Debates about the genuine disease status of controversial diseases rely on intuitions about a range of factors. Adopting tools from experimental philosophy, this paper explores some of the factors that influence judgments about whether low sexual desire should be considered a disease and whether it should be medically treated. Drawing in part on some assumptions underpinning a divide in the literature between viewing low sexual desire as a genuine disease and seeing it as improperly medicalized, we investigate whether health and (...) disease judgments are affected by factors such as an individual’s gender, the cause of the low desire, whether the desire is high or low, and both personal and societal valuations of the condition. Our main findings indicate that (a) the cause of a condition influences whether it is judged a disorder, (b) how the individual values the condition influences whether the condition is seen as a proper target of medical intervention, and (c) perceived dysfunction influences judgments regarding health, disorder classification, medicalization, and medical intervention. Our findings help further illuminate the intricate interplay of factors that influence judgments about health and disease in controversial conditions. (shrink)

Despite its public visibility and impact on policy, the activity of expert communication rarely receives more than a passing mention in codes of scientific integrity. This paper makes the case for an ethics of expert communication, introducing a framework where expert communication is represented as an intrinsically ethical activity of a deliberative agent. Ethical expert communication cannot be ensured by complying with various requirements, such as restricting communications to one's area of expertise or disclosing conflicts of interest. Expert communication involves (...) morally laden trade‐offs that must be weighed by a deliberative agent. A basic normative framework is introduced, and concrete provisions are proposed for codes of scientific integrity. (shrink)

We simulate trial data to test speculative claims about research methods, such as the impact of publication bias.

Medicine is increasingly subject to various forms of criticism. This paper focuses on dominant forms of criticism and offers a better account of their normative character. It is argued that together, these forms of criticism are comprehensive, raising questions about both medical science and medical practice. Furthermore, it is shown that these forms of criticism mainly rely on standards of evaluation that are assumed to be internal to medicine and converge on a broader question about the aim of medicine. Further (...) work making medicine’s internal norms explicit and determining the aim of medicine would not only help to clarify to what extent the criticism is justified, but also assist an informed deliberation about the future of medicine. To illustrate some of the general difficulties associated with such a task, the paper concludes by critically engaging Edmund Pellegrino’s account of the aim of medicine as well as the Hastings Center’s consensus report. (shrink)

The explanatory/pragmatic-trial distinction enjoys a burgeoning philosophical and medical literature and a significant contingent of support among philosophers and healthcare stakeholders as an important way to assess the design and results of randomized controlled trials. A major motivation has been the need to provide relevant, generalizable data to drive healthcare decisions. While talk of pragmatic and explanatory trials could be seen as convenient shorthand, the distinction can also be seen as harboring deeper issues related to inferential strategies used to evaluate (...) causal claims regarding medical treatments. A comprehensive, critical analysis of the distinction and underlying epistemological framework upon which the distinction is based, particularly with respect to treatment effectiveness, has yet to be forthcoming. I provide this, analyzing the distinction’s relationship to generalizability and cognate distinctions between ideal conditions and real-world practice, internal and external validity, and efficacy and effectiveness. I also analyze recent philosophical work that relies on the explanatory/pragmatic-trial distinction and that advocates for more pragmatic trials. I conclude that as an organizing principle for trial-design decisions and trial evaluation, the explanatory/pragmatic-trial distinction is conceptually problematic and not as useful as its proponents seem to think. Since some pragmatic-trial features can be inimical to establishing treatment effectiveness, pragmatic-trial features should not be conflated with pragmatic trials’ avowed goals. If the distinction is to be useful, it and some associated concepts, including generalizability, should be reformulated, lest they continue to underlie a medical epistemology that could contribute to methodologically flawed and potentially unethical advice for the design and interpretation of trials. (shrink)

Social inequality may obstruct the generation of knowledge, as the rich and powerful may bring about social acceptance of skewed views that suit their interests. Epistemic equality in the context of justification is a means of preventing such obstruction. Drawing on social epistemology and theories of equality and distributive justice, we provide an account of epistemic equality. We regard participation in, and influence over a knowledge-generating discourse in an epistemic community as a limited good that needs to be justly distributed (...) among putative members of the community. We argue that rather than trying to operationally formulate an exact criterion for distributing this good, epistemic equality may be realized by insisting on active participation of members of three groups in addition to credited experts: relevant disempowered groups, relevant uncredited experts, and relevant stakeholders. Meeting these conditions fulfills the political, moral, and epistemic aims of epistemic equality. (shrink)

