The organ donation and transplantation (ODT) system heavily relies on the willingness of individuals to donate their organs. While it is widely believed that public trust plays a crucial role in shaping donation rates, the empirical support for this assumption remains limited. In order to bridge this knowledge gap, this article takes a foundational approach by elucidating the concept of trust within the context of ODT. By examining the stakeholders involved, identifying influential factors, and mapping the intricate trust relationships among trustors, trustees, and objects of trust, we aim to provide a comprehensive understanding of trust dynamics in ODT. We employ maps and graphs to illustrate the functioning of these trust relationships, enabling a visual representation of the complex interactions within the ODT system. Through this conceptual groundwork, we pave the way for future empirical research to investigate the link between trust and organ donation rates, informed by a clarified understanding of trust in ODT. This study can also provide valuable insights to inform interventions and policies aimed at enhancing organ donation rates.

Trust and trustworthiness are essential for good healthcare, especially in mental healthcare. New technologies, such as mobile health apps, can affect trust relationships. In mental health, some apps need the trust of their users for therapeutic efficacy and explicitly ask for it, for example, through an avatar. Suppose an artificial character in an app delivers healthcare. In that case, the following questions arise: Whom does the user direct their trust to? Whether and when can an avatar be considered trustworthy? Our study aims to analyze different dimensions of trustworthiness in the context of mobile health app use. We integrate O'Neill's account of autonomy, trust, and trustworthiness into a model of trustworthiness as a relational concept with four relata: B is trustworthy with respect to A regarding the performance of Z because of C. Together with O'Neill's criteria of trustworthiness (honesty, competence, and reliability), this four-sided model is used to analyze different dimensions of trustworthiness in an exemplary case of mobile health app use. Our example focuses on an app that uses an avatar and is intended to treat sleep difficulties. The conceptual analysis shows that interpreting trust and trustworthiness in health app use is multi-layered and involves a net of interwoven universal obligations. At the same time, O'Neill's approach to autonomy, trust, and trustworthiness offers a normative account to structure and analyze these complex relations of trust and trustworthiness using mobile health apps.

AAL encompasses smart home technologies that are installed in the personal living environment in order to support older, disabled, as well as chronically ill people with the goal of delaying or reducing their need for nursing care in a care facility. Artificial intelligence (AI) is seen as an important tool for assisting the target group in their daily lives. A literature search and qualitative content analysis of 255 articles from computer science and engineering was conducted to explore the usage of ethical concepts. From an ethical point of view, the concept of independence and self-determination on the one hand and the possible loss of privacy on the other hand are widely discussed in the context of AAL. These concepts are adopted by the technical discourse in the sense that independence, self-determination and privacy are recognized as important values. Nevertheless, our research shows that these concepts have different usages and meanings in the ethical and the technical discourses. In the paper, we aim to map the different meanings of independence, self-determination and privacy as they can be found in the context of technological research on AI-based AAL systems. It investigates the interpretation of these ethical and social concepts which technicians try to build into AAL systems. In a second step, these interpretations are contextualized with concepts from the ethical discourse on AI-based assistive technologies.

Ambient Assisted Living (AAL) refers to technologies that track daily activities of persons in need of care to enhance their autonomy and minimise their need for assistance. New technological developments show an increasing effort to integrate automated emotion recognition and regulation (ERR) into AAL systems. These technologies aim to recognise emotions via different sensors and, eventually, to regulate emotions defined as “negative” via different forms of intervention. Although these technologies are already implemented in other areas, AAL stands out by its tendency to enable an inconspicuous 24-hour surveillance in the private living space of users who rely on the technology to maintain a certain degree of independence in their daily activities. The combination of both technologies represents a new dimension of emotion recognition in a potentially vulnerable group of users. Our paper aims to provide an ethical contextualisation of the novel combination of both technologies. We discuss different concepts of emotions, namely Basic Emotion Theory (BET) and the Circumplex Model of Affect (CMA), that form the basis of ERR and provide an overview over the current technological developments in AAL. We highlight four ethical issues that specifically arise in the context of ERR in AAL systems, namely concerns regarding (1) the reductionist view of emotions, (2) solutionism as an underlying assumption of these technologies, (3) the privacy and autonomy of users and their emotions, (4) the tendency of machine learning techniques to normalise and generalise human behaviour and emotional reactions.

Consumer-targeted sleep tracking applications (STA) that run on mobile devices (e.g., smartphones) promise to be useful tools for the individual user. Assisted by built-in and/or external sensors, these apps can analyze sleep data and generate assessment reports for the user on their sleep duration and quality. However, STA also raise ethical questions, for example, on the autonomy of the sleeping person, or potential effects on third parties. Nevertheless, a specific ethical analysis of the use of these technologies is still missing so far. The aim of the current analysis is to identify the characteristics of sleep tracking apps and to explore the specific ethical aspects associated with this form of self-tracking. Firstly, the field of mobile health applications was screened for STA to explore their typical functions and target user groups. Secondly, an ethical analysis was conducted focusing on the three ethical dimensions: (1) medicalization, (2) vulnerability, and (3) relationality. The analysis indicates that these three normative dimensions are decisive for assessing STA and that the ethical profile of this technology varies greatly depending on the respective user group. As the three dimensions medicalization, vulnerability, and relationality play a distinguishing role in the use of STA, they should be especially addressed in responsible development and implementation of STA. In addition, the analysis helps to evaluate the use of STA, in terms of different risks for specific user groups, the sensitive contexts of usage, and potential interference with the intimacy of third parties.

Background: In nursing homes, residents’ relatives represent important sources of support for nurses. However, in the heightened stress of emergency situations, interaction between nurses and relatives can raise ethical challenges. Research objectives: The present analysis aimed at elaborating a typology of nurses’ experience of ethical support and challenges in their interaction with relatives in emergency situations. Research design: Thirty-three semi-structured interviews and six focus groups were conducted with nurses from different nursing homes in Germany. Data were analysed according to Mayring’s method of qualitative content analysis. Participants and research context: Participants were licensed nurses working in nursing homes. Ethical considerations: Ethical approval was granted by Ostfalia University of Applied Sciences (02.07.2020) and the Ethics Committee of Hannover Medical School (Nr. 8866_BO_K_2020; 27.01.2020). Interviewees were anonymised and focus group were pseudonymised during transcription. All participants provided written consent. Findings/results: In emergency situations, relatives can represent important sources of support for nurses. However, they may also give rise to different challenges, relating to four ethical conflicts: (1) the challenge of meeting the information needs of relatives while providing appropriate care to all residents; (2) the challenge of managing relatives’ demands for hospitalisation when hospitalisation is not deemed necessary by nurses; (3) the challenge of managing relatives’ demands for lifesaving treatment when such treatment contradicts the will of the resident; and (4) the challenge of attempting to initiate hospitalisation when relatives oppose this course of action. Several external factors make these conflicts especially challenging for nurses: fear of legal consequences, a low staffing ratio, and a lack of qualified nursing staff. Conclusions: Conflict between nurses and relatives typically revolves around hospitalisation and the initiation of lifesaving treatment. Whether nurses perceive interaction with relatives as supportive or conflictual essentially depends on the quality of the relationship, which may be negatively influenced by a number of external factors.