SGEM#343: Doctors are Doctors So Why Should It Be, You and I Should Get Along So Awfully – Weight Bias in Medicine

Date: August 31st, 2021 Reference: McLean et al. Interphysician weight bias: A cross-sectional observational survey study to guide implicit bias training in the medical workplace. AEM Sept 2021 Guest Skeptic: Dr. Corey Heitz is an emergency physician in Roanoke, Virginia. He is also the CME editor for Academic Emergency Medicine. Case: You are working in the emergency department (ED) with the new resident, one of whom is overweight. You overhear his colleagues wonder where he went, chuckling, and one of them comments that “he probably went for second breakfast.” Realizing that these residents are making fun of their colleague’s weight, you decide to address the issue. Background: We have talked about biases many times on the SGEM. Usually when we use the term bias it is in the context of something that systematically moves us away from the “truth”. Science does not make truth claims and the term is used as a shorthand for the best point estimate of an observed effect size. An example in the medical literature would be selection bias. This is when subjects for a research study are not randomly selected. This can skew the results and impact the conclusions.  Another example would be publication bias. Studies with “positive” results are more likely to be published while those with “negative” results are more likely to end up in the bottom of the file drawer. There are many other types of bias in the practice of medicine. Some of my favourite ones are anchoring bias, base-rate neglect, and hindsight bias. For a description of these and many more check out Dr. Pat Croskerry list of 50 cognitive biases in medicine. You can also click on the codex for an extensive list of different biases. This SGEM episode focuses on a kind of bias as defined by the common English language as “a particular tendency, trend, inclination, feeling, or opinion, especially one that is preconceived or unreasoned”. It is a sense of prejudice or stereotyping and the formation of a foregone conclusion independent of current evidence. There are many biases in the house of medicine. We have discussed some of them on  the SGEM. They include things like age, gender, socioeconomic status, race, and other factors. The gender pay gap is one of the topics that has been spoken about most on the SGEM. A paper by Wiler et al AEM 2019 showed females in academic emergency medicine were paid ~$12,000/year less than their male colleagues (SGEM#248). The September 2021 issue of AEM is a special issue focusing on biases in emergency medicine. It includes articles on racial, ethnic and gender disparities. One specific topic jumped out as something that has not received much attention, weight bias. There is literature on physicians’ weight biases towards patients and patients’ weight bias towards physicians. However, there is limited information on physician-to-physician weight bias. Clinical Question: What is the prevalence of interphysician implicit, explicit, and professional weight bias? Reference: McLean et al. Interphysician weight bias: A cross-sectional observational survey study to guide implicit bias training in the medical workplace. AEM Sept 2021 Population: Practicing physicians and physicians-in-training in North America Excluded: Those who did not consent; did not identify as physicians or physicians-in-training; or were not currently residing in North America. Intervention: Survey instruments measuring implicit weight bias (IWB), explicit weight bias (EWB), and professional weight bias (PWB) Comparison: None Outcome: Descriptive analyses along with correlative models Dr. Mary McLean This is an SGEMHOP episode which means we have the lead author on the show. Dr. Mary McLean is an Assistant Program Director at St. John’s Riverside Hospital Emergency Medicine Residency in Yonkers, New York. She is the New York ACEP liaison for the Research and Education Committee and is a past ALL NYC EM Resident Education Fellow. Dr. McLean was the guest skeptic on the SGEM#310 reviewing an article showing EM physicians are not great at performing the HINTS exam. Implicit Bias: Implicit bias is unconscious and often subtle type of bias that is hard to pinpoint in ourselves and notoriously hard to measure. Implicit weight bias (IWB) was measured using the Implicit Association Test (IAT) based on work from Project Implicit which is a Harvard-based research organization. The weight bias IAT has been previously validated for the general population. This was adapted by adding the theme of physicians in the medical workplace. Project Implicit’s silhouette images of people with obesity was modified to add stethoscopes and clipboards, and adjust clothing to look like scrubs, white coats, or professional clothing. The good and bad layperson descriptor words