Addressing biases at an earlier stage of medical career is critical for future physicians engaging with diverse patients, since it is established that bias negatively influences provider-patient interactions18, clinical decision-making19 and reduces favorable treatment outcomes2. We set out with an intention to explore how bias is addressed within the medical curriculum. An obvious question we posed was how has the trend in bias research changed over time, more specifically a) what is the timeline of papers published? b) what bias characteristics have been studied in the physician-trainee population and c) how are these biases addressed? With the introduction of ‘standards of diversity’ by the Liaison Committee on Medical Education, along with the Association of American Medical Colleges (AAMC) and the American Medical Association (AMA)20,21, we certainly expected and observed a sustained uptick in research pertaining to bias. As shown here, research addressing bias in the target population (MS and Res) is on the rise, however only 139 papers fit our inclusion criteria. Of these studies, nearly 90% have been published since 2005 after the “Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care” report was published in 20035. However, given the well documented effects of physician held bias, we anticipated more research pertaining to bias at the medical student or resident level.
A key component from this study was that we generated descriptive categories of biases. Sorting the biases into descriptive categories helps to identify a more targeted approach for a specific bias intervention, rather than to broadly reduce bias as a whole. In fact, our analysis found a number of publications (labeled “non-specified bias” in Table 1.) which studied implicit bias without specifying the patient attribute or the characteristic that the bias was against. In total, we generated 11 descriptive categories of bias from our mapping review which are shown in Table 1 and Fig. 3. Further, our bias descriptors grouped similar kinds of biases within a single category. For example, the category, “disease specific stigma” included papers that studied bias against any type of disease (Mental illness, HIV stigma, diabetes) or a condition (Pain management) although the diseases or conditions themselves grouped under the same bias category are unique.
Previous implicit bias intervention strategies have been shown to be ineffective when biased attitudes of participants were assessed after a lag22. Understanding the descriptive categories of bias and previous existing research efforts, as we present here is only a fraction of the issue. The theory of “cognitive bias”231 and related branches of research24–28 have been studied in the field of psychology for over three decades. Thereafter, psychologists have classified cognitive bias errors into different types, grounded in heuristics29. It is only recently that cognitive bias theory has been applied to the field of medical education, to explain its negative influence on clinical decision-making pertaining only to racial minorities1,2, 10–12,30. In order to elicit meaningful changes with respect to targeted bias intervention, it is necessary to understand the psychological underpinnings (attitudes) underlying a certain descriptive category of bias (behaviors). It calls for a push for deeper understanding of one’s attitude/s underlying one’s biased behavior/s31. The questions we need to ask ourselves are: a) Can these descriptive biases be identified under certain type/s of cognitive errors that elicits the bias and vice versa b) Are we working towards a change in attitudes or a change in behaviors? and c) What are ways in which we can positively influence an attitude change in order to overcome a specific behavior over longer periods of time? And most importantly, are we creating a culture of voluntary debiasing enrollment by participants as opposed to mandating it? Therefore, an interdisciplinary approach, a marriage between cognitive psychologists and medical educators, is key in targeting biases held by medical students, residents and ultimately future physicians. This review may also be of interest to behavioral psychologists keen on providing targeted debiasing strategies to clinicians depending on the characteristics (age, weight, sex or race) the portrayed bias is against.
The next element in change is directing intervention strategies at the right stage in clinical education. Our study demonstrated that most of the research collected at the medical student level was focused on documenting evidence of bias. The ratio of research in favor of intervening strategies soared only at the resident level (see Fig. 3). However, it would be prudent to begin the bias intervention processes earlier in learning, rather than debiasing at a later stage32.
This study has limitations. First, the list of the descriptive bias categories that we generated was not grounded in any particular theory so assigning a category was subjective. Further, we did not attempt to categorize these bias characteristics (Table 1) into various types of cognitive errors33 as it is out of our scope of expertise. However, this would be an opportunity for future research. Additionally, our review did not assess the effectiveness of the intervention strategies mentioned in the included research articles. Future work would aim at evaluating quality and assessing the effectiveness of strategies over time.