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PURPOSE: Cancer care in Germany during the COVID-19 pandemic was affected by resource scarcity and the necessity to prioritize medical measures. This study explores ethical criteria for prioritization and their application in cancer practices from the perspective of German oncologists and other experts. METHODS: We conducted fourteen semi-structured interviews with German oncologists between February and July 2021 and fed findings of interviews and additional data on prioritizing cancer care into four structured group discussions, in January and February 2022, with 22 experts from medicine, nursing, law, ethics, health services research and health insurance. Interviews and group discussions were digitally recorded, transcribed verbatim and analyzed using qualitative content analysis. RESULTS: Narratives of the participants focus on "urgency" as most acceptable criterion for prioritization in cancer care. Patients who are considered curable and those with a high level of suffering, were given a high degree of "urgency." However, further analysis indicates that the "urgency" criterion needs to be further distinguished according to at least three different dimensions: "urgency" to (1) prevent imminent harm to life, (2) prevent future harm to life and (3) alleviate suffering. In addition, "urgency" is modulated by the "success," which can be reached by means of an intervention, and the "likelihood" of reaching that success. CONCLUSION: Our analysis indicates that while "urgency" is a well-established criterion, its operationalization in the context of oncology is challenging. We argue that combined conceptual and clinical analyses are necessary for a sound application of the "urgency" criterion to prioritization in cancer care.

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A growing trend in bioethics highlights the importance of using big data science methods to advance normative insight. This has been called the "digital turn" in bioethics by Salloch and Ursin. Automated data processing can, for example, detect significant patterns of correlation that have escaped the attention of human scholars. Although we agree that such technological innovations could bolster existing methods in empirical bioethics (EB), we argue that it should not be conceptualized as a new turn but rather as a revivification, and possibly an amplification of entrenched debates in EB. We begin by highlighting some convergences between EB and digital bioethics that Salloch and Ursin seem to categorize as fundamental differences and end up with elaborating on some risks related to the integration of empirical findings with normative (philosophical) analysis in the digitalization trend.

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Moral distress denotes a negative reaction to a morally challenging situation. It has been associated with adverse outcomes for healthcare professionals, patients and healthcare institutions. We argue that existing definitions, along with measures of moral distress, compromise the validity of empirical research. First, the definition and measurement of moral distress conflate moral events and psychological distress, even though they are distinct phenomena that should be assessed independently. Second, in many studies, there is a lack of clarity in distinguishing between moral and non-moral events. Finally, prior research on moral distress often overlooks the substantial body of evidence demonstrating the impact of diverse work-related factors, beyond moral events, on both distress and job retention. These challenges might undermine the effectiveness of interventions aimed at alleviating moral distress. We outline a comprehensive research agenda that encompasses conceptual clarifications, the refinement of data collection instruments, the design of studies and the application of appropriate statistical methods.

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BACKGROUND: The emergence of molecular HIV surveillance (MHS) and cluster detection and response (CDR) programs as key features of the United States (US) HIV strategy since 2018 has caused major controversies. HIV surveillance programs that re-use individuals' routinely collected clinical HIV data do not require consent on the basis that the public benefit of these programs outweighs individuals' rights to opt out. However, criticisms of MHS/CDR have questioned whether expanded uses of HIV genetic sequence data for prevention reach beyond traditional public health ethics frameworks. This study aimed to explore views on consent within MHS/CDR among critical stakeholders. METHODS: In 2021 we interviewed 26 US HIV stakeholders who identified as being critical or concerned about the rollout of MHS/CDR. Stakeholders included participants belonging to networks of people living with HIV, other advocates, academics, and public health professionals. This analysis focused on identifying the range of positions among critical and concerned stakeholders on consent affordances, opt-outs, how to best inform people living with HIV about how data about them are used in public health programs, and related ethical issues. RESULTS: Participants were broadly supportive of introducing some forms of consent into MHS/CDR. However, they differed on the specifics of implementing consent. While some participants did not support introducing consent affordances, all supported the idea that people living with HIV should be informed about how HIV surveillance and prevention is conducted and how individuals' data are used. CONCLUSIONS: MHS/CDR has caused sustained controversy. Among critical stakeholders, consent is generally desirable but contested, although the right for people living with HIV to be informed was centrally supported. In an era of big data-driven public health interventions and routine uses of HIV genetic sequence data in surveillance and prevention, CDC and other agencies should revisit public health ethics frameworks and consider the possibility of consent processes.

