Alleviating the burden of malaria with gene drive technologies? A biocentric analysis of the moral permissibility of modifying malaria mosquitoes.

Gene drive technologies (GDTs) have been proposed as a potential new way to alleviate the burden of malaria, yet have also raised ethical questions. A central ethical question regarding GDTs relates to whether it is morally permissible to intentionally modify or eradicate mosquitoes in this way and how the inherent worth of humans and non-human organisms should be factored into determining this. Existing analyses of this matter have thus far generally relied on anthropocentric and zoocentric perspectives and rejected an individualist biocentric outlook in which all living organisms are taken to matter morally for their own sake. In this paper, we reconsider the implications of taking a biocentric approach and highlight nuances that may not be evident at first glance. First, we shortly discuss biocentric perspectives in general, and then outline Paul Taylor's biocentric theory of respect for nature. Second, we explore how conflicting claims towards different organisms should be prioritised from this perspective and subsequently apply this to the context of malaria control using GDTs. Our ethical analysis shows that this context invokes the principle of self-defence, which could override the pro tanto concerns that a biocentrist would have against modifying malaria mosquitoes in this way if certain conditions are met. At the same time, the case study of GDTs underlines the relevance of previously posed questions and criticism regarding the internal consistency of Taylor's egalitarian biocentrism.

Responsibility beyond design: Physicians' requirements for ethical medical AI.

Medical AI is increasingly being developed and tested to improve medical diagnosis, prediction and treatment of a wide array of medical conditions. Despite worries about the explainability and accuracy of such medical AI systems, it is reasonable to assume that they will be increasingly implemented in medical practice. Current ethical debates focus mainly on design requirements and suggest embedding certain values such as transparency, fairness, and explainability in the design of medical AI systems. Aside from concerns about their design, medical AI systems also raise questions with regard to physicians' responsibilities once these technologies are being implemented and used. How do physicians' responsibilities change with the implementation of medical AI? Which set of competencies do physicians have to learn to responsibly interact with medical AI? In the present article, we will introduce the notion of forward-looking responsibility and enumerate through this conceptual lens a number of competencies and duties that physicians ought to employ to responsibly utilize medical AI in practice. Those include amongst others understanding the range of reasonable outputs, being aware of own experience and skill decline, and monitoring potential accuracy decline of the AI systems.

Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI.

The use of black box algorithms in medicine has raised scholarly concerns due to their opaqueness and lack of trustworthiness. Concerns about potential bias, accountability and responsibility, patient autonomy and compromised trust transpire with black box algorithms. These worries connect epistemic concerns with normative issues. In this paper, we outline that black box algorithms are less problematic for epistemic reasons than many scholars seem to believe. By outlining that more transparency in algorithms is not always necessary, and by explaining that computational processes are indeed methodologically opaque to humans, we argue that the reliability of algorithms provides reasons for trusting the outcomes of medical artificial intelligence (AI). To this end, we explain how computational reliabilism, which does not require transparency and supports the reliability of algorithms, justifies the belief that results of medical AI are to be trusted. We also argue that several ethical concerns remain with black box algorithms, even when the results are trustworthy. Having justified knowledge from reliable indicators is, therefore, necessary but not sufficient for normatively justifying physicians to act. This means that deliberation about the results of reliable algorithms is required to find out what is a desirable action. Thus understood, we argue that such challenges should not dismiss the use of black box algorithms altogether but should inform the way in which these algorithms are designed and implemented. When physicians are trained to acquire the necessary skills and expertise, and collaborate with medical informatics and data scientists, black box algorithms can contribute to improving medical care.

National Standards for Public Involvement in Research: missing the forest for the trees.

Biomedical research funding bodies across Europe and North America increasingly encourage-and, in some cases, require-investigators to involve members of the public in funded research. Yet there remains a striking lack of clarity about what 'good' or 'successful' public involvement looks like. In an effort to provide guidance to investigators and research organisations, representatives of several key research funding bodies in the UK recently came together to develop the National Standards for Public Involvement in Research. The Standards have critical implications for the future of biomedical research in the UK and in other countries as researchers and funders abroad look to the Standards as a model for their own policy development. We assess the Standards and find that despite offering useful suggestions for dealing with practical challenges associated with public involvement, the Standards fail to address fundamental questions about when, why and with whom public involvement should be undertaken in the first place. We show that presented without this justificatory context, many of the recommendations in the Standards are, at best, fragments that require substantial elaboration by those looking to apply the Standards in their own work and, at worst, subject to potentially harmful misapplication by well-meaning investigators. As funding bodies increasingly push for public involvement in research, the key lesson of our analysis is that future recommendations about how public involvement should be conducted cannot be coherently formulated without a clear sense of the underlying goals and rationales for public involvement.

The usual suspects: why techno-fixing dementia is flawed.

