Research FocusThe promotion of domain-specific knowledge is a central goal of higher education and, in the field of medicine, it is particularly essential to promote global health. Domain-specific knowledge on its own is not exhaustive; confidence regarding the factual truth of this knowledge content is also required. An increase in both knowledge and confidence is considered a necessary prerequisite for making professional decisions in the clinical context. Especially the knowledge of human physiology is fundamental and simultaneously critical to medical decision-making. (...) However, numerous studies have shown difficulties in understanding and misconceptions in this area of knowledge. Therefore, we investigate how preclinical medical students acquire knowledge in physiology over the course of their studies and simultaneously gain confidence in the correctness of this knowledge as well as the interrelations between these variables, and how they affect the development of domain-specific knowledge.MethodIn a pre–post study, 169 medical students’ development of physiology knowledge and their confidence related to this knowledge were assessed via paper-pencil questionnaires before and after attending physiology seminars for one semester. Data from a longitudinal sample of n = 97 students were analyzed using mean comparisons, regression analyses, and latent class analyses. In addition, four types of item responses were formed based on confidence and correctness in the knowledge test.ResultsWe found a significant and large increase in the students’ physiology knowledge, with task-related confidence being the strongest predictor. Moreover, a significantly higher level of confidence at t2 was confirmed, with the level of prior confidence being a strong predictor. Furthermore, based on the students’ development of knowledge and confidence levels between measurement points, three empirically distinct groups were distinguished: knowledge gainers, confidence gainers, and overall gainers. The students whose confidence in incorrect knowledge increased constituted one particularly striking group. Therefore, the training of both knowledge and the ability to critically reflect on one’s knowledge and skills as well as an assessment of their development in education is required, especially in professions such as medicine, where knowledge-based decisions made with confidence are of vital importance. (shrink)

Researchers are studying how artificial intelligence (AI) can be used to better detect, prognosticate and subgroup diseases. The idea that AI might advance medicine’s understanding of biological categories of psychiatric disorders, as well as provide better treatments, is appealing given the historical challenges with prediction, diagnosis and treatment in psychiatry. Given the power of AI to analyse vast amounts of information, some clinicians may feel obligated to align their clinical judgements with the outputs of the AI system. However, a potential (...) epistemic privileging of AI in clinical judgements may lead to unintended consequences that could negatively affect patient treatment, well-being and rights. The implications are also relevant to precision medicine, digital twin technologies and predictive analytics generally. We propose that a commitment to epistemic humility can help promote judicious clinical decision-making at the interface of big data and AI in psychiatry. (shrink)

It is common to think of medical and ethical modes of thought as different in kind. In such terms, some clinical situations are made more complicated by an additional ethical component. Against this picture, we propose that medical and ethical modes of thought are not different in kind, but merely different aspects of what it means to be human. We further propose that clinicians are uniquely positioned to synthesise these two aspects without prior knowledge of philosophical ethics.

In most socialised health systems there are formal processes that manage resource scarcity and determine the allocation of funds to health services in accordance with their priority. In this analysis, part of a larger qualitative study examining the ethical issues entailed in doctors’ participation as technical experts in priority setting, we describe the values and ethical commitments of doctors who engage in priority setting and make an empirically derived contribution towards the identification of an ethical framework for doctors’ macroallocation work. (...) We conducted semi-structured interviews with 20 doctors, each of whom participated in macroallocation at one or more levels of the Australian health system. Our sampling, data-collection, and analysis strategies were closely modelled on grounded moral analysis, an iterative empirical bioethics methodology that employs contemporaneous interchange between the ethical and empirical to support normative claims grounded in practice. The values held in common by the doctors in our sample related to the domains of personal ethics, justice, and practices of argumentation. Applying the principles of grounded moral analysis, we identified that our participants’ ideas of the good in macroallocation and their normative insights into the practice were strongly aligned with the three levels of Paul Ricoeur’s ‘little ethics’: ‘aiming at the “good life” lived with and for others in just institutions’. Our findings suggest new ways of understanding how doctors’ values might have procedural and substantive impacts on macroallocation, and challenge the prevailing assumption that doctors in this milieu are motivated primarily by deontological considerations. Our empirical bioethics approach enabled us to identify an ethical framework for medical work in macroallocation that was grounded in the values and ethical intuitions of doctors engaged in actions of distributive justice. The concordance between Ricoeur’s ‘little ethics’ and macroallocation practitioners’ experiences, and its embrace of mutuality, suggest that it has the potential to guide practice, support ethical reflection, and harmonise deliberative practices amongst actors in macroallocation generally. (shrink)