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BACKGROUND: Our objective was to evaluate whether the description of a machine learning (ML) app or brain imaging technology to predict the onset of schizophrenia or alcohol use disorder (AUD) influences healthcare professionals' judgments of stigma, empathy, and compassion. METHODS: We randomized healthcare professionals (N = 310) to one vignette about a person whose clinician seeks to predict schizophrenia or an AUD, using a ML app, brain imaging, or a psychosocial assessment. Participants used scales to measure their judgments of stigma, empathy, and compassion. RESULTS: Participants randomized to the ML vignette endorsed less anger and more fear relative to the psychosocial vignette, and the brain imaging vignette elicited higher pity ratings. The brain imaging and ML vignettes evoked lower personal responsibility judgments compared to the psychosocial vignette. Physicians and nurses reported less empathy than clinical psychologists. CONCLUSIONS: The use of predictive technologies may reinforce essentialist views about mental health and substance use that may increase specific aspects of stigma and reduce others.

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The shift towards "empirical bioethics" was largely triggered by a recognition that stakeholders' views and experiences are vital in ethical analysis where one hopes to produce practicable recommendations. Such perspectives can provide a rich resource in bioethics scholarship, perhaps challenging the researcher's perspective. However, overreliance on a picture painted by a group of research participants-or on pre-existing literature in that field-can lead to a biased view of a given context, as the subjectivity of data generated in these ways cannot (and should not wholly) be escaped. In response, we propose the implementation of a complementary approach of ethno-immersion in bioethics research. By positioning oneself in the context being researched, the researcher can better understand the realities of that context. The researcher's understanding will, naturally, be subjective too. However, it will act as a better developed and more informed outsider view, when considering the picture painted by participants and previous studies, thus enabling the researcher to introduce more nuance when analysing data. We introduce this approach after examining what we call the context detachment problem, whereby some bioethics scholarship-empirical or otherwise-fails to reflect the reality of the healthcare setting it concerns. Our proposed ethno-immersion (which differs from formal ethnography) is then explored as a response, highlighting its benefits, and answering the question of timing within a research project. Finally, we reflect on the applicability of our proposal to non-empirical bioethics scholarship, concluding that it remains important but may require some adjustments.

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Synthetic biology is a broad term covering multiple scientific methodologies, technologies, and practices. Pairing biology with engineering, synbio seeks to design and build biological systems, either through improving living cells by adding in new functions, or creating new structures by combining natural and synthetic components. As with all new technologies, synthetic biology raises a number of ethical considerations. In order to understand what these issues might be, and how they relate to those covered in ethics literature on synbio, we conducted an interview study with practicing synthetic biologists affiliated with a synthetic biology centre in Australia. Scientists identified a range of ethical challenges germane to the field, including precarious employment, pressures from industry, gender inequity, and the negative effects of the hyping of synbio. These challenges differed markedly from those identified in the ethics literature, whose treatment of the harms and benefits of synbio remains largely speculative and abstract. In our discussion of the pragmatic, every day ethical issues synthetic biologists face, we illustrate how issues of waste or research integrity play pivotal roles in everything from lived experiences in the laboratory, to long-term research trajectories guiding the field. In a confirmation of the ethical relevance of our participant's views on the field, we argue that the subjects they raise must be included in any ethical analysis of synbio as a field.

