The paper addresses the question of how different types of evidence ought to inform public health policy. By analysing case studies on obesity, the paper draws lessons about the different roles that different types of evidence play in setting up public health policies. More specifically, it is argued that evidence of difference-making supports considerations about ‘what works for whom in what circumstances’, and that evidence of mechanisms provides information about the ‘causal pathways’ to intervene upon.

In this paper, I want to substantiate three related claims regarding causal discovery from non-experimental data. Firstly, in scientific practice, the problem of ignorance is ubiquitous, persistent, and far-reaching. Intuitively, the problem of ignorance bears upon the following situation. A set of random variables V is studied but only partly tested for (conditional) independencies; i.e. for some variables A and B it is not known whether they are (conditionally) independent. Secondly, Judea Pearl’s most meritorious and influential algorithm for causal discovery (...) (the IC algorithm) cannot be applied in cases of ignorance. It presupposes that a full list of (conditional) independence relations is on hand and it would lead to unsatisfactory results when applied to partial lists. Finally, the problem of ignorance is successfully treated by means of ALIC, the adaptive logic for causal discovery presented in this paper. (shrink)

An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis falls far short of that standard. Different meta-analyses (...) of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

Contemporary philosophical debates about causation are dominated by two approaches, which are often referred to as difference-making and causal process approaches to causation, respectively. I provide a characterization of the dialectic between these two approaches, on which that dialectic turns crucially on the question as to whether our common sense concept of causation involves a commitment to locality – i.e., to the claim that causal relations are always subject to spatial constraints. I then argue that we can extract from existing (...) work on perceptual judgement (specifically work that invokes the notion of a simple theory of perception) materials for an argument in favour of a positive answer to that question, and that this work can also help to bring out a distinctive kind of role that a commitment to locality plays in our reasoning about causal relationships. (shrink)

Nineteenth-century medical advances were entwined with a conceptual innovation: the idea that many cases of disease which were previously thought to have diverse causes could be explained by the action of a single kind of cause, for example a certain bacterial or parasitic infestation. The focus of modern epidemiology, however, is on chronic non-communicable diseases, which frequently do not seem to be attributable to any single causal factor. This paper is an effort to resolve the resulting tension. The paper criticises (...) the monocausal model of disease, so successful in the nineteenth century. It also argues that a multifactorial model of disease can only be satisfactory if it amounts to more than a mere rejection of the monocausal model. A third alternative, the contrastive model, is proposed and defended on the grounds that it links the notions of disease and of general explanation, while avoiding the philosophical naiveties and practical difficulties of the monocausal model. (shrink)

The paper discusses the evolving concept of causationin epidemiology and its potential interaction with logic and scientific philosophy. Causes arecontingent but the necessity which binds them totheir effects relies on contrary-to-fact conditionals,i.e. conditional statements whose antecedent is false.Chance instead of determinism plays a growing role inscience and, although rarely acknowledged yet, inepidemiology: causes are multiple and chancy; a priorevent causes a subsequent event if the probabilitydistribution of the subsequent event changesconditionally upon the probability of the prior event.There are no known (...) sufficient causes in epidemiology.We merely observe tendencies toward sufficiency ortendencies toward necessity: cohort studies evaluatethe first tendencies, and case-control studies thelatter.In applied sciences, such as medicine andepidemiology, causes are intrinsically connected withgoals and effective strategies: they are recipewhich have a potential harmful or sucessful use; theyare contrastive since they make a differencebetween circumstances in which they are present andthose in which they are absent: causes do notexplain Event E but event E rather thaneven F. Causation is intrinsically linked with thenotion of ``what is pathological''.Any definition of causation will inevitably collapseinto the use made of epidemiologic methods. Theprogressive methodological sophistication of the lastforty years is in perfect alignment with a gradualimplicit overhaul of our concept of causation. (shrink)

