Yeazel, Mark W.

Purpose The purpose of this study was to examine the relationship between manifestations of racism in medical school and subsequent changes in graduating medical students’ intentions to practice in underserved or minority communities, compared with their attitudes and intentions at matriculation. Method The authors used repeated-measures data from a longitudinal study of 3,756 students at 49 U.S. medical schools that were collected from 2010 to 2014. They conducted generalized linear mixed models to estimate whether manifestations of racism in school curricula/policies, school culture/climate, or student attitudes/behaviors predicted first- to fourth-year changes in students’ intentions to practice in underserved communities or primarily with minority populations. Analyses were stratified by students’ practice intentions (no/undecided/yes) at matriculation. Results Students’ more negative explicit racial attitudes were associated with decreased intention to practice with underserved or minority populations at graduation. Service learning experiences and a curriculum focused on improving minority health were associated with increased intention to practice in underserved communities. A curriculum focused on minority health/disparities, students’ perceived skill at developing relationships with minority patients, the proportion of minority students at the school, and the perception of a tense interracial environment were all associated with increased intention to care for minority patients. Conclusions This study provides evidence that racism manifested at multiple levels in medical schools was associated with graduating students’ decisions to provide care in high-need communities. Strategies to identify and eliminate structural racism and its manifestations in medical school are needed.

SummaryThis study aimed to identify factors associated with high obesity care self‐competence among US medical students. The authors performed a cross‐sectional analysis of 2014 survey data on fourth year medical students collected online as part of the Medical Student Cognitive Habits and Growth Evaluation Study (CHANGES). Independent variables included quality and quantity of interaction with patients and peers with obesity; hours of communication and partnership skills training; negative remarks against patients with obesity by supervising physicians, and witnessed discrimination against patients with obesity. The dependent variable was self‐competence in providing obesity care. Of 5823 students invited to participate, 3689 (63%) responded and were included in our analyses. Most students were white (65%), half were women and 42% had high self‐competence in caring for patients with obesity. Factors associated with high self‐competence included increased interaction with peers with obesity (39% vs. 49%, P < 0.001) and increased partnership skills training (32% vs. 61%, P < 0.001). Increased partnership skills training and quantity of interactions with peers with obesity were associated with high student self‐competence in providing obesity‐related care to patients. Medical schools might consider increasing partnership skills training to improve students’ preparedness and skill in performing obesity‐related care.

Purpose To determine baseline individual and school-related factors associated with increased risk of developing depression symptoms by year four (Y4) of medical school, and to develop a prognostic index that stratifies risk of developing depression symptoms (Depression-PI) among medical students. Method The authors analyzed data from 3,743 students (79% of 4,732) attending 49 U.S. medical schools who completed baseline (2010) and Y4 (2014) surveys. Surveys included validated scales measuring depression, stress, coping, and social support. The authors collected demographics and school characteristics and conducted multivariate analysis to identify baseline factors independently associated with Y4 depression symptoms. They used these factors to create a prognostic index for developing depression. They randomly divided the data into discovery (n = 2,455) and replication (n = 1,288) datasets and calculated c statistics ( c ). Results The authors identified eight independent prognostic factors for experiencing depression symptoms during training within the discovery dataset: age; race; ethnicity; tuition; and baseline depression symptoms, stress, coping behaviors, and social support. The Depression-PI stratified four risk groups. Compared with the low risk group, those in the intermediate, high, and very high risk groups had an odds ratio of developing depression of, respectively, 1.75, 3.98, and 9.19 ( c = 0.71). The replication dataset confirmed the risk groups. Conclusions Demographics; tuition; and baseline depression symptoms, stress, coping behaviors, and social support are independently associated with risk of developing depression during training among U.S. medical students. By stratifying students into four risk groups, the Depression-PI may allow for a tiered primary prevention approach.

Despite the widespread inclusion of diversity-related curricula in U.S. medical training, racial disparities in the quality of care and physician bias in medical treatment persist. The present study examined the effects of both formal and informal experiences on non-African American medical students’ ( N = 2,922) attitudes toward African Americans in a longitudinal study of 49 randomly selected U.S. medical schools. We assessed the effects of experiences related to medical training, accounting for prior experiences and attitudes. Contact with African Americans predicted positive attitudes toward African Americans relative to white people, even beyond the effects of prior attitudes. Furthermore, students who reported having witnessed instructors make negative racial comments or jokes were significantly more willing to express racial bias themselves, even after accounting for the effects of contact. Examining the effects of informal experiences on racial attitudes may help develop a more effective medical training environment and reduce racial disparities in healthcare.

Context Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. Objectives This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. Methods This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web‐based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Results Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Conclusions Medical schools may reduce students’ weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients.

Summary The objective of this study was to critically review the empirical evidence from all relevant disciplines regarding obesity stigma in order to (i) determine the implications of obesity stigma for healthcare providers and their patients with obesity and (ii) identify strategies to improve care for patients with obesity. We conducted a search of M edline and PsychInfo for all peer‐reviewed papers presenting original empirical data relevant to stigma, bias, discrimination, prejudice and medical care. We then performed a narrative review of the existing empirical evidence regarding the impact of obesity stigma and weight bias for healthcare quality and outcomes. Many healthcare providers hold strong negative attitudes and stereotypes about people with obesity. There is considerable evidence that such attitudes influence person‐perceptions, judgment, interpersonal behaviour and decision‐making. These attitudes may impact the care they provide. Experiences of or expectations for poor treatment may cause stress and avoidance of care, mistrust of doctors and poor adherence among patients with obesity. Stigma can reduce the quality of care for patients with obesity despite the best intentions of healthcare providers to provide high‐quality care. There are several potential intervention strategies that may reduce the impact of obesity stigma on quality of care.

Purpose High-quality supportive care is an essential component of comprehensive cancer care. We implemented a patient-centered quality of cancer care survey to examine and identify predictors of quality of supportive care for bowel problems, pain, fatigue, depression, and other symptoms among 1,109 patients with colorectal cancer. Patients and Methods Patients with new diagnosis of colorectal cancer at any Veterans Health Administration medical center nationwide in 2008 were ascertained through the Veterans Affairs Central Cancer Registry and sent questionnaires assessing a variety of aspects of patient-centered cancer care. We received questionnaires from 63% of eligible patients (N = 1,109). Descriptive analyses characterizing patient experiences with supportive care and binary logistic regression models were used to examine predictors of receipt of help wanted for each of the five symptom categories. Results There were significant gaps in patient-centered quality of supportive care, beginning with symptom assessment. In multivariable modeling, the impact of clinical factors and patient race on odds of receiving wanted help varied by symptom. Coordination of care quality predicted receipt of wanted help for all symptoms, independent of patient demographic or clinical characteristics. Conclusion This study revealed substantial gaps in patient-centered quality of care, difficult to characterize through quality measurement relying on medical record review alone. It established the feasibility of collecting patient-reported quality measures. Improving quality measurement of supportive care and implementing patient-reported outcomes in quality-measurement systems are high priorities for improving the processes and outcomes of care for patients with cancer.

ObjectiveTo examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students.MethodsA web‐based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti‐fat attitudes test.ResultsA majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non‐Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice.ConclusionsImplicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact.