The Case

You are sitting in a committee meeting, discussing an application to promote another physician in your group to a leadership position. They are an outstanding candidate. A member on the committee comments that a leadership position should be awarded to a physician having a normal weight as opposed to one who is overweight. This makes you feel uncomfortable, and you wonder if you should speak up.

Clinical Question

Is there interphysician implicit, explicit, and/or professional weight bias in emergency medicine?

Background

Bias, as defined by the common English language, is “a particular tendency, trend, inclination, feeling, or opinion, especially one that is preconceived or unreasoned.”¹ It is a sense of prejudice or stereotyping and the formation of a foregone conclusion independent of current evidence.

Bias can be either implicit or explicit. Implicit bias is an unconscious and often subtle type of bias that is hard to pinpoint and difficult to measure. Explicit bias is a more outward bias expressed in words or actions that’s easier to identify in other people and ourselves.

Examples of these types of biases in the house of medicine include age, gender, socioeconomic status, and race. Weight bias has not received as much attention. There is literature on physicians’ weight biases toward patients.^2–4 However, there is limited information on physician-to-physician weight bias.⁵

Implicit weight bias (IWB) can be measured using the Implicit Association Test (IAT) based on work from Project Implicit, a Harvard-based research organization. Explicit weight bias (EWB) was quantified using a modified Anti-Fat Attitudes Questionnaire.⁶ Participants were asked to respond on a seven-point Likert scale from 1 (strongly agree) to 7 (strongly disagree), shown in Table 1.

Table 1: Modified Anti-Fat Attitudes Questionnaire

This recent study added a third category of bias called professional weight bias (PWB). This was defined as the reduced willingness to collaborate with, seek advice from, and foster mutually beneficial professional relationships with physician colleagues with obesity. The same seven-point Likert scale was used to assess PWB (see Table 2).

Table 2: Professional Weight Bias Questionnaire

Reference: McLean ME, McLean LE, McLean-Holden AC, et al. Interphysician weight bias: a cross-sectional observational survey study to guide implicit bias training in the medical workplace. Acad Emerg Med. 2021;28(9):1024-1034.

• Population: Practicing physicians and physicians-in-training in the United States and Canada
• Intervention: Survey instruments measuring IWB, EWB, and PWB
• Comparison: None
• Outcome: Descriptive analyses along with correlative models

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.”

Results

The survey was completed by 620 people. The mean age was 44 years, 58 percent identified as female, the mean body mass index was 26, 73 percent were Caucasian, 78 percent were emergency physicians, and 72 percent were attending physicians.

Key Result: A high percentage of participants indicated IWB against other physicians, while other results suggested some EWB and PWB do exist.

• Implicit Weight Bias:
  • Eighty-seven percent of participants had a D-score above 0, indicating IWB against other physicians.
  • Male sex and increased age were both positively correlated with anti-fat weight bias.
• Explicit Weight Bias and Professional Weight Bias:
  • Ranges and means on the rating scales showed levels of variability, but overall suggested bias does exist.
  • Male sex positively correlated with both EWB and PWB.

Evidence-Based Medicine Commentary

1. Low r Values: The r value represents strength of correlations and ranges from (-1) to (+1), with 0 representing no association, (-1) representing maximal negative association, and (+1) representing maximal positive association. Correlations do not address causality between two things. Some of the r values for correlation in this study were low (0.24, 0.16, and 0.73). However, small correlations are in line with previous literature on the topic.7–9
2. Respondent Bias: Any survey literature is limited by respondent bias—when respondents know what they are being asked about, this may influence the honesty and accuracy of their answers. It would have been apparent to the physicians being surveyed that the study was about weight bias. Physicians are typically motivated and trained to control expression of their biases. This could have underestimated the amount of bias in this cohort. 
3. Externally Unvalidated Tool: The PWB scale was developed by this research group for this study. It was tested on emergency physicians and residents in the United States and Canada. We need to be cautious not to overinterpret the results until this tool has been externally validated with emergency physicians in other countries.

Bottom Line

Implicit, explicit, and professional biases exist in emergency physicians. Recognizing these biases can be a potential step to help mitigate the negative impact these biases may have on interprofessional relationships.

Case Resolution

You decide to speak truth to power and acknowledge that everyone has some biases. This specific comment about a candidate being overweight could suggest a possible interprofessional weight bias. You recommend to the other committee members that the weight of the candidate should not be part of the decision whether to promote the physician to a leadership position.

Thank you to Dr. Corey Heitz, an emergency physician in Roanoke, Virginia, for his help with this review.

Remember to be skeptical of anything you learn, even if you heard it on the Skeptics’ Guide to Emergency Medicine. Plus-circle

References

1. Bias. Dictionary.com website. Accessed Oct. 8, 2021.
2. Anderson DA, Wadden TA. Bariatric surgery patients’ views of their physicians’ weight-related attitudes and practices. Obes Res. 2004;12(10):1587-1595.
3. Richard P, Ferguson C, Lara AS, et al. Disparities in physician-patient communication by obesity status. Inquiry. 2014;51:0046958014557012.
4. Puhl RM, Brownell KD. Confronting and coping with weight stigma: an investigation of overweight and obese adults. Obesity (Silver Spring). 2006;14(10):1802-1815.
5. Maxfield CM, Thorpe MP, Desser TS, et al. Bias in radiology resident selection: do we discriminate against the obese and unattractive? Acad Med. 2019;94(11):1774-1780.
6. Crandall CS. Prejudice against fat people: ideology and self-interest. J Pers Soc Psychol. 1994;66(5):882-94.
7. Cameron CD, Brown-Iannuzzi JL, Payne BK. Sequential priming measures of implicit social cognition: a meta-analysis of associations with behavior and explicit attitudes. Pers Soc Psychol Rev. 2012;16(4):330-350.
8. Fazio RH. Attitudes as object-evaluation associations of varying strength. Soc Cogn. 2007;25(5):603-637.
9. Hofmann W, Gawronski B, Gschwendner T, et al. A meta-analysis on the correlation between the implicit association test and explicit self-report measures. Pers Soc Psychol Bull. 2005;31(10):1369-1385.