André Ricardo Andrade de Oliveira, Cláudia Elisa Grasel, Daniela Zilio
et al.
Resumo Este estudo buscou verificar, por meio de questionário autoaplicável, o conhecimento e a aceitação dos profissionais de saúde em relação às diretivas antecipadas de vontade e aos cuidados paliativos na atenção primária. Participaram 40 profissionais de saúde, predominantemente enfermeiros, médicos e técnicos de enfermagem. Houve prevalência de participantes do sexo feminino (77,5%), com idade entre 30 e 59 anos (82,5%), tempo de formação de 10 a 19 anos (45%) e casados (65%). A maioria (65%) conhecia as diretrizes da Organização Mundial da Saúde sobre os cuidados paliativos. Entretanto, mais da metade (55%) desconhecia as diretivas antecipadas de vontade. O conhecimento das diretrizes da Organização Mundial da Saúde sobre os cuidados paliativos mostrou-se razoável, mas o desconhecimento sobre diretivas antecipadas foi elevado, do que se infere a necessidade de inclusão de conteúdos sobre cuidados paliativos e diretivas antecipadas de vontade nos currículos de formação e de atualização dos profissionais de saúde.
Abstract Background Moral injury is a significant issue for healthcare workers, often stemming from exposure to ethical dilemmas and distressing events. This study aims to explore the relationship between moral injury and healthcare workers’ career calling, using the job demands-resources model as a theoretical framework. The goal is to understand how moral injury affects healthcare workers’ sense of purpose and vocation and identify factors that may mitigate this impact. Methods A cross-sectional survey was conducted with a sample of 506 Chinese healthcare workers. The study used self-report questionnaires to assess moral injury, authentic self-expression, self-compassion, ethical leadership, and career calling. Path analysis was used to test the proposed mediating and moderating relationships within the job demands-resources model. Results Moral injury has a negative effect on healthcare workers’ career calling. This effect is mediated by authentic self-expression – the inability to openly discuss moral distress weakens the sense of purpose. Self-compassion and ethical leadership buffer against the negative impact of moral injury on career calling. Conclusions This research contributes to the understanding of moral injury and career calling in healthcare workers, with practical implications for safeguarding healthcare professionals’ well-being and commitment to their vocation.
El objetivo del presente artículo es el de Contribuir al conocimiento y reflexión sobre las experiencias que enfrenta el personal médico en situaciones críticas. Se llevaron a cabo once entrevistas a médicos en diversas regiones del país, utilizando un guion elaborado a partir de una revisión de la literatura en artículos académicos y medios de comunicación en línea. Con los datos recopilados, se construyó una matriz y se realizó un análisis temático. Se identificaron cinco conjuntos de temas: (i) Información general de los médicos y motivos para trabajar en zonas críticas; (ii) efectos de la violencia y la pandemia por COVID-19 en la prestación de servicios de salud; (iii) Recursos en salud; (iv) La ambivalencia del triaje: alivio ante la escasez, pero descontento moral hacia los médicos y (v) Gobernanza y políticas públicas. Como conclusiones se puede decir que la interacción de dos situaciones críticas, la violencia y la pandemia de COVID-19, plantea desafíos éticos que requieren una reflexión profunda.
Agueda Muñoz-del-Carpio-Toia, Hardy Erick Guerra-Pérez, Lucía Begazo-Muñoz-del-Carpio
et al.
Abstract Background Lately, the misconduct in research among scientist has been escalating. The use of artificial intelligence has been converted in a double ace card, on one side it has simplificated the way of obtaining valious data for researchers in an easy way, but in the other hand, has promoted that researchers became careless about the scientific method. This situation has become a problem among university teachers since the students are tempt to obtain results in an easy way, leaving ethics aside. The objective of the study was to determine the knowledge and practices regarding scientific integrity among university students in Peru. Methods A descriptive cross-sectional quantitative study was conducted, applying a validated survey on knowledge and practices regarding scientific integrity to 1,420 university students in the Southern Region of Peru, with 60.85% being women. The questionnaire consisted of 21 questions, and data were analysed using descriptive and inferential statistics. Robust statistics were applied, and comparisons were made based on gender, age, and region. Ages ranged from 17 to 29 years (M = 21.14, SD = 2.72). Results The majority demonstrated high levels of knowledge and regular levels of practices regarding scientific integrity. Statistically significant differences were found based on gender (women > men), age (older than 23 years > younger than 22 years), and region. Inappropriate practices were identified in the use of artificial intelligence in academic work. Conclusions It was concluded that university students have high levels of knowledge regarding scientific integrity; however, they exhibit regular and low levels of application in research projects.
