NUR 552 Module 3 Harmful Bias Essay With a Clinical Scenario Example

"It's Probably Her Weight": Harmful Weight Bias, a Delayed Diagnosis and How the Outcome Could Have Been Different

Student Name

Edson College of Nursing and Health Innovation, Arizona State University

NUR 552: Dynamics of Professional Nursing I

Instructor Name

Month Day, Year

"It's Probably Her Weight": Harmful Weight Bias, a Delayed Diagnosis and How the Outcome Could Have Been Different

Introduction

Bias in health care is rarely announced. It shows up in what we assume, how quickly we look for explanations and whose complaints we take seriously. This paper examines weight bias, the negative attitudes and assumptions directed at people because of their body size, through a composite clinical scenario on a telemetry unit. It explains the bias and its effects, shows how it shaped care in the scenario and describes how the outcome could have been improved.

Understanding Weight Bias

Weight bias includes stereotypes that people with obesity are lazy, undisciplined or responsible for their illness, and it appears in health care as well as in society. A review of research on obesity stigma documented these attitudes among physicians, nurses and other health professionals and described how they affect the care patients receive (Puhl & Heuer, 2009). A later review found that weight stigma in health care is linked to less time spent with patients, less patient-centered communication, assumptions that symptoms are caused by weight and patients delaying or avoiding care (Phelan et al., 2015). Weight bias is often implicit: clinicians may hold it without being aware of it, which is why the self-identification modules in this course matter.

The report on harmful bias from the Josiah Macy Jr. Foundation calls on health professions education to recognize bias as a cause of harm and to change learning environments and systems, not only individual attitudes (Josiah Macy Jr. Foundation, 2020). That framing is useful here, because the bias in the scenario passed through several people and several routines.

Clinical Scenario

Ms. R., a composite patient, is 41, has a body mass index of 44 and was admitted to telemetry after a fainting episode at home. On the second evening she told her nurse she felt short of breath walking to the bathroom. The nurse noted a room-air saturation of 93%, a heart rate of 108 and a respiratory rate of 22. In handoff, the nurse said, "She gets winded, but honestly it's probably her weight." The night nurse checked on Ms. R. once, found her sitting up and noted "dyspnea on exertion, baseline per report."

The next morning, Ms. R.'s heart rate was 118. When the physician assistant saw her, she said she had been told her breathing was "just her size" and apologized for "being dramatic." A CT angiogram later that day showed bilateral pulmonary emboli. She recovered, but she told the case manager she would not have come to the hospital again if her sister had not insisted.

How the Bias Shaped Care

The bias operated at three points. First, the evening nurse reached for weight as the explanation before considering a new problem, even though the vital signs had changed from admission. Second, the handoff carried the explanation forward as a fact, so the night nurse inherited the conclusion without the data. Third, Ms. R. had absorbed the message: she minimized her own symptoms and apologized for them, which is consistent with research showing that stigmatized patients may delay seeking care (Phelan et al., 2015). No one intended harm, and each decision seemed reasonable in the moment, which is how implicit bias usually works.

How the Outcome Could Be Improved

At the bedside: the nurse could have compared the new vital signs with the admission values and asked what had changed, treating breathlessness as a symptom to explain rather than a trait to expect. A simple question, "Is this new for you?", would have shown that it was.

In handoff: describing data instead of conclusions, for example "new dyspnea with walking, heart rate 108, saturation 93% from 97% on admission," lets the next nurse think independently.

At the unit level: equipment and routines can reduce stigma. Appropriately sized gowns, blood pressure cuffs and chairs signal respect. Unit education on weight bias, including the self-assessment used in this course, and a norm of challenging remarks such as "it's probably her weight" in handoff would make the bias easier to see. The Macy report's emphasis on changing systems supports these unit changes (Josiah Macy Jr. Foundation, 2020).

With the patient: acknowledging that her symptoms were real and that she was right to report them could help repair trust.

Conclusion

Weight bias in this scenario did not come from hostility. It came from a quick explanation that felt like clinical judgment and moved from nurse to nurse. Recognizing it requires attention to data, careful handoff language and unit routines that make respect visible. Each of those changes is within nursing's reach.

References

Josiah Macy Jr. Foundation. (2020). Addressing harmful bias and eliminating discrimination in health professions learning environments. https://macyfoundation.org/publications/conference-summary-addressing-harmful-bias-and-eliminating-discrimination

Phelan, S. M., Burgess, D. J., Yeazel, M. W., Hellerstedt, W. L., Griffin, J. M., & van Ryn, M. (2015). Impact of weight bias and stigma on quality of care and outcomes for patients with obesity. Obesity Reviews, 16(4), 319-326. https://doi.org/10.1111/obr.12266

Puhl, R. M., & Heuer, C. A. (2009). The stigma of obesity: A review and update. Obesity, 17(5), 941-964. https://doi.org/10.1038/oby.2008.636