The concept of intersectionality in bioethics: a systematic review.

BACKGROUND: Intersectionality is a concept that originated in Black feminist movements in the US-American context of the 1970s and 1980s, particularly in the work of feminist scholar and lawyer Kimberlé W. Crenshaw. Intersectional approaches aim to highlight the interconnectedness of gender and sexuality with other social categories, such as race, class, age, and ability to look at how individuals are discriminated against and privileged in institutions and societal power structures. Intersectionality is a "traveling concept", which also made its way into bioethical research. METHODS: We conducted a systematic review to answer the question of where and how the concept of intersectionality is applied in bioethical research. The PubMed and Web of Science databases were systematically searched and 192 articles addressing bioethical topics and intersectionality were finally included. RESULTS: The qualitative analysis resulted in a category system with five main categories: (1) application purpose and function, (2) social dimensions, (3) levels, (4) health-care disciplines and academic fields, and (5) challenges, limitations, and critique. The variety of academic fields and health-care disciplines working with the concept ranges from psychology, through gynaecology to palliative care and deaf studies. Important functions that the concept of intersectionality fulfils in bioethical research are making inequities visible, creating better health data collections and embracing self-reflection. Intersectionality is also a critical praxis and fits neatly into the overarching goal of bioethics to work toward social justice in health care. Intersectionality aims at making research results relevant for respective communities and patients, and informs the development of policies. CONCLUSIONS: This systematic review is, to the best of our knowledge, the first one to provide a full overview of the reference to intersectionality in bioethical scholarship. It creates a basis for future research that applies intersectionality as a theoretical and methodical tool for analysing bioethical questions.

What Are Humans Doing in the Loop? Co-Reasoning and Practical Judgment When Using Machine Learning-Driven Decision Aids.

Within the ethical debate on Machine Learning-driven decision support systems (ML_CDSS), notions such as "human in the loop" or "meaningful human control" are often cited as being necessary for ethical legitimacy. In addition, ethical principles usually serve as the major point of reference in ethical guidance documents, stating that conflicts between principles need to be weighed and balanced against each other. Starting from a neo-Kantian viewpoint inspired by Onora O'Neill, this article makes a concrete suggestion of how to interpret the role of the "human in the loop" and to overcome the perspective of rivaling ethical principles in the evaluation of AI in health care. We argue that patients should be perceived as "fellow workers" and epistemic partners in the interpretation of ML_CDSS outputs. We further highlight that a meaningful process of integrating (rather than weighing and balancing) ethical principles is most appropriate in the evaluation of medical AI.

Intraoperative application of mixed and augmented reality for digital surgery: a systematic review of ethical issues.

Introduction: Head-mounted displays (HMDs) that superimpose holograms onto patients are of particular surgical interest as they are believed to dramatically change surgical procedures by including safety warning and allowing real-time offsite consultations. Although there are promising benefits of mixed and augmented reality (MR/AR) technologies in surgery, they also raise new ethical concerns. The aim of this systematic review is to determine the full spectrum of ethical issues that is raised for surgeons in the intraoperative application of MR/AR technology. Methods: Five bibliographic databases were searched for publications on the use of MR/AR, HMDs and other devices, their intraoperative application in surgery, and ethical issues. We applied qualitative content analysis to the n = 50 articles included. Firstly, we coded the material with deductive categories derived from ethical frameworks for surgical innovations, complications and research. Secondly, clinical aspects with ethical relevance were inductively coded as ethical issues within the main categories. Thirdly, we pooled the ethical issues into themes and sub-themes. We report our findings according to the reporting guideline RESERVE. Results: We found n = 143 ethical issues across ten main themes, namely patient-physician relationship, informed consent, professionalism, research and innovation, legal and regulatory issues, functioning equipment and optimal operating conditions, allocation of resources, minimizing harm, good communication skills and the ability to exercise sound judgement. The five most prevalent ethical issues are "Need for continuous research and innovation", "Ensuring improvement of the learning curve", "MR/AR enables new maneuvers for surgeons", "Ensuring improvement of comfort, ergonomics, and usability of devices," and "Not withholding MR/AR if it performs better". Conclusions: Recognizing the evidence-based limitations of the intraoperative MR/AR application is of paramount importance to avoid ethical issues, but clinical trials in surgery pose particular ethical risks for patients. Regarding the digital surgeon, long-term impact on human workforce, potentially harmful "negative training," i.e., acquiring inappropriate behaviors, and the fear of surveillance need further attention. MR/AR technologies offer not only challenges but significant advantages, promoting a more equitable distribution of surgical expertise and optimizing healthcare. Aligned with the core principle of social justice, these technologies enable surgeons to collaborate globally, improving training conditions and addressing enduring global healthcare inequalities.