There are two competing views regarding the role of mechanistic knowledge in inferences about the effectiveness of interventions. One view holds that inferences about the effectiveness of interventions should be based only on data from population-level studies (often statistical evidence from randomised trials). The other view holds that such inferences must be based in part on mechanistic evidence. The competing views are local principles of inference, the plausibility of which can be assessed by a more general normative principle of inference. (...) Bayesianism tells us to base inferences on both the ‘likelihood’ and the ‘prior’. The likelihood represents statistical evidence. One influence on the prior probability of a hypothesis like ‘d causes x’ is mechanistic knowledge of how d causes x. Thus, reasoning about such inferences by appealing to both statistical and mechanistic evidence is vindicated by our best general theory of inference. The primary contribution of this paper is to assess the merits and weaknesses of the arguments on both sides of the debate, using the Bayesian framework. This analysis lends support to those who argue that we should base our causal inferences about interventions in part on mechanistic evidence. (shrink)

This dissertation explores the influence of time constraints on different research practices. The first two parts present case studies, which serve as a basis for discussing the epistemological and ethical implications of temporal limitations in scientific research. Part I is a case study on gravitational wave research, conducted by the LIGO Scientific Collaboration. This exemplifies fundamental research – without immediate societal applications, open-ended in terms of timeline and in terms of research goals. It is based, in part, on qualitative interviews (...) conducted with gravitational wave physicists. I show that considerations about time and speed play a role in every stage of research: goal setting, method design, and the evaluation and communication of results. Part II provides a case study on translational medicine, an approach explicitly dedicated to accelerating research in order to develop and implement new therapies. This epitomizes applied research with high social stakes, motivated by non-epistemic goals. Here, epistemic trade-offs between speed and reliability intersect with ethical trade-offs between different types of harms. In Part III, the insights from both of these case studies are used as the basis for a more general discussion concerning the pragmatic aspects of epistemic practices, especially in relation to current debates centered on the role of values in science. A particular focus is on the value of speed and the ability to generate reliable results, either via choice of methods, or via decisions about which goals to set, as well as decisions about when to stop further testing. The primary thesis of the dissertation is that pragmatic considerations stemming from limitations of resources are a necessary feature of the pursuit of epistemic aims, and that the epistemic is thus inherently pragmatic. (shrink)

In the last decade, many problematic cases of scientific conduct have been diagnosed; some of which involve outright fraud others are more subtle. These and similar problems can be interpreted as caused by lack of scientific objectivity. The current philosophical theories of objectivity do not provide scientists with conceptualizations that can be effectively put into practice in remedying these issues. We propose a novel way of thinking about objectivity for individual scientists; a negative and dynamic approach.We provide a philosophical conceptualization (...) of objectivity that is informed by empirical research. In particular, it is our intention to take the first steps in providing an empirically and methodologically informed inventory of factors that impair the scientific practice. The inventory will be compiled into a negative conceptualization, which could in principle be used by individual scientists to assess objectivity of scientific practice. We propose a preliminary outline of a usable and testable instrument for indicating the objectivity of scientific practice. (shrink)

Phenomenology informs a number of contemporary attempts to give more weight to the lived experience of patients and overcome the limitations of a one-sidedly biomedical understanding of illness. Susan Bredlau has recently presented a reading of Plato’s dialogue Charmides, which portrays Socrates as a pioneer of the phenomenological approach to illness. I use a critical discussion of Bredlau’s interpretation of the Charmides to show that the phenomenology of illness also has its shortcomings and needs to be complemented by still other (...) approaches. While Bredlau does make a number of highly apt and relevant suggestions as to how a narrow biomedical approach to illness may be corrected, some of which are related to phenomenology, the attribution to Plato’s Socrates of a phenomenological approach is mistaken. Characteristically, Socrates shows little interest in the personal experience of a patient. He is more concerned with the patient’s lifestyle and conduct and so suggests an alternative or complementary perspective, stressing the importance of education and prevention to health care. (shrink)

