Many authors have argued in favour of an ontology of properties as powers, and it has been widely argued that this ontology allows us to address certain philosophical problems in novel and illuminating ways, for example, causation, representation, intentionality, free will and liberty. I argue that the ontology of powers, even if successful as an account of fundamental natural properties, does not provide the insight claimed as regards the aforementioned non-fundamental phenomena. I illustrate this argument by criticizing the powers theory (...) of causation presented by Mumford and Anjum and showing that related criticisms can be directed at other abuses of powers. (shrink)

Evidence-Based Medicine is a relatively new movement that seeks to put clinical medicine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence—the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs.

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.

I examine the positive and negative features of homeopathy from an ethical perspective. I consider: (a) several potentially beneficial features of homeopathy, including non-invasiveness, cost-effectiveness, holism, placebo benefits and agent autonomy; and (b) several potentially negative features of homeopathy, including failure to seek effective healthcare, wastage of resources, promulgation of false beliefs and a weakening of commitment to scientific medicine. A utilitarian analysis of the utilities and disutilities leads to the conclusion that homeopathy is ethically unacceptable and ought to be (...) actively rejected by healthcare professionals. (shrink)

The philosophy of evidence-based medicine -- What is EBM? -- What is good evidence for a clinical decision? -- Ruling out plausible rival hypotheses and confounding factors : a method -- Resolving the paradox of effectiveness : when do observational studies offer the same degree of evidential support as randomized trials? -- Questioning double blinding as a universal methodological virtue of clinical trials : resolving the Philip's paradox -- Placebo controls : problematic and misleading baseline measures of effectiveness -- Questioning (...) the methodological superiority of "placebo" over "active" controlled trials -- Examining the paradox that traditional roles for mechanistic reasoning and expert -- Judgment have been up-ended by EBM -- A qualified defence of the EBM stance on mechanistic reasoning -- Knowledge that versus knowledge how : situating the EBM position on expert clinical judgment -- Moving EBM forward. (shrink)

Proponents of Evidence-based medicine (EBM) do not provide a clear role for basic science in therapeutic decision making. Of what they do say about basic science, most of it is negative. Basic science resides on the lower tiers of EBM's hierarchy of evidence. Therapeutic decisions, according to proponents of EBM, should be informed by evidence from randomised studies (and systematic reviews of randomised studies) rather than basic science. A framework of models explicates the links between the mechanisms of basic science, (...) experimental inquiry, and observed data. Relying on the framework of models I show that basic science often plays a role not only in specifying experiments, but also analysing and interpreting the data that is provided. Further, and contradicting what is implied in EBM's hierarchy of evidence, appeals to basic science are often required to apply clinical research to therapeutic questions. © 2010 Springer Science+Business Media B.V. (shrink)

It is surely obvious that medicine, like any other rational activity, must be based on evidence. The interest is in the details: how exactly are the general principles of the logic of evidence to be applied in medicine? Focussing on the development, and current claims of the ‘Evidence-Based Medicine’ movement, this article raises a number of difficulties with the rationales that have been supplied in particular for the ‘evidence hierarchy’ and for the very special role within that hierarchy of randomized (...) controlled trials (and meta-analyses of the results of randomized controlled trials). The point is not at all to question the application of a scientific approach to evidence in medicine, but, on the contrary, to indicate a number of areas where philosophers of science can contribute to a proper implementation of exactly that scientific-evidential approach. (shrink)

The evidence from randomized controlled trials (RCTs) is widely regarded as supplying the ‘gold standard’ in medicine—we may sometimes have to settle for other forms of evidence, but this is always epistemically second-best. But how well justified is the epistemic claim about the superiority of RCTs? This paper adds to my earlier (predominantly negative) analyses of the claims produced in favour of the idea that randomization plays a uniquely privileged epistemic role, by closely inspecting three related arguments from leading contributors (...) to the burgeoning field of probabilistic causality—Papineau, Cartwright and Pearl. It concludes that none of these further arguments supplies any practical reason for thinking of randomization as having unique epistemic power. IntroductionWhy the issue is of great practical importance—the ECMO casePapineau on the ‘virtues of randomization’Cartwright on causality and the ‘ideal’ randomized experimentPearl on randomization, nets and causesConclusion. (shrink)