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Empirical data can be an extremely powerful and influential tool in bioethical research. However, when researchers or policy makers look for answers to ethical questions by engaging with empirical research, there can be a tendency (conscious or unconscious) to shape, report, and use empirical research in a way that confirms their own preferred ethical conclusions. This skewing effect - what we call 'normative bias' - is often so subtle it falls short of clear misconduct and thus can be difficult to call out. However, we argue that this subtle influence of bias has the potential to significantly influence debate and policy around highly sensitive ethical issues and must be guarded against. In this paper we share the lessons we have learned through a journey of self-reflection around the effect that normative bias can have when reporting on and referring to empirical data relating to ethical issues. We use a variety of papers from our area of the ethics of routine prenatal screening to illustrate these subtle but often powerfully distorting effects of bias. Our aim in doing so is not to criticise the work of others, as we recognise our own normative bias, but to improve awareness of this issue, remind the need for reflexivity to guard against our own biases, and introduce a new criterion - the idea of a 'limitation prominence assessment' - that can work as a practical way to evaluate the seriousness of the limitations of an empirical study and thus, the risks of the study being misread or misinterpreted through superficial reading.

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The integration of normative analysis with empirical data often remains unclear despite the availability of many empirical bioethics methodologies. This paper sought bioethics scholars' experiences and reflections of doing empirical bioethics research to feed these practical insights into the debate on methods. We interviewed twenty-six participants who revealed their process of integrating the normative and the empirical. From the analysis of the data, we first used the themes to identify the methodological content. That is, we show participants' use of familiar methods explained as "back-and-forth" methods (reflective equilibrium), followed by dialogical methods where collaboration was seen as a better way of doing integration. Thereafter, we highlight methods that were deemed as inherent integration approaches, where the normative and the empirical were intertwined from the start of the research project. Second, we used the themes to express not only how we interpreted what was said but also how things were said. In this, we describe an air of uncertainty and overall vagueness that surrounded the above methods. We conclude that the indeterminacy of integration methods is a double-edged sword. It allows for flexibility but also risks obscuring a lack of understanding of the theoretical-methodological underpinnings of empirical bioethics research methods.

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Health innovation is mainly envisioned in direct connection to medical research institutions or pharmaceutical and technology companies. Yet, these types of innovation often do not meet the needs and expectations of individuals affected by health conditions. With the emergence of digital health technologies and social media, we can observe a shift, which involves people living with illness modifying and improving medical and health devices outside of the formal research and development sector, figuring both as users and innovators. This patient-led innovation has been celebrated in innovation studies and economics as a "bottom-up" type of innovation. In this article, we take a closer look at open-source patient-led innovation in the context of type 1 diabetes care. In our inquiry, we pay particular attention to the social and ethical dimensions of this innovation, building on empirical material. Upon exploring the notion of patient-led innovation and its socio-political context through the lens of intersectional and global health justice, we argue that a proactive strategy is needed to ensure that open-source patient-led innovation will be more globally accessible, center the health needs of the most underserved populations, as well as facilitate equitable and just health benefits. To support this aim, we provide a range of examples of different initiatives addressing the persistent inequalities that have so far inhibited patient-led innovation from more fully materializing its innovative potential.

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It can be assumed that value judgements, which are needed to judge what is 'good' or 'better' and what is 'bad' or 'worse', are involved in every decision-making process. The theoretical understanding and analysis of value judgements is, therefore, important in the context of bioethics, for example, to be able to ethically assess real decision-making processes in biomedical practice and make recommendations for improvements. However, real decision-making processes and the value judgements inherent in them must first be investigated empirically ('empirical bioethics'). For this to succeed, what exactly a 'value judgement' is and of what components it might consist must initially be theoretically clarified. A corresponding conceptual model can then support or even enable empirical data collection and analysis and, above all, subsequent ethical analysis and evaluation. This paper, therefore, presents a value judgement model with its theoretical derivation. It also illustrates its application in an interview study of decision-making between animal experimentation and alternative methods in the context of biomedical research. Though the model itself can be theoretically deepened and extended, the application of the model works in general and helps to uncover what value judgements can enter into decision-making. However, the empirical methods, for example, qualitative interviews, can also be better oriented towards eliciting value judgements (as understood according to the model). Further applications of the model to other topics or by means of other empirical methods are conceivable.