Clotilde Brayé, Aurélien Bricout, Arnaud Gotlieb
et al.
Medical Intelligent Systems (MIS) are increasingly integrated into healthcare workflows, offering significant benefits but also raising critical safety and ethical concerns. According to the European Union AI Act, most MIS will be classified as high-risk systems, requiring a formal risk management process to ensure compliance with the ethical requirements of trustworthy AI. In this context, we focus on risk reduction optimization problems, which aim to reduce risks with ethical considerations by finding the best balanced assignment of risk assessment values according to their coverage of trustworthy AI ethical requirements. We formalize this problem as a constrained optimization task and investigate three resolution paradigms: Mixed Integer Programming (MIP), Satisfiability (SAT), and Constraint Programming(CP).Our contributions include the mathematical formulation of this optimization problem, its modeling with the Minizinc constraint modeling language, and a comparative experimental study that analyzes the performance, expressiveness, and scalability of each approach to solving. From the identified limits of the methodology, we draw some perspectives of this work regarding the integration of the Minizinc model into a complete trustworthy AI ethical risk management process for MIS.
Purpose: The pathway to clinical medical physics involves 3 distinct stages of accredited positions, including (i) graduate education, (ii) residency training & (iii) employment. While CAMPEP accredits programs & people, the type of positions and numbers available are each more influenced by local institutional free market forces driving their choices. Methods: Understanding the overall status and trajectories of the full range of residency positions was the rationale for this survey, using publicly available data reported 2017 to 2023 timeframe. Results: Current data shows 108 therapy residency programs with 163 positions, and 38 diagnostic imaging residency programs with 39 positions. The total numbers show growth in positions by +6.5/year in therapy, and +2.1/year in imaging. There are 18 therapy and 10 imaging residencies longer than 2 years, all at university hospitals, and nearly all requiring a PhD. The number of programs that accept graduates with either MS or PhD, versus PhD only, has grown, from 69 to 105 from 2017 to 2023. There was a trend in large health networks increasing their residency numbers from 9 to 23 in this timeframe. The total 7-year growth trend was compared to numbers of graduating students, showing reasonable agreement between positions with expected inter-year variation. Conclusions: There has been growth in numbers of accredited residencies, with accompanying shifts in program types & student education expected. Most are 2-years, while there is smaller growth in longer programs with research added in, primarily at university hospitals. Major growth has occurred in residencies accepting both MS and PhD graduates, while those accepting only PhD graduates tends to be more imaging focused and at university centers. Overall, the number positions has been keeping pace with the known growth in graduates from accredited medical physics graduate programs.
The recent recognition of Iraq's National Council for Accreditation of Medical Colleges (NCAMC) by the World Federation for Medical Education (WFME) marks a crucial step towards enhancing medical education quality. However, this acknowledgment brings responsibilities. Both NCAMC and Iraqi medical colleges must embrace continuous quality improvement methodologies like the PDSA/PDCA cycles and innovate in education for sustainability. Iraqi medical colleges should view accreditation as the beginning of a comprehensive journey towards excellence, integrating total quality management principles into their operations and striving for innovation beyond basic standards. NCAMC, on the other hand, must leverage this recognition to drive substantial improvements, including establishing an online database for self-evaluation data and addressing internal challenges like funding and assessor development. Strategic collaboration between NCAMC, medical colleges, and stakeholders is vital to maximize accreditation's impact on healthcare outcomes and education effectiveness. In conclusion, WFME's recognition signifies a commitment to excellence in Iraqi medical education, necessitating collaborative efforts for continuous improvement and a brighter future in healthcare education and outcomes.