While practitioners think highly of randomized studies, some philosophers argue that there is no epistemic reason to randomize. Here I show that their arguments do not entail their conclusion. Moreover, I provide novel reasons for randomizing in the context of interventional studies. The overall discussion provides a unified framework for assessing baseline balance, one that holds for interventional and observational studies alike. The upshot: practitioners’ strong preference for randomized studies can be defended in some cases, while still offering a nuanced (...) approach to evidence-appraisal, one where not all non-randomized studies are treated equally. (shrink)

Jonathan Y. Tsou examines and defends positions on central issues in philosophy of psychiatry. The positions defended assume a naturalistic and realist perspective and are framed against skeptical perspectives on biological psychiatry. Issues addressed include the reality of mental disorders; mechanistic and disease explanations of abnormal behavior; definitions of mental disorder; natural and artificial kinds in psychiatry; biological essentialism and the projectability of psychiatric categories; looping effects and the stability of mental disorders; psychiatric classification; and the validity of the DSM's (...) diagnostic categories. The main argument defended by Tsou is that genuine mental disorders are biological kinds with harmful effects. This argument opposes the dogma that mental disorders are necessarily diseases that result from biological dysfunction. Tsou contends that the broader ideal of biological kinds offers a more promising and empirically ascertainable naturalistic standard for assessing the reality of mental disorders and the validity of psychiatric categories. (shrink)

The public discussion on artificial intelligence for public health often revolves around future applications like drug discovery or personalized medicine. But already deployed artificial intelligence for content recommendation, especially on social networks, arguably plays a far greater role. After all, such algorithms are used on a daily basis by billions of users worldwide. In this paper, we argue that, left unchecked, this enormous influence of recommendation algorithms poses serious risks for public health, e.g., in terms of misinformation and mental health. (...) But more importantly, we argue that this enormous influence also yields a fabulous opportunity to provide quality information and to encourage healthier habits at scale. We also discuss the philosophical, technical and socio-economical challenges to seize this immense opportunity, and sketch the outlines of potential solutions. In particular, we argue that it would be extremely helpful if public and private institutions could publicly take a stand, as this may then generate the necessary social, economical and political pressure to massively invest in the research, development and deployment of the potential solutions. (shrink)

The EBM+ programme is an attempt to improve the way in which present-day evidence-based medicine (EBM) assesses causal claims: according to EBM+, mechanistic studies should be scrutinised alongside association studies. This paper addresses two worries about EBM+: (i) that it is not feasible in practice, and (ii) that it is too malleable, i.e., its results depend on subjective choices that need to be made in order to implement the procedure. Several responses to these two worries are considered and evaluated. The (...) paper also discusses the question of whether we should have confidence in medical interventions, in the light of Stegenga's arguments for medical nihilism. (shrink)

As a result of the world-wide COVID-19 epidemic, an internal tension in the goals of medicine has come to the forefront of public debate. Medical professionals are continuously faced with a tug of...

Codes of ethics currently offer no guidance to scientists acting in capacity of expert. Yet communicating their expertise is one of the most important activities of scientists. Here I argue that expert communication has a specifically ethical dimension, and that experts must face a fundamental trade-off between "actionability" and "transparency" when communicating. Some recommendations for expert communication are suggested.

What is a valid measuring instrument? Recent philosophy has attended to logic of justification of measures, such as construct validation, but not to the question of what it means for an instrument to be a valid measure of a construct. A prominent approach grounds validity in the existence of a causal link between the attribute and its detectable manifestations. Some of its proponents claim that, therefore, validity does not depend on pragmatics and research context. In this paper, I cast doubt (...) on the possibility of a context-independent causal account of validity (what I call unconditional validity). I assess several versions, arguing that all of them fail to judge the validity of measuring instruments correctly. Because different research purposes require different properties from measuring instruments, no account of validity succeeds without referring to the specific research purpose that creates the need for measurement in the first place. (shrink)

This article develops a constructive criticism of methodological conventionalism. Methodological conventionalism asserts that standards of inductive risk ought to be justified in virtue of their ability to facilitate coordination in a research community. On that view, industry bias occurs when conventional methodological standards are violated to foster industry preferences. The underlying account of scientific conventionality, however, is problematically incomplete. Conventions may be justified in virtue of their coordinative functions, but often qualify for posterior empirical criticism as research advances. Accordingly, industry (...) bias does not only threaten existing conventions but may impede their empirically warranted improvement if they align with industry preferences. My empiricist account of standards of inductive risk avoids such a problem by asserting that conventional justification can be pragmatically warranted but has, in principle, only a provisional status. Methodological conventions, therefore, should not only be defended from preference-based infringements on their coordinative function but ought to be subjected to empirical criticism. (shrink)

