kirwan Institute, Editor. 2016, The Ohio State University

[6] Van den Bergh, L., et al., The Implicit Prejudice Attitudes of Teachers: Relations to Teacher Expectations and the Ethnic Achievement Gap. American Educational Research Journal, 2010. 47(2): p. 497-527.

[7] Bertrand, M. and S. Mullainathan, Are Emily and Greg More Employable than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination. The American Economic Review, 2004. 94(4): p. 991-1013.

[8] Reeves, A.N., Written in Black & White: Exploring Confirmation Bias in Racialized Perceptions of Writing Skills, in Yellow Paper Series. 2014, Nextions.

[9] Beattie, G., Our Racist Heart?: An Exploration of Unconscious Prejudice in Everyday Life. 2013, London: Routledge. 302.

[10] Moss-Racusin, C.A., et al., Science Faculty’s Subtle Gender Biases Favor Male Students. Proceedings of the National Academy of Sciences, 2012. 109(41): p. 16474-16479.

[11] Sabin, J.A. and A.G. Greenwald, The Influence of Implicit Bias on Treatment Recommendations for 4 Common Pediatric Conditions: Pain, Urinary Tract Infection, Attention Deficit Hyperactivity Disorder, and Asthma. American Journal of Public Health, 2012. 102(5): p. 988-995.

[12] Green, A.R., et al., Implicit Bias among Physicians and its Prediction of Thrombolysis Decisions for Black and White Patients. Journal of General Internal Medicine, 2007. 22(9): p. 1231-1238.

[13] Hagiwara, N., D.A. Kashy, and L.A. Penner, A novel analytical strategy for patient-physician communication research: The one-with-many design. Patient Education and Counseling, 2014. 95: p. 325-331.

[14] Cooper, L.A., et al., The Associations of Clinicians’ Implicit Attitudes About Race with Medical Visit Communication and Patient Ratings of Interpersonal Care. American Journal of Public Health, 2012. 102(5): p. 979–987.