History of medicine. Medical expeditions, General works
The TraX Engine is an advanced data processing tool developed by ADVACAM in collaboration with the European Space Agency (ESA), specifically designed for analyzing data from Timepix detectors equipped with various sensor materials (Si, CdTe, GaAs, SiC). TraX Engine can process large datasets across various scientific and medical applications, including space radiation monitoring, particle therapy, and imaging. In space applications, the TraX Engine has been used to process data from satellites like OneWeb JoeySat deployed in LEO orbit, where it continuously monitors space radiation environments measuring flux, dose, and dose rate in real-time. In medical applications, particularly in particle therapy, the TraX Engine is used to process data to characterize radiation fields in terms of particle flux, Linear Energy Transfer, and spatial distribution of the radiation dose. The TraX Engine can identify and classify scattered particles, such as secondary protons and electrons, and estimate their contribution to out-of-field doses. In imaging applications, the TraX Engine is integrated into Compton cameras, where it supports photon source localization through directional reconstruction of photons. The system ability to identify gamma radiation source with high precision makes it suitable for medical imaging tasks, such as tracking I-131 used in thyroid cancer treatment or localizing radiation sources. This paper presents the architecture and capabilities of the newly developed software TraX Engine, alongside results from various applications, demonstrating its role in particle tracking, radiation monitoring, imaging, and others. With its modular architecture, the TraX Engine offers multiple interfaces, including a command-line tool, an API, a web portal, and a graphical user interface, ensuring usability across different fields and user expertise levels.
Ahora que hacemos memoria de la celebración del décimo aniversario de Francisco y su responsabilidad como papa, realizamos este artículo que recoge nuestra última actividad docente y académica: mi ponencia “Ética y pensamiento social desde Francisco”; relacionada con una reciente publicación del que soy coautor y como investigador asociado, unido al proyecto universitario de investigación “Querida Amazonia” (Universidad Anáhuac, México). En esta intervención, planteé estas cuestiones y temáticas que son el inicio de dicho libro. Precedido del prólogo de Michael F. Czerny, Cardenal y colaborador del papa. En este trabajo, profundizamos dichas temáticas, proponiendo claves o criterios para promover una educación y formación moral, social, solidaria y humanista. Unida a una ecología integral y bioética global, guiados por la enseñanza y testimonio de Francisco.
Mirjam Faissner, Anna Werning, Michael Winkelkötter
et al.
Abstract Background Mental healthcare users and patients were described as a particularly vulnerable group in the debate on the burdens of the COVID-19 pandemic. Just what this means and what normative conclusions can be derived from it depend to a large extent on the underlying concept of vulnerability. While a traditional understanding locates vulnerability in the characteristics of social groups, a situational and dynamic approach considers how social structures produce vulnerable social positions. The situation of users and patients in different psychosocial settings during the COVID-19 pandemic has not yet been comprehensively considered and ethically analyzed under the aspect of situational vulnerability. Methods We present the results of a retrospective qualitative analysis of a survey of ethical challenges in different mental healthcare facilities of a large regional mental healthcare provider in Germany. We evaluate them ethically using a dynamic and situational understanding of vulnerability. Results Difficulties in implementing infection prevention measures, restrictions of mental health services in favor of infection prevention, social isolation, negative health effects on mental healthcare users and patients, and challenges in implementing regulations on state and provider levels within the local specificities emerged across different mental healthcare settings as ethically salient topics. Conclusions Applying a situational and dynamic understanding of vulnerability allows the identification of specific factors and conditions that have contributed to an increased context-dependent vulnerability for mental healthcare users and patients. These factors and conditions should be considered on the level of state and local regulations to reduce and address vulnerability.
We extend Langdon Winner's idea that artifacts have politics into the realm of mathematics. To do so, we first provide a list of examples showing the existence of mathematical artifacts that have politics. In the second step, we provide an argument that shows that all mathematical artifacts have politics. We conclude by showing the implications for embedding ethics into mathematical curricula. We show how acknowledging that mathematical artifacts have politics can help mathematicians design better exercises for their mathematics students.
