Implicit Bias Training for Nurses and Other Healthcare Professionals
Online Continuing Education Course
Implicit biases are deeply ingrained attitudes and stereotypes that affect our judgments and behaviors, often unconsciously. In healthcare settings, these biases can have a significant impact on patient outcomes, healthcare disparities, and overall quality of care. This continuing education (CEU) course aims to equip nurses and other healthcare professionals with the knowledge, skills, and strategies to recognize and address implicit biases, ultimately promoting culturally competent and equitable care. Meets mandates for many states including CA, IL, KY, MI, MD and WA.
Course Price: $20.00
Contact Hours: 2
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Accreditation / Approval Information
Implicit Bias Training for Nurses and other Healthcare Professionals meets the requirements of HB 28: Public Health - Implicit Bias Training and the Office of Minority Health and Health Disparities. Approved by the Maryland Department of Health (MDH).
Implicit Bias Training for Nurses and Other Healthcare Professionals
Copyright © 2023 Wild Iris Medical Education, Inc. All Rights Reserved.
LEARNING OUTCOME AND OBJECTIVES: Upon completion of this course, you will be able to identify the characteristics of implicit bias, its possible impacts on healthcare outcomes, and strategies aimed at reducing implicit bias in the healthcare setting. Specific learning objectives to address potential knowledge gaps include:
- Define implicit bias, including examples of biased behavior.
- Describe the impact of implicit bias on disparities in healthcare outcomes.
- Identify strategies intended to remedy the negative impact of implicit bias.
TABLE OF CONTENTS
WHAT IS IMPLICIT BIAS?
Bias and prejudice have existed since ancient times. Most of the documented occurrences of bias describe overt or conscious bias. It is only fairly recently that the concept of implicit bias has been described. In 1995, psychologists Mahzarin Banaji and Anthony Greenwald used the term implicit bias to describe “social behavior [that] often operates in an implicit or unconscious fashion. The identifying feature of implicit cognition is that past experiences influence judgment in a fashion not introspectively known by the actor” (UCC, 2022).
Definitions of Implicit Bias
Biases are attitudes, behaviors, and actions that are prejudiced in favor of or against a person or group. Implicit bias, also known as unconscious bias, is a form of bias that is both automatic and unintentional. It may include stereotypes, judgments, and assumptions that someone unknowingly believes are true and that may be based on factors such as age, race, weight, gender, gender orientation, sexual orientation, religion, socioeconomic status, or more.
Although people with implicit biases are unaware of their prejudices, these biases may still affect their behaviors and decisions. Another important facet of implicit bias is that it is not only outside of the person’s awareness, but it may directly contradict what they verbalize as their beliefs and values (NIH, 2022; Maryville University, n.d.).
DIFFERENTIATING BETWEEN IMPLICIT AND EXPLICIT BIAS
Explicit bias, also known as conscious bias, is overt and easily recognized. People who have explicit biases are very much aware of their feelings, attitudes, and behaviors, which are typically presented with intent. In its extreme, explicit bias is characterized by “overt negative behavior that can be expressed through physical and verbal harassment or through more subtle means such as exclusion.”
Implicit bias, however, is outside of a person’s awareness. Unlike explicit bias, it can automatically, progressively, and adversely affect behavior in a manner that is not immediately apparent and outside a person’s consciousness (NCCC, n.d.).
Types of Bias
There are numerous types of bias, as described below:
- Ability bias occurs when assumptions are made about people based on physical and mental capabilities. Example: A highly experienced candidate for a position in software design uses a wheelchair. The interviewer decides to hire a less-experienced person who is nondisabled. When discussing the hiring process with his boss, he says that the job requires that the successful candidate have a lot of energy and stamina. He is not aware that he has exhibited implicit bias against people with disabilities, perhaps making implicit assumptions about the energy and stamina of these individuals.
- Age bias occurs when assumptions are made about others based on age. This type of bias can be implicit or explicit. Ageism (prejudice or discrimination on the basis of age) can be directed at older adults and young people alike. Example: A manager makes a decision to hire a recent university graduate because the assumption is made that older candidates (e.g., over the age of 55) will not be able to learn new skills quickly because of their age.
- Affinity bias is the tendency for people to gravitate toward other people who are similar to themselves. Example: Colleagues may be more likely to welcome a new employee who has a similar background (e.g., living in the same or similar town, attending the same university) and similar career goals and objectives. It is the similarity that binds these people together.
- Attribution bias is part of the way people assess others and their achievements. One believes their own personal achievements are earned by hard work and failures are due to external factors, whereas other people’s successes are due to good luck and failures due to mistakes or not being capable. This type of bias is more often explicit rather than implicit. Example: A person who does not receive a promotion at work attributes their failure to external, unfair factors and attributes a promotion given to another person as due to luck rather than ability.
- Beauty bias is the tendency for people to judge others based on their appearance. In other words, they treat attractive people in a positive manner and treat people who may not be particularly attractive in a negative manner. This bias can be implicit or explicit. Example: Two men are sitting at different tables in a restaurant; one is extremely handsome, one is not. The handsome man receives prompt attention, while the other man is kept waiting for someone to take his order.
