Representation Matters: An Assessment of Diversity in Current Major Textbooks on Burn Care.
W Gaya ShivegaMelissa M McLawhornShawn TejiramTaryn E TravisJeffrey W ShuppLaura S JohnsonPublished in: Journal of burn care & research : official publication of the American Burn Association (2022)
Ethnic and gender disparities in healthcare have been well described. Increasing attention is paid to representative diversity in the images and educational resources used during medical training. Nearly 40% of the population of the United States identifies as a person of color, and patients of color reflect 41% of the total burn population seen in the United States. Additionally, national data on providers suggest about 5% of the Burn Team should be people of color. A better understanding of the diversity represented by burn-related medical literature could affect the management of patients with diverse backgrounds, as well as recruitment of black, indigenous, and people of color (BIPOC) into this field. The goal of this study is to investigate the representation of diverse skin tones in several leading medical textbooks of burn care. All photographs that contained people were evaluated for the number of people present and the depicted role of the person present. Diversity count was assessed in a binary fashion-was the individual represented a BIPOC? About 2579 total individuals were identified. BIPOC was represented in 363 total images (14%). There were 6 providers of color identified out of a total of 161 (3.7%); 30 providers were women (19%), of whom only 1 was a female provider of color. BIPOC patients and providers are underrepresented in the leading textbooks of burn care. Proper representation must be included in modern educational materials to better prepare providers for a diverse population of burn-injured patients and ensure effective and thoughtful care.
Keyphrases
- healthcare
- end stage renal disease
- palliative care
- ejection fraction
- newly diagnosed
- chronic kidney disease
- quality improvement
- wound healing
- prognostic factors
- peritoneal dialysis
- primary care
- systematic review
- machine learning
- adipose tissue
- type diabetes
- dna methylation
- gene expression
- metabolic syndrome
- pregnant women
- pain management
- cross sectional
- insulin resistance
- optical coherence tomography
- convolutional neural network
- social media
- soft tissue
- health insurance