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Background: There is a lack of empirical data on lay attitudes toward different sorts of deception in medicine. However, lay attitudes toward deception should be taken into account when we consider whether deception is ever permissible in a medical context. The objective of this study was to examine lay attitudes of U.S. citizens toward different sorts of deception across different medical contexts. Methods: A one-time online survey was administered to U.S. users of the Amazon "Mechanical Turk" website. Participants were asked to answer questions regarding a series of vignettes depicting different sorts of deception in medical care, as well as a question regarding their general attitudes toward truth-telling. Results: Of the 200 respondents, the majority found the use of placebos in different contexts to be acceptable following partial disclosure but found it to be unacceptable if it involved outright lying. Also, 55.5% of respondents supported the use of sham surgery in clinical research, although 55% claimed that it would be unacceptable to deceive patients in this research, even if this would improve the quality of the data from the study. Respondents supported fully informing patients about distressing medical information in different contexts, especially when the patient is suffering from a chronic condition. In addition, 42.5% of respondents believed that it is worse to deceive someone by providing the person with false information than it is to do so by giving the person true information that is likely to lead them to form a false belief, without telling them other important information that shows it to be false. However, 41.5% believed that the two methods of deception were morally equivalent. Conclusions: Respondents believed that some forms of deception were acceptable in some circumstances. While the majority of our respondents opposed outright lying in medical contexts, they were prepared to support partial disclosure and the use of placebos when it is in the patient's interests or when it is what the person would want. These results support the position that physicians should be allowed a greater degree of authority to make a professional judgment about whether deception might be morally warranted by the circumstances, provided that it doesn't involve outright lying.
Pubmed ID: 26682239 RIS Download
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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