Today, mechanisms and mechanistic explanation are very popular in philosophy of science and are deemed a welcome alternative to laws of nature and deductive‐nomological explanation. Starting from Mitchell's pragmatic notion of laws, I cast doubt on their status as a genuine alternative. I argue that (1) all complex‐systems mechanisms ontologically must rely on stable regularities, while (2) the reverse need not hold. Analogously, (3) models of mechanisms must incorporate pragmatic laws, while (4) such laws themselves need not always refer to (...) underlying mechanisms. Finally, I show that Mitchell's account is more encompassing than the mechanistic account *Received August 2008; revised January 2010. †To contact the author, please write to: Centre for Logic and Philosophy of Science, Ghent University, Blandijnberg 2, B‐9000 Belgium; e‐mail: [email protected]. (shrink)

This paper attempts to elucidate three characteristics of causal relationships that are important in biological contexts. Stability has to do with whether a causal relationship continues to hold under changes in background conditions. Proportionality has to do with whether changes in the state of the cause “line up” in the right way with changes in the state of the effect and with whether the cause and effect are characterized in a way that contains irrelevant detail. Specificity is connected both to (...) David Lewis’ notion of “influence” and also with the extent to which a causal relation approximates to the ideal of one cause–one effect. Interrelations among these notions and their possible biological significance are also discussed. (shrink)

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences - pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory (...) of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification. (shrink)

Causation appears to present us with an interpretative difficulty. While arguably a redundant relation given fundamental physics, it is nevertheless apparently pragmatically indispensable. This chapter revisits certain arguments made previously by the author for these claims with the benefit of hindsight, starting with the role of causal models in the human sciences, and attempting to explain why it is not possible to straightforwardly ground such models in fundamental physics. This suggests that further constraints, going beyond physics, are needed to legitimate (...) such models. These supplementary constraints could be reified, but that would seem to conflict with the completeness of physics. A response is to emphasize the practical role of causal talk, and the author suggests that a fictionalist approach might be worth exploring. After clarifying fictionalism as a general approach, they carry out in some detail the project of clarifying what a fictionalist attitude to causation would involve. (shrink)

Translating risk estimates derived from epidemiologic study into evidence of causality for a particular patient is problematic. The difficulty of this process is not unique to the medical context; rather, courts are also challenged with the task of using risk estimates to infer evidence of cause in particular cases. Thus, an examination of how this is done in a legal context might provide insight into when and how it is appropriate to use risk information as evidence of cause in a (...) medical context. A careful study of the case of Goodman v. Viljoen, a medical malpractice suit litigated in the Ontario Superior Court of Justice in 2011, reveals different approaches to how risk information is used as or might be considered a substitute for evidence of causation, and the pitfalls associated with these approaches. Achieving statistical thresholds, specifically minimizing the probability of falsely rejecting the null hypothesis, and exceeding a relative risk of 2, plays a significant role in establishing causality of the particular in the legal setting. However, providing a reasonable explanation or establishing “biological plausibility” of the causal association also seems important, and (to some) may even take precedent over statistical thresholds for a given context. (shrink)