Mass drug administration for neglected tropical disease control and elimination: a systematic review of ethical reasons.

BACKGROUND: Neglected tropical diseases (NTDs) are a diverse group of debilitating diseases and conditions afflicting more than one billion people in impoverished communities. Control of these diseases is crucial to achieve Sustainable Development Goal 3 and the pledge to 'leave no one behind'. Relying on large-scale delivery of wide-spectrum drugs to individuals in at-risk communities irrespective of their health status, mass drug administration is a core strategy for tackling half of the NTDs targeted by the latest WHO roadmap (2021-2030). However, ethical challenges surround its implementation and long-term impact. This systematic review aims to give a comprehensive picture of the variety of ethical reasons for and against mass drug administration for NTD control and elimination, facilitating further debate in ethics and policy. METHODS: PubMed and Web of Science Core Collection were searched for all relevant publications. Of the 486 retrieved records, 60 met the inclusion criteria for qualitative analysis. Ethical reasons discussing the topic at hand were extracted from full texts and synthesised through the Kuckartz method of qualitative content analysis. RESULTS: Data extraction revealed 61 ethical reasons, of which 20 (32.7%) had positive, 13 (21.3%) had ambivalent and 28 (45.9%) had negative implications regarding mass drug administration for NTDs. The health benefits and cost-effectiveness of the measure were extensively highlighted. However, equity, autonomy and sustainability emerged as the domains with the most pressing ethical concerns. Many issues related to implementation are yet to be adequately addressed in policy documents. CONCLUSIONS: This is the first systematic review of ethical reasons pertaining to mass drug administration for NTD control and elimination. Due to the diversity of included studies, no general recommendations can be made. Instead, context-specific strategies seem necessary. Alternative approaches tackling socioecological determinants of ill health are needed for long-term sustainability. Future research could benefit from contributions of non-Western philosophies and perspectives by local researchers.

Training the Next Generation of Infectious Disease Researchers: A Biorisk Management Module Embedded in a European Master Program.

Introduction: The current global situation with increasing zoonotic transmissions of pathogens, rapidly changing ecosystems due to the climate change and with it the distribution of potential vectors, demands new ways of teaching and educating students in the field of infectious disease research. Methods: The international master program "Infectious Diseases and One Health-IDOH" started its second application period in 2019. Biosafety is an integral part of IDOH, exemplified by a biosafety level 3 hands-on training at the Animal Health Research Center IRTA-Centre de Recerca en Sanitat Animal (CReSA), Barcelona. At Hanover Medical School, biosafety is expanded to a comprehensive biorisk management approach with focus on risk assessment, bioethics, and training in a mobile containment laboratory. This article illustrates in depth the intention and the individual teaching units of the biorisk management module within the third semester of the IDOH master. Risk assessment is taught based on the new WHO Laboratory Biosafety Manual 4th edition, which represents a paradigm shift toward a risk-based approach instead of a prescriptive definition of biosafety levels. This methodology will enable the international IDOH students to cope with different national legislations and to provide guidance on biosafety in their home countries. In the final unit, the students operate a mobile containment laboratory and simulated a viral hemorrhagic fever outbreak in Africa. Conclusion: In sum, this module combines theoretical risk assessment and its practical implementation in the mobile laboratory as a future direction for training infectiologists. In addition, our report may serve as a blue print for others to amend their education with the herewith mentioned pillars of biosafety teaching.