Moral, social, political, and other “nonepistemic” values can lead to bias in science, from prioritizing certain topics over others to the rationalization of questionable research practices. Such values might seem particularly common or powerful in the social sciences, given their subject matter. However, I argue first that the well-documented phenomenon of motivated reasoning provides a useful framework for understanding when values guide scientific inquiry (in pernicious or productive ways). Second, this analysis reveals a parity thesis: values influence the social and (...) natural sciences about equally, particularly because both are so prominently affected by desires for social credit and status, including recognition and career advancement. Ultimately, bias in natural and social science is both natural and social— that is, a part of human nature and considerably motivated by a concern for social status (and its maintenance). Whether the pervasive influence of values is inimical to the sciences is a separate question. (shrink)

In recent years, a plethora of high-profile scientific publications has been reporting about machine learning algorithms outperforming clinicians in medical diagnosis or treatment recommendations. This has spiked interest in deploying relevant algorithms with the aim of enhancing decision-making in healthcare. In this paper, we argue that instead of straightforwardly enhancing the decision-making capabilities of clinicians and healthcare institutions, deploying machines learning algorithms entails trade-offs at the epistemic and the normative level. Whereas involving machine learning might improve the accuracy of medical (...) diagnosis, it comes at the expense of opacity when trying to assess the reliability of given diagnosis. Drawing on literature in social epistemology and moral responsibility, we argue that the uncertainty in question potentially undermines the epistemic authority of clinicians. Furthermore, we elucidate potential pitfalls of involving machine learning in healthcare with respect to paternalism, moral responsibility and fairness. At last, we discuss how the deployment of machine learning algorithms might shift the evidentiary norms of medical diagnosis. In this regard, we hope to lay the grounds for further ethical reflection of the opportunities and pitfalls of machine learning for enhancing decision-making in healthcare. (shrink)

Advanced medical imaging, such as CT, fMRI and PET, has undergone enormous progress in recent years, both in accuracy and utilization. Such techniques often bring with them an illusion of immediacy, the idea that the body and its diseases can be directly inspected. In this paper we target this illusion and address the issue of the reliability of advanced imaging tests as knowledge procedures, taking positron emission tomography in oncology as paradigmatic case study. After individuating a suitable notion of reliability, (...) we argue that PET is a highly theory-laden and non-immediate knowledge procedure, in spite of the photographic-like quality of the images it delivers; the diagnostic conclusions based on the interpretation of PET images are population-dependent; PET images require interpretation, which is inherently observer-dependent and therefore variable. We conclude with a three-step methodological proposal for enhancing the reliability of advanced medical imaging. (shrink)

In their insightful article, Brent Kious and Margaret Battin (2019) correctly identify an inconsistency between an involuntary psychiatric commitment for suicide prevention and physician aid in dying (PAD). They declare that it may be possible to resolve the problem by articulating “objective standards for evaluating the severity of others’ suffering,” but ultimately they admit that this task is beyond the scope of their article since the solution depends on “a deep and difficult” question about comparing the worseness of two possible (...) scenarios: letting someone die (who could have been helped) with not letting someone die (whose suffering could only be alleviated by death). In our commentary, we argue that creating such standards is more difficult than the authors assume because of the many types of deep uncertainties we have to deal with: (1) diagnostic, (2) motivational, and (3) existential. (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)

The purpose of this chapter is to describe what we see as several important new directions for philosophy of medicine. This recent work (i) takes existing discussions in important and promising new directions, (ii) identifies areas that have not received sufficient and deserved attention to date, and/or (iii) brings together philosophy of medicine with other areas of philosophy (including bioethics, philosophy of psychiatry, and social epistemology). To this end, the next part focuses on what we call the “epistemological turn” in (...) recent work in the philosophy of medicine; the third part addresses new developments in medical research that raise interesting questions for philosophy of medicine; the fourth part is a discussion of philosophical issues within the practice of diagnosis; the fifth part focuses on the recent developments in psychiatric classification and scientific and ethical issues therein, and the final part focuses on the objectivity of medical research. (shrink)

