In this article we address the ethical decision-making processes of social work professionals in Spain during the first wave of COVID-19. We present some of the findings from a broader international research project led by professor Sarah Banks and carried out in collaboration with the The first wave of COVID-19 had a major impact in Spain, hitting harder the most vulnerable groups. In this unprecedented and unexpected context, social workers had to make difficult ethical decisions on fundamental issues such as respecting service-user's autonomy, prioritizing wellbeing, maintaining confidentiality or deciding the fair distribution of the scarce resources. There were moments of uncertainty and difficult institutional responses. The broader international project was carried out using an online questionnaire addressed to social work professionals in several countries. In this article, through several specific cases, we examine the ethical decision-making processes of social work professionals in Spain, as well as the way to resolve that situations. We have used a qualitative content analysis with a deductive approach to analyze the responses and cases. Findings show many difficult situations concerning the prioritization of the wellbeing of users without limiting their autonomy, the invention of new organizational protocols to provide support and resources for vulnerable people… Social workers had to manage the bureaucracy and had to solve some emergency situations getting personally involved or developing other cooperation mechanisms. The pandemic forced them to look for new forms of social intervention.
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http://dx.doi.org/10.1177/14733250211050118 | DOI Listing |
Sci Eng Ethics
January 2025
Department of Philosophy and Religious Studies, North Carolina State University, Raleigh, NC, USA.
The incorporation of ethical settings in Automated Driving Systems (ADSs) has been extensively discussed in recent years with the goal of enhancing potential stakeholders' trust in the new technology. However, a comprehensive ethical framework for ADS decision-making, capable of merging multiple ethical considerations and investigating their consistency is currently missing. This paper addresses this gap by providing a taxonomy of ADS decision-making based on the Agent-Deed-Consequences (ADC) model of moral judgment.
View Article and Find Full Text PDFInt Ophthalmol
January 2025
Department of Ophthalmology, Ege University Medical Faculty Hospital, Ege University, 35100, Bornova, Izmir, Turkey.
Purpose: To evaluate the severity distribution of chemical burn-induced Limbal stem cell deficiency (LSCD) according to the novel global consensus classification and to compare the treatment approach, before and after the global consensus.
Methods: Medical records of 127 eyes of 109 patients with LSCD were included. LSCD stages were categorized according to the global consensus classification published by "International LSCD Working Group".
Intensive Care Med Exp
January 2025
Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL, 32224, USA.
Background: The discharge practices from the intensive care unit exhibit heterogeneity and the recognition of eligible patients for discharge is often delayed. Recognizing the importance of safe discharge, which aims to minimize readmission and mortality, we developed a dynamic machine-learning model. The model aims to accurately identify patients ready for discharge, offering a comparison of its effectiveness with physician decisions in terms of safety and discrepancies in discharge readiness assessment.
View Article and Find Full Text PDFClin Pract
January 2025
Department of Cardiothoracic Surgery, General University Hospital of Patras, 26504 Patras, Greece.
Artificial intelligence (AI) has emerged as a transformative technology in healthcare, with its integration into cardiac surgery offering significant advancements in precision, efficiency, and patient outcomes. However, a comprehensive understanding of AI's applications, benefits, challenges, and future directions in cardiac surgery is needed to inform its safe and effective implementation. A systematic review was conducted following PRISMA guidelines.
View Article and Find Full Text PDFEntropy (Basel)
January 2025
Bayesian Intelligence, Upwey, VIC 3158, Australia.
Reproducibility is a key measure of the veracity of a modelling result or finding. In other research areas, notably in medicine, reproducibility is supported by mandating the inclusion of an agreed set of details into every research publication, facilitating systematic reviews, transparency and reproducibility. Governments and international organisations are increasingly turning to modelling approaches in the development and decision-making for policy and have begun asking questions about accountability in model-based decision making.
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