- Confirmation bias occurs when someone has preconceived opinions and, rather than being objective, looks for evidence to back up these opinions. This type of bias is more often explicit rather than implicit. Example: A manager is interviewing candidates for a position in the department. While looking through their resumes prior to the interviews, the manager finds that one of the candidates lists English as a second language. The manager assumes that this candidate will not be able to communicate adequately with patients and colleagues and focuses on items in the resume and during the interview that support this assumption.
- Conformity bias is closely related to the phenomenon of peer pressure. It occurs when someone allows their views to be influenced by other people whose acceptance they are seeking. Example: A newly hired nurse becomes the target of several bullies in the department. They believe that the new nurse is going to be overbearing and hard to work with because she is pursuing graduate education to become a nurse practitioner. Another nurse disagrees, and generally opposes bullying, but is afraid of losing the friendship of the bullies. So, while not participating in the actual bullying, this nurse does nothing to stop it or help the new colleague adapt to a new work environment. This is an active, conscious choice, which makes it explicit bias.
- Gender, gender identification, sexual orientation biases occur when it is assumed that someone is or is not capable based on these characteristics. Example: A woman who has come out as a lesbian is overlooked for a promotion that would have required her to supervise a large number of female employees. The employer believes that the woman who is a lesbian would be looking for romantic relationships among the women she is supervising simply because she is a lesbian. This is also a conscious choice, making it explicit.
- Name bias exists when people judge someone based on their name and perceived backgrounds. Example: The name of a managerial candidate for the position of department head of the psychology department in a large metropolitan hospital is Abdullah Khan. One of the administrators on the hiring committee states, “It sounds like he’s a Muslim. If he gets hired, we’ll probably have to make all kinds of special arrangements for him to pray on work time. I don’t care what someone’s religion is and I am very tolerant, but we don’t have time to make a lot of extra accommodations.” This administrator shares these opinions with colleagues and triggers similar concerns among a few of them. The administrator may or may not have made a conscious decision to prevent the candidate’s hiring. Even though the administrator believes they are tolerant, their actions say otherwise.
- Race and ethnicity bias is a form of bias that occurs when people make assumptions based on others’ race or ethnicity. Example: People assume that Hispanic individuals do not speak English fluently. This may cause an employer to overlook Hispanic people for jobs that require strong English communication abilities. This type of bias can be both explicit or implicit.
- Weight bias occurs when people judge others negatively based on their weight, whether they are overweight or underweight. Example: A dietitian in an outpatient clinic is preparing to provide dietary consultation for a patient. The dietitian is obviously severely underweight and is receiving treatment for a gastrointestinal disease that resulted in weight loss. The patient sees the dietitian and says, “If you expect me to get as skinny as you are, forget about it. You are probably judging me because I am fat. I think I need another dietitian—someone who won’t judge me.” The patient may be the victim of implicit bias. However, the patient may also harbor implicit bias toward people who are very thin.
(Maryville University, n.d.; Toll, 2021)
DECISION-MAKING AND IMPLICIT BIAS
Research suggests that people are more likely to show bias when criteria for decision-making is unclear. Therefore employers, colleagues, and supervisors must have clear, objective standards for making decisions such as hiring, firing, resigning, promoting, and performing procedures.
Implicit bias is also more likely to appear when people make decisions when they are stressed or in a hurry. People are advised, as much as possible, to avoid making important decisions when stressed or lacking the time needed to make appropriate decisions in an objective fashion (Milano, 2020).
Sharon is a nurse manager of a large pediatric unit in a community hospital. She prides herself on her lack of prejudices and sees herself as tolerant of others regardless of race, gender, gender identification, sexual orientation, economic status, or religion. Sharon often fondly recalls her days as a college student. She was pretty, popular, the homecoming queen, and a cheerleader. Her friends were similar in appearance and interests, as they are to this day.
After interviewing candidates for promotion, Sharon makes her selection. Shortly afterward, Sharon is called to her supervisor’s office. One of the rejected candidates has filed a complaint against Sharon. The complaint includes references to Sharon’s “selection of nurses for promotion, and even nurses who are hired to fill vacancies, who are a particular physical type: blond, pretty, and who share Sharon’s passion for popularity and physical beauty.” The complainant also states that Sharon asks questions about current leisure activities and what extracurricular activities were pursued in high school and college. “Does being a cheerleader make someone a better nurse than others?” “Why are these kinds of questions given so much emphasis in a job interview?”
Sharon is shocked. She says her selection of nurses is without bias. The supervisor asks Sharon to objectively look at her history of hiring and promoting nurses. Sharon protests that she doesn’t have any biases. Again, her supervisor asks that she review how she chooses nurses for promotion and to hire.
Sharon looks at her hiring and promoting records for the past year. She sees that the 25 nurses she either hired or promoted share many characteristics. They are almost all blond and very attractive. Male hires are also very attractive and were high-profile athletes in college. Sharon reviews her summary notes for each candidate. Her comments include descriptions of what leisure activities these nurses pursued and continue to pursue. With one or two exceptions, all of them had leisure interests that closely mimic Sharon’s. Although the chosen candidates were qualified for the positions they filled, there were other candidates who were better qualified. Rejected candidates did not value the same social activities as Sharon, and they were not as physically attractive as the successful candidates. Sharon is beginning to wonder if she has implicit biases that she was unaware of.