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BACKGROUND: Empirical research can become relevant for bioethics in at least two ways. First, by informing the development or refinement of ethical recommendations. Second, by evaluating how ethical recommendations are translated into practice. This study aims to investigate the scope and objectives of empirical studies evaluating how ethical recommendations are translated into practice. METHODS: A sample of the latest 400 publications from four bioethics journals was created and screened. All publications were included if they met one of the following three criteria: (1) evaluative empirical research, (2) non-evaluative empirical research and (3) borderline cases. For all publications categorized as evaluative empirical research we analyzed which objects (norms and recommendations) had been evaluated. RESULTS: 234 studies were included of which 54% (n = 126) were categorized as non-evaluative empirical studies, 36% (n = 84) as evaluative empirical studies, and 10% (n = 24) as borderline cases. The object of evaluation were aspirational norms in 5 of the 84 included evaluative empirical studies, more specific norms in 14 (16%) studies and concrete best practices in 65 (77%) studies. The specific best practices can be grouped under five broader categories: ethical procedures, ethical institutions, clinical or research practices, educational programs, and legal regulations. CONCLUSIONS: This mapping study shows that empirical evaluative studies can be found at all stages in the translational process from theory to best practices. Our study suggests two intertwined dimensions for structuring the field of evaluative/translational empirical studies in bioethics: First, three broader categories of evaluation objects and second five categories for types of best practices. TRIAL REGISTRATION: The methodology used was described in a study protocol that was registered publicly on the Open Science Framework ( https://osf.io/r6h4y/ ).

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While various definitions of moral distress have been proposed, some agreement exists that it results from illegitimate constraints in clinical practice affecting healthcare professionals' moral agency. If we are to reduce moral distress, instruments measuring it should provide relevant information about such illegitimate constraints. Unfortunately, existing instruments fail to do so. We discuss here several shortcomings of major instruments in use: their inability to determine whether reports of moral distress involve an accurate assessment of the requisite clinical and logistical facts in play, whether the distress in question is aptly characterized as moral, and whether the moral distress reported is an appropriate target of elimination. Such failures seriously limit the ability of empirical work on moral distress to foster appropriate change.

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The so-called "empirical turn" in bioethics gave rise to extensive theoretical and methodological debates and has significantly shaped the research landscape from two decades ago until the present day. Attentive observers of the evolution of the bioethical research field now notice a new trend towards the inclusion of data science methods for the treatment of ethical research questions. This new research domain of "digital bioethics" encompasses both studies replacing (or complementing) socio-empirical research on bioethical topics ("empirical digital bioethics") and argumentative approaches towards normative questions in the healthcare domain ("argumentative digital bioethics"). This article draws on insights taken from the debate on the "empirical turn" for sounding out perspectives for the newly developing field of "digital bioethics." We particularly discuss the disciplinary boundaries, chances and challenges, and potentially undesirable developments of the research field. The article closes with concrete suggestions on which debates need to be initiated and which measures need to be taken so that the path forward of "digital bioethics" will be a scientific success.

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BACKGROUND: Over the last decades, the neurosciences, behavioral sciences, and the social sciences have all seen a rapid development of innovative research methods. The field of bioethics, however, has trailed behind in methodological innovation. Despite the so-called "empirical turn" in bioethics, research methodology for project development, data collection and analysis, and dissemination has remained largely restricted to surveys, interviews, and research papers. We have previously argued for a "Design Bioethics" approach to empirical bioethics methodology, which develops purpose-built methods for investigation of bioethical concerns. In this paper we compare a research tool created using a design bioethics approach to a "methods-as-usual" approach in empirical bioethics. METHODS: Our study compared dimensions of engagement with a digital game we created, called "Tracing Tomorrow," to a standard vignette survey. The two tools investigated the same subject matter, digital phenotyping for mental health, in a sample of 301 UK adolescents. RESULTS: Participants who played the game reported a greater sense of presence, emotional engagement, cognitive absorption, and mental health ethics insight, compared to participants who completed the vignette survey. Perceived authenticity and curiosity/motivation to learn more was equivalent for both methods. CONCLUSION: The results of this study highlights the importance of purpose-built methodology for empirical bioethics research.