The contribution of food and diet to health is much disputed in the background culture in the US. Many commercial or ideological advocates make claims, sometimes with health as a primary goal, but often accompanied by commercial or ideological interests. These compete culturally with authoritative recommendations made by publicly funded groups. For public policy concerning diet and health to be legitimate, not only should it not be inconsistent with the scientific evidence, but also it should not be inconsistent with the (...) political environment. Healthy Eating Policy and Political Philosophy (HEPPP), by Barnhill and Bonotti (2022), addresses how policy in this complex area might be justified. In the present essay I highlight some important strengths of their work and also make some points about how it might be clarified or enlarged in scope. The great strength of HEPPP is that it emphasizes the role of a political philosophy in evaluating the legitimacy of public policy. They presume a well-off liberal democratic state, and specifically they draw on Rawls’ political liberalism, as developed in Political Liberalism (PL). One of several interlocking technical concepts developed in this book, public reason speaks to the boundaries of what should be acceptable in public deliberation about constitutional essentials and basic justice. HEPPP explores the application of an extension of public reason to the justification of policies related to “healthy eating.“ Public reason has two components, both of which pertain to a common understanding among citizens: (1) a common understanding of the principles and ideals that are the foundation of the political society, and (2) a common understanding of the standards that govern reason and evidence, including common sense. HEPPP argues that even though for diet and health the complexity of the scientific evidence goes far beyond anything like common sense for a typical citizen, the technical idea of “accessibility” of the scientific evidence justifies reliance on it within the concept of public reason. I question this accessibility argument about scientific evidence and public reason because the nature of the population-level epidemiological evidence about diet and health is that it often includes judgments that are based on arguable interpretations, framing incidence in terms of risk and prevention; thus the issue is more than one of potential accessibility of scientific evidence. Nevertheless, evaluation and consideration of the scientific evidence is of obvious practical importance in policy deliberation concerning policy related to what Rawls call “ordinary legislation.“ Even though public reason applied to healthy eating policy may not be as pertinent as it is for constitutional essentials and basic justice, and even though it is unlikely to result in a “correct outcome,“ invoking reasons based on political values and principles held in common has important value even in these deliberations about more ordinary questions. That value applies not to the specifics of the particular issue, but to the larger context for the particular policy being deliberated, as a potential contribution to an overlapping consensus that is stable for the right reasons. If this vision of political liberalism were achieved, then contentious debate about health eating policy and its scientific basis could occur within that context and be resolved within the basic political structure. Because public health and political liberalism have a common concern for a good at the population level, they have an underlying affinity. Healthy eating policies could be evaluated in two not-unrelated ways: based on their instrumental contribution to the good of the public body of citizens as population-level health, and according to their stabilizing contribution to an overlapping consensus among citizens. In this latter way a policy would contribute to a conditional integral common good a la Sulmasy, one that has the prospect of conditioning a political system, and by doing so create the conditions of the possibility of a constitutive integral common good that is constituted on the right reasons for allegiance to an overlapping consensus. To conclude with reference to HEPPP, public reason may play an important function with respect to the political common good, even as debates about the weight and meaning of scientific evidence from epidemiology play out in deliberation of ordinary legislation concerning healthy eating. (shrink)

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved (...) in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed. (shrink)

The epidemiologist Bradford Hill famously argued that in epidemiology, specificity of association (roughly, the fact that an environmental or behavioral risk factor is associated with just one or at most a few medical outcomes) is strong evidence of causation. Prominent epidemiologists have dismissed Hill’s claim on the ground that it relies on a dubious `one-cause one effect’ model of disease causation. The paper examines this methodological controversy, and argues that specificity considerations do have a useful role to play in causal (...) inference in epidemiology. More precisely, I argue that specificity considerations help solve a pervasive inferential problem in contemporary epidemiology: the problem of determining whether an exposure-outcome correlation might be due to confounding by a social factor. This examination of specificity has interesting consequences for our understanding of the methodology of epidemiology. It highlights how the methodology of epidemiology relies on local tools designed to address specific inference problems peculiar to the discipline, and shows that observational causal inference in epidemiology can proceed with little prior knowledge of the causal structure of the phenomenon investigated. I also argue that specificity of association cannot (despite claims to the contrary) be entirely explained in terms of Woodward’s well-known concept of “one-to-one” causal specificity. This is because specificity as understood by epidemiologists depends on whether an exposure (or outcome) is associated with a `heterogeneous’ set of variables. This dimension of heterogeneity is not captured in Woodward’s notion, but is crucial for understanding the evidential import of specificity of association. (shrink)

Researchers, clinicians, and patients have good reasons for wanting answers to causal questions of disease and therapeutic intervention. This paper uses microbiologist Robert Koch’s pioneering work and famous postulates to extrapolate a logical sequence of evidence for confirming the causes of disease: association between individuals with and without a disease; isolation of causal agents; and the creation of a counterfactual. This paper formally introduces counter-counterfactuals, which appear to have been used, perhaps intuitively, since the time of Koch and possibly earlier. (...) An argument is presented that counter-counterfactuals are a useful tool for identifying necessary causes of disease, and sometimes must be used in place of isolation which is not always possible. In addition, a logical sequence of causal evidence for a therapeutic intervention is presented: creating a counterfactual, comparisons between subjects in receipt of treatment versus those who are not, and counter-counterfactuals. (shrink)

