Evidence hierarchies are widely used to assess evidence in systematic reviews of medical studies. I give several arguments against the use of evidence hierarchies. The problems with evidence hierarchies are numerous, and include methodological shortcomings, philosophical problems, and formal constraints. I argue that medical science should not employ evidence hierarchies, including even the latest and most-sophisticated of such hierarchies.

This article examines the business case for diversity, according to which diversity should be promoted because diverse groups outperform nondiverse groups. Philosophers who defend BCD usually...

In his seminal Inference to the Best Explanation, Peter Lipton adopted a causal view of explanation and a broadly Millian view of how causal knowledge is obtained. This made his account vulnerable to critics who charged that Inference to the Best Explanation is merely a dressed-up version of Mill’s methods, which in the critics’ view do the real inductive work. Lipton advanced two arguments to protect Inference to the Best Explanation against this line of criticism: the problem of multiple differences (...) and the problem of inferred differences. Lipton claimed that these two problems show Mill’s method of difference to be largely unworkable unless it is embedded in an explanationist framework. Here I consider both arguments as well as the best Millian defense against them. Since the existing Millian defense is only partially successful, I will develop a new and improved account. As an integral part of the argument, I show that my solutions to the problems of multiple and inferred differences offer new insight into Lipton’s main case study: Ignaz Semmelweis’s discovery of the cause of childbed fever. I conclude that the method of difference can overcome Lipton’s challenges outside an explanationist framework. (shrink)

The rapid, recent emergence of new medical knowledge models has engendered a dizzying number of new medical initiatives, programs and approaches. Fields such as evidence-based medicine and translational medicine all promise a renewed relationship between knowledge and medicine. The question for philosophy and other fields has been whether these new models actually achieve their promises to bring about better kinds of medical knowledge—a question that compels scholars to analyze each model’s epistemic claims. Yet, these analyses may miss critical components that (...) explain how these models actually work and function. Using the case of translational medicine, this paper suggests that analyses which treat these models as a primarily epistemic interventions miss the way that new approaches are increasingly shaped by specific financial and commercial agendas. Ultimately, social epistemological analyses that are attentive to market forces are required to make sense of emerging bioscientific research models, which are increasingly tethered to or a manifestation of increasingly financialized models of science research and innovation. (shrink)

This paper looks at an appeal to the authority of biomedical research that has recently been used by empirical economists to motivate and justify their methods. I argue that those who make this appeal mistake the nature of biomedical research. Randomised trials, which are said to have revolutionised biomedical research, are a central methodology, but according to only one paradigm. There is another paradigm at work in biomedical research, the inferentialist paradigm, in which randomised trials play no special role. I (...) outline the inferentialist alternative in broad strokes, apply it to a recent controversy in econometrics and draw some general conclusions concerning econometric methodology. (shrink)

Epidemiological models have played a central role in the COVID-19 pandemic, particularly when urgent decisions were required and available evidence was sparse. They have been used to predict the evolution of the disease and to inform policy-making. In this paper, we address two kinds of epidemiological models widely used in the pandemic, namely, compartmental models and agent-based models. After describing their essentials—some real examples are invoked—we discuss their main strengths and weaknesses. Then, on the basis of this analysis, we make (...) a comparison between their respective merits concerning three different goals: prediction, explanation, and intervention. We argue that there are general considerations which could favour any of those sorts of models for obtaining the aforementioned goals. We conclude, however, that preference for particular models must be grounded case-by-case since additional contextual factors, as the peculiarities of the target population and the aims and expectations of policy-makers, cannot be overlooked. (shrink)

