A patient should not expect to receive a lower standard of care because of her race, age or any other irrelevant characteristic. However, implicit associations (unconscious, uncontrollable, or arational processes) may influence our judgements resulting in bias. Implicit biases occur between a group or category attribute, such as being black, and a negative evaluation (implicit prejudice) or another category attribute, such as being violent (implicit stereotype) [1].Footnote 1 In addition to affecting judgements, implicit biases manifest in our non-verbal behaviour towards others, such as frequency of eye contact and physical proximity. Implicit biases explain a potential dissociation between what a person explicitly believes and wants to do (e.g. treat everyone equally) and the hidden influence of negative implicit associations on her thoughts and action (e.g. perceiving a black patient as less competent and thus deciding not to prescribe the patient a medication).

The term ‘bias’ is typically used to refer to both implicit stereotypes and prejudices and raises serious concerns in healthcare. Psychologists often define bias broadly; such as ‘the negative evaluation of one group and its members relative to another’ [2]. Another way to define bias is to stipulate that an implicit association represents a bias only when likely to have a negative impact on an already disadvantaged group; e.g. if someone associates young girls with dolls, this would count as a bias. It is not itself a negative evaluation, but it supports an image of femininity that may prevent girls from excelling in areas traditionally considered ‘masculine’ such as mathematics [3]. Another option is to stipulate that biases are not inherently bad, but only to be avoided when they incline us away from the truth [4].

In healthcare, we need to think carefully about exactly what is meant by bias. To fulfil the goal of delivering impartial care, healthcare professionals should be wary of any kind of negative evaluation they make that is linked to membership of a group or to a particular characteristic. The psychologists’ definition of bias thus may be adequate for the case of implicit prejudice; there are unlikely, in the context of healthcare, to be any justified reasons for negative evaluations related to group membership. The case of implicit stereotypes differs slightly because stereotypes can be damaging even when they are not negative per se. At least at a theoretical level, there is a difference between an implicit stereotype that leads to a distorted judgement and a legitimate association that correctly tracks real world statistical information. Here, the other definitions of bias presented above may prove more useful.

The majority of people tested from all over the world and within a wide range of demographics show responses to the most widely used test of implicit attitudes, the Implicit Association Test (IAT), that indicate a level of implicit anti-black bias [5]. Other biases tested include gender, ethnicity, nationality and sexual orientation; there is evidence that these implicit attitudes are widespread among the population worldwide and influence behaviour outside the laboratory [6, 7]. For instance, one widely cited study found that simply changing names from white-sounding ones to black-sounding ones on CVs in the US had a negative effect on callbacks [8]. Implicit bias was suspected to be the culprit, and a replication of the study in Sweden, using Arab-sounding names instead of Swedish-sounding names, did in fact find a correlation between the HR professionals who preferred the CVs with Swedish-sounding names and a higher level of implicit bias towards Arabs [9].

We may consciously reject negative images and ideas associated with disadvantaged groups (and may belong to these groups ourselves), but we have all been immersed in cultures where these groups are constantly depicted in stereotyped and pejorative ways. Hence the description of ‘aversive racists’: those who explicitly reject racist ideas, but who are found to have implicit race bias when they take a race IAT [10]. Although there is currently a lack of understanding of the exact mechanism by which cultural immersion translates into implicit stereotypes and prejudices, the widespread presence of these biases in egalitarian-minded individuals suggests that culture has more influence than many previously thought.

The implicit biases of concern to health care professionals are those that operate to the disadvantage of those who are already vulnerable. Examples include minority ethnic populations, immigrants, the poor, low health-literacy individuals, sexual minorities, children, women, the elderly, the mentally ill, the overweight and the disabled, but anyone may be rendered vulnerable given a certain context [11]. The vulnerable in health-care are typically members of groups who are already disadvantaged on many levels. Work in political philosophy, such as the De-Shalit and Wolff concept of ‘corrosive disadvantage’, a disadvantage that is likely to lead to further disadvantages, is relevant here [12]. For instance, if a person is poor and constantly worried about making ends meet, this is a disadvantage in itself, but can be corrosive when it leads to further disadvantages. In a country such as Switzerland, where private health insurance is mandatory and yearly premiums can be lowered by increasing the deductible, a high deductible may lead such a person to refrain from visiting a physician because of the potential cost incurred. This, in turn, could mean that the diagnosis of a serious illness is delayed leading to poorer health. In this case, being poor is a corrosive disadvantage because it leads to a further disadvantage of poor health.

The presence of implicit biases among healthcare professionals and the effect on quality of clinical care is a cause for concern [13,14,15]. In the US, racial healthcare disparities are widely documented and implicit race bias is one possible cause. Two excellent literature reviews on the issue of implicit bias in healthcare have recently been published [16, 17]. One is a narrative review that selects the most significant recent studies to provide a helpful overall picture of the current state of the research in healthcare on implicit bias [16]. The other is a systematic review that focusses solely on racial bias and thus captures only studies conducted in the US, where race is the most prominent issue [17]. Our review differs from the first because it poses a specific question, is systematic in its collection of studies, and includes an examination of studies solely employing the vignette method. Its systematic method lends weight to the evidence it provides and its inclusion of the vignette method enables it to compare two different literatures on bias in healthcare. It differs from the second because it includes all types of bias, not only racial; partly as a consequence, it captures many studies conducted outside the US. It is important to include studies conducted in non-US countries because race understood as white/black is not the source of the most potentially harmful stereotypes and disparities in all cultural contexts. For example, a recent vignette study in Switzerland found that in the German-speaking part of the country, physicians displayed negative bias in treatment decisions towards fictional Serbian patients (skin colour was unspecified, but it would typically be assumed to be white), but no significant negative bias towards fictional patients from Ghana (skin colour would be assumed to be black) [18]. In the Swiss German context, the issue of skin colour may thus be less significant for potential bias than that of country of origin.Footnote 2

Top 19 what is implicit bias edit by Top Q&A

Top 20+ what is the treatment for severe foraminal stenosis

List of 12 what day is easter

Top 10+ what is the unemployment rate