Sharon denies having biases until she sees objective evidence that she does. Her self-image is as someone who is tolerant and bias free. In Sharon’s case, the two most likely forms of bias influencing her decisions are affinity bias and beauty bias. Affinity bias is characterized by the tendency for people to gravitate toward others who are similar to themselves. Sharon unconsciously favors people whose appearance and interests are similar to hers. Beauty bias also influences Sharon. She tends to unconsciously judge people based on their appearance.
Sharon’s first reaction is to deny that she is biased. This is common among persons functioning under the influence of unconscious bias. Her supervisor’s guidance triggers in Sharon an initial acknowledgment of the possible existence of implicit bias. The objective evidence of employment practices helps Sharon in her self-examination. By taking these steps, Sharon is alerted to the need to alter her interviewing process and to continue self-analysis for the existence of implicit bias.
IMPACTS OF IMPLICIT BIAS ON HEALTHCARE
Implicit bias can be a cause of disparities in healthcare assessment and decision-making. For healthcare professionals, an inability to acknowledge the seriousness of implicit bias may also lead to ineffective diagnosis and treatment and poor patient outcomes (Daumeyer et al., 2019).
Research also shows that implicit biases based on race, gender, gender orientation, sexual orientation, weight, and health insurance coverage can influence how healthcare professionals interact with patients in the following ways:
- Quality of assessment
- Diagnostic decision-making process
- Management of symptoms
- Treatment recommendations
- Referrals to specialists
- Interpersonal behaviors such as communication, empathy, trust, etc.
A review of a number of research studies shows that bias in the healthcare community has far-reaching consequences for healthcare recipients.
- A literature review from 2018 showed that some medical professionals were more likely to view women experiencing chronic pain as emotional, hysterical, or sensitive.
- Results from a 2019 study showed that more than 80% of medical students had an implicit bias against lesbian and gay people.
- A 2017 study found that healthcare professionals were more likely to assume that older adult patients are offensive, helpless, demanding, and unwilling to receive treatment.
- A 2020 study showed that 83.6% of respondents implicitly preferred people without disabilities and viewed people with disabilities as having a lower quality of life due to their disabilities.
- Results from a 2015 study indicated that healthcare professionals can view people with obesity as lazy, weak-willed, lacking self-control, and unlikely to adhere to treatment regimens.
- Research from 2017 indicated that some physicians may be more likely to think that people from low socioeconomic backgrounds are less intelligent, independent, responsible, and rational than people from higher socioeconomic backgrounds.
(Smith Haghighi, 2019)
Therefore, healthcare professionals are encouraged to become aware of their own implicit biases, recognize such biases in others, and implement strategies to remedy the negative impacts of implicit bias. The American College of Physicians’ (ACP) position paper clearly advocates not only for universal access to high-quality healthcare in the United States but for ending discrimination based on personal characteristics and understanding and improving social determinants of health (Butkus et al., 2020).
Bias and Health Outcomes Related to Sexual Orientation
Casey and colleagues (2019) examined “reported experiences of discrimination against lesbian, gay, bisexual, transgender, and queer (LGBTQ) adults in the United States, which broadly contribute to poor health outcomes.” Principle findings include:
- More than 1 in 6 LGBTQ adults reported avoiding healthcare due to anticipated discrimination.
- 16% of LGBTQ adults reported discrimination in healthcare encounters.
- LGBTQ adults experienced interpersonal discrimination, including slurs, microaggressions, sexual harassment, violence, and harassment regarding bathroom use.
A review of 14 qualitative studies regarding the LGBTQ community’s experiences of mental health services showed that members of this community often faced stigma and overt and implicit bias within mental health services. The review found that participants’ experiences of accessing mental health care were related to “experiencing stigma and staff’s lack of knowledge and understanding of LGBT people’s needs” (Rees et al., 2021).
Bias and Health Outcomes Related to Race
The majority of healthcare professionals are dedicated to providing equal and appropriate care to all patients regardless of race. However, healthcare professionals are not immune to implicit racial bias. The 2019 National Healthcare and Disparities Report found disparate impacts on healthcare quality due to race/ethnicity, with White patients more likely to receive better quality care than:
- Black patients
- Native American patients
- Alaska Native patients
- Hispanic patients
- Native Hawaiian/Pacific Islander patients
Research findings indicate that these groups have a harder time accessing healthcare compared to Whites, which can result in treatment delays that lead to poor healthcare outcomes.
In interviews with African Americans receiving mental health services from the U.S. Department of Veterans Affairs (VA) for the purpose of examining their views and experiences of race in healthcare, participants described “threatening cues,” including lack of diverse racial representation in healthcare environments, perceptions of healthcare providers’ fears of Black patients, and fear of being judged negatively based on stereotypes of African Americans. These evaluations of perceived racial bias were found to influence participants’ behaviors and communication during engagement with healthcare professionals (Eliacin et al., 2020).