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Background: Due to rising healthcare expenditures, countries with publicly funded healthcare systems face challenges when providing newly approved expensive anti-cancer treatments to all eligible patients. In the Netherlands in 2015, the so-called Coverage Lock (CL), was introduced to help safeguard the sustainability of the healthcare system. Since then, newly approved treatments are no longer automatically reimbursed. Previous work has shown that as policies for access to CL treatments are lacking, patient access to non-reimbursed treatments is limited and variable, which raises ethical issues. The ethics of access were discussed in a series of multi-stakeholder dialogues in the Netherlands. Methods: Three dialogues were held in early 2023 and included physicians, health insurers, hospital executives, policymakers, patients, citizens, and representatives of pharmaceutical companies, patient and professional organizations. In advance, participants had received an 'argument scheme' featuring three models: 1) access based on third-party payment (e.g., by pharmaceutical companies, health insurers or hospitals) 2) access based on out-of-pocket payments by patients 3) no access to CL treatments. During the dialogues, participants were asked to discuss the merits of the ethical arguments for and against these models together, and ultimately to weigh them. The discussions were audio-taped, transcribed, coded, and thematically analyzed. Results: Generally, most stakeholders were in favour of allowing access-at least when treatments are clearly beneficial-to treatments in the CL. When discussing third-party payment, stakeholders favoured payment by pharmaceutical companies over payment by health insurers or hospitals, not wanting to usurp collective funds while cost-effectiveness assessments are still pending. Largely, stakeholders were not in favour of out-of-pocket payments, emphasizing solidarity and equal access as important pillars of the Dutch healthcare system. Recurrent themes included the conflict between individual and collective interests, shifting attitudes, withholding access as a means to put pressure on the system, and the importance of transparency about access to CL-treatments. Conclusion: Policies for access to non-reimbursed treatments should address stakeholders' concerns regarding transparency, equal access and solidarity, and loss of potential health benefits for patients. Multi-stakeholder dialogues are an important tool to help inform policy-making on access to newly approved (too) expensive treatments in countries facing challenges to the sustainability of healthcare systems.

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BACKGROUND: This is the first qualitative study to investigate how researchers, who do empirical work in bioethics, relate to objectives of empirical research in bioethics (ERiB). We explore reasons that make some objectives more acceptable, while others are deemed less acceptable. METHODS: Using qualitative exploratory study design, we interviewed bioethics researchers, who were selected to represent different types of scholars working in the field. The interview data of 25 participants were analyzed in this paper using thematic analysis. RESULTS: From the eight objectives presented to the study participants, understanding the context of a bioethical issue and identifying ethical issues in practice received unanimous agreement. Participants also supported other objectives of ERiB but with varying degrees of agreement. The most contested objectives were striving to draw normative recommendations and developing and justifying moral principles. The is-ought gap was not considered an obstacle to ERiB, but rather a warning sign to critically reflect on the normative implications of empirical results. CONCLUSIONS: Our results show that the most contested objectives are also the more ambitious ones, whereas the least contested ones focus on producing empirical results. The potential of empirical research to be useful for bioethics was mostly based on the reasoning pattern that empirical data can provide a testing ground for elements of normative theory. Even though empirical research can inform many parts of bioethical inquiry, normative expertise is recommended to guide ERiB. The acceptability of ambitious objectives for ERiB boils down to finding firm ground for the integration of empirical facts in normative inquiry.

