의과대학 학생들은 비만한 사람들에 대한 스스로의 부정적 편견을 인지하고 있을까?

의과대학 학생들은 비만한 사람들에 대한 스스로의 부정적 편견을 인지하고 있을까?

Are Medical Students Aware of Their Anti-obesity Bias?

David P. Miller, Jr., MD, MS, John G. Spangler, MD, MPH, Mara Z. Vitolins, DrPH, RD, Stephen W. Davis, MA, Edward H. Ip, PhD, Gail S. Marion, PA, PhD, and Sonia J. Crandall, PhD

목적 : 비만에 대한 부정적 편견(Anti-obesity prejudices)는 비만한 환자들이 받는 돌봄(care)의 질에 영향을 미친다. 저자들은 의과대학 학생들 사이에 체중과 관련한 편견이 어느 정도나 있는지, 그리고 그들이 스스로 인지하고 있는지를 알아보고자 하였다.

방법 : 2008년과 2011년 사이에, 저자들은 Wake Forest School of Medicine에 재학중인 모든 의과대학 3학년 학생들에게 Weight Implicit Associate Test (IAT)검사를 수행하였다. 이 검사는 학생들이 뚱뚱한, 혹은 날신한 사람에 대해 은연중에 가지고 있는 선호도를 검사하기 위한 것이다. 학생들은 또한 겉으로 표현되는(explicit) 체중 관련 선호도에 대해 의미차별척도 문항(semantic differential item)으로 응답하였다. 저자들은 학생들이 편견을 인식하는 정도를 Explicit Preferences와 IAT score과의 연관성으로 평가하였다.

결과 : 354명의 의과대학 학생들 중에서 310(88%)명이 설문에 응하고, 참여에 동의했다. 

Explicit : 전체적으로는 33% (101/310) 학생이 비만한 사람들에 대한 부정적 편견이 있음을 스스로 보고하였다(self-reported). 날씬한 사람에 대한 부정적 편견이 있다고 스스로 보고한 학생은 아무도 없었다. 

Implicit : IAT점수에 따르면, 절반 이상의 학생이 체중과 연관된 편견을 가지고 있었다. 39%는 비만한 사람에 대한, 17%는 날씬한 사람에 대한 편견이 있었으며, 67%의 학생은 스스로의 비만에 대한 편견을 인지하지 못하고 있었다. 남학생들만이 Explicit한 anti-fat bias이 있는 것으로 나타났다. 

Implicit anti-fat bias와 상관관계가 있는 인구학적 요소들은 없었으며, 학생들의 explicit bias와 implicit bias는 상관관계가 없었다.

결론 : 의과대학 학생의 1/3 이상이 implicit anti-fat bias를 가지고 있었으나, 그것을 인지하고 있는 학생은 매우 적었다. 따라서 의과대학의 비만 관련 교과과정은 이러한 편견과 그것이 의료에 미치는 영향을 다루도록 해야 할 것이다.

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Data analysis

To determine which factors, if any, predicted a significant anti-obesity bias, we created logistic regression models for the outcomes of having a significant implicit (unconscious) anti-obesity bias and a significant explicit (conscious) anti-obesity bias. We included as covariates age (as a continuous variable), gender, race/ethnicity, and time in the academic year when the survey was taken (beginning of third year, middle of third year, end of third year). We conducted all analyses using SPSS software, version 19 (IBM Corporation, Armonk, New York) with two-sided tests and an alpha of .05. 

We examined whether students were aware of their implicit bias in three ways. 

First, we compared students’ self-reported biases with their implicit (unconscious) biases (prefer fat, slight or no preference, prefer thin) using chi-square tests. 

Second, we used the Pearson correlation coefficient to determine whether students’ self-reported biases (measured on the seven-point Likert scale) predicted their implicit biases (measured by the difference in latency times from the IAT). 

Third, we reran our multivariate logistic regression model for implicit bias, including students’ explicit bias as a predictor variable to obtain the beta coefficient and significance level for explicit bias.

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Awareness of bias

Among the students with a significant weight-related bias, only 23% (40/173) were aware of that bias. Two-thirds of students (67%, 81/121) with a significant anti-fat bias thought they were neutral, and all students (100%, 52/52) with an anti-thin bias thought they were neutral or had an anti-fat bias. We found no significant correlation between students’ stated bias and their implicit bias when examining the entire sample (Pearson correlation coefficient 0.03, P = .58) or individual subgroups by gender, age, or race. Similarly, an explicit weight-related bias was not a significant predictor of an implicit bias in our logistic regression model (β = −0.14, P = .30).

Logistic regression

In our multivariate logistic regression model, only male gender predicted an explicit anti-fat bias (odds ratio [OR] 3.0, 95% confidence interval [CI] 1.8–5.3). Students’ explicit anti-fat bias decreased with age, but this finding was not statistically significant (OR 0.9 for each one-year increase in age, P = .18). Similar to the results of our bivariate analyses, no demographic or clerkship timing factors were associated with an implicit anti-fat bias in our multivariate model.

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Acad Med. 2013 Jul;88(7):978-982.

Are Medical Students Aware of Their Anti-obesity Bias?

Miller DP Jr, Spangler JG, Vitolins MZ, Davis SW, Ip EH, Marion GS, Crandall SJ.

Source

Dr. Miller is associate professor, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. Dr. Spangler is professor, Department of Family and Community Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. Dr. Vitolins is professor, Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina. Mr. Davis is assistant professor, Department of Family and Community Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. Dr. Ip is professor, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina. Dr. Marion is professor, Department of Family and Community Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina. Dr. Crandall is professor, Department of Physician Assistant Studies, Wake Forest School of Medicine, Winston-Salem, North Carolina.

Abstract

PURPOSE:

Anti-obesity prejudices affect the quality of care obese individuals receive. The authors sought to determine the prevalence of weight-related biases among medical students and whether they were aware of their biases.

METHOD:

Between 2008 and 2011, the authors asked all third-year medical students at Wake Forest School of Medicine to complete the Weight Implicit Association Test (IAT), a validated measure of implicit preferences for "fat" or "thin" individuals. Students also answered a semantic differential item assessing their explicit weight-related preferences. The authors determined students' awareness of their biases by examining the correlation between students' explicit preferences and their IAT scores.

RESULTS:

Of 354 medical students, 310 (88%) completed valid surveys and consented to participate. Overall, 33% (101/310) self-reported a significant ("moderate" or "strong") explicit anti-fat bias. No students self-reported a significant explicit anti-thin bias. According to the IAT scores, over half of students had a significant implicit weight bias: 39% (121/310) had an anti-fat bias and 17% (52/310) an anti-thin bias. Two-thirds ofstudents (67%, 81/121) were unaware of their implicit anti-fat bias. Only male gender predicted an explicit anti-fat bias (odds ratio 3.0, 95% confidence interval 1.8-5.3). No demographic factors were associated with an implicit anti-fat bias. Students' explicit and implicit biases were not correlated (Pearson r = 0.03, P = .58).

CONCLUSIONS:

Over one-third of medical students had a significant implicit anti-fat bias; few were aware of that bias. Accordingly, medical schools' obesity curricula should address weight-related biases and their potential impact on care.