Similarly, in a meta-analysis of peer-reviewed articles on implicit bias displayed by healthcare professionals, findings indicated that Black patients felt that healthcare providers assumed Black patients to be less adherent than White patients and reported poor provider communication and undertreatment of pain to be significant issues (Fitgerald & Hurst, 2017).
Biased Language and Patient Care
Language used to describe patients may also reflect implicit bias. In one study, stigmatizing language triggered biased behavior in participants. Medical students and residents in internal and emergency medicine programs at an urban academic medical center were presented with a randomized vignette study of two charts using stigmatizing versus neutral language to describe the same hypothetical patient. Exposure to the stigmatizing language in the chart was linked to more negative attitudes toward the patient as well as less aggressive management of the patient’s pain even though the participants were not consciously aware of bias (Goddu et al., 2018).
WORKPLACE DIVERSITY AND UNCONSCIOUS BIAS
Concerns about a lack of healthcare workforce diversity are triggering increased interest in researching the link between workplace diversity, implicit bias, and patient outcomes. A 2019 cross-sectional study showed that Black, Hispanic, and Native American people were underrepresented in healthcare professions (Salsberg et al., 2019).
Diversity in the workplace has been linked to decreased implicit bias and improved performance and outcomes (Gomez & Bernet, 2019). Marcelin and colleagues (2019) conducted an investigation regarding how to recognize and mitigate implicit bias and how this can create an equitable healthcare environment. They found that increasing diversity improves healthcare delivery as well as mitigates implicit bias.
In a study of medical students, changes in implicit racial attitudes were assessed by the Black-White Implicit Association Test, administered during the first semester and again during the last semester of medical school. Findings indicated that students who reported highly favorable contact with African American faculty members had decreased racial bias, and those who reported unfavorable contact had increased racial bias (Van Ryn et al., 2015).
STATEGIES TO OVERCOME IMPLICIT BIAS IN HEALTHCARE
A well-designed implicit bias training process is a valuable component of bias reduction. However, training must be part of an organizational system that identifies and addresses the causes of implicit bias within the healthcare system. Those in leadership must recognize their biases as well of those of the organization. An organization devoted to inclusivity and a no-tolerance policy toward bias will identify factors that contribute to workplace inequities and change processes and attitudes that enable biased behaviors.
“PRESS” Model for Organizations
Livingston (2020) has developed a five-stage model called PRESS through which organizations can move as they work to reduce bias in the healthcare setting. While this model has yet to be evaluated via scientific research, it provides a potential strategy for bias reduction.
- Problem awareness: Some people deny that there is bias in their organizations. Therefore, the first step is to acknowledge that bias exists and that it is a problem. Education and screening tests for implicit bias may help staff members and administrators to identify their own implicit biases.
- Root-cause analysis: Root-cause analysis refers to the process of understanding the root causes of bias. An analysis of the structural dynamics that are part of the organization means not only identifying causes of bias but taking steps to address those causes.
- Empathy: Empathy, as opposed to sympathy or pity, is more likely to lead to actions that reduce bias. Empathy is defined as understanding others’ emotions together with the ability to imagine what someone else is experiencing. Empathy can be increased by exposure and education, such as listening to colleagues who are members of minority groups talk about their personal experiences of bias and how it affects their lives.
- Strategy: Most strategies for change address three interconnected factors: personal attitudes, informal cultural norms, and formal institutional policies. Personal attitudes can be explored via screening tools and interactions. Informal cultural norms can be made clearer via formal education and informal discussions. Formal institutional policies can include zero tolerance for bias, ongoing education for all staff members, and exposure to real-life examples of the effects of bias.
- Sacrifice: All members of the organization must appreciate that implementing antibias strategies requires an investment of time, energy, resources, and commitment in order to achieve ongoing, organization-wide promotion of greater diversity, equity, and inclusion.
Sabin (2022) conducted an extensive literature review on addressing implicit bias in healthcare. After completing the review, she concluded that self-awareness is a cornerstone of efforts to reduce bias.
HARVARD IMPLICIT ASSOCIATION TEST
One way to develop self-awareness is through the use of an educational tool. The Harvard Implicit Association Test (IAT) was created in 1998 for the purpose of measuring and detecting a person’s implicit bias. The test can be used to measure biases in relation to race, sexual orientation, gender, age, and various other categories. This test has been found to offer some insight into how groups of people with different traits, behaviors, and cultures are viewed by others.
The IAT takes about 10–15 minutes to complete and can be accessed on the Project Implicit website (see “Resources” at the end of this course). Participants are asked to sort and categorize a variety of images and words and respond to a questionnaire related to the topic. The strength of association between the various types of content is measured based on how quickly the user reacts to the associations (MAEPD System, n.d.). Results are classified as no bias, slight bias, moderate bias, or strong bias toward people of different races, sexual orientation, and other bias-related categories.
The IAT is not a perfect measurement of implicit bias. There are some criticisms, including the fact that people may take the test multiple times and provide different answers or that various issues could influence someone’s reaction time while taking the test. However, the test results are a good way to start introspection and the process of self-awareness (Practical Psychology, 2022).
Another strategy to develop self-awareness is the “ASK” model, a practical tool that can be used to address the impact of implicit bias and how culture influences someone’s daily encounters with others (Rose, 2022).