Background: Evidence suggesting adverse drug reactions often emerges unsystematically and unpredictably in form of anecdotal reports, case series and survey data. Safety trials and observational studies also provide crucial information regarding the (un-)safety of drugs. Hence, integrating multiple types of pharmacovigilance evidence is key to minimising the risks of harm. Methods: In previous work, we began the development of a Bayesian framework for aggregating multiple types of evidence to assess the probability of a putative causal link between drugs and side (...) effects. This framework arose out of a philosophical analysis of the Bradford Hill Guidelines. In this article, we expand the Bayesian framework and add “evidential modulators,” which bear on the assessment of the reliability of incoming study results. The overall framework for evidence synthesis, “E-Synthesis”, is then applied to a case study. Results: Theoretically and computationally, E-Synthesis exploits coherence of partly or fully independent evidence converging towards the hypothesis of interest (or of conflicting evidence with respect to it), in order to update its posterior probability. With respect to other frameworks for evidence synthesis, our Bayesian model has the unique feature of grounding its inferential machinery on a consolidated theory of hypothesis confirmation (Bayesian epistemology), and in allowing any data from heterogeneous sources (cell-data, clinical trials, epidemiological studies), and methods (e.g., frequentist hypothesis testing, Bayesian adaptive trials, etc.) to be quantitatively integrated into the same inferential framework. Conclusions: E-Synthesis is highly flexible concerning the allowed input, while at the same time relying on a consistent computational system, that is philosophically and statistically grounded. Furthermore, by introducing evidential modulators, and thereby breaking up the different dimensions of evidence (strength, relevance, reliability), E-Synthesis allows them to be explicitly tracked in updating causal hypotheses. (shrink)

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance of boundary (...) conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit. (shrink)

A key question for evidence-based medicine is how best to model the way in which EBM should‘[integrate] individual clinical expertise and the best external evidence’. We argue that the formulations and models available in the literature today are modest variations on a common theme and face very similar problems when it comes to risk analysis, which is here understood as a decision procedure comprising a factual assessment of risk, the risk assessment, and the decision what to do based on this (...) assessment, the risk management. Both the early and updated models of evidence-based clinical decisions presented in the writings of Haynes, Devereaux and Guyatt assume that EBM consists of, among other things, evidence from clinical research together with information about patients’ values and clinical expertise. On this A-view, EBM describes all that goes on in a specific justifiable medical decision. There is, however, an alternative interpretation of EBM, the B-view, in which EBM describes just one component of the decision situation and in which, together with other types of evidence, EBM leads to a justifiable clincial decision but does not describe the decision itself. This B-view is inspired by a 100-years older version of EBM, a Swedish standard requiring medical decision-making, professional risk-taking and practice to be in accordance with‘science and proven experience’. In the paper, we outline how the Swedish concept leads to an improved understanding of the way in which scientific evidence and clinical experience can and cannot be integrated in light of EBM. How scientific evidence and clinical experience is integrated influences both the way we do risk assessment and risk management. In addition, the paper sketches the as yet unexplored historical background to VBE and EBM. (shrink)

The problem of collecting, analyzing and evaluating evidence on adverse drug reactions (ADRs) is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of the health-care practice. Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special (...) attention to the privileged role assigned to randomized controlled trials in Evidence Based Medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended effects, in that the unknowns at stake are heterogonous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their main focus is methodological, and regards the fact that bias and confounding do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints which we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood to be different in the case of evidence for risk vs. benefit assessment. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. (shrink)

The problem of collecting, analyzing and evaluating evidence on adverse drug reactions (ADRs) is an example of the more general class of epistemological problems related to scientific inference and prediction, as well as a central problem of the health-care practice. Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special (...) attention to the privileged role assigned to randomized controlled trials in Evidence Based Medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended effects, in that the unknowns at stake are heterogonous in the two contexts. This point has been emphasized by epidemiologists in the last decade. Their main focus is methodological, and regards the fact that bias and confounding do not affect studies on intended and unintended effects in the same way. However, deeper concerns ground the intuition for such a distinction; these are related to the constraints which we impose on evidence and their epistemological justification. My thesis is that such constraints ought to be understood to be different in the case of evidence for risk vs. benefit assessment. I present the recent debate on the causal association between acetaminophen and asthma in order to illustrate the point at issue. (shrink)