Dementia is highly prevalent and up until now, still incurable. If we may believe the narrative that is currently dominant in dementia research, in the future we will not have to suffer from dementia anymore, as there will be a simple techno-fix solution. It is just a matter of time before we can solve the growing public health problem of dementia. In this paper we take a critical stance towards overly positive narratives of techno-fixes by placing our empirical analysis of dementia research protocols and political statements in a framework of technology assessment. From this perspective, it becomes obvious that a techno-fix is just one of many ways to approach societal problems and more importantly that technologies are way less perfect than they are presented. We will argue that this narrow scope, which focusses on the usual suspects for solving illnesses, reduces dementia to organismic aspects, and may be counterproductive in finding a cure for dementia. We conclude with outlining how the narrow scope can be balanced with other narratives and why we should have a reasonable scepticism towards the usual suspects.

The implausibility of response shifts in dementia patients.

Dementia patients may express wishes that do not conform to or contradict earlier expressed preferences. Our understanding of the difference between their prior preferences and current wishes has important consequences for the way we deal with advance directives. Some bioethicists and gerontologists have argued that dementia patients change because they undergo a 'response shift'. In this paper we question this assumption. We will show that proponents of the response shift use the term imprecisely and that response shift is not the right model to explain what happens to dementia patients. We propose a different explanation for the changed wishes of dementia patients and conclude that advance directives of dementia patients cannot be simply put aside.

Beyond competence: advance directives in dementia research.

Dementia is highly prevalent and incurable. The participation of dementia patients in clinical research is indispensable if we want to find an effective treatment for dementia. However, one of the primary challenges in dementia research is the patients' gradual loss of the capacity to consent. Patients with dementia are characterized by the fact that, at an earlier stage of their life, they were able to give their consent to participation in research. Therefore, the phase when patients are still competent to decide offers a valuable opportunity to authorize research, by using an advance research directive (ARD). Yet, the use of ARDs as an authorization for research participation remains controversial. In this paper we discuss the role of autonomous decision-making and the protection of incompetent research subjects. We will show why ARDs are a morally defensible basis for the inclusion of this population in biomedical research and that the use of ARDs is compatible with the protection of incompetent research subjects.

Establishing a multistakeholder research agenda: lessons learned from a James Lind Alliance Partnership.

OBJECTIVE: The James Lind Alliance (JLA) offers a method for better aligning health and care agenda's with the needs of patients, carers and clinicians by bringing them together in a Priority Setting Partnership (PSP). In this paper, we draw attention to crucial lessons learnt when establishing such a shared research agenda. KEY ARGUMENTS: Having specific strategies and plans in place for maximising dialogic processes in a PSP can help facilitate and maintain trust, innovation and equal inclusion. CONCLUSION: Eight lessons learnt have been formulated, based on our observations and reflections on the JLA PSP and our expertise on patient participation and participatory research.

User Experiences With and Recommendations for Mobile Health Technology for Hypertensive Disorders of Pregnancy: Mixed Methods Study.

BACKGROUND: Hypertensive disorders of pregnancy (HDP) are a primary cause of adverse maternal and neonatal outcomes worldwide. For women at risk of hypertensive complications, guidelines recommend frequent surveillance of blood pressure and signs of preeclampsia. Clinic visits range from every 2 weeks to several times a week. Given the wide ubiquity of smartphones and computers in most countries and a growing attention for self-management, digital technologies, including mobile health (mHealth), constitute a promising component of monitoring (self-measured) blood pressure during pregnancy. Currently, little is known about the experiences of women using such platforms and how mHealth can be aligned with their needs and preferences. OBJECTIVE: The objectives were twofold: (1) to explore the experiences of Dutch women who had an increased risk of HDP with a blended care approach (mHealth combined with face-to-face care) for remote self-monitoring of blood pressure and preeclampsia symptoms and (2) to formulate recommendations for the use and integration of mHealth in clinical care. METHODS: Alongside a prospective blended care study (SAFE@home study) that monitors pregnant women at increased risk of HPD with mHealth technology, a mixed methods study was conducted, including questionnaires (n=52) and interviews (n=11). Results were analyzed thematically. RESULTS: Of the 4 themes, 2 themes were related to the technologies themselves (expectations, usability), and 2 themes were related to the interaction and use of mHealth (autonomy and responsibilities of patients, responsibilities of health care professionals). First, the digital platform met the expectations of patients, which contributed to user satisfaction. Second, the platform was considered user-friendly, and patients favored different moments and frequencies for measuring their blood pressure. Third, patient autonomy was mentioned in terms of increased insight about their own condition and being able to influence clinical decision making. Fourth, clinical expertise of health care professionals was considered essential to interpret the data, which translates to subsequent responsibilities for clinical management. Data from the questionnaires and interviews corresponded. CONCLUSIONS: Blended care using an mHealth tool to monitor blood pressure in pregnancy was positively evaluated by its users. Insights from participants led to 7 recommendations for designing and implementing similar interventions and to enhance future, morally sound use of digital technologies in clinical care.