- Awareness: Healthcare professionals must increase their awareness of implicit bias to communicate more effectively with patients and colleagues. Improved communication is linked to enhanced trustworthiness.
- Sensitivity: Healthcare professionals must be sensitive in their approach to both similarities and differences from other people.
- Knowledge: Healthcare professionals should improve their health literacy, which is the comprehension of healthcare and specific health conditions.
The American Academy of Family Physicians (Edgoose et al., 2019) has identified the following eight strategies, recognized by the mnemonic IMPLICIT, that can be used to heighten awareness of implicit biases:
- Introspection: Set aside time to take an objective inventory of implicit biases that may be present in oneself.
- Mindfulness: Develop a state of active, open attention to the present by observing one’s thoughts and feelings without judging them as good or bad. Cultivating mindfulness is a tool to identify and manage difficult emotions, such as those that accompany implicit bias, while avoiding self-criticism and self-judgment (Psychology Today, n.d.).
- Perspective-taking: Look at situations and circumstances from a viewpoint that is typically different from one’s usual viewpoint. Role playing exercises in an educational setting, such as “putting yourself in someone else’s shoes,” have been shown to be helpful (APA, 2023).
- Learning to slow down: Avoid jumping to conclusions about a person or groups of people. Taking the time to slow down allows for the acknowledgment of positive examples of people from the groups for which one may have implicit biases (Maryville University, n.d.).
- Individualization: See each person’s individual characteristics that are different from shared characteristics within a group. By individualizing people, healthcare professionals can identify positive characteristics as well as mistaken negative assumptions (Maryville University, n.d.).
- Checking messaging: Use statements that embrace inclusivity rather than focusing on what makes someone “different.” One example is Apple corporation’s inclusion statement: “At Apple, we’re not all the same, and that’s our greatest strength” (Maryville University n.d.).
- Institutionalizing fairness: Develop organizational programs that include implicit bias recognition and management for all employees. Components of such programs should include building skills in diversity, equity, and inclusion (Sabin, 2022).
- Take two: Acknowledge that overcoming unconscious biases is not the result of one training session or one self-awareness test. It is a life-long learning process that requires continual effort.
Two patients arrive at an outpatient clinic for evaluation prior to surgery for a hip replacement. David is a nurse who is doing the initial pre-operative patient education. He reviews patient information prior to meeting with them. The first patient is Monica, a 55-year-old Asian American woman. The address she provided is known locally as the “poor side of town.” She also noted that her parents are natives of Vietnam and came to the United States just before her birth. Monica listed her occupation as mental health specialist and English as her second language.
The second patient is Adam. He is a 22-year-old White American of European descent. He is on leave from his graduate school studies until he recovers from surgery. He lives in an upper middle-class neighborhood. Adam is engaged to be married, and his wedding is scheduled for early next year.
David prides himself on his unbiased treatment of patients of different races, cultures, genders, and sexual orientation. He begins to make some initial plans for patient education. For Monica, he obtains printed patient education materials in Vietnamese and contacts the interpreter department to find out if anyone is fluent in that language. He assumes that Monica will have trouble paying for any healthcare costs based on her residence address. David also assumes that Monica may work as a counselor in one of the community clinics in her part of town, which is not a safe neighborhood. He also wonders if she will take analgesics as recommended after her surgery, thinking, “Aren’t Asians supposed to be stoic about pain?”
David believes that planning for Adam’s patient education will be easier than Monica’s. He assumes that cost will not be an issue because of his address and the fact that he is studying in a graduate university program. David wonders if Adam’s fiancé will accompany him to his appointment, and guesses that, unless she has a healthcare background, she will be upset at the thought of surgery.
Monica enters David’s office. She is well-dressed, confident, and speaks with a very slight accent in her fluent English. Monica is wearing a diamond-studded wedding band and is accompanied by her husband, whom David recognizes as a local politician who works hard to better the lives of people living in disadvantaged circumstances. David learns that Monica recently completed her Ph.D. in psychology and works at a community clinic in her neighborhood. She has done considerable reading about hip replacement, and David finds that her knowledge is accurate and thorough.
David thinks to himself, “With her abilities, why is she not working and living in a more affluent part of town?” As if reading his mind, Monica tells David that she has chosen to live in the neighborhood in which she grew up and to help the disadvantaged groups in that area. “I’ve been fortunate in my life. I want to help my neighbors be fortunate, too. My husband agrees with me and also works to improve things for the neighborhood and its inhabitants.”
David realizes that he has been wrong on almost every one of his assumptions about Monica. He had anticipated her to be poor, lacking skills in English, and unable to comprehend the necessary patient education. After Monica and her husband leave, David begins to wonder how he could have been so wrong.
David expects that his next meeting with Adam will not contradict any of his assumptions. He is looking forward to an easy teaching session.
Adam enters with a young man whom he introduces as his fiancé. The fiancé, whose name is William, explains that he is here to help interpret for Adam, a native of France, whose English is limited. The two men met when they were attending university in France and recently moved to the United States to continue their studies. William, an American by birth, is fluent in several languages, including French, and says with a smile, “We are both working hard to help him learn English as quickly as possible. He is a good student!” The well-to-do address is that of William’s parents. The two young men are staying there as they continue their studies and prepare for their much-anticipated wedding. Adam may have some initial difficulty with costs related to the surgery, but William assures David that he and his parents are prepared to help with the financial aspects of the surgery. William also explains that he is a bit squeamish around “blood and other medical stuff,” but Adam is very stoic and may actually end up comforting him!