Randomized controlled trials (RCTs) are widely taken as the gold standard for establishing causal conclusions. Ideally conducted they ensure that the treatment ‘causes’ the outcome—in the experiment. But where else? This is the venerable question of external validity. I point out that the question comes in two importantly different forms: Is the specific causal conclusion warranted by the experiment true in a target situation? What will be the result of implementing the treatment there? This paper explains how the probabilistic theory (...) of causality implies that RCTs can establish causal conclusions and thereby provides an account of what exactly that causal conclusion is. Clarifying the exact form of the conclusion shows just what is necessary for it to hold in a new setting and also how much more is needed to see what the actual outcome would be there were the treatment implemented. (shrink)

The claims of randomized controlled trials to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This article describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. (...) It argues that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The article reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

What kinds of evidence reliably support predictions of effectiveness for health and social care interventions? There is increasing reliance, not only for health care policy and practice but also for more general social and economic policy deliberation, on evidence that comes from studies whose basic logic is that of JS Mill's method of difference. These include randomized controlled trials, case–control studies, cohort studies, and some uses of causal Bayes nets and counterfactual-licensing models like ones commonly developed in econometrics. The topic (...) of this paper is the 'external validity' of causal conclusions from these kinds of studies. We shall argue two claims. Claim, negative: external validity is the wrong idea; claim, positive: 'capacities' are almost always the right idea, if there is a right idea to be had. If we are right about these claims, it makes big problems for policy decisions. Many advice guides for grading policy predictions give top grades to a proposed policy if it has two good Mill's-method-of difference studies that support it. But if capacities are to serve as the conduit for support from a method-of-difference study to an effectiveness prediction, much more evidence, and much different in kind, is required. We will illustrate the complexities involved with the case of multisystemic therapy, an internationally adopted intervention to try to diminish antisocial behaviour in young people. (shrink)

The claims of RCTs to be the gold standard rest on the fact that the ideal RCT is a deductive method: if the assumptions of the test are met, a positive result implies the appropriate causal conclusion. This is a feature that RCTs share with a variety of other methods, which thus have equal claim to being a gold standard. This paper describes some of these other deductive methods and also some useful non-deductive methods, including the hypothetico-deductive method. It argues (...) that with all deductive methods, the benefit that the conclusions follow deductively in the ideal case comes with a great cost: narrowness of scope. This is an instance of the familiar trade-off between internal and external validity. RCTs have high internal validity but the formal methodology puts severe constraints on the assumptions a target population must meet to justify exporting a conclusion from the test population to the target. The paper reviews one such set of assumptions to show the kind of knowledge required. The overall conclusion is that to draw causal inferences about a target population, which method is best depends case-by-case on what background knowledge we have or can come to obtain. There is no gold standard. (shrink)

Evidence-Based Medicine is a relatively new movement that seeks to put clinical med- icine on a firmer scientific footing. I take it as uncontroversial that medical practice should be based on best evidence-the interesting questions concern the details. This paper tries to move towards a coherent and unified account of best evidence in medicine, by exploring in particular the EBM position on RCTs (randomized controlled trials).

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)

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)

Peter Urbach has argued, on Bayesian grounds, that experimental randomization serves no useful purpose in testing causal hypothesis. I maintain that he fails to distinguish general issues of statistical inference from specific problems involved in identifying causes. I concede the general Bayesian thesis that random sampling is inessential to sound statistical inference. But experimental randomization is a different matter, and often plays an essential role in our route to causal conclusions.

The validity of clinical trials for certain alternative treatments has been called into question by supporters of unconventional and pseudoscientific practices, who criticize the way their beliefs are investigated scientifically or the verdicts reached by science. This chapter focuses on the following basic question: what treatments can be scientifically investigated at all? It aims to provide a better understanding of what conditions medical treatments must fulfill to be eligible for scientific investigation. In particular, the discussion is a rejoinder to the (...) claims put forward by adherents of alternative medicine that their treatments are inaccessible to scientific scrutiny. (shrink)

It is argued that randomization has no role to play in the design or analysis of an experiment. If a Bayesian approach is adopted this conclusion is easily demonstrated. Outside that approach two principles, of conditionality and similarity, lead, via the likelihood principle, to the same conclusion. In the case of design, however, it is important to avoid confounding the effect of interest with an unexpected factor and this consideration leads to a principle of haphazardness that is clearly related to, (...) but not identical with, randomization. The role of exchangeability is discussed. (shrink)