IMPORTANCE As the clinical workforce becomes more diverse, physicians encounter patients who demean them based on social characteristics. Little is known about physicians' perspectives on these encounters and their effects. This knowledge would help develop policies and best practices for institutions and training programs. OBJECTIVE To describe the range and importance of encounters with biased patients and the barriers and facilitators to effective responses. DESIGN, SETTING, AND PARTICIPANTS This qualitative study recruited convenience samples of hospitalist attending physicians, internal medicine residents, and medical students from 3 campuses affiliated with 1 academic medical center. Data were collected from 50 individuals within 13 focus groups from May 9 through October 15, 2018. Focus groups were conducted using open-ended probes, audiotaped, and transcribed. Participants used their own definition of biased patient behavior. Each transcript was independently coded by at least 2 investigators. Data were analyzed from May 2018 through February 2019. MAIN OUTCOMES AND MEASURES Major themes associated with types of encounter, importance to the participant, and barriers and facilitators to effective responses were abstracted through the constant comparative approach. RESULTS Overall, 50 individuals (11 hospitalists, 26 residents, and 13 students) participated; 24 (48%) were nonwhite. At total of 26 participants (52%) identified as women; 22 (44%), as men; and 2 (4%), as gender nonconforming. Reports of biased behavior ranged from patient refusal of care and explicit racist, sexist, or homophobic remarks to belittling compliments or jokes. Targeted physicians reported an emotional toll that included exhaustion, self-doubt, and cynicism. Nontargeted bystanders reported moral distress and uncertainty about how to respond. Participant responses ranged from withdrawal from clinical role to a heightened determination to provide standard of care. Barriers to effective responses included lack of skills, insufficient support from senior colleagues and the institution, and perception of lack of utility associated with responding. Participants expressed a need for training on dealing with biased patients and for clear institutional policies to guide responses. CONCLUSIONS AND RELEVANCE In this qualitative study of physicians and medical students, encounters with demeaning patients ranged from refusal of care to belittling jokes and were highly challenging and painful. Addressing biased patient behavior will require a concerted effort from medical schools and hospitals to create policies and trainings conducive to a clinical environment that respects the diversity of patients and physicians alike.
Objectives
Our goal was to identify if there might be advantages to combining two major public health concerns, i.e., homicides and suicides, in an analysis with well-established macro-level economic determinants, i.e., unemployment and inequality.
Methods
Mortality data, unemployment statistics, and inequality measures were obtained for 40 countries for the years 1962–2008. Rates of combined homicide and suicide, ratio of suicide to combined violent death, and ratio between homicide and suicide were graphed and analyzed. A fixed effects regression model was then performed for unemployment rates and Gini coefficients on homicide, suicide, and combined death rates.
Results
For a majority of nation states, suicide comprised a substantial proportion (mean 75.51%; range 0–99%) of the combined rate of homicide and suicide. When combined, a small but significant relationship emerged between logged Gini coefficient and combined death rates (0.0066, p < 0.05), suggesting that the combined rate improves the ability to detect a significant relationship when compared to either rate measurement alone. Results were duplicated by age group, whereby combining death rates into a single measure improved statistical power, provided that the association was strong.
Conclusions
Violent deaths, when combined, were associated with an increase in unemployment and an increase in Gini coefficient, creating a more robust variable. As the effects of macro-level factors (e.g., social and economic policies) on violent death rates in a population are shown to be more significant than those of micro-level influences (e.g., individual characteristics), these associations may be useful to discover. An expansion of socioeconomic variables and the inclusion of other forms of violence in future research could help elucidate long-term trends.
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