Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself.
Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms, and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever randomized controlled trial designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology.
This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.
"This book is just what philosophy of medicine needs – careful argumentative analysis of issues that matter to the practice of biomedical science." - Harold Kincaid, University of Cape Town, South Africa
"With his usual clarity, Professor Gillies manages to deal simultaneously with two among the most complex and thorny issues in science and philosophy of science: causality and probability. And he does so in a field – medicine – where their complexity grows exponentially, because of the theoretical and practical challenges of understanding and curing disease. The book is therefore an essential guide to those who want to delve into medicine." - Federica Russo, University of Amsterdam, The Netherlands
"This book develops a philosophical theory of causality in a very engaging and readable way. It sheds light on many historical examples of medical discovery and also on present-day causal modelling methods. Essential reading for anyone interested in causality, probability, or medicine." - Jon Williamson, University of Kent, UK
Part 1: Causality and Action
1. An action-related theory of causality
2. General discussion of AIM theories of causality
3. An example from medicine. Koch’s work on bacterial diseases and his postulates
Part 2: Causality and Mechanisms
4. Mechanistic theories of causality and causal theories of Mechanism
5. Types of evidence: (i) evidence of mechanism
6. Types of evidence: (ii) statistical evidence in human populations
7. Combining statistical evidence with evidence of mechanism
8. The Russo-Williamson thesis: (i) effects of smoking on health
9. The Russo-Williamson thesis: (ii) the evaluation of streptomycin and thalidomide
10. Objections to the Russo-Williamson thesis
11. Discovering cures in medicine and seeking for deeper explanations
Part 3: Causality and Probability
12. Indeterministic causality
13. Causal networks
14. How should probabilities be interpreted?
15. Pearl’s alternative approach to linking causality and probability
16. Extension of the action-related theory to the indeterministic case
Appendix 1. Example of a simple medical intervention which is not an intervention in Woodward’s sense
Appendix 2. Mathematical Terminology
Appendix 3. Sudbury’s Theorems
Glossary of Medical Terms