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BACKGROUND: This study aims to quantitatively and qualitatively evaluate the activities of a Bioethics Unit (BU) 5 years since its implementation (2016-2020). The BU is a research unit providing empirical research on ethical issues related to clinical practice, clinical ethics consultation, and ethical education for health care professionals (HPS). METHODS: We performed an explanatory, sequential, mixed-method, observational study, using the subsequent qualitative data to explain the initial quantitative findings. Quantitative data were collected from an internal database and analyzed by descriptive analysis. Qualitative evaluation was performed by semi-structured interviews with 18 HPs who were differently involved in the BU's activities and analyzed by framework analysis. RESULTS: Quantitative results showed an extensive increment of the number of BU research projects over the years and the number of work collaborations with other units and wards. Qualitative findings revealed four main themes, concerning: 1. the reasons for contacting the BU and the type of collaboration; 2. the role of the bioethicist; 3. the impact of BU activities on HPs, in terms of developing deeper and more mature thinking; 4. the need to extend ethics support to other settings. Overall, our results showed that performing both empirical bioethics research and more traditional clinical ethics activities at the same unit would produce an impetus to increase collaboration and spread an 'ethical culture' among local HPs. CONCLUSIONS: Our findings contribute to a growing body of literature on the models of clinical ethics support services and the role of empirical research in bioethics internationally. They also prepare the ground for the implementation of a multidisciplinary Clinical Ethics Committee (CEC) that aims to support the BU's ethics consultation service within the local context.

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BACKGROUND: The rise of digital methods and computational tools has opened up the possibility of collecting and analyzing data from novel sources, such as discussions on social media. At the same time, these methods and tools introduce a dependence on technology, often resulting in a need for technical skills and expertise. Researchers from various disciplines engage in empirical bioethics research, and software development and similar skills are not usually part of their background. Therefore, researchers often depend on technical experts to develop and apply digital methods, which can create a bottleneck and hinder the broad use of digital methods in empirical bioethics research. OBJECTIVE: This study aimed to develop a research platform that would offer researchers the means to better leverage implemented digital methods, and that would simplify the process of developing new methods. METHODS: This study used a mixed methods approach to design and develop a research platform prototype. I combined established methods from user-centered design, rapid prototyping, and agile software development to iteratively develop the platform prototype. In collaboration with two other researchers, I tested and extended the platform prototype in situ by carrying out a study using the prototype. RESULTS: The resulting research platform prototype provides three digital methods, which are composed of functional components. This modular concept allows researchers to use existing methods for their own experiments and combine implemented components into new methods. CONCLUSIONS: The platform prototype illustrates the potential of the modular concept and empowers researchers without advanced technical skills to carry out experiments using digital methods and develop new methods. However, more work is needed to bring the prototype to a production-ready state.

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Attempts to conduct systematic reviews of ethical arguments in bioethics are fundamentally misguided. All areas of enquiry need thorough and informative literature reviews, and efforts to bring transparency and systematic methods to bioethics are to be welcomed. Nevertheless, the raw materials of bioethical articles are not suited to methods of systematic review. The eclecticism of philosophy may lead to suspicion of philosophical methods in bioethics. Because bioethics aims to influence medical and scientific practice it is tempting to adopt scientific language and methods. One manifestation is the increasing innovation in, and use of, systematic reviews of ethical arguments in bioethics. Yet bioethics, as a broadly philosophical area of enquiry, is unsuited to systematic review. Bioethical arguments are evaluative, so notions of quality and bias are inapplicable. Bioethical argument is conceptual rather than numerical, and the classification of concepts is itself a process of argument that cannot aspire to neutrality. Any 'systematic review' of ethical arguments in bioethics thus falls short of that name. Furthermore, labels matter. Although the bioethics research community may find that adopting the language and the outward methods of clinical science offers apparent prospects of credibility, policy influence and funding, we argue that such misdirection carries risks and is unlikely to pay dividends in the long term. Bioethical sources are amenable to the review methods of the social sciences, and it is on these methods that specific methods of bioethics literature review should be built.

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