The promising field of organic electronics has ushered in a new era of biosensing technology, offering a promising frontier for applications in both medical diagnostics and environmental monitoring. This review paper provides a comprehensive overview of the remarkable progress and potential of organic electronics in biosensing applications. It explores the multifaceted aspects of organic materials and devices, highlighting their unique advantages, such as flexibility, biocompatibility, and low-cost fabrication. The paper delves into the diverse range of biosensors enabled by organic electronics, including electrochemical, optical, piezoelectric, and thermo sensors, showcasing their versatility in detecting biomolecules, pathogens, and environmental pollutants. Furthermore, integrating organic biosensors into wearable devices and the Internet of Things (IoT) ecosystem is discussed, offering real-time, remote, and personalized monitoring solutions. The review also addresses the current challenges and prospects of organic biosensing, emphasizing the potential for breakthroughs in personalized medicine, environmental sustainability, and the advancement of human health and well-being.
Explainable AI (XAI) is often promoted with the idea of helping users understand how machine learning models function and produce predictions. Still, most of these benefits are reserved for those with specialized domain knowledge, such as machine learning developers. Recent research has argued that making AI explainable can be a viable way of making AI more useful in real-world contexts, especially within low-resource domains in the Global South. While AI has transcended borders, a limited amount of work focuses on democratizing the concept of explainable AI to the "majority world", leaving much room to explore and develop new approaches within this space that cater to the distinct needs of users within culturally and socially-diverse regions. This article introduces the concept of an intercultural ethics approach to AI explainability. It examines how cultural nuances impact the adoption and use of technology, the factors that impede how technical concepts such as AI are explained, and how integrating an intercultural ethics approach in the development of XAI can improve user understanding and facilitate efficient usage of these methods.
Medical image segmentation plays an irreplaceable role in computer-assisted diagnosis, treatment planning, and following-up. Collecting and annotating a large-scale dataset is crucial to training a powerful segmentation model, but producing high-quality segmentation masks is an expensive and time-consuming procedure. Recently, weakly-supervised learning that uses sparse annotations (points, scribbles, bounding boxes) for network training has achieved encouraging performance and shown the potential for annotation cost reduction. However, due to the limited supervision signal of sparse annotations, it is still challenging to employ them for networks training directly. In this work, we propose a simple yet efficient scribble-supervised image segmentation method and apply it to cardiac MRI segmentation. Specifically, we employ a dual-branch network with one encoder and two slightly different decoders for image segmentation and dynamically mix the two decoders' predictions to generate pseudo labels for auxiliary supervision. By combining the scribble supervision and auxiliary pseudo labels supervision, the dual-branch network can efficiently learn from scribble annotations end-to-end. Experiments on the public ACDC dataset show that our method performs better than current scribble-supervised segmentation methods and also outperforms several semi-supervised segmentation methods.
In this work, we evaluate how neural networks with periodic activation functions can be leveraged to reliably compress large multidimensional medical image datasets, with proof-of-concept application to 4D diffusion-weighted MRI (dMRI). In the medical imaging landscape, multidimensional MRI is a key area of research for developing biomarkers that are both sensitive and specific to the underlying tissue microstructure. However, the high-dimensional nature of these data poses a challenge in terms of both storage and sharing capabilities and associated costs, requiring appropriate algorithms able to represent the information in a low-dimensional space. Recent theoretical developments in deep learning have shown how periodic activation functions are a powerful tool for implicit neural representation of images and can be used for compression of 2D images. Here we extend this approach to 4D images and show how any given 4D dMRI dataset can be accurately represented through the parameters of a sinusoidal activation network, achieving a data compression rate about 10 times higher than the standard DEFLATE algorithm. Our results show that the proposed approach outperforms benchmark ReLU and Tanh activation perceptron architectures in terms of mean squared error, peak signal-to-noise ratio and structural similarity index. Subsequent analyses using the tensor and spherical harmonics representations demonstrate that the proposed lossy compression reproduces accurately the characteristics of the original data, leading to relative errors about 5 to 10 times lower than the benchmark JPEG2000 lossy compression and similar to standard pre-processing steps such as MP-PCA denosing, suggesting a loss of information within the currently accepted levels for clinical application.
Alan F. T. Winfield, Anouk van Maris, Pericle Salvini
et al.