Philosophical discussions have critically analysed the methodological pitfalls and epistemological implications of evidence assessment in medicine, however they have mainly focused on evidence of treatment efficacy. Most of this work is devoted to statistical methods of causal inference with a special attention to the privileged role assigned to randomized controlled trials (RCTs) in evidence based medicine. Regardless of whether the RCT’s privilege holds for efficacy assessment, it is nevertheless important to make a distinction between causal inference of intended and unintended (...) effects, in that the unknowns at stake are heterogonous in the two contexts. However, although “lower level” evidence is increasingly acknowledged to be a valid source of information contributory to assessing the risk profile of medications on theoretical or empirical grounds, current practices have difficulty in assigning a precise epistemic status to this kind of evidence because they are more or less implicitly parasitic on the (statistical) methods developed to test drug efficacy. My thesis is that (1) “lower level” evidence is justified on distinct grounds and at different conditions depending on the different epistemologies which one wishes to endorse, in that each impose different constraints on the methods we adopt to collect and evaluate evidence; (2) such constraints ought to be understood to be different in the case of evidence for risk versus benefit assessment for a series of reasons which I will illustrate on the basis of the recent debate on the causal association between acetaminophen (a.k.a. paracetamol) and asthma. (shrink)

Courts play a key role in deciding on public health controversies, but the legitimacy of judicial intervention remains highly controversial. In this article I suggest that we need to carefully distinguish between different reasons for persistent disagreement in the domain of public health. Adjudicating between public health controversies rooted in factual disagreements allows us to investigate more closely the epistemic capacities of the judicial process. While the critics typically point out the lack of appropriate expertise of judges—in particular with respect (...) to health and public health—we should not move too fast in inferring from this a generalized competence problem. This article offers four reasons for vindicating the importance of judicial intervention in factual disagreements: the relative independence of judges from the political establishment, the judicial commitment to evidence, the specific nature of judicial reasoning and an additional voice for the people in the policy-making process. (shrink)

Modern health care relies extensively on the use of technologies for assessing and treating patients, so it is important to be certain that health care technologies perform their professed functions in an effective and safe manner. Philosophers of technology have developed methods to assign and evaluate the functions of technological products, the major elements of which are described in the ICE theory. This paper questions whether the standard of evidence advocated by the ICE theory is adequate for ascribing and assessing (...) technologies employed in health care. The paper proposes that the general problem with the standard of evidence embodied in the ICE theory is too permissive for assessing medical technologies, in that it does not take into account the relative benefit and harm of medical technologies in ensuring safe functional performance in patients. The paper illustrates how evidence-based medicine has demonstrated the value of clinical research methods, including observational studies, randomized and non-randomized clinical trials, and formal techniques, such as meta-analysis, to measure therapeutic effectiveness. I argue, therefore, that evidence from clinical research studies should take precedence over the testimonial evidence and other types of non-clinical evidence, in providing justification for health technologies. (shrink)

Proponents of evidence-based medicine have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on evidence (...) hierarchies of methodology fails to lend credence to the common practice of corroboration in medicine. I argue that the strength of evidence lies in the evidence itself, and not the methodology used to obtain that evidence. Ultimately, when it comes to evaluating the effectiveness of medical interventions, it is the evidence obtained from the methodology rather than the methodology that should establish the strength of the evidence. (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)

Educationalists introduce students to literature search strategies that, with rare exceptions, focus chiefly on the location of primary research reports and systematic reviews of those reports. These sources are, however, unlikely to adequately address the normative and/or metaphysical questions that nurses frequently and legitimately interest themselves in. To meet these interests, non‐research texts exploring normative and/or metaphysical topics might and perhaps should, in some situations, be deemed suitable search targets. This seems plausible and, moreover, students are encouraged to ‘read widely’. (...) Yet accepting this proposition creates significant difficulties. Specifically, if non‐research scholarly sources and artistic or literary (humanities) products dealing with normative/metaphysical issues were included in what are, at present, scientifically orientated searches, it is difficult to draw boundaries around what – if anything – is to be excluded. Engaging with this issue highlights problems with qualitative scholarship's designation as ‘evidence’. Thus, absurdly, if qualitative scholarship's findings are labelled evidence because they generate practice‐relevant understanding/insight, then any literary or artistic artefact (e.g. a throwaway lifestyle magazine) that generates kindred understandings/insights is presumably also evidence? This conclusion is rejected and it is instead proposed that while artistic, literary, and qualitative inquiries can provide practitioners with powerful and stimulating non‐evidential understanding, these sources are not evidence as commonly conceived. (shrink)

