What Attributes Make United States Plastic Surgery Programs Desirable? Perspectives from Medical Students and Residents. Article Swipe

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Magnus Chun , Alisa O. Girard , Yichi Zhang , Abigail Meyers , Idean Roohani , Tracey Cook , Ping Song , Abigail E. Chaffin ·

YOU? · · 2022 · Open Access ·

Resident happiness and well-being, followed by preferred geographical location, were the most favorable program attributes. Plastic surgery residency programs may seek to better integrate these preferences within their curricula, as well as showcase them on social media, to attract high-quality applicants and optimize the training experience for matched residents.

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Outreach Medicine Curriculum Medical education Specialty Ranking (information retrieval) Context (archaeology) Demographics Social media Family medicine Happiness Quality (philosophy) Graduate medical education Psychology Accreditation Demography Social psychology Geography Pedagogy Sociology Philosophy Computer science Political science Archaeology Law Epistemology Machine learning

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Type: article
Language: en
Landing Page: https://pubmed.ncbi.nlm.nih.gov/35958739
OA Status: green
Cited By: 4
References: 23
Related Works: 10
OpenAlex ID: https://openalex.org/W4291676210

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Title: What Attributes Make United States Plastic Surgery Programs Desirable? Perspectives from Medical Students and Residents.

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Type: article

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Language: en

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Publication year: 2022

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Publication date: 2022-01-01

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Authors: Magnus Chun, Alisa O. Girard, Yichi Zhang, Abigail Meyers, Idean Roohani, Tracey Cook, Ping Song, Abigail E. Chaffin

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Landing page: https://pubmed.ncbi.nlm.nih.gov/35958739

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OA URL: https://www.ncbi.nlm.nih.gov/pmc/articles/9350546

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Concepts: Outreach, Medicine, Curriculum, Medical education, Specialty, Ranking (information retrieval), Context (archaeology), Demographics, Social media, Family medicine, Happiness, Quality (philosophy), Graduate medical education, Psychology, Accreditation, Demography, Social psychology, Geography, Pedagogy, Sociology, Philosophy, Computer science, Political science, Archaeology, Law, Epistemology, Machine learning

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Cited by: 4

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