Protecting Practitioners in Stressed Systems: Translational Bioethics and the COVID-19 Pandemic
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2022/09/01
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Description:COVID-19 revealed health-care systems in crisis. Intersecting crises of stress, overwork, and poor working conditions have led to workforce strain, under-staffing, and high rates of job turnover. Bioethics researchers have responded to these conditions by investigating the ethical challenges of pandemic response for individuals, institutions, and health systems. This essay draws on pandemic findings to explore how empirical bioethics can inform post-pandemic translational bioethics. Borrowing from the concept of translational science in medicine, this essay proposes that translational bioethics should communicate knowledge about ethical challenges in health-care work to support health systems change. The authors draw from their experience with the Study to Examine Physicians' Pandemic Stress (STEPPS), an interdisciplinary research project that investigates physicians' experiences at the front lines of the COVID-19 pandemic. Using STEPPS as an example of empirical bioethics with potential for translation, the authors review their research and discuss the ongoing process for translating their findings, focusing on how bioethics research and practice can contribute to supporting the health-care workforce. [Description provided by NIOSH]
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ISSN:0031-5982
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Volume:65
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Issue:4
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NIOSHTIC Number:nn:20067787
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Citation:Perspect Biol Med 2022 Autumn; 65(4):637-645
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Contact Point Address:Mara Buchbinder, Department of Social Medicine, University of North Carolina at Chapel Hill, 333 S. Columbia Street, 341A MacNider Hall, Chapel Hill, NC 27599-7240
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Email:mara_buchbinder@med.unc.edu
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Federal Fiscal Year:2022
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Performing Organization:University of North Carolina Chapel Hill
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Peer Reviewed:True
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Start Date:20210901
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Source Full Name:Perspectives in Biology and Medicine
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End Date:20230831
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Main Document Checksum:urn:sha-512:54a9dcf3dcb11033140d745c8602bf75f46e87f985ab0ffbafbe9c7da3383617295671dce811500d3b996b65c67d27867b3ca3a58b3b2372917738f87544edb7
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