A Personalized Patient Preference Predictor for Substituted Judgments in Healthcare: Technically Feasible and Ethically Desirable.

When making substituted judgments for incapacitated patients, surrogates often struggle to guess what the patient would want if they had capacity. Surrogates may also agonize over having the (sole) responsibility of making such a determination. To address such concerns, a Patient Preference Predictor (PPP) has been proposed that would use an algorithm to infer the treatment preferences of individual patients from population-level data about the known preferences of people with similar demographic characteristics. However, critics have suggested that even if such a PPP were more accurate, on average, than human surrogates in identifying patient preferences, the proposed algorithm would nevertheless fail to respect the patient's (former) autonomy since it draws on the 'wrong' kind of data: namely, data that are not specific to the individual patient and which therefore may not reflect their actual values, or their reasons for having the preferences they do. Taking such criticisms on board, we here propose a new approach: the Personalized Patient Preference Predictor (P4). The P4 is based on recent advances in machine learning, which allow technologies including large language models to be more cheaply and efficiently 'fine-tuned' on person-specific data. The P4, unlike the PPP, would be able to infer an individual patient's preferences from material (e.g., prior treatment decisions) that is in fact specific to them. Thus, we argue, in addition to being potentially more accurate at the individual level than the previously proposed PPP, the predictions of a P4 would also more directly reflect each patient's own reasons and values. In this article, we review recent discoveries in artificial intelligence research that suggest a P4 is technically feasible, and argue that, if it is developed and appropriately deployed, it should assuage some of the main autonomy-based concerns of critics of the original PPP. We then consider various objections to our proposal and offer some tentative replies.

Expectation of clinical decision support systems: a survey study among nephrologist end-users.

BACKGROUND: Chronic kidney disease (CKD), a major public health problem with differing disease etiologies, leads to complications, comorbidities, polypharmacy, and mortality. Monitoring disease progression and personalized treatment efforts are crucial for long-term patient outcomes. Physicians need to integrate different data levels, e.g., clinical parameters, biomarkers, and drug information, with medical knowledge. Clinical decision support systems (CDSS) can tackle these issues and improve patient management. Knowledge about the awareness and implementation of CDSS in Germany within the field of nephrology is scarce. PURPOSE: Nephrologists' attitude towards any CDSS and potential CDSS features of interest, like adverse event prediction algorithms, is important for a successful implementation. This survey investigates nephrologists' experiences with and expectations towards a useful CDSS for daily medical routine in the outpatient setting. METHODS: The 38-item questionnaire survey was conducted either by telephone or as a do-it-yourself online interview amongst nephrologists across all of Germany. Answers were collected and analysed using the Electronic Data Capture System REDCap, as well as Stata SE 15.1, and Excel. The survey consisted of four modules: experiences with CDSS (M1), expectations towards a helpful CDSS (M2), evaluation of adverse event prediction algorithms (M3), and ethical aspects of CDSS (M4). Descriptive statistical analyses of all questions were conducted. RESULTS: The study population comprised 54 physicians, with a response rate of about 80-100% per question. Most participants were aged between 51-60 years (45.1%), 64% were male, and most participants had been working in nephrology out-patient clinics for a median of 10.5 years. Overall, CDSS use was poor (81.2%), often due to lack of knowledge about existing CDSS. Most participants (79%) believed CDSS to be helpful in the management of CKD patients with a high willingness to try out a CDSS. Of all adverse event prediction algorithms, prediction of CKD progression (97.8%) and in-silico simulations of disease progression when changing, e. g., lifestyle or medication (97.7%) were rated most important. The spectrum of answers on ethical aspects of CDSS was diverse. CONCLUSION: This survey provides insights into experience with and expectations of out-patient nephrologists on CDSS. Despite the current lack of knowledge on CDSS, the willingness to integrate CDSS into daily patient care, and the need for adverse event prediction algorithms was high.

