Implicit bias

Imagine walking down the road at night. Your gut reaction to seeing a young black man in urban clothing will probably be different than seeing an old white lady pushing a stroller.

These gut reactions occur within milliseconds, before you can consciously assess the situation. So why does this occur? The reason your initial thoughts and feelings might be different in these two situations can be attributed to implicit biases.

An implicit bias is the unconscious attitude and beliefs that affect a person’s feelings, behavior or judgement without their knowledge.

Explicit, or conscious, bias is when someone is aware of their thoughts and emotions towards a specific group. This can be seen in hate speech, discrimination, and sometimes prejudice.

With implicit bias, it gets a little tricky because people are often unaware that their behavior or judgement are being affected since the bias is subconscious.

In healthcare, implicit bias also plays a role and can directly affect healthcare outcomes and patient satisfaction.

Now, implicit biases are formed when you make subconscious generalizations and form stereotypes that attribute certain characteristics with specific groups of people.

This is a cognitive strategy that’s intended to make it faster and easier to make judgements or take action. With enough repeated reinforcement, these can become involuntary habits that are difficult for you to detect.

For example, as a new resident, you might notice that most Latinx patients refuse certain elective surgical procedures. Throughout the years, without you noticing, you gradually stopped discussing these procedures with Latinx patients.

If asked, you would probably say you’re not treating Latinx people any differently than other groups. Implicit bias is more likely to occur in high pressure, time sensitive situations that require a lot of multitasking; something that’s common in many healthcare settings.

In order to better study implicit bias, Harvard developed the Implicit Association Test, or IAT. This is a tool that can help evaluate individually held implicit biases by measuring the strength of automatic associations between subject categories.

So for example, you might be asked to associate “good at math” with the categories of “men,”and “women.” If it takes you longer to associate one category with “good at math,” then your IAT score would increase, indicating potential bias.

After 8 years, 4.5 million tests were completed online by the general population, and showed that individually held impli​cit racial ​biases are pervasive, often unrecognized, and can be a predictor of behavior.

When studied further in healthcare providers, similar results have been found. Now, the validity and reliability of the IAT has been criticized.

For example, the same person taking the test multiple times can lead to different results. So the IAT might be more useful when assessing an organization or population instead of individuals.

IAT has been compared to other tools designed to measure implicit bias such as vignettes, simulations, and clinical evaluations, and it produced comparable results.

These and other studies have shown that implicit biases are held by a range of healthcare professionals, from physicians and nurses to counsellors, social workers, and students.

These biases can be against many factors like race, ethnicity, gender, age, religion, socioeconomic status, disability, and mental health. ​

To assess the impact of implicit bias, a landmark study conducted in 2003 by the Institute of Medicine showed that even when factors like race, ethnicity and socioeconomic levels are accounted for, there’s still lower quality of care and worse outcomes for people of certain social groups, and implicit bias is one of the contributing factors.

Further studies have shed light on how this occurs because implicit biases are associated with incomplete patient assessments, minimized involvement in patient care, lack of thorough testing, inappropriate diagnoses and treatments, and insufficient follow ups and referrals.

Others have shown providers with high IAT scores tended to have shorter interactions with black patients. Implicit biases can also erode the patient-provider relationship on both a personal and societal level.

Healthcare providers that are unaware of their prejudices may not recognize how certain behaviors, language, and actions may offend, marginalize or harm a patient.

In studies that asked black patients to evaluate providers, patients reported having less respect, confidence, and trust in providers with high IAT scores; and they also reported less confidence in treatment plans, and more difficulty remembering discussions or following recommendations.

So the effects of implicit bias on the patient-provider relationship can result in a lack of trust, dissatisfaction with care, incomplete follow-up and and follow-through with provider instructions, and hesitance to interact with the healthcare setting.