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Tool 1: Data to Drive Change and Address Implicit Bias at the Organizational Level
Published in Danielle Laraque-Arena, Lauren J. Germain, Virginia Young, Rivers Laraque-Ho, Leadership at the Intersection of Gender and Race in Healthcare and Science, 2022
A long-trusted tool in identifying and increasing awareness of implicit bias is the Harvard Implicit Association Test (IAT). Debuted by Drs. Anthony Greenwald and Mahzarin Banaji in 1998, IAT is a response-latency assessment that measures the relative strength of associations between pairs of concepts by asking individuals to sort them. For example, the race IAT asks the subject to sort pictures (of white and black people) and words (good or bad) into pairs. Results are based on the observation that people place two words in the same category more quickly if the words are already associated in the brain and therefore measure attitudes and beliefs that people may be unwilling or unable to report (Greenwald et al., 1998). While many studies have demonstrated the benefit of IAT as an inexpensive tool that provides individualized feedback of unconscious biases, there is no documented evidence that completion of the module alone leads to changed behavior. Active cultural/behavioral change must be engaged in tandem with bias awareness to better mitigate its effects. Additionally, meta-analyses suggest that the implications at the individual level are not replicable at greater scales and have little effect on diminishing inequities at the institutional level (Bezrukova et al., 2016).
Learning from low- and middle-income countries
Published in Nigel Crisp, Turning the World Upside Down Again, 2022
Other studies of theirs have focused on exploring entrenched biases against innovation or research from low- and middle-income countries. They have, for example, published a systematic review and narrative synthesis of research articles exploring bias based on the geography of author affiliation. They have also published a randomised controlled trial showing how English clinicians rate research from low- and middle-income countries far lower than research from high-income countries, even when the research is identical. Their Implicit Association Test has demonstrated unconscious bias against research from low- and middle - income countries.15
Unconscious bias
Published in Anna-leila Williams, Integrating Health Humanities, Social Science, and Clinical Care, 2018
At present, the most widely used assessment tool for unconscious bias is the Implicit Association Test (IAT). The IAT is a latency response measure that relies on reaction times to determine conceptual and evaluative associations (Greenwald, McGhee, & Schwartz, 1998). The IAT has been widely studied – when I entered the term “implicit association test” into the search engine, PubMed, I received more than 1,000 hits. From 1998 to 2015, over 12 million people took the internet-based, self-assessment IAT (C. Vitiello, personal communication, October 13, 2017). Within the research community, the IAT receives criticism primarily from those who question whether it is actually testing familiarity and cultural knowledge rather than unconscious bias (Arkes & Tetlock, 2004; Blanton, Strauts, Jaccard, Mitchell, & Tetlock, 2015; Ottaway, Hayden, & Oakes, 2001). Of note, the instrument performs well in psychometric testing, including reliability and estimates of validity (Kang & Lane, 2010). The IAT is particularly effective, and superior to self-report, at identifying bias around socially sensitive issues related to race, gender, ethnicity, sexual orientation, and age (Greenwald, Poehlman, Uhlmann, & Banaji, 2009). I encourage you to check out the IAT self-assessment tests available at https://implicit.harvard.edu/implicit/takeatest.html and learn more about Project Implicit, a multi-national, research network devoted to understanding unconscious bias and related constructs.
Adaptive leadership during challenging times: Effective strategies for health professions educators: AMEE Guide No. 148
Published in Medical Teacher, 2023
Judy McKimm, Subha Ramani, Kirsty Forrest, Jo Bishop, Ardi Findyartini, Chloe Mills, Mohammed Hassanien, Abdulmonem Al-Hayani, Paul Jones, Vishna Devi Nadarajah, Greg Radu
Unconscious (implicit) biases are part of everyone's unconscious minds that unknowingly influence decisions or judgements. They are shaped or develop naturally during exposure to ‘life’: experiences, upbringing, culture, and surrounding environments. They are unintentional and not necessarily bad but need to be addressed when they contribute to discrimination in modern society. These biases can affect our behaviours and the interactions we have with colleagues (Marcelin et al. 2019; Teal et al. 2012). Addressing unconscious biases requires that one must recognise and understand them (Liao and Thomas 2020; Velarde et al. 2022). There are surveys and recognised instruments such as the Implicit Association Test that can be of help. Discussion of one’s test results amongst those in dissimilar social groups is particularly powerful in a safe environment that allows alternative viewpoints to be shared. Utilising facilitated discussions to promote bias literacy can be effective in minimising bias in the workplace. Biases are shown by learners as well as leaders, an example of which is detailed in Box 5.
R.E.A.C.T: A framework for role modeling anti-racism in the clinical learning environment
Published in Medical Teacher, 2022
Self-reflection is a primary step that is often described in anti-racism discussions (Jones 2018). In their ‘Framework for Addressing and Eliminating Racism at the AAMC, Academic Medicine, and Beyond,’ The Association of American Medical Colleges includes individual self-reflection as one of their pillars (AAMC). This entails taking an inventory of the believes that we hold and how they are informed. As medical educators, it is important to acknowledge that physicians can unwittingly perpetuate inequities and racism through their actions. In order to effectively role model and truly embrace anti-racism, medical educators must first reflect on their own implicit biases. The term implicit bias describes the attitudes or stereotypes that exist outside one’s consciousness but nevertheless affects understanding, interactions, and decisions (Van Ryn and Saha 2011). The Implicit Association Test (IAT) is a tool that has been widely used to demonstrate how bias affects our preferences and the associations that we make. It can be used as a tool to uncover implicit biases and for self-reflection (Greenwald et al. 1998).
Longitudinal outcomes one year following implicit bias training in medical students
Published in Medical Teacher, 2022
Anne C. Gill, Yuanyuan Zhou, Jocelyn T. Greely, Anitra D. Beasley, Joel Purkiss, Malvika Juneja
In 2008, educational researchers at Baylor College of Medicine, Houston, Texas, were inspired by research from Green et al. (2007) which found that physicians’ clinical decisions were strongly associated with their Implicit Association Test (IAT) (Greenwald et al. 1998) results. Specifically, as the degree of anti-Black racial bias increased, recommendations for thrombolysis for Black patients decreased. Recognizing the importance of the work, we created a workshop for third-year medical students using the IAT as a trigger to increase awareness about implicit bias and strategies for managing potential biases in medical decision-making. Briefly, the IAT is a well-established computer-based test that purports to measure implicit biases by calculating the time it takes a user to match images or words to a construct or social group. The contention is that the user takes less time to match a series of words or images to a construct/social group if they already associate the words and images with that construct/group and longer if they do not. (Greenwald et al. 1998).