It is nearly 20 years since Tony Hope wrote an editorial in this journal on Empirical Medical Ethics,1 arguing for both a recognition of the increasing amount of work being done in ‘empirical ethics’ and for its importance as a new direction for medical ethics research. Since then empirical ethics has flourished, with debates over the role of ‘empirical’ data in ethical reasoning producing a growing body of literature and the JME and other bioethics journals regularly publishing empirical studies. While (...) bio/medical ethics has grappled with ‘incorporating’ or using more empirical data in ethical analysis, with varying degrees of success, and some criticism, there has not been a corresponding willingness of more empirical disciplines to embrace ethical analysis. This is a particular lack for applied research areas that see their role as predominately influencing policy and practice, such as health services research. Health services research ‘is the integration of epidemiological, sociological, economic, and other analytic sciences in the study of health services.’ Whose ‘main goals … are to identify the most effective ways to organize, manage, finance, and deliver high quality care; reduce medical errors; and improve patient safety’.2 Health services research brings together a wide variety of disciplines and would seem ideally placed to include ethics. However, if you search health services research journals and conference programmes there is very little consideration of ethics as a substantive topic and often scant attention paid to the ethical issues that might be raised by an intervention or policy. Ethics and ethical issues are generally confined to discussions over priority setting, and occasionally health technology assessment, with other areas of health service research seldom engaging in ethical debate. In the Encyclopaedia of Health Services Research,3 ethics …. (shrink)

In this paper, we argue that there are reasons to believe that an implicit bias for normalcy influences what are considered medically necessary treatments in psychiatry. First, we outline two prima facie reasons to suspect that this is the case. A bias for ‘the normal’ is already documented in disability studies; it is reasonable to suspect that it affects psychiatry too, since psychiatric patients, like disabled people, are often perceived as ‘weird’ by others. Secondly, psychiatry's explicitly endorsed values of well-being (...) and function are hard to measure directly, which is why we see simpler box-ticking conceptions of recovery used in large research studies. This need not be problematic, but might lead to researchers and clinicians focusing too much on treatments that promote easy-to-measure proxies for recovery, instead of what actually matters to psychiatric patients themselves. Next, we provide examples of treatments and treatment decisions within two areas – self-injury and psychosis – which are hard to explain unless we assume that an implicit and harmful normalcy bias is at work. We conclude with some suggestions for clinicians and future research. (shrink)

In medical research, it is not unusual that risks are ruled out without any specification the exact risk that was ruled out. This makes it difficult to balance expected health benefits and risk of harm when choosing between alternative treatment options. International guidelines for reporting medical research results are sufficiently specific when it comes to establishing health benefits. However, there is a lack of standards for reporting on ruling out risks. We argue that transparency is needed, as in the case (...) of non-inferiority trials. The Consolidated Standards of Reporting Trials and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements should be revised accordingly. (shrink)

Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...) associated with experimental design, including controlled variation and randomization, this chapter will provide a summary of key ethical issues that tend to arise in experimental contexts. In addition, by exploring assumptions about the nature of causation and by analyzing features of causal relationships, systems, and inferences in social contexts, this chapter will summarize the ways in which experimental design can undermine the integrity of not only social and behavioral research but policies implemented on the basis of such research. (shrink)

My doctoral project is a study of epistemological and ethical issues in Evidence-Based Medicine, a movement in medicine which emphasizes the use of randomized controlled trials. Much of the research on EBM suggests that, for a large part of the movement's history, EBM considered expertise, mechanisms, and values to be forces contrary to its goals and has sought to remove them, both from medical research and from the clinical encounter. I argue, however, that expertise, mechanisms and values have important epistemological (...) and ethical roles to play and can be incorporated into the current EBM movement. (shrink)