There is growing interest in nature-based interventions to improve human health and wellbeing. An important nascent area is exploring the potential of outdoor therapies to treat and prevent common mental health problems like depression. In this conceptual analysis on the nature–depression nexus, we distil some of the main issues for consideration when NBIs for depression are being developed. We argue that understanding the mechanisms, or ‘active ingredients’ in NBIs is crucial to understand what works and for whom. Successfully identifying modifiable (...) mediating intervention targets will pave the way for interventions with increased efficacy. We highlight a non-exhaustive list of five clinically relevant putative, candidate mechanisms which may underly the beneficial effects of NBIs on depression: stress, rumination, mindfulness, sleep and exercise. We also make the case that when developing NBIs it is important to not neglect young people, explore personalised approaches and focus on both treatment and prevention approaches. To achieve these aims methodologically rigorous programmes of clinical research are needed that include well-powered and controlled experimental designs including randomised controlled trials, qualitative research, longitudinal studies and large prospective cohorts. (shrink)

Theory of illness causation is an important issue in all biomedical sciences, and solid etiological explanations are needed in order to develop therapeutic approaches in medicine and preventive interventions in public health. Until now, the literature about the theoretical underpinnings of illness causation research has been scarce and fragmented, and lacking a convenient summary. This interdisciplinary book provides a convenient and accessible distillation of the current status of research into this developing field, and adds a personal flavor to the discussion (...) by proposing the etiological stance as a comprehensive approach to identify modifiable causes of illness. (shrink)

In order to support health interventions, biomedical and population health researchers need to collect solid evidence. This article asks what type of evidence this should be and expands on previous work that focused on etiological explanations, or causal-mechanical explanations of why and how illness occurs. The article proposes adding predictive evidence to the explanatory evidence, in order to form a joint evidence set, or JES = [A,B,C,D], which consists of four different types of evidence: association [A], biology [B], confirmation [C], (...) and difference-making [D]. The article discusses explanatory coherence as a backbone for this proposal, suggests criteria for each type of evidence, and offers a rubric for multi-evidence mapping. (shrink)

In this paper we argue for a naturalistic solution to some of the methodological controversies in regulatory science, on the basis of two case studies: toxicology and health claim regulation. We analyze the debates related to the scientific evidence that is considered necessary for regulatory decision making in each of those two fields, with a particular attention to the interactions between scientific and regulatory aspects. This analysis allows us to identify two general stances in the debate: a) one that argues (...) for more permissive standards of evidence and for methodological pluralism, and b) an opposing one that not only defends strict evidence requirements but also stipulates the use of one particular scientific methodologies for data generation. We argue that the real-world outcomes produced by alternative regulatory options are a vital piece of information that allows for the empirical assessment of these two stances. In particular, this information on outcomes makes it possible to analyze which standards of evidence and scientific methods generate the most useful knowledge as input for regulatory decision making. Our conclusion is that instead of an a priori selection of methodologies and standards, such decisions ought to be based on empirical evidence related to real-world outcomes. (shrink)

In 2015, Tomasetti and Vogelstein published a paper in Science containing the following provocative statement: “… only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to “bad luck,” that is, random mutations arising during DNA replication in normal, noncancerous stem cells.” The paper—and perhaps especially this rather coy reference to “bad luck”—became a flash point for a series of letters and reviews, followed by replies and yet (...) further counterpoints. In this paper, I critically assess Tomasetti and Vogelstein's argument, discuss the meaning of “luck” (or, better: “chance”) in the context of the debate, and use this case study to address larger questions about methodological criteria for causal explanations of population level patterns in biomedicine. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

Do experiences with nature –– from wilderness backpacking to plants in a preschool to a wetland lesson on frogs, promote learning? Until recently, claims outstripped evidence on this question. But the field has matured, not only substantiating previously unwarranted claims but deepening our understanding of the cause-and-effect relationship between nature and learning. Hundreds of studies now bear on this question, and converging evidence strongly suggests that experiences of nature boost academic learning, personal development, and environmental stewardship. This brief integrative review (...) summarizes recent advances and the current state of our understanding. The research on personal development and environmental stewardship is compelling although not quantitative. Report after report –– from independent observers as well as participants themselves –– indicate shifts in perseverance, problem-solving, critical thinking, leadership, teamwork, and resilience. Similarly, over fifty studies point to nature playing a key role in the development of pro-environmental behavior, particularly by fostering an emotional connection to nature. In academic contexts, nature-based instruction outperforms traditional instruction. The evidence here is particularly strong, including experimental evidence; evidence across a wide range of samples and instructional approaches; outcomes such as standardized test scores and graduation rates; and evidence for specific explanatory mechanisms and active ingredients. Nature may promote learning by improving learners’ attention, levels of stress, self-discipline, interest, and enjoyment in learning, and physical activity and fitness. Nature also appears to provide a calmer, quieter, safer context for learning; a warmer, more cooperative context for learning; and a combination of “loose parts” and autonomy that fosters developmentally beneficial forms of play. It is time to take nature seriously as a resource for learning — particularly for students not effectively reached by traditional instruction. (shrink)