were also replaced with words used to describe good and bad doctors, based on Stern's medical professionalism framework Explicit Bias: Explicit bias is a more outward bias expressed in words or actions, that’s easier for us to pinpoint in other people and in ourselves The Anti-fat Attitudes Questionnaire (Crandall et al 1994), which was originally validated for the general population was the tool used to assess explicit weight bias (EWB). It was adapted to focus on interphysician views and practices. The adapted items were kept as similar as possible to the validated original - for example, only changing the word “person” to the word “doctor” and leaving the remainder of the item unchanged, unless another tweak was absolutely necessary. NOTE: The word “fat” as a descriptor is used in the questionnaire and to investigate explicit and professional weight bias. This word can be inflammatory, but it’s used with purpose. It’s meant to evoke an emotional response from subjects, which is necessary for this kind of research. Physicians were asked 13 questions on a 7-point Likert scale (1- strongly agree, 2- agree, 3- somewhat agree, 4- neither agree or disagree, 5- somewhat disagree, 6- disagree and 7- strongly disagree). Professional Bias: Professional bias was defined as the reduced willingness to collaborate with, seek advice from, and foster mutually beneficial professional relationships with physician colleagues with obesity. To assess professional weight bias (PWB) a new scale of explicit questions that applied specifically to the medical workplace and nuances of physician careers was created. Subjects were asked to used the same Likert scale to rate their agreement with several items. Each item was meant to capture participants’ views on physicians with obesity regarding collaboration, hiring, promotion, leadership opportunities, and other classic measures of professional success determined by group consensus within our team. Authors’ Conclusions: “Our findings highlight the prevalence of interphysician implicit WB; the strong correlations between implicit, explicit, and professional WB; and the potential disparities faced by physicians with obesity. These results may be used to guide implicit bias training for a more inclusive medical workplace.” Quality Checklist for Observational Study: Did the study address a clearly focused issue? Unsure Did the authors use an appropriate method to answer their question? Unsure Was the cohort recruited in an acceptable way? Yes Was the exposure accurately measured to minimize bias? Yes Was the outcome accurately measured to minimize bias? Yes Have the authors identified all-important confounding factors? Unsure Was the follow up of subjects complete enough? Yes How precise are the results? Fairly accurate Do you believe the results? Yes Can the results be applied to the local population? Unsure Do the results of this study fit with other available evidence? Yes Results: Surveys were electronically sent to individuals of which 1,198 opened the document. There were 620 participants who completed the survey. The mean age was 44 years, 58% identified as female, mean BMI was 26, 73% were Caucasian, 78% emergency physicians and 72% were attending physicians. Key Result: A high percentage of participants indicated IWB against other physicians while other results suggested some EWB and PWB does exist. Implicit Weight Bias (IWB): 87% of participants had a D-score above 0, indicating implicit weight bias against other physicians(34% demonstrated severe anti-fat weight bias and 31% moderate) Male and increased age were both positively correlated with anti-fat weight bias Explicit Weight Bias (EWB) and Professional Weight Bias (PWB): Ranges and means on the rating scales showed levels of variability, suggested bias does exist Positive correlation was seen with IWB (r=0.24 for EWB, r=0.16 for PWB) r=0.73 correlating EWB to PWB Male sex positively correlated with both EWB and PWB 1. Correlative Measurements: A lot of correlative measurements were used. Can you explain some of the differences between a D score, r value, B value, and β values? The D-score is a standardized difference calculated from IAT response time data. It ranges from (-1) to (+1), with 0 representing neutrality. In simple terms, a positive D score means you sorted faster when pictures of physicians with obesity were paired with negative words, and slower when physicians with obesity were paired with positive words. This is interpreted as representing implicit bias, with a (+1) indicating maximal anti-fat bias. The opposite is true for negative D scores, with (-1) indicating maximal anti-thin bias. The r value represents strength of correlations. It also ranges from (-1) to (+1), with 0 representing no association, (-1) representing maximal negative association, and (+1) representing maximal positive association.