From text to interaction: The digital advance directive method for advance directives

Advance directives allow people to specify individual treatment preferences in case of decision-making incapacity involving decisions of utmost importance. There are many tools that provide information on the topic, digital forms for structured data input, or platforms that support data storage and availability. Yet, there is no tool supporting the innermost process of an advance directive: decision making itself. To address this issue, we developed a visual-interactive, semi-quantitative method for generating digital advance directives (DiADs) that harnesses the potential of digitalization in healthcare. In this article, we describe the DiAD method and its app lined with the exemplary narrative of user Mr S. linking the theory to an exemplary use case. The DiAD method is intended to lower barriers and increase comfort in creating an advance directive by shifting the focus from heavily text-based processes to visual representation and interaction, that is, from text to reflection. Keywords: Advance directive; data model; data representation; digital healthcare; visual-interactive application

The Advance Care Compass- A New Mechanics for Digitally Transforming Advance Directives

Advance directives allow people to declare their treatment preferences for a potential future state of incompetency. Covid-19, with its high numbers of quickly deteriorating patients requiring intensive care, has acutely demonstrated how helpful it would be for clinicians to have reliable, readily available, up-to-date information at hand to be able to act in accordance with what the individual patient would have wanted. Yet for the past few decades advance directives have fallen short of their potential, for various reasons. At worst, advance directives are perceived as unwieldy legal documents that put excessive demands on patients without providing useful guidance for better care. Recent efforts such as advance care planning have tried to remedy some of these shortcomings but have so far met with limited success. We suggest a new concept-the Advance Care Compass-that harnesses the potential of digitalization in healthcare to overcome many of difficulties encountered so far

Revisiting respect for persons: conceptual analysis and implications for clinical practice

In everyday conversations, professional codes, policy debates, and academic literature, the concept of respect is referred to frequently. Bioethical arguments in recent decades equate the idea of respect for persons with individuals who are capable of autonomous decision-making, with the focus being explicitly on 'autonomy,' 'capacity,' or 'capability.' In much of bioethics literature, respect for persons is replaced by respect for autonomy. Though the unconditional respect for persons and their autonomy (irrespective of actual decision-making capacity) is established in Kantian bioethics, current argument and debates often revolve around a thin concept of autonomy, focusing on capacity and capability: persons are owed respect because they are 'rational beings' or with a focus on 'agency' and 'decision-making abilities.' However, these aspects alone are insufficient while engaging the concept of respect for persons, particularly in healthcare settings. This paper sets out to explore if the concept of respect for persons-as opposed to a thin concept of autonomy-could help us engage better in healthcare practices. We shall probe the practical value of the experiential aspect of respect-understood as the recognition of persons as respect-worthy through certain dispositions and deliberative acts-by reflecting on instances in clinical practice that tend to be dismissed as negligible or even unavoidable in a stressful environment such as a busy hospital. We shall argue that these instances are far from trivial but carry moral significance and express an unacceptable-disrespectful-attitude that can compromise the moral habitus in hospital settings. In our conclusion, we call for practicing recognition respect in the health professional-patient encounter by focussing on manners, attitudes, and behaviors. Furthermore, we call for continuous medical ethics education programs to address the moral significance of disrespectful behaviors and their manifestations in particular socio-cultural contexts. Keywords: Autonomy; Clinical practice; Dignity; Ethics; Recognition; Respect

How to counter the anti-vaccine rhetoric: Filling information voids and building resilience

Widely circulating anti-vaccine misinformation online has been constituting a large obstacle for the success of COVID-19 vaccination campaigns and for the well-being of people during the pandemic. In this paper we discuss strategies to mitigate negative effects of online anti-vaccine contents on public health and to prevent hesitant individuals from falling prey of the traps set by anti-vaccine disinformation spreaders. Here we discuss the importance of filling information voids and understanding trends and concerns that shape the vaccine debate, and we highlight the relevance of building resilience to vaccine misinformation by strengthening public health and digital literacy

Financial incentives for participants in health research: when are they ethical?

Offering financial incentives to recruit participants, retain them and promote health-related behaviours is a common practice in health research. The development of health re- search standards has given rise to a rich and long-standing debate regarding the ethical issues associated with the use of financial incentives. Some researchers argue that financial incentives compromise the integrity of the research process and its outcomes. Since financial incentives can influence decision-making, they may jeopardise the voluntariness of research participants’ consent. In particular, they argue that the use of financial incentives may lead to undue inducement, exploitation and biased enrolment of research participants. At the same time, other researchers argue that financial incentives represent a flexible tool that can be designed in ways that do not compromise scientific integrity. They highlight that financial incentives can be fair inducements for participation, a way of acknowledging participants’ time and effort, and a means to achieve diverse sample compositions. They also point out that in some situations, these incentives can enable re-search that would otherwise be unfeasible. Defining when financial incentives might be suitable or not in health research studies is an important task ahead. It re- mains to be discussed how to weight the ethical issues at stake when offering financial incentives to influence be- haviour in implementation research, the relationship be- tween incentives and health outcomes in the context of socioeconomic disparities, and how to establish adequate incentives to influence health-related behaviours and out- comes. A public debate on financial incentives for par- ticipants in health studies will encourage the generation of better guidance for researchers, and contribute to safe- guard participants’ well-being in the creation of high-qual- ity knowledge

Black box algorithms in mental health apps: An ethical reflection

Mental health apps bring unprecedented benefits and risks to individual and public health. A thorough evaluation of these apps involves considering two aspects that are often neglected: the algorithms they deploy and the functions they perform. We focus on mental health apps based on black box algorithms, explore their forms of opacity, discuss the implications derived from their opacity, and propose how to use their outcomes in mental healthcare, self‐care practices, and research. We argue that there is a relevant distinction between functions performed by algorithms in mental health apps, and we focus on the functions of analysis and generation of advice. When performing analytic functions, such as identifying patterns and making predictions concerning people's emotions, thoughts, and behaviors, black box algorithms can be better than other algorithms to provide information to identify early signs of relapse, support diagnostic processes, and improve research by generating outcomes that lead to a better understanding of mental health. However, when carrying out the function of providing mental health advice, black box algorithms have the potential to deliver unforeseen advice that may harm users. We argue that the outcomes of these apps may be trustworthy as a complementary source of information, but express caution about black box algorithms that give advice directly to users. To reap the benefits of mental health apps based on black box algorithms and avoid unintended consequences, we critically need to know whether these algorithms are fulfilling the function of providing mental health advice