David once again has his expectations turned upside down. Adam is not fluent in English, his finances are limited, and, as a gay man, his fiancé is also male. David realizes that he must provide patient education materials in English and in French and make arrangements for an interpreter to help in William’s absence after surgery.
David uncomfortably realizes that he has made a lot of assumptions based on stereotypes, which are part of implicit bias. He realizes that he must objectively review his behaviors and beliefs in an effort to recognize and reduce faulty assumptions made under the influence of implicit bias.
Although David prides himself on being unbiased, his actions contradict this belief. He makes assumptions about people based on where they live, their native language, culture, sexual orientation, and socioeconomic status. To David’s chagrin, he realizes that he may have many unconscious stereotypes and that these may indicate biases he never realized he had.
David has acknowledged his unconscious biases. It is important that he now reviews present and past assumptions and behaviors to identify when and how implicit bias influencing his decisions. He can then take the next step to learn how to change his behavior patterns and thoughts to avoid acting from his own biases.
Strategies for Working with Patients
Rose (2022) has also identified actions that may help in bias reduction in healthcare. These include:
- Ask patients to share their social histories with the healthcare team so that the team can support and comprehend the particular challenges those patients face.
- Seek out information on implicit bias in order to understand the potential for implicit bias in oneself and to be better able recognize it.
- Review one’s decision-making process, be aware of the rationale for decision-making, and avoid making assumptions based on physical appearance, social history, or socioeconomic status.
- Use shared decision-making strategies in treatment planning.
- Acknowledge cultural differences and diversity and be sensitive to potential bias.
- Identify sources of stress and factors that add emotional pressure and try to mitigate stressful situations that may lead to biased decisions.
BIAS REPORTING SYSTEMS
Some healthcare organizations have instituted bias reporting systems. For example, UW Medicine provides an online tool that allows the target or observer of a biased incident to report their concerns. These incidents are evaluated by a skilled incident-response team that gathers additional information and either directs the concern to an existing system or refers the incident for further investigation and follow-up. A quarterly report provides data on the number of bias incidents, the groups affected by the incident, groups reported to have perpetrated the incidents, locations of reported incidents, and the themes of reported incidents (UW Medicine, 2023).
Education and training must be ongoing and part of a broad organizational strategy designed for all employees. Gonzalez and colleagues (2021) have proposed 12 characteristics for effective implicit bias recognition and management training programs.
Create a safe learning environment. It is not easy to recognize and analyze personal implicit biases. Discussions about bias often cause people to become defensive and emotional. People may be afraid of being labeled as racist, homophobic, sexist, etc. A safe learning environment is essential if healthcare professionals are to learn about implicit bias and how to reduce it. A safe environment is one that allows learners to frankly analyze their thoughts and behaviors and maintains confidentiality of the learners.
Adults learn most effectively when they feel that they are being respected and that their input is important. Adults must also know why they are learning. It cannot be assumed that learners will automatically “know” that they must learn about implicit bias. Facilitators must give examples of how implicit bias impacts healthcare services within their organizations. Examples should not include personal identifiers so that confidentiality is maintained and learners do not fear that their own confidentiality is in jeopardy. Adults must know the relevance of education. In other words, they need to know how a training is expected to impact their professional practice and patient outcomes.
- Reduce the hierarchy in the safe learning environment. The learning environment consists of learners and facilitators. Facilitators are often viewed as having power over learners. It is important to provide learners with opportunities to ask questions and relay feelings without fear of judgment, ridicule, or censorship. Facilitators should be persons who have experience in helping to reduce implicit bias, are comfortable teaching adults, and include the adult learners in the teaching/learning environment by encouraging questions and objectively addressing issues that are challenging.
- Reduce self-blame. Normalizing bias while simultaneously reducing self-blame helps to diffuse anxiety and even resentment related to self-examination of personal implicit biases. Bias is, to some extent, human nature, and not necessarily someone’s “fault.” Healthcare professionals must develop skills to not only recognize their personal biases, but implement strategies so that biases can be reduced and not influence clinical practice. The facilitator should address the issues related to self-blame frankly and be prepared to deal with the possible resentment of learners who are struggling to acknowledge their own implicit biases.
- Integrate the science behind implicit bias. Describing the psychology and neuroscience of implicit bias helps to defuse learner tension and adds legitimacy to implicit bias training. Additionally, adults must be able to understand how any new knowledge can be used in a practical fashion. Theorizing should be kept to a minimum.
- Create activities that embrace discomfort. Discomfort is an important part of implicit bias training. Discomfort that arises during education and training triggers learners to question their assumptions and highlights the need for change. However, discomfort should not overwhelm the learners. A safe environment means that the discomfort should be accompanied with information about dealing with uncomfortable truths and offering support while remaining objective when discussions lead to issues that are thought-provoking and unsettling.