Many philosophers and statisticians argue that risk assessors are morally obligated to evaluate the probabilities and consequences of methodological error, and to base their decisions of whether to adopt a given parameter value, model, or hypothesis on those considerations. This argument is couched within the rubric of null hypothesis testing, which I suggest is a poor descriptive and normative model for risk assessment. Risk regulation is not primarily concerned with evaluating the probability of data conditional upon the null hypothesis, but (...) rather with measuring risks, estimating the consequences of available courses of action and inaction, formally characterising uncertainty, and deciding what to do based upon explicit values and decision criteria. In turn, I defend an ideal of value-neutrality, whereby the core inferential tasks of risk assessment – such as weighing evidence, estimating parameters, and model selection – should be guided by the aim of correspondence to reality. This is not to say that value-judgments be damned, but rather that they should be accounted for within a structured approach to decision analysis, rather than embedded within risk assessment in an informal manner. (shrink)

The teratogenicity of the Zika virus was considered established in 2016, and is an interesting case because three different sets of causal criteria were used to assess teratogenicity. This paper appeals to the thesis of Russo and Williamson (2007) to devise an epistemological framework that can be used to compare and evaluate sets of causal criteria. The framework can also be used to decide when enough criteria are satisfied to establish causality. Arguably, the three sets of causal criteria considered here (...) offer only a rudimentary assessment of mechanistic studies, and some suggestions are made as to alternative ways to establish causality. (shrink)

Contemporary reasoning about health is infused with the work products of experts, and expert reasoning about health itself is an active site for invention and design. Building on Toulmin’s largely undeveloped ideas on field-dependence, we argue that expert fields can develop new inference rules that, together with the backing they require, become accepted ways of drawing and defending conclusions. The new inference rules themselves function as warrants, and we introduce the term “warranting device” to refer to an assembly of the (...) rule plus whatever material, procedural, and institutional resources are required to assure its dependability. We present a case study on the Cochrane Review, a new method for synthesizing evidence across large numbers of scientific studies. After reviewing the evolution and current structure of the device, we discuss the distinctive kinds of critical questions that may be raised around Cochrane Reviews, both within the expert field and beyond. Although Toulmin’s theory of field-dependence is often criticized for its relativism, we find that, as a matter of practical fact, field-specific warrants do not enjoy immunity from external critique. On the contrary, they can be opened to evaluation and critique from any interested perspective. (shrink)

Multidisciplinary models aggregating ‘lower-level’ biological and ‘higher-level’ psychological and social determinants of a phenomenon raise a puzzle. How is the interaction between the physical, the psychological and the social conceptualized and explained? Using biopsychosocial models of pain as an illustration, I argue that these models are in fact level-neutral compilations of empirical findings about correlated and causally relevant factors, and as such they neither assume, nor entail a conceptual or ontological stratification into levels of description, explanation or reality. If inter-level (...) causation is deemed problematic or if debates about the superiority of a particular level of description or explanation arise, these issues are fueled by considerations other than empirical findings. (shrink)

Contrastive neuroimaging is often taken to provide evidence about the localization of cognitive functions. After canvassing some problems with this approach, I offer an alternative: neuroimaging gives evidence about regions of the brain that bear difference-making relationships to psychological processes of interest. I distinguish between the specificity and what I call the systematicity of a difference-making relationship, and I show how at least some neuroimaging experiments can give evidence for systematic difference-making.