How reliable are causal inferences in complex empirical scenarios? For example, a physician prescribes a drug to a patient, and then the patient undergoes various changes to their symptoms. They then increase their confidence that it is the drug that causes such changes. Are such inferences reliable guides to the causal relation in question, particularly when the physician can gain a large volume of such clinical experience by treating many patients? The evidence-based medicine movement says no, while some physicians and (...) philosophers support such appeals to first-person experience. We develop a formal model and simulate causal inference based on clinical experience. We conclude that in very particular clinical scenarios such inference can be reliable, while in many other routine clinical scenarios such inferences are not reliable. (shrink)

Heterogeneous treatment effects represent a major issue for medicine as they undermine reliable inference and clinical decision-making. To overcome the issue, the current vision of precision and personalized medicine acknowledges the need to control individual variability in response to treatment. In this paper, we argue that gene-treatment-environment interactions (G × T × E) undermine inferences about individual treatment effects from the results of both genomics-based methodologies—such as genome-wide association studies (GWAS) and genome-wide interaction studies (GWIS)—and randomized controlled trials (RCTs). Then, (...) we argue that N-of-1 trials can be a solution to overcome difficulties in handling individual variability in treatment response. Although this type of trial has been suggested as a promising strategy to assess individual treatment effects, it nonetheless has limitations that limit its use in everyday clinical practice. We analyze the existing variability within the designs of N-of-1 trials in terms of a continuum where each design prioritizes epistemic and pragmatic considerations. We then support wider use of the designs located at the pragmatic end of the explanatory-pragmatic continuum. (shrink)

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments’ efficacy and a ground for drug approval. Our purpose is twofold. First, we (...) show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments’ efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results. (shrink)

This thesis analyses the use of 'Evidence-Based' methodologies of evidence assessment and intervention and policy design from medicine, and their use in sport and exercise science. It argues that problems exist with the application of Evidence-Based methodologies in sports science, meaning that the quality of evidence used to inform decision-making is lower than is often assumed. This thesis also offers realistic solutions to these problems, broadly arguing for the importance of taking evidence from mechanistic studies seriously, in addition to evidence (...) from RCTs. (shrink)

Background The edge metaphor is ubiquitous in describing the present situation in the world, and nowhere is this as clearly visible as in medicine. “The edge of medicine” has become the title of books, scholarly articles, media headlines, and lecture series and seems to be imbued with hype, hope, and aversion. In order better to understand what is at stake at “the edge of medicine” this article addresses three questions: What does “the edge of medicine” mean in contemporary debates on (...) modern medicine? What are the challenges “on the edge of medicine” (in these various meanings of “on the edge”)? How can philosophy and ethics contribute with addressing these challenges? Methods Literature searches in PubMed and Google Scholar are used to identify uses of the phrase “the edge of medicine” while conventional content analysis is used to analyze meanings of and challenges with “the edge of medicine.” These results are then investigated with respect to how philosophy and ethics can address the identified challenges. Results The literature reveals that “the edge of medicine” has many meanings, such as: Border; Margin (of life); Frontier; Forefront; Fringes; Plunge (abyss); Brink (verge); Conflict; and Balancing. In general, the various meanings address four basic challenges: setting limits, keeping control, make meaning, and handling conflicts or aporias. The analysis of each of the meanings of “the edge of medicine” identifies a wide range of important and urgent tasks for the humanities in general, and for philosophy and ethics in particular: 1) clarifying concepts; 2) clarifying assumptions and premises of arguments, methods, advice, and decisions; 3) elaborate new concepts and new theories; 4) conceptualize and handle uncertainty, moral regret, and residue; 5) reveal “the emperor’s new clothes;” 6) identify trends and reflect on their implications; 7) demarcation; and 8) reflecting on goodness in medicine. Conclusion The phrase “the edge of medicine” expresses a wide range of challenges for modern health care. Together with other disciplines philosophy and ethics can and should make crucial contributions at “the edge of medicine,” which is where the future of human beings and societies is created and formed. (shrink)

Machine Learning (ML) is on the rise in medicine, promising improved diagnostic, therapeutic and prognostic clinical tools. While these technological innovations are bound to transform health care, they also bring new ethical concerns to the forefront. One particularly elusive challenge regards discriminatory algorithmic judgements based on biases inherent in the training data. A common line of reasoning distinguishes between justified differential treatments that mirror true disparities between socially salient groups, and unjustified biases which do not, leading to misdiagnosis and erroneous (...) treatment. In the curation of training data this strategy runs into severe problems though, since distinguishing between the two can be next to impossible. We thus plead for a pragmatist dealing with algorithmic bias in healthcare environments. By recurring to a recent reformulation of William James’s pragmatist understanding of truth, we recommend that, instead of aiming at a supposedly objective truth, outcome-based therapeutic usefulness should serve as the guiding principle for assessing ML applications in medicine. (shrink)