- Implement critical reflection exercises. Critical reflection helps learners to recognize their position in the organization and the world at large to improve understanding of their assumptions as they relate to power and bias. Examples of critical reflection may include presenting learnings with various case studies or role-playing implicit bias situations and then asking learners to share their thoughts and feelings about what they have witnessed and how bias might be reduced in similar circumstances.
- Explore the relationship between experience, implicit, explicit, and structural biases. Implicit biases are formed from someone’s life experiences and socialization processes and reflect biased norms within such contexts. Education to reduce implicit bias must stress that this cannot be accomplished by a lone individual but must be part of an organization-wide process. Adults have many life experiences that can help them contribute to a discussion about their experiences, implicit and explicit bias, and structural bias (institutional practices that give advantage to some and disadvantage to others based on identity). It is essential that adult learners be encouraged to share their life experiences.
- Implement perspective taking exercises. These exercises serve to help healthcare professionals’ awareness of how standard procedures may be interpreted differently from patient to patient. Understanding the context of a patient’s reaction will help learners to acknowledge their biases and improve patient communication. The perspectives and life experiences of both patients and healthcare professionals can be used in discussion and, in a learning environment, as role play to experience the damage that bias can cause and to learn behaviors to reduce such circumstances.
- Implement skill building exercises. Role play and clinical vignettes help to identify ways to address bias. Learners can practice verbalizing how to address bias and reflectively review vignettes for the way patient–healthcare professional interactions are conducted. Adult learners may use role play to “act out” situations they have encountered, reflect on how they responded to these situations, and consider options for some responses that may have been more effective.
- Make implicit bias education part of life-long learning. As previously noted, a single training session is not effective. Education and training must be part of an ongoing process that continues for each and every employee. Implicit bias education is truly a life-long learning process. Leadership should not only support bias training and education, but include it as part of mandatory organizational education and training efforts.
- Include formative and summative assessments. The effectiveness of the education and training must be evaluated. An organization must establish a system of monitoring incidents of bias before and after training and compare the results. The desired effect of monitoring is to be able to objectively measure outcomes and, hopefully, show that the training has helped to reduce bias. These types of assessments should be used to add to the body of knowledge that is essential to implementing education and training that has an ongoing effect on reducing bias.
- Obtain explicit support from leadership. Without leadership support, implicit bias training is doomed to fail. Leadership must support structural change as identified during education, training, and bias monitoring. Their support can be gauged by their backing of the development of policies related to bias reduction and ongoing training and education for the purpose of bias reduction.
(Fairbanks, 2021; Gonzalez et al., 2021)
STUDYING THE EFFECTIVENESS OF IMPLICIT BIAS TRAINING
Despite a growing recognition of the impact of implicit bias and the need to reduce/eliminate it, there are few studies thus far that provide definitive evidence as to the effectiveness of reduction interventions (FitzGerald et al., 2019). Some researchers have found evidence of attitude change and limited behavior change attributed to diversity training, but they concluded that a single diversity training program is not enough to reduce implicit bias in the workplace (Chang et al., 2019).
Vela and colleagues (2022) conducted an extensive literature review of practices to eliminate explicit and implicit biases in healthcare. Quite a few of the articles reviewed showed successful promotion of awareness of implicit bias and an interest in reducing such bias. However, none of the interventions reviewed achieved sustained reduction of implicit bias in healthcare professionals. None of the studies demonstrated that an intervention improved clinical outcomes, the learning environment, interprofessional team dynamics, patient care, health disparities, or patient and healthcare professionals’ satisfaction. Considerably more research is needed to provide definitive evidence regarding approaches to reduce implicit bias and its effects that are effective in the long-term.
Evidence indicates that implicit bias has negative effects on patient outcomes and satisfaction, on healthcare professionals’ job satisfaction, and on the effectiveness of interactions between patients and providers. Although it is extensively hypothesized that education and training will help to reduce implicit bias, research is not yet conclusive in support of this hypothesis.
Therefore, it is not enough for healthcare professionals to know that implicit bias has multiple negative consequences. They must actively promote and participate in research projects and help to use findings to improve education and training. For example, those who are attending education and training programs can complete implicit bias assessment tools before and after such education. In this way, healthcare professionals can help reduce the occurrence and impact of implicit bias.
NOTE: Complete URLs for references retrieved from online sources are provided in the PDF of this course.