G. F. Stout is famous as an early twentieth century proselyte for abstract particulars, or tropes as they are now often called. He advanced his version of trope theory to avoid the excesses of nominalism on the one hand and realism on the other. But his arguments for tropes have been widely misconceived as metaphysical, e.g. by Armstrong. In this paper, I argue that Stout’s fundamental arguments for tropes were ideological and epistemological rather than metaphysical. He moulded his scheme to (...) fit what is actually given to us in perception, arguing that our epistemic practices would break down in an environment where only universals were given to us. (shrink)

Within public health, and increasingly other areas of social policy, there are widespread calls to increase or improve the use of evidence for policy-making. Often these calls rest on an assumption that increased evidence utilisation will be a more efficient or effective means of achieving social goals. Yet a clear elucidation of what can be considered “good evidence” for policy is rarely articulated. Many of the current discussions of best practise in the health policy sector derive from the evidence-based medicine (...) movement, embracing the “hierarchy of evidence” that places experimental trials as pre-eminent in terms of methodological quality. However, a number of problems arise if these hierarchies are used to rank or prioritise policy relevance. Challenges in applying evidence hierarchies to policy questions arise from the fact that the EBM hierarchies rank evidence of intervention effect on a specified and limited number of outcomes. Previous authors have noted that evidence forms at the top of... (shrink)

Thinking about illness causation has a long and rich history in medicine. After a hiatus in the 1990s, the last one-and-a-half decades have seen a surge of publications on causality in the biomedical sciences. Interestingly, this surge is visible not only in the medical, epidemiological, bioinformatics, and public health literatures, but also among philosophical publications. In this essay, I review and discuss one most recent addition to the literature, "Causality: Philosophical Theory Meets Scientific Practice" written by philosophers Phyllis Illari and (...) Federica Russo about causality in the sciences, and particularly about the health sciences. (shrink)

This chapter concerns the normativity of the concepts of paternalism and libertarian paternalism. The first concept is central in evaluating public health policy, but its meaning is controversial. The second concept is equally controversial and has received much attention recently. It may or may not shape the future evaluation of public health policy. In order to facilitate honest and fruitful debate, I consider three approaches to these concepts, in terms of their normativity. Concepts, I claim, may be considered nonnormative, normatively (...) charged, or normative in that they involve more complex relationships between values or duties. While the last approach is often best, other approaches may be appropriate depending on the context and purpose of discussion. The chapter’s conceptual investigation is illustrated by application to two public health policies: a tax on the consumption of fat and the encouragement of health-promoting food displays in restaurants and supermarkets. (shrink)

An otherwise lawlike generalisation hedged by a ceteris paribus (CP) clause qualifies as a law of nature, if the CP clause can be substituted with a set of conditions derived from the multivariate regression model used to interpret the empirical data in support of the gen- eralisation. Three studies in human biology that use regression analysis are surveyed, showing that standard objections to cashing out CP clauses in this way—based on alleged vagueness, vacuity, or lack of testability—do not apply. CP (...) laws also cannot be said to be simply false due to the indefinitely many conditions not explicitly stated in their associated model: scientific CP clauses imply that these are, given the evidence, not nomically relevant. (shrink)

Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell us about which (...) inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (shrink)

This paper seeks to determine the significance, if any, of epidemiological evidence to prove the specific causation element of liability in negligence or other relevant torts—in particular, what importance can be attached to a relative risk > 2, where that figure represents a sound causal inference at the general level. The paper discusses increased risk approaches to epidemiological evidence and concludes that they are a last resort. The paper also criticizes the proposal that the probability of causation can be estimated (...) with reference to the RR, such that RR > 2 is necessary and sufficient for causation. It is argued, following arguments by Sander Greenland and others, that RR > 2 is not necessary for proof of specific causation, except under restrictive biological assumptions that are not known to be satisfied for any important disease, and therefore must never be required. However, the paper argues that in some circumstances RR > 2 can be sufficient to prove causation at law. This position is defended against the widely held judicial and academic view that epidemiological evidence must be accompanied by something else, particular to the case at hand, if it is to have probative force for specific causation. It is argued that far from being epistemically irrelevant, to achieve correct and just outcomes it is in fact mandatory to take epidemiological evidence into account in deciding specific causation. Failing to consider such evidence when it is available leads to error and injustice. The conclusion is that in certain circumstances epidemiological evidence of RR > 2 is not necessary to prove specific causation but that it is sufficient. This “sufficiency” is confined to circumstances where there is no other evidence, as a way of getting clear on what the epidemiological evidence says. Once we have worked out what it says, this must be weighed against the other relevant evidence, if there is any. (shrink)

The epistemological analysis offered in this paper reveals that a combination of pieces of evidence, none of them sufficient by itself to warrant a causal conclusion to the legally required degree of proof, may do so jointly. The legal analysis offered here, interlocking with this, reveals that Daubert’s requirement that courts screen each item of scientific expert testimony for reliability can actually impede the process of arriving at the conclusion most warranted by the evidence proffered.

Evidence-based medicine (EBM) makes use of explicit procedures for grading evidence for causal claims. Normally, these procedures categorise evidence of correlation produced by statistical trials as better evidence for a causal claim than evidence of mechanisms produced by other methods. We argue, in contrast, that evidence of mechanisms needs to be viewed as complementary to, rather than inferior to, evidence of correlation. In this paper we first set out the case for treating evidence of mechanisms alongside evidence of correlation in (...) explicit protocols for evaluating evidence. Next we provide case studies which exemplify the ways in which evidence of mechanisms complements evidence of correlation in practice. Finally, we put forward some general considerations as to how the two sorts of evidence can be more closely integrated by EBM. (shrink)

This paper sets out to analyze how causation works by focusing on biology, as represented by epidemiology and by scientific information on how the body works (“physiology”). It starts by exploring the specificity of evolved physiological systems, in which evolutionary, developmental and proximal causes all fit together, and the concept of function is meaningful; in contrast, this structure does not apply in epidemiology (or outside biology). Using these two contrasting branches of biology, I examine the role both of mechanism and (...) of difference making in causation. I find that causation necessarily involves both mechanism and difference making, and that they play complementary roles. Both are seen as ontologically necessary, even if the evidence is not always available for both. Influential monist accounts that focus on one of these, at the expense of ignoring the other, are found to be inadequate on these and on other grounds. Recent attempts to combine them are reviewed, notably that of Russo and Williamson (Int Stud Philos Sci 21:157–170, 2007), and it is argued that their epistemic view requires there to be a source of the different types of evidence that a rational agent would consider, and that this source must be ontic. I then analyze how causal relationships work in evolved physiological systems and in those studied by epidemiology, with a particular focus on how mechanism interacts with input. Finally, I consider this concept of causation from the perspective of everyday language, and of its possible generalisability outside biology. (shrink)

According to Russo and Williamson (Int Stud Philos Sci 21(2):157–170, 2007, Hist Philos Life Sci 33:389–396, 2011a, Philos Sci 1(1):47–69, 2011b ), in order to establish a causal claim of the form, ‘_C_ is a cause of _E_’, one typically needs evidence that there is an underlying mechanism between _C_ and _E_ as well as evidence that _C_ makes a difference to _E_. This thesis has been used to argue that hierarchies of evidence, as championed by evidence-based movements, tend to (...) give primacy to evidence of difference making over evidence of mechanisms and are flawed because the two sorts of evidence are required and they should be treated on a par. An alternative approach gives primacy to evidence of mechanism over evidence of difference making. In this paper, we argue that this alternative approach is equally flawed, again because both sorts of evidence need to be treated on a par. As an illustration of this parity, we explain how scientists working in the ‘EnviroGenomarkers’ project constantly make use of the two evidential components in a dynamic and intertwined way. We argue that such an interplay is needed not only for causal assessment but also for policy purposes. (shrink)