Cancer—and scientific research on cancer—raises a variety of compelling philosophical questions. This entry will focus on four topics, which philosophers of science have begun to explore and debate. First, scientific classifications of cancer have as yet failed to yield a unified taxonomy. There is a diversity of classificatory schemes for cancer, and while some are hierarchical, others appear to be “cross-cutting,” or non-nested. This literature thus raises a variety of questions about the nature of the disease and disease classification. Second, (...) philosophers of science have historically taken the aim of science to be arriving at true theories. However, scientists studying cancer come from a variety of disciplines, with different scientific as well as practical aims. Perhaps it is not surprising, then, that historians and philosophers of science do not seem to agree on how best to characterize the aim and structure of cancer research; it is far from clear whether the appropriate characterization of the aim is arriving at true theories, or even whether the proper units of analysis are “theories”, or instead, “models”, “explanatory frameworks”, “research programs”, “paradigms”, or perhaps, “experimental traditions”. With the rise of “big data” science—such as the Cancer Genome Atlas Project (or TCGA)—and “systems” approaches to the study of disease, both philosophers and historians of science are rethinking how best to describe and explain these distinctive kinds of scientific inquiry. -/- Third, cancer is in part a byproduct of our developmental and life history, as well as our evolutionary history. Cancer progression can be compared to a reversion of development, or, to the evolution of multicellularity. Thus, cancer raises intriguing questions about how we conceive of “functions”, “development”, and the role of our evolutionary history and particularly, selective trade-offs, in vulnerability to disease. -/- Last but not least, cancer research provides a case study for consideration of the roles of values at the science-policy interface. Epidemiological and toxicological research on cancer’s causes informs toxics law and regulatory policy, which raises a variety of questions about the nature of evidence and inductive risk in such contexts. (shrink)

This dissertation in Theory of Practical Knowledge contends that depression is a disorder of the self. Using the existential-phenomenology of Maurice Merleau-Ponty, I argue that if we want to disclose the basic structure of depressed experience, then we must likewise disclose how selfexperience is inseparable from depressed experience. However, even though depression is a contemporary psychiatric category of illness, it is nevertheless a historically and heterogenous concept. To make sense of depression in the context of contemporary psychiatric practice, I show (...) that depression has historically been characterized by two broad models of causation; that is, a phenomenon that is causally explained by either a biological dysfunction or a psychological conflict. But this stark characterization is not limited just to history; by conducting qualitative interviews with psychiatric professionals, I illustrate how this causal dichotomy remains prevalent in contemporary psychiatric practice. On one hand, the clinicians report dissatisfaction with the depression diagnostic criteria (i.e. it is impersonal or vague), while on the other hand, the clinicians also recognize that a depression diagnosis is useful insofar as a diagnosis facilitates access to various resources associated with psychiatric care. Consequently, clinicians have developed a coping strategy that is witnessed in their empathetic desire to distance patients from their depression diagnosis, which led to statements such as, “you are not the problem, the problem is depression.” One consequence of this approach is that depression is artificially cleaved from the person who experiences depression, which subsequently means that depression is viewed to be something independent of oneself. Because I argue that depression and the self are mutually implicated, it is crucial to disseminate some of the most influential contemporary models of selfhood. I show that the brainbound, situated, psychological, and narrative model of self, all have respective strengths and weaknesses. But I also go beyond these models and characterize selfhood as a developmental phenomenon that is expressed as an embodied-style. This style reflects the way in which we establish perceptual contact with the otherness, without which there could be no self-experience. (shrink)

Reasoning in medicine requires the critical use of a clinical methodology whose validity must be evaluated as well as its limits. In the last decade, an increasing amount of evidence has shown severe limitations and flaws in the conduct of prognostic studies. The main reason behind this fact is that prognostic judgments are at high risk of error. In this paper we investigate the pragmatic and illocutionary aspects of different forms of linguistic acts and judgments involved in clinical practice. More (...) specifically, we analyze the role of uncertainty with regard to ‘particular’ clinical judgments and its relation with ‘general’ evidence. Focusing on how prognostic judgments are formulated and justified, our main purpose is to highlight the explication, the structure and the limits of prognosis from a linguistic and epistemological perspective. (shrink)