We raise a problem of applicability of RCTs to validate nuclear diagnostic imaging tests. In spite of the wide application of PET and other similar techniques that use radiopharmaceuticals for diagnostic purposes, RCT-based evidence on their validity is sparse. We claim that this is due to a general conceptual problem that we call Prevalence of Treatment, which arises in connection with designing RCTs for testing any diagnostic procedure in the present context of medical research, and is particularly apparent in this (...) case. We also identify three practical reasons why RCTs do not qualify as the best option for PET validation, which have to do with specific characteristics of nuclear diagnostic imaging, and of radiopharmaceuticals. The paper is meant to contribute both to the philosophical discussion on the EBM hierarchy of evidence, and on the specific debate on radiopharmaceuticals in nuclear medicine. (shrink)

What clinicians, biomedical scientists, and other health care professionals know as individuals or as groups and how they come to know and use knowledge are central concerns of medical epistemology. Activities associated with knowledge production and use are called epistemic practices. Such practices are considered in biomedical and clinical literatures, social sciences of medicine, philosophy of science and philosophy of medicine, and also in other nonmedical literatures. A host of different kinds of knowledge claims have been identified, each with different (...) uses and logics of justification. A general framework is needed to situate these diverse contributions in medical epistemology, so we can see how they fit together. But developing such a framework turns out to be quite tricky. In this survey, three possible frameworks are considered along with the difficulties associated with each of them. The essay concludes with a fourth framework, which considers any epistemology as part of a practice that is oriented toward overcoming errors that emerge in antecedently given practices where knowledge is developed and used. As medicine indirectly advances health by directly mitigating disease, so epistemology indirectly advances knowledge by directly mitigating error. (shrink)

We claim that if a complete philosophy of evidence-based practice is intended, then attention to the nature of causation in health science is necessary. We identify how health science currently conceptualises causation by the way it prioritises some research methods over others. We then show how the current understanding of what causation is serves to constrain scientific progress. An alternative account of causation is offered. This is one of dispositionalism. We claim that by understanding causation from a dispositionalist stance, many (...) of the processes within an evidence-based practice framework are better accounted for. Further, some of the problems associated with the health research, e.g. external validity of causal findings, dissolve. (shrink)

Evidence-based medicine has always required integration of patient values with ‘best’ clinical evidence. It is widely recognized that scientific practices and discoveries, including those of EBM, are value-laden. But to date, the science of EBM has focused primarily on methods for reducing bias in the evidence, while the role of values in the different aspects of the EBM process has been almost completely ignored.

In this paper, I discuss the objectivity of science in the context of commercialized research. Objectivity has traditionally been associated with the behavior of individual scientists and their willingness and ability to base their reasoning on data and logic. By introducing some examples of problematic practices in current research, I show that this view is insufficient. A view that I call the Social View on objectivity succeeds better in accommodating the way in which commercialization affects research.

Journal peer review is an essential part of academic practices.1 But how well does it serve its purpose and which factors have an influence on how close it comes to achieving its aims? Peer review has been widely discussed in empirical literature: it has been studied both qualitatively and quantitatively (e.g., by Cole, who in his 1992 book uses data on how grant applications submitted to National Science Foundation were...

Traditionally, mechanistic reasoning has been assigned a negligible role in standard EBM literature, although some recent authors have argued for an upgrade. Even so, the mechanistic reasoning that has received attention has almost exclusively been positive—both in an epistemic sense of claiming that there is a mechanistic chain and in a health-related sense of there being claimed benefits for the patient. Negative mechanistic reasoning has been neglected, both in the epistemic and in the health-related sense. I distinguish three main types (...) of negative mechanistic reasoning and subsume them under a new definition of mechanistic reasoning in the context of assessing medical interventions. This definition is wider than a previous suggestion in the literature. Each negative type corresponds to a range of evidential strengths, and it is argued that there are differences with respect to typical evidential strengths. The variety of negative mechanistic reasoning should be acknowledged in EBM, and it presents a serious challenge to proponents of so-called medical hierarchies of evidence. (shrink)

Evidence hierarchies are lists of investigative strategies ordered with regard to the claimed strength of evidence. They have been used for a couple of decades within EBM, particularly for the assessment of evidence for treatment recommendations, but they remain controversial. An under-investigated question, from critics and adherents of evidence hierarchies alike, is what the order in the hierarchy means. Four interpretations of the order are distinguished and discussed. The two most credible ones are, roughly expressed, "typically stronger" or "ideally stronger". (...) The well-known GRADE framework seems to assume some "typically stronger" reading. Unfortunately, even if the interpretation of an evidence hierarchy were established, hierarchies appear to be rather unhelpful for the task of evidence aggregation. Nevertheless, a specification of the intended order relation may be helpful in sorting out disagreements in debates on evidence hierarchies. Therefore, proponents and adversaries of evidence hierarchies are equally obliged to specify the order interpretations they are assuming in their arguments. (shrink)

Debates about the ethics and effects of placebos and whether ‘placebos’ in clinical trials of complex treatments such as acupuncture are adequate rage. Yet there is currently no widely accepted definition of the ‘placebo’. A definition of the placebo is likely to inform these controversies. Grünbaum’s characterization of placebos and placebo effects has been touted by some authors as the best attempt thus far, but has not won widespread acceptance largely because Grünbaum failed to specify what he means by a (...) therapeutic theory and because he does not stipulate a special role for expectation effects. Grünbaum claims that placebos are treatments whose ‘characteristic features’ do not have therapeutic effects on the target disorder. I show that with four modifications, Grünbaum’s definition provides a defensible account of placebos for the purpose of constructing placebo controls within clinical trials. The modifications I introduce are: adding a special role for expectations, insisting that placebo controls control for all and only the effects of the incidental treatment features, relativizing the definition of placebos to patients, and introducing harmful interventions and nocebos to the definitional scheme. I also provide guidance for classifying treatment features as characteristic or incidental. (shrink)

The American Journal of Bioethics, Volume 12, Issue 3, Page 33-34, March 2012.

Proponents of evidence-based medicine and some philosophers of science seem to agree that knowledge of mechanisms can help solve the problem of applying results of controlled studies to target populations (‘the problem of extrapolation’). We describe the problem of extrapolation, characterize mechanisms, and outline how mechanistic knowledge might be used to solve the problem. Our main thesis is that there are four often overlooked problems with using mechanistic knowledge to solve the problem of extrapolation. First, our understanding of mechanisms is (...) often (and arguably, likely to remain) incomplete. Secondly, knowledge of mechanisms is not always applicable outside the tightly controlled laboratory conditions in which it is gained. Thirdly, mechanisms can behave paradoxically. Fourthly, as Daniel Steel points out, using mechanistic knowledge faces the problem of the ‘extrapolator’s circle’. At the same time, when the problems with mechanistic knowledge have been addressed, such knowledge can and should be used to mitigate (nothing can entirely solve) the problem of extrapolation. (shrink)

There are some philosophical questions that can be answered without attention to the social context in which evidence is produced and distributed.ing away from social context is an excellent way to ignore messy details and lay bare the underlying structure of the limits of inference. Idealization is entirely appropriate when one is essentially asking: In the best of all possible worlds, what am I entitled to infer? Yet, philosophers’ concerns often go beyond this domain. As an example I examine the (...) debate on mechanistic evidence and then reevaluate a canonical case study in this debate. I show that for the assessment of actual evidence, produced in a world that is far from ideal, omission of the social aspects of medical epistemology leads philosophers to draw the wrong lessons from cases they take as paradigmatic cases for their views. I close by arguing that social epistemology provides an avenue to incorporate these complications and provides the necessary framework to understand medical evidence. (shrink)

Philosophy of medicine has traditionally examined two issues: the scientific ontology for medicine and the epistemic significance of the types of evidence used in medical research. In answering each question, philosophers have typically brought to bear tools from traditional analytic philosophy. In contrast, this volume explores medical knowledge from the perspective offered by social epistemology.While many of the same issues are addressed, the approach to these issues generates both fresh questions and new insights into old debates. In addition, the broader (...) purview offered by social epistemology opens up opportunities to address new topics such as the role of consensus conferences, epistemic injustice, the value of medical knowledge, continuing medical education, and industry funding. This article situates and summarizes the contributions to this special issue. (shrink)

Arguments that medical decision making should rely on a variety of evidence often begin from the claim that meta-analysis has been shown to be problematic. In this paper, I first examine Stegenga’s argument that meta-analysis requires multiple decisions and thus fails to provide an objective ground for medical decision making. Next, I examine three arguments from social epistemologists that contend that meta-analyses are systematically biased in ways not appreciated by standard epistemology. In most cases I show that critiques of meta-analysis (...) fail to account for the full range of meta-analytic procedures. In the remainder of cases, I argue that the critiques identify problems that do not uniquely cut against meta-analysis. I close by suggesting one reason why it may be pragmatically rational to violate the principle of total evidence and by outlining the criteria for a successful argument against meta-analysis. A set of criteria I contend remain unmet. (shrink)

It is sometimes thought that randomized study group allocation is uniquely proficient at producing comparison groups that are evenly balanced for all confounding causes. Philosophers have argued that in real randomized controlled trials this balance assumption typically fails. But is the balance assumption an important ideal? I run a thought experiment, the CONFOUND study, to answer this question. I then suggest a new account of causal inference in ideal and real comparative group studies that helps clarify the roles of confounding (...) variables and randomization. 1Confounders and Causes2The Balance Assumption3The CONFOUND Study 3.1CONFOUND 13.2CONFOUND 24Disjunction C and the Ideal Study 4.1The ultimate ‘other cause’: C4.2The ideal comparative group study4.3Required conditions for causal inference5Confounders as Causes, Confounders as Correlates6Summary. (shrink)

According to the Russo-Williamson Thesis, causal claims in the health sciences need to be supported by both difference-making and mechanistic evidence. In this article, we attempt to determine whether Evidence-based Medicine can be improved through the consideration of mechanistic evidence. We discuss the practical composition and function of each RWT evidence type and propose that exposure-outcome evidence provides associations that can be explained through a hypothesis of causation, while mechanistic evidence provides finer-grained associations and knowledge of entities that ultimately explains (...) a causal hypothesis. We suggest that mechanistic evidence holds untapped potential to add value to the assessment of evidence quality in EBM and propose initial recommendations for the integration of mechanistic and exposure-outcome evidence to improve EBM by robustly leveraging available evidence in support of good medical decisions. (shrink)

This thesis is a philosophical examination of the explanatory roles of diagnoses in psychiatry. In medicine, diagnoses normally serve as causal explanations of patients’ symptoms. Given that psychiatry is a discipline whose practice is shaped by medical traditions, it is often implied that its diagnoses also serve such explanatory functions. This is evident in clinical texts that portray psychiatric diagnoses as referring to diseases that cause symptoms. However, there are problems which cast doubt on whether such portrayals are justified. I (...) address these problems and examine whether psychiatric diagnoses provide explanations of symptoms. The first problem is conceptual. In diagnostic manuals, psychiatric diagnoses are defined by their symptoms. This suggests that invoking them as explanations of the symptoms amounts to circularity. I argue that this can be resolved with an appropriate conceptual framework that captures the complex semantic values of diagnostic terms and their different uses in clinical discourse. I put forward such a framework based on two-dimensional semantics. The second problem is ontological. Empirical research suggests that diagnostic categories in psychiatry do not correspond to invariant causal types, but are associated with variable combinations of diverse causes that interact across biological, psychological, and social levels. Given this heterogeneity, I argue that psychiatric diagnoses fall short of paradigmatic cases of causal explanation, but that some can still provide other sorts of useful causal explanatory information. The original contribution of this thesis is the illumination of the conceptual relations between diagnoses and symptoms. This philosophical work is important, because it can be brought to valuable application in modifying psychiatric practice. (shrink)

Evidence based medicine (EBM) is under critical debate, and person centered healthcare (PCH) has been proposed as an improvement. But is PCH offered as a supplement or as a replacement of EBM? Prima facie PCH only concerns the practice of medicine, while the contended features of EBM also include methods and medical model. I here argue that there are good philosophical reasons to see PCH as a radical alternative to the existing medical paradigm of EBM, since the two seem committed (...) to conflicting ontologies. This paper aims to make explicit some of the most fundamental assumptions that motivate EBM and PCH, respectively, in order to show that the choice between them ultimately comes down to ontological preference. While EBM has a solid foundation in positivism, or what I here call Humeanism, PCH is more consistent with causal dispositionalism. I conclude that if there is a paradigmatic revolution on the way in medicine, it is first of all one of ontology. (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)