At the end of World War II anti-Semitism was pervasive in the United States. Quotas to limit the number of Jewish students were put in place at most U.S. medical schools in the 1920s and were well-entrenched by 1945. By 1970 the quota was gone. Why? Multiple factors contributed to the end of the quota. First, attitudes toward Jews shifted as Americans recoiled from the horrors of the Holocaust and over half a million Jewish GIs returned home from World War II. Many entered the higher education system. Second, governmental and private investigations in New York City, New York State and Philadelphia exposed the quota. Third, New York State, led by Governor Thomas E. Dewey, established 4 publicly supported nondiscriminatory medical schools. These schools adsorbed many New York Jewish applicants. Fourth, from the 1920s through the 1960s some medical schools consistently or intermittently ignored the quota. Finally, the federal and several state governments passed nondiscrimination in higher education legislation. The quotas ended because of a combination of changing societal attitudes and government and private social action. This remarkable social change may be instructive as higher education now grapples with allegations of a quota system for Asian-Americans.
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http://dx.doi.org/10.1016/j.amjms.2019.08.005 | DOI Listing |
Anesth Analg
February 2025
From the Department of Surgical Specialties and Anesthesiology of São Paulo State University (UNESP), Medical School, Botucatu, Brazil.
Background: Proficiency in endotracheal intubation (ETI) is essential for medical professionals and its training should start at medical schools; however, large caseload may be required before achieving an acceptable success rate with direct laryngoscopy. Video laryngoscopy has proven to be an easier alternative for intubation with a faster learning curve, but its availability in medical training may be an issue due to its high market prices. We devised a low-cost 3-dimensionally printed video laryngoscope (3DVL) and performed a randomized trial to evaluate if the intubation success rate on the first attempt with this device is noninferior to a standard commercially available video laryngoscope (STVL).
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Faculty of Medicine, Jordan University for Science and Technology, Irbid, Jordan.
Background: Artificial intelligence (AI) is set to shape the future of medical practice. The perspective and understanding of medical students are critical for guiding the development of educational curricula and training.
Objective: This study aims to assess and compare medical AI-related attitudes among medical students in general medicine and in one of the visually oriented fields (pathology), along with illuminating their anticipated role of AI in the rapidly evolving landscape of AI-enhanced health care.
J Med Educ Curric Dev
January 2025
University of Kansas, Department of Surgery, Kansas City, KS, USA.
Background: The demographics of medical schools reveal a growing trend towards greater gender and underrepresented in medicine (UIM) representation among students, yet surgical residency lags behind. This study explores the demographics of first-year medical students (M1s) and their initial career interests.
Methods: A panel of faculty physicians and fourth-year medical students in surgical and nonsurgical specialties was held for M1s during orientation week.
Cureus
December 2024
Obstetrics and Gynecology, Shri B M Patil Medical College Hospital and Research Centre, BLDE (Deemed to be University), Vijayapura, IND.
Background Cervical cancer typically progresses over 10-20 years, making it a preventable disease and underscoring the importance of screening. In low-resource settings, Papanicolaou (Pap) smears and visual inspection with acetic acid (VIA) serve as primary screening tools. This study was conducted as part of the noncommunicable disease camps organized by the government of Karnataka, India.
View Article and Find Full Text PDFMayo Clin Proc Digit Health
December 2024
Department Radiology, Stanford University, Stanford, CA.
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
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