The trustworthiness of nutrition science has been questioned recently. According to the critics, the food industry has corrupted scientists in the field. I argue that the worries that commercialization threatens the epistemic trustworthiness of nutrition science are indeed well-founded. However, it is problematic that the discussion has revolved around how funding can threaten the integrity of researchers and the methodological quality of the studies. By extending Wilholt’s :233–253, 2013) account of epistemic trustworthiness, I argue that when assessing the epistemic trustworthiness (...) of research that forms the basis for different health policy measures, it is necessary to evaluate research at the macro-level and whether agenda setting advances the goals that are assigned to the field. The prevalence of commercial funding becomes problematic if it leads to a situation where the body of available evidence that is used for making health policy decisions does not reflect the shared sense of what epistemic and non-epistemic goals of the inquiry are important. (shrink)

Medical interventions that cure or prevent medical conditions are central to medicine; and thus, understanding them is central to our understanding of medicine. My purpose in this paper is to explore the conceptual foundations of medicine by providing a singular analysis of the concept of a ‘preventive or curative medical intervention’. Borrowing a general account of prevention from Phil Dowe, I provide an analysis of prevention, cure, risk reduction, and a preventive or curative intervention, before turning to preventive and curative (...) medical interventions. The resulting counterfactual-mechanistic account holds that preventive and curative medical interventions reduce the probability of a medical condition in an actual population compared to their counterfactual omission, commonly by disrupting an etiological or constitutive mechanism for the condition. (shrink)

Calls for evidence-based approaches to COVID-19 have sparked up discussions on the use of evidence for policy. In this note, we expand these discussions: while the debate has mostly focused on the types of evidence to be used for policy, we argue that the assessment of judgments involved in data practices and evidence production should play a central role in evaluating policy.

Biased research occurs frequently in the sciences. In this paper, I will focus on one particular kind of biased research: research that is subject to sponsorship bias. I will address the following epistemological question: what precisely is epistemically wrong with biased research of this kind? I will defend the evidential account of epistemic wrongness: that is, research affected by sponsorship bias is epistemically wrong if and only if the researchers in question make false claims about the evidential support of some (...) hypothesis H by data E. I will argue that the evidential account captures the epistemic wrongness of three paradigmatic types of sponsorship bias. (shrink)

As it has historically been the case with many pandemics, the Covid-19 experience will induce many philosophers to reconsider the value of medical practice. This should be a good opportunity to critically scrutinize the way medical research and medical interventions are carried out. For much of its history, medicine has been very inefficient. But, even in its contemporary forms, a review of common protocols in medical research and medical interventions reveal many shortcomings, especially related to methodological flaws, and more importantly, (...) conflicts of interests due to profit incentives. In the face of these problems, we propose a program of “gentle medicine”. This term, originally formulated by philosopher Jacob Stegenga, describes a form of medicine in which physicians intervene less than they currently do. As part of this general program, we advance a series of reform recommendations that could be enacted both by medical staff in their everyday practice, but also by public health officials and policymakers. (shrink)

What is medicine? One obvious answer in the context of the contemporary clinical tradition is that medicine is the process of curing sick people. However, this “curative thesis” is not satisfactory, even when “cure” is defined generously and even when exceptions such as cosmetic surgery are set aside. Historian of medicine Roy Porter argues that the position of medicine in society has had, and still has, little to do with its ability to make people better. Moreover, the efficacy of medicine (...) for improving population health has been famously doubted by historians and epidemiologists. The curative thesis demands that we have mostly been stupid, duped, or staggeringly hopeful, given that medicine has not until recently offered more than a handful of effective cures. I suggest, in this article, that the core medical competence is neither to cure, nor to prevent, disease, but to understand and to predict it. I argue that this approach does a better job than the curative thesis at explaining why not all medicine is concerned with curative efforts and that it enjoys historical support from the ancient entanglement of prophecy and medicine and from the fact that medicine thrived for centuries with almost no effective cures and continues to thrive today in various forms that are mostly without curative efficacy. I suggest that this approach grounds a fairer approach to alternative, traditional, and other medical practices, as well as some fresh lessons for the development of mainstream medicine. (shrink)