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 this essay, I argue that Ted Poston's theory of explanatory coherentism is well-suited as a tool for causal explanation in the health sciences, particularly in epidemiology. Coherence has not only played a role in epidemiology for more than half a century as one of Hill's viewpoints, it can also provide background theory for the development of explanatory systems by integrating epidemiologic evidence with a diversity of other error-independent data. I propose that computational formalization of Hill's viewpoints in an explanatory (...) coherentist framework would provide an excellent starting point for a formal epistemological (knowledge-theoretical) project designed to improve causal explanation in the health sciences. As an example, I briefly introduce Paul Thagard's ECHO system and offer my responses to possible objections to my proposal. (shrink)

Bradford Hill (1965) highlighted nine aspects of the complex evidential situation a medical researcher faces when determining whether a causal relation exists between a disease and various conditions associated with it. These aspects are widely cited in the literature on epidemiological inference as justifying an inference to a causal claim, but the epistemological basis of the Hill aspects is not understood. We offer an explanatory coherentist interpretation, explicated by Thagard's ECHO model of explanatory coherence. The ECHO model captures the complexity (...) of epidemiological inference and provides a tractable model for inferring disease causation. We apply this model to three cases: the inference of a causal connection between the Zika virus and birth defects, the classic inference that smoking causes cancer, and John Snow’s inference about the cause of cholera. (shrink)

Models of illness causation play a crucial role in medicine and public health. In their recent paper on this topic, Michael Kelly, Rachel Kelly, and Federica Russo state that the integration of social, biological, and behavioral causes in one and the same etiologic mechanism remains to be clarified. In particular, they think that current models of illness causation do not appreciate "the truly integrated nature of bio-social-behavioral pathogenesis". In brief, Kelly, Kelly, and Russo suggest that two levels of explanation are (...) at work in medicine and public health, biological and social; that integration is difficult because of resistance to including social determinants of disease in both the... (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)

In this chapter, I first outline the public health workflow from assessment via goal definition and intervention to evaluation. Further, I discuss the types and subtypes of explanation used in public health research and practice: scientific, justificatory, methodological, and prospective. In doing this, I take the discussion far beyond the usual focus in philosophy of science as answers to “why?”-questions. The chapter ends with a few comments on my proposal.

The search for causes of perinatal brain damage needs a solid theoretical foundation. Current theory apparently does not offer a unanimously accepted view of what constitutes a cause, and how it can be identified. We discuss nine potential theoretical misconceptions: (1) too narrow a view of what is a cause (causal production vs. facilitation), (2) extrapolating from possibility to fact (potential vs. factual causation), (3) if X, then invariably Y (determinism vs. probabilism), (4) co-occurrence in individuals vs. association in populations, (...) (5) one cause is all that is needed (single cause attribution vs. multicausal constellations), (6) drawing causal inferences from very small numbers of observations (the tendency to generalize), (7) unstated causal inferences, (8) ignoring heterogeneity, and (9) failing to consider alternative explanations for what is observed. We hope that our critical discussion will contribute to fruitful research and help reduce the burden of perinatal brain damage. (shrink)

At the core of medicine is the idea to help fellow human beings by improving or even restoring their health. Let us call this the auxiliary stance of medicine—the motivation of medical intervention by reference to a moral obligation to guide our peers in their attempt to live a healthy and productive life. In parallel, the auxiliary stance is also central to public health, with a focus on prevention and health promotion. Taken together, we can view medicine and public health (...) as the two main human auxiliary endeavors to protect individuals and populations from health risks and help them to heal when sick. (shrink)

This book covers the overlap between informatics, computer science, philosophy of causation, and causal inference in epidemiology and population health research. Key concepts covered include how data are generated and interpreted, and how and why concepts in health informatics and the philosophy of science should be integrated in a systems-thinking approach. Furthermore, a formal epistemology for the health sciences and public health is suggested. -/- Causation in Population Health Informatics and Data Science provides a detailed guide of the latest thinking (...) on causal inference in population health informatics. It is therefore a critical resource for all informaticians and epidemiologists interested in the potential benefits of utilising a systems-based approach to causal inference in health informatics. (shrink)

Biomedical research and study design have recently been examined in detail by philosophers of science, who, like biomedical researchers, are concerned with the ability to accurately represent causal relationships through scientific study and apply these relationships to improve the health of individuals and populations. Epistemology—defined by the OED as "the theory of knowledge, especially with regard to its methods, validity, and scope, and the distinction between justified belief and opinion"—is fundamental to these concerns. In particular, philosophers of science and biomedical (...) researchers have discussed the epistemological value of randomized-controlled trials in regards to their individual components.... (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)

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)

Agent-based models (ABMs) are one type of simulation model used in the context of the COVID-19 pandemic. In contrast to equation-based models, ABMs are algorithms that use individual agents and attribute changing characteristics to each one, multiple times during multiple iterations over time. This paper focuses on three philosophical aspects of ABMs as models of causal mechanisms, as generators of emergent phenomena, and as providers of explanation. Based on my discussion, I conclude that while ABMs cannot help much with causal (...) inference, they can be viewed as etio-prognostic explanations of illness occurrence and outcome. (shrink)

Dieser Aufsatz beschreibt und erörtert fünf Aspekte der gegenwärtigen Wissenschaft: Verfahren, Zwiespalt, Schweigen, Hoffnung, und Probieren.

My goal in this paper is twofold. First, I want to analyze two early texts by Vilém Flusser in order to explore what may have been his conceptualization of the relationship between science and philosophy. My analysis suggests that Flusser thought of both as tools to analyze reality by analyzing language. While he saw science as a (sometimes too vigorous) force forward, he viewed philosophy as what can prevent some of the negative consequences of such progress. In direct comparison, Flusser (...) thought of science as a discourse with the purpose to provide novel information and of philosophy as what can keep objective science in check by moving the discourse into the realm of the subjective. It remains to be explored whether these results also apply to Flusser’s later writings. My second goal is to show the relationship between three aspects of modern science (crisis, contrast, and trying out) and what I see as Flusser’s early (mid 1960s) view of science in relation to philosophy and poetry. -/- . (shrink)

In this paper, we build upon the model of authenticity proposed by Lehman and colleagues, which includes the dimensions consistency, conformity, and connection. We expand this “3C-view” by adding a fourth dimension, continuity, which results in what we have come to call “4C-view of authenticity.” We discuss our proposal from a process perspective and emphasize that congruence might be a reasonable candidate for a concept that unifies the four dimensions of authenticity.

Explaining the causal mechanisms that contribute to autism spectrum disorder occurrence remains a conundrum in developmental medicine, neuroscience, and child psychiatry. Recent research has resulted in agreement on behavioral definitions and their underlying cognitive processes, early diagnosis and standardized assessments, evidence-based interventions, systems-level approaches to neurobiology, and identification of genetic variants and their interaction with epigenetic and environmental factors. However, an explanatory model of autism causation remains elusive.Perhaps..