American Psychological Association (APA). (2023). Perspective taking. https://dictionary.apa.org
Butkus R, Rapp K, Cooney TG, & Engel L. (2020). Envisioning a better U.S. health care system for all: Reducing barriers to care and addressing social determinants of health. Annals of Internal Medicine, 21. https://doi.org/10.7326/M19-2410
Casey L, Reisner SL, Finding MG, Blendon RJ, Benson JM, Sayde JM, & Miller C. (2019). Discrimination in the U.S.: Experiences of lesbian, gay, bisexual, transgender, and queer Americans. Health Serv Res., 54, 1454–66. https://doi.org/10.1111/1475-6773.13229
Chang EH, Milkman KL, Gromet DM, Rebele RW, Massey C, Duckworth AL, & Grant AM. (2019). The mixed effects of online diversity training. Proc Natl Acad Aci USA, 116(16), 7778–83. https://doi.org/10.1073/pnas.1816076116
Daumeyer NM, Onyeador IN, Brown X, & Richeson J.A. (2019). Consequences of attributing discrimination to implicit vs. explicit bias. Journal of Experimental Psychology, 84. https://doi.org/10.1016/j.jesp.2019.04.010
Edgoose JYC, Quiogue M, & Sidhar K. (2019). How to identify, understand, and unlearn implicit bias in patient care. Fam Pract Manag, 26(4), 29–33. PMID:31287266
Eliacin J, Matthias MS, Cunningham B, & Burgess DJ. (2020). Veterans’ perceptions of racial bias in VA mental healthcare and their impacts on patient engagement and patient-provider communication. Patient Education and Counseling, 103(9), 1798–1804. https://doi.org/10.1016/j.pec.2020.03.017
Fairbanks B. (2021). 7 adult learning theories and principles to enhance your education. University of Phoenix. https://www.phoenix.edu
FitzGerald C, Martin A, Berner D, & Hurst S. (2019). Interventions designed to reduce implicit prejudices and implicit stereotypes in real world contexts: A systematic review. BMC Psychology, 7(29). https://doi.org/10.1186/s40359-019-0299-7
FitzGerald C & Hurst S. (2017). Implicit bias in healthcare professionals: A systematic review. BMC Medical Ethics, 18(19). https://doi.org/10.1186/s12910-017-0179-8
Goddu AP, O’Conor KJ, Lanzkron S, Saheed MO, Saha S, Pek ME, Haywood C, & Beach MC. (2018). Do words matter? Stigmatizing language and the transmission of bias in the medical record. Journal of General Internal Medicine, 33, 685–91. https://doi.org/10.1007/s11606-017-4289-2
Gomez LE & Bernet P. (2019). Diversity improves performance and outcomes. J Natl Med Assoc, 111(4), 383–92. https://doi.org/10.1016/j.jnma.2019.01.006
Gonzalez CM, Lypson ML, & Sukhera J. (2021). Twelve tips for teaching implicit bias recognition and management. Med Teach, 43(12), 1368–73. PMID: 33556288. https://doi.org/10.1080/0142159X.2021.1879378
Livingston R. (2020). Racial equity in the workplace: A five-step plan. https://robertwlivingston.com
Marcelin JR, Siraj DS, Victor R, Kotadia S, & Maldonado YA. (2019). The impact of unconscious bias in healthcare: How to recognize and mitigate it. The Journal of Infectious Diseases, 220(suppl 2), 15, S62–S73. https://doi.org/10.1093/infdis/jiz214
Maryville University. (n.d.). How to identify and overcome your implicit bias. https://online.maryville.edu
Massachusetts Adult Education Professional Development (MAEPD) System. (n.d.). Project implicit: Harvard University’s implicit association test. https://www.sabes.org
Milano B. (2020, December 10). Turning a light on our implicit biases. Harvard Gazette. https://news.harvard.edu
National Center for Cultural Competence. (n.d.). Two types of bias. https://nccc.georgetown.edu
National Institutes of Health (NIH). (2022). Implicit bias. https://diversity.nih.gov
Practical Psychology. (2022). Implicit association test. https://practicalpie.com
Psychology Today. (n.d.). Mindfulness. https://www.psychologytoday.com
Rees SN, Crowe M, & Harris S. (2020). The lesbian, gay, bisexual and transgender communities’ mental health care needs and experiences of mental health services: An integrative review of qualitative studies. Psychiatric Mental Health Nursing, 28(4), 578–89. https://doi.org/10.1111/jpm.12720
Rose JA. (2022). The role of implicit bias and culture in managing or navigating healthcare. Hospital for Special Surgery. https://www.hss.edu
Sabin JA. (2022). Tackling implicit bias in health care. New England Journal of Medicine, 387, 105–7. https://doi.org/10.1056/NEJMp2201180
Salsberg E, Richwine C, Westergaard S, et al. (2021). Estimation and comparison of current and future racial/ethnic representation in the U.S. health care workforce. JAMA, 4(3), e213789. https://doi.org/10.1001/jamanetworkopen.2021.3789
Smith Haghighi A. (2021, August 30). Biases in healthcare: An overview. Medical News Today. https://www.medicalnewstoday.com
Toll E. (2021). Types of unconscious bias. Diversity Resources. https://www.diversityresources.com
University College Cork (UCC). (2022). Implicit bias. https://www.ucc.ie/en/edi/hub/implicitbias/
UW Medicine. (2023). UW Medicine bias reporting tool. https://equity.uwmedicine.org
Van Ryn M, Hardeman R, Phelan SM, et al. (2015). Medical school experiences associated with change in implicit racial bias among 3547 students: A medical student CHANGES study report. J Gen Intern Med, 30(12), 1748–56. https://doi.org/10.1007/s11606-015-3447-7
Vela MB, Erondu AI, Smith NA, Peek ME, Woodruff JN, & Chin MH. (2022). Eliminating explicit and implicit biases in health care: Evidence and research needs. Annual Review of Public Health, 43, 477–501. https://doi.org/10.1146/annurev-publhealth-052620-103528