Physicians' duty to climate protection as an expression of their professional identity: a defence from Korsgaard's neo-Kantian moral framework.

The medical profession is observing a rising number of calls to action considering the threat that climate change poses to global human health. Theory-led bioethical analyses of the scope and weight of physicians' normative duty towards climate protection and its conflict with individual patient care are currently scarce. This article offers an analysis of the normative issues at stake by using Korsgaard's neo-Kantian moral account of practical identities. We begin by showing the case of physicians' duty to climate protection, before we succinctly introduce Korsgaard's account. We subsequently show how the duty to climate protection can follow from physicians' identity of being a healthcare professional. We structure conflicts between individual patient care and climate protection, and show how a transformation in physicians' professional ethos is possible and what mechanisms could be used for doing so. An important limit of our analysis is that we mainly address the level of individual physicians and their practical identities, leaving out important measures to respond to climate change at the mesolevels and macrolevels of healthcare institutions and systems, respectively.

Ethical Requirements for Human Challenge Studies: A Systematic Review of Reasons.

Human challenge studies (HCS) are controlled clinical trials in which participants are deliberately infected with a pathogen. Such trials are being developed for an increasing number of diseases. Partly as a result of the coronavirus disease 2019 (COVID-19) pandemic, there has been a recent ethical debate about the reasons for and against HCS in general, or rather, about the requirements that individual HCS must fulfill to be ethically acceptable. A systematic review was conducted to categorize and summarize such requirements and the reasons given for them. Ethics literature was searched in PubMed, Google Scholar, BELIT, and PhilPapers; eligibility criteria were articles published in a scientific/scholarly journal (original research, reviews, editorials, opinion pieces, and conference/meeting reports). Of 1,322 records identified, 161 publications were included, with 183 requirements (with associated reasons) in 10 thematic categories extracted via qualitative content analysis. In synthesizing and interpreting the requirements and their reasons, three issues emerge as particularly sensitive in the case of HCS: the meaning of the right to withdraw from research procedures, communication of researchers with the public and various stakeholders, and the conditions of informed consent. However, four other issues, not specific to HCS, stand out as the most controversial: the acceptable level of risk to participants, payment of participants, protection of vulnerable groups, and standards for international collaborations. Controversies in these areas indicate that further debate is warranted, possibly leading to more specific instructions in ethics guidance documents.

Should Artificial Intelligence be used to support clinical ethical decision-making? A systematic review of reasons.

BACKGROUND: Healthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use. METHODS: PubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis. RESULTS: Artificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process. CONCLUSIONS: The prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human-machine interaction, have been neglected in the debate on AI for clinical ethics so far. TRIAL REGISTRATION: This review is registered at Open Science Framework ( https://osf.io/wvcs9 ).

Whose health and which health? Two theoretical flaws in the One Health paradigm.

The One Health approach is a prominent paradigm for research and healthcare practice and increasingly applied in various fields. Theoretical and normative implications of the approach, however, remain underexposed so far, leading to conceptual incoherencies and uncertainties in the application of the concept. This article sheds light on two particularly influential theoretical flaws inherent to the One Health approach. The first difficulty relates to the question of whose health is considered in the One Health paradigm: humans and animals are obviously situated on a different level than the environment, so that the individual, population, and ecosystem dimensions need to be considered. The second theoretical flaw is related to the question of which concept of health can be meaningfully referred to when speaking of One Health. This problem is addressed by analyzing four key theoretical conceptions of health from the philosophy of medicine (well-being, natural functioning, capacity of achieving vital goals, and homeostasis and resilience) regarding their suitability for the aims of One Health initiatives. It appears that none of the concepts analyzed fully meets the demands of an equitable consideration of human, animal, and environmental health. Potential solutions lie in accepting that one concept of health is more appropriate for some entities than for others and/or forgoing the idea of a uniform conception of health. As a result of the analysis, the authors conclude that theoretical and normative assumptions underlying concrete One Health initiatives should be made more explicit.

