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2. Recognize the complex etiology of obesity and communicate this to
colleagues and patients to avoid stereotypes that obesity is attributable
to personal willpower.
3. Recognize that many patients have tried to lose weight repeatedly.
4. Emphasize behavior changes rather than just the number on the scale.
5. Offer concrete advice — start an exercise program, eat at home, etc. —
rather than simply saying, “You need to lose weight.”
6. Acknowledge the difficulty of lifestyle changes.
7. Recognize that small weight losses can result in significant health gains.
Thousands of health professionals have taken a free online continuing medical education
course offered by the UConn Rudd Center for Food Policy and Obesity titled: Weight bias in
clinical settings: Improving health care delivery for obese patients.
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It is also useful to identify one’s own bias. Asking the following questions can be helpful in
this regard:
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1. Do I make assumptions based only on weight regarding a person’s
character, intelligence, professional success, health status, or lifestyle
behaviors?
2. Am I comfortable working with people of all shapes and sizes?
3. Do I give appropriate feedback to encourage healthful behavior change?
4. Am I sensitive to the needs and concerns of obese individuals?
5. Do I treat the individual or only the condition?
As discussed previously, the free online validated survey tool, the Weight Implicit Association
Test (IAT), is an excellent resource for uncovering an implicit weight bias.
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Race Bias
In socially sensitive areas such as interracial attitudes and beliefs, implicit attitudes are a
better predictor of discriminatory behavior than is self-report.
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The IAT has been used in
health disparities research with physicians to measure implicit attitudes about race. One study
found that physicians hold implicit race bias, similar to others in society,
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and recent research
is showing that these attitudes affect medical care.
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In a cross-sectional study of 40 primary
care clinicians and 269 patients in urban community-based practices, Cooper and associates
measured clinicians’ implicit general race bias and race and compliance stereotyping with 2
implicit association tests and related them to audiotape measures of visit communication and
patient ratings. Results indicated that among Black patients, general race bias was associated
with more clinician verbal dominance, lower patient positive affect, and poorer ratings of
interpersonal care; race and compliance stereotyping was associated with longer visits,
slower speech, less patient centeredness, and poorer ratings of interpersonal care.
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