BackgroundEvaluation of decision-making capacity to consent to medical treatment has proved to be difficult in patients with dementia. Studies showed that physicians are often insufficiently trained in the evaluation of decision-making capacity. In this study, we present findings from a secondary analysis of a qualitative interviews with physicians. These interviews were initially used to assess usability of an instrument for the evaluation of decision-making capacity. By looking at difficult cases of decision-making capacity evaluation in patients with dementia, we provide recommendations (...) for such evaluations in clinical practice.MethodsWe used thematic coding to analyse physicians’ narratives of problematic decision-making capacity evaluations in patients with dementia to uncover challenging issues of decision-making capacity evaluation.ResultsIn this study, decision-making capacity evaluations in patients with dementia were mainly perceived as challenging when they pertained to treatment refusals and treatment unrelated circumstances, such as psychiatric consultation, advance directives, and new living arrangements. Furthermore, the physicians reported training needs regarding situation-independent challenges with decision-making capacity evaluation.ConclusionsUpon further examining self-reported training needs and challenging cases, we have developed recommendations to improve decision-making capacity evaluations in clinical practice. In these recommendations, we argue that being able to evaluate decision-making capacity is an integral part of the informed consent process. (shrink)

Assistive systems based on Artificial Intelligence (AI) are bound to reshape decision-making in all areas of society. One of the most intricate challenges arising from their implementation in high-stakes environments such as medicine concerns their frequently unsatisfying levels of explainability, especially in the guise of the so-called black-box problem: highly successful models based on deep learning seem to be inherently opaque, resisting comprehensive explanations. This may explain why some scholars claim that research should focus on rendering AI systems understandable, rather (...) than explainable. Yet, there is a grave lack of agreement concerning these terms in much of the literature on AI. We argue that the seminal distinction made by the philosopher and physician Karl Jaspers between different types of explaining and understanding in psychopathology can be used to promote greater conceptual clarity in the context of Machine Learning (ML). Following Jaspers, we claim that explaining and understanding constitute multi-faceted epistemic approaches that should not be seen as mutually exclusive, but rather as complementary ones as in and of themselves they are necessarily limited. Drawing on the famous example of Watson for Oncology we highlight how Jaspers’ methodology translates to the case of medical AI. Classical considerations from the philosophy of psychiatry can therefore inform a debate at the centre of current AI ethics, which in turn may be crucial for a successful implementation of ethically and legally sound AI in medicine. (shrink)

Digital Pills are an innovative drug-device technology that permits to combine traditional medications with a monitoring system that automatically records data about medication adherence as well as patients’ physiological data. Although DP are a promising innovation in the field of digital medicine, their use has also raised a number of ethical concerns. These ethical concerns, however, have been expressed principally from a theoretical perspective, whereas an ethical analysis with a more empirically oriented approach is lacking. There is also a lack (...) of clarity about the empirical evidence available concerning the application of this innovative digital medicine. To map the studies where DP have been tested on patients and discuss the ethically relevant issues evident therein, we performed a scoping review of the empirical literature concerning DP. Our search allowed us to identify 18 papers reporting on studies where DP were tested on patients. These included studies with different designs and involving patients with a variety of conditions. In the empirical literature, a number of issues with ethical relevance were evident. At the patient level, the ethical issues include users’ interaction with DP, personal sphere, health-related risks and patients’ benefits. At the provider level, ethically relevant issues touch upon the doctor-patient relationship and the question of data access. At the societal level, they concern the benefits to society, the quality of evidence and the dichotomy device-medicine. We conclude that evidence concerning DP is not robust and that more research should be performed and study results made available to evaluate this digital medicine. Moreover, our analysis of the ethically relevant aspects within empirical literature underscores that there are concrete and specific open questions that should be tackled in the ethical discussion about this new technological solution. (shrink)

In the future, policies surrounding end-of-life decisions will be faced with the question of whether competent people in a completely locked-in state should be enabled to make end-of-life decisions via brain-computer interfaces (BCI). This article raises ethical issues with acting through BCIs in the context of these decisions, specifically self-administration requirements within assisted suicide policies. We argue that enabling patients to end their life even once they have entered completely locked-in state might, paradoxically, prolong and uphold their quality of life.

While the developers of the “Ixtlan Basic Kit” promise a curative treatment taking advantage of increased neuroplasticity for targeting the underlying neurological causes of Alzheimer's disease and...

The concepts of hope and its absence, hopelessness, are seen as crucial in palliative care for people with motor neurone disease. A primary measure in psychological research on hopelessness in people with motor neurone disease is the Beck Hopelessness Scale. This scale can be understood as being conceptually based on the philosophical standard account of hope, which understands hope as an intentional expectancy. This essay argues that this is a misconstruction of hopelessness in palliative care. Rather, pre-intentional hope is essential (...) for palliative care of people with motor neurone disease. Pre-intentional hope enables the formation of intentional hopes and is intrinsically relational. Finally, it is argued that the absence of pre-intentional hope should not be subjected to psychiatric diagnosis, for example, in the form of demoralization disorder. (shrink)