Responsibility and decision-making authority in using clinical decision support systems: an empirical-ethical exploration of German prospective professionals' preferences and concerns.

Machine learning-driven clinical decision support systems (ML-CDSSs) seem impressively promising for future routine and emergency care. However, reflection on their clinical implementation reveals a wide array of ethical challenges. The preferences, concerns and expectations of professional stakeholders remain largely unexplored. Empirical research, however, may help to clarify the conceptual debate and its aspects in terms of their relevance for clinical practice. This study explores, from an ethical point of view, future healthcare professionals' attitudes to potential changes of responsibility and decision-making authority when using ML-CDSS. Twenty-seven semistructured interviews were conducted with German medical students and nursing trainees. The data were analysed based on qualitative content analysis according to Kuckartz. Interviewees' reflections are presented under three themes the interviewees describe as closely related: (self-)attribution of responsibility, decision-making authority and need of (professional) experience. The results illustrate the conceptual interconnectedness of professional responsibility and its structural and epistemic preconditions to be able to fulfil clinicians' responsibility in a meaningful manner. The study also sheds light on the four relata of responsibility understood as a relational concept. The article closes with concrete suggestions for the ethically sound clinical implementation of ML-CDSS.

A systematic review documenting reasons whether physicians should provide treatment to their family and friends.

BACKGROUND: Physicians are likely to be asked to provide medical care to relatives or friends. Evidence suggests that most physicians treat loved ones during their active years. However, in the academic literature, critical approaches to the matter are dominating. Ethical guidelines often discourage physicians from treating family members and friends outside of exceptional circumstances. OBJECTIVE: This systematic review aims to identify reasons for and against treating family and friends as portrayed in the literature published. METHODS: A search string designed for the database "PubMed," snowball sampling, and hand searching was used to identify possibly eligible publications. Seventy-six publications were screened for all reasons presented in favour of and against physicians treating loved ones. Qualitative content analysis was used for data extraction. Combining a deductive and inductive approach, a coding system was developed. RESULTS: Many publications analysed represent articles portraying personal experiences; fewer show original research. Reasons against and in favour of treating family and friends were identified. Several publications specify conditions under which the treatment of loved ones may be legitimate. The reasons identified can be assigned to a micro or macro level of human interaction. CONCLUSIONS: This systematic review shows that the discourse of physicians treating loved ones is held predominantly in the context of personal experiences. The majority of authors seem to have a rather pragmatic interest in the topic, and systematic or analytic approaches are rare. While most authors mention various codes of ethics, several publications criticize these or consider them insufficient.

Ethical guidelines, such as the Code of Medical Ethics of the American Medical Association, ask physicians not to treat their family members and friends. However, studies show that most physicians are confronted with loved ones asking for medical interventions during their careers. The divide between the ethical guidelines and the physicians' actual practice demonstrates the ethical dilemma at hand. In this systematic review, literature addressing the topic of physicians treating family and friends (PTFF) is analysed. The majority of publications voice concerns about PTFF. A common reason against PTFF is the risk of losing objectivity. Other publications endorse PTFF, mentioning, for example, the possibility of saving costs. Specific situations in which PTFF is justified are presented as well. The analysis of publications on the topic indicates a rather clinical approach, less of a philosophical one. Several authors criticize too little assistance in this matter of the ethical guidelines. The examination of the existing literature on the topic of PTFF suggests that, as the circumstances are very context-specific, a universal answer applying to each case of PTFF will hardly be found.

The birth of the "digital turn" in bioethics?

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.