In this thesis, I give a metascientific account of causality in medicine. I begin with two historical cases of causal discovery. These are the discovery of the causation of Burkitt’s lymphoma by the Epstein-Barr virus, and of the various viral causes suggested for cervical cancer. These historical cases then support a philosophical discussion of causality in medicine. This begins with an introduction to the Russo- Williamson thesis (RWT), and discussion of a range of counter-arguments against it. Despite these, I argue (...) that the RWT is historically workable, given a small number of modifications. I then expand Russo and Williamson’s account. I first develop their suggestion that causal relationships in medicine require some kind of evidence of mechanism. I begin with a number of accounts of mechanisms and produce a range of consensus features of them. I then develop this consensus position by reference to the two historical case studies with an eye to their operational competence. In particular, I suggest that it is mechanistic models and their representations which we are concerned with in medicine, rather than the mechanism as it exists in the world. -/- I then employ these mechanistic models to give an account of the sorts of evidence used in formulating and evaluating causal claims. Again, I use the two human viral oncogenesis cases to give this account. I characterise and distinguish evidence of mechanism from evidence of difference-making, and relate this to mechanistic models. I then suggest the relationship between types of evidence presents us with a means of tackling the reference-class problem. This sets the scene for the final chapter. Here, I suggest the manner in which these two different classes of evidence become integrated is also reflected in the way that developing research programmes change as their associated causal claims develop. (shrink)

This article focuses on the assessment of mechanistic relations with specific attention to medicine, where mechanistic models are widely employed. I first survey recent contributions in the philosophical literature on mechanistic causation, and then take issue with Federica Russo and Jon Williamson’s thesis that two types of evidence, probabilistic and mechanistic, are at stake in the health sciences. I argue instead that a distinction should be drawn between previously acquired knowledge of mechanisms and yet-to-be-discovered knowledge of mechanisms and that both (...) probabilistic evidence and manipulation are essential with respect to newly discovered mechanisms. (shrink)

This paper addresses questions about how the levels of causality (generic and single-case causality) are related. One question is epistemological: can relationships at one level be evidence for relationships at the other level? We present three kinds of answer to this question, categorised according to whether inference is top-down, bottom-up, or the levels are independent. A second question is metaphysical: can relationships at one level be reduced to relationships at the other level? We present three kinds of answer to this (...) second question, categorised according to whether single-case relations are reduced to generic, generic relations are reduced to single-case, or the levels are independent. We then explore causal inference in autopsy. This is an interesting case study, we argue, because it refutes all three epistemologies and all three metaphysics. We close by sketching an account of causality that survives autopsy—the epistemic theory. (shrink)

Since the second half of the twentieth century, biomedical research has made increasing use of epidemiological methods to establish empirical evidence on a population level. This paper is about practices with data in epidemiological research, based on a case study in Denmark. I propose an epistemology of record linkage that invites exploration of epidemiological studies as heterogeneous assemblages. Focusing on data collecting, sampling and linkage, I examine how data organisation and processing become productive beyond the context of their collection. The (...) case study looks at how a local population database established in 1976 to investigate possibilities for the prevention of cardiovascular disease is used thirty years later to test hypotheses on the aetiology of breast cancer. For two breast cancer investigations based on the same core data set, I follow the underlying record linkage practice and describe how research objects such as molecular markers become relevant with respect to public health through information networking. Epidemiological association studies function as tools that performatively enrol different contexts into statistical risk estimation, thereby configuring options for research as well as for clinical testing and public health policy. (shrink)

Psychedelic-assisted Psychotherapy combines the use of psychedelic compounds, such as psilocybin, with psychotherapy. PAP has shown some promise as a novel treatment for Major Depressive Disorder, and empirical research suggests that its efficacy turns on the altered states induced by psychedelic compounds. In this paper we draw on the literature of phenomenology to explain the therapeutic potential of psychedelic experiences. Svenaeus characterises mental illness as a form of suffering that entails three distinct but related experiences of alienation or “unhomelike being-in-the-world”: (...) illness suffering, which relates to embodiment; existential suffering, which relates to self-narratives, and political suffering, which relates to social relationships. Ratcliffe further characterises the experience of MDD in phenomenological terms as a loss of pre-intentional possibility that manifests as excessive noematic feeling in the experience of embodiment, restrictive narratives in the construction of self, and disconnectedness in experience of the social world. We contend that PAP ameliorates the suffering associated with MDD by inducing and consolidating a state of broadened pre-intentional possibility—one that entails sudden, profound and enduring changes in embodiment, self-narratives, and social experience. We argue further that this phenomenological account is consistent with a bio-psycho-social model of mental health and illness, and we frame it as an argument supporting the plausibility of recent claims about treatment success. This helps to justify ongoing future empirical research in this setting. (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)