This paper introduces a draft open standard for the robot equivalent of an aircraft flight data recorder, which we call an ethical black box. This is a device, or software module, capable of securely recording operational data (sensor, actuator and control decisions) for a social robot, in order to support the investigation of accidents or near-miss incidents. The open standard, presented as an annex to this paper, is offered as a first draft for discussion within the robot ethics community. Our intention is to publish further drafts following feedback, in the hope that the standard will become a useful reference for social robot designers, operators and robot accident/incident investigators.
Roosmarijne M. K. Kox, H. Roeline W. Pasman, Martijn Huisman
et al.
Abstract Background Literature shows that middle-aged and older adults sometimes experience a wish to die. Reasons for these wishes may be complex and involve multiple factors. One important question is to what extent people with a wish to die have medically classifiable conditions. Aim (1) Estimate the prevalence of a current wish to die among middle-aged and older adults in The Netherlands; (2) explore which factors within domains of vulnerability (physical, cognitive, social and psychological) are associated with a current wish to die; (3) assess how many middle-aged and older adults with a current wish to die do not have a medically classifiable condition and/or an accumulation of age-related health problems. Methods Data of 2015/16 from the Longitudinal Aging Study Amsterdam were used for this cross-sectional study (1563 Dutch middle-aged and older adults aged between 57 and 99 years), obtained through structured medical interviews and self-reported questionnaires. Three experienced physicians assessed whether the participants with a current wish to die could be classified as having a medically classifiable condition and/or an accumulation of age-related health problems. Results N = 62 participants (4.0%) had a current wish to die. Having a current wish to die was associated with multiple characteristics across four domains of vulnerability, among which: self-perceived health, problems with memory, self-perceived quality of life and meaningfulness of life. Fifty-four participants with a current wish to die were assessed with having a medically classifiable condition, of which one was also assessed with having an accumulation of age-related health problems. Six people were assessed to have neither, and for two people it was unclear. Conclusion A small minority of middle-aged and older adults in the Netherlands have a current wish to die. Most of them can be classified with a medical condition and one person with an accumulation of age-related health problems. Furthermore, the findings show that having a current wish to die is multi-faceted. There is still a need for more knowledge, such as insight in to what extent suffering stemming from the medical classifiable disease contributes to the development of the wish to die.
There is a clear need to involve patients in medical decisions. However, cognitive psychological research has highlighted the cognitive limitations of humans with respect to 1. Probabilistic assessment of the patient state and of potential outcomes of various decisions, 2. Elicitation of the patient utility function, and 3. Integration of the probabilistic knowledge and of patient preferences to determine the optimal strategy. Therefore, without adequate computational support, current shared decision models have severe ethical deficiencies. An informed consent model unfairly transfers the responsibility to a patient who does not have the necessary knowledge, nor the integration capability. A paternalistic model endows with exaggerated power a physician who might not be aware of the patient preferences, is prone to multiple cognitive biases, and whose computational integration capability is bounded. Recent progress in Artificial Intelligence suggests adding a third agent: a computer, in all deliberative medical decisions: Non emergency medical decisions in which more than one alternative exists, the patient preferences can be elicited, the therapeutic alternatives might be influenced by these preferences, medical knowledge exists regarding the likelihood of the decision outcomes, and there is sufficient decision time. Ethical physicians should exploit computational decision support technologies, neither making the decisions solely on their own, nor shirking their duty and shifting the responsibility to patients in the name of informed consent. The resulting three way (patient, care provider, computer) human machine model that we suggest emphasizes the patient preferences, the physician knowledge, and the computational integration of both aspects, does not diminish the physician role, but rather brings out the best in human and machine.
Fermilab is developing a compact superconducting CSRF accelerator as a source of a high-power, high-energy electron beam to produce an x-ray beam comparable to $\geq$ 2 MCi of cobalt-60. As part of this development, we are presently assembling a 20 kW, 1.6 MeV prototype that incorporates the four enabling technologies described below. These technologies support a heat budget that is within the capacity of commercially available cryocoolers and eliminate the need for liquid cryogens. The use of superconducting technologies promises efficiencies, wall-plug to beam, of 80% or greater. A summary of the design and progress to date will be given. In addition, we will present a review of developments within the medical device sterilization industry that are motivating the development of this technology.