This document discusses causes and probabilities for health from a philosophical perspective. It introduces medical humanities and the philosophical study of medicine. It discusses different levels of causation for populations and individuals. It also discusses how probabilities are interpreted differently for generic groups versus single cases. The document questions who philosophical perspectives in medicine are for, suggesting laymen, medical practitioners, and how Western medicine can learn from other healing traditions.

1. Causes and probabilities
for health
Federica Russo
Center Leo Apostel, Free University Brussels
Center for Reasoning, University of Kent

2. Overview
Medical humanities and philosophy of science
Causes for health
Probabilities for health
For whom? For what?
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3. Medical Humanities
PHIL SCI PERSPECTIVE
ON MEDICINE
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4. The ‘human’ study of medicine
Medicine, experimental medicine, and the
biological understanding of wellness and
disease
Medical humanities bring ‘Man’ into medicine
Anthropological, psychological, sociological,
philosophical understanding of wellness and
disease
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5. Phil med moves beyond ethics
Traditional phil med is about ethics
Fresh philosophical look at medicine:
How do we know: epistemology and methodology
of medical research
What it is: metaphysics of the ‘objects’ of medicine
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6. Medical Humanities
TYPICAL QUESTIONS IN PHIL MED
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7. Ethics questions, e.g.:
Is it ethical to conduct research on stem cells?
Should we accept euthanasia?
Is it ethical to deliver web-based diagnoses
online to patients?
…
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8. Phil Sci questions, e.g.:
What notion of cause is applicable to biomedical
contexts?
How to interpret probability in biomedical
contexts?
What procedures grant extrapolation from
animal models to humans?
…
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9. Medical Humanities
EXAMPLES
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10. Do electromagnetic fields cause brain tumour?
John lived 40 years close to an antenna tower.
Did this cause him cancer?
How much is the risk of developing CHD lowered
if I quit smoking?
Did the campaign in schools lower smoking rates?
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11. Causes for Health
GENERIC AND SINGLE CASE
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12. Medical knowledge and
Personalised medicine
Medical knowledge: Personalised medicine:
Generic causal relations Single Case causal relations
Are in principle repeatable Are tailored to the individual
patient
Are supposed to hold of
the majority of the Make use of specific, unique
population information about the
patient
Epidemiological studies
plus lab results
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13. Causes for Health
LEVELS OF CAUSATION
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14. A chicken-egg question?
No primacy of either level
Mutual need of both levels
An iterative process
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15. Probabilities for Health
GENERIC AND SINGLE CASE
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16. Different levels of causation,
different interpretations of probability
Generic
Heavy smokers have 10 times more chances
to develop lung cancer
Frequency of occurrence of disease in a given population
Single Case
John’s chances of recovery after operation are 80%
Degree of belief in occurrence of a specific event
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17. Causes for Health
CAUSES AS DIFFERENCE-MAKERS
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18. What causes are, what causes do
A virus causes infection
Penicillin cures infection
Socio-economic status influences access to healthcare
Smoking restricts blood vessels
Different ‘things’ can be causes
What they all do is to make a difference
to a condition of health or of disease
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19. Causes for Health
VARIATIONAL EPISTEMOLOGY
AND METHODOLOGY
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20. Look at variations in order to …
Find out causes of disease
Find out causes of recovery
Find out regulatory mechanisms
Comparisons between groups
Exposed / unexposed; healthy / ill
What makes conditions vary across groups / individuals
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21. Probabilities for Health
ODDS AND RISKS
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22. Risks, Odds and Probabilities:
Easy to compute
Risks and odds compare proportions in groups
n11 / n11 n12 p11
RR Factor Disease
n21 / n21 n22 p21 Yes No
Oddsexp n11 / n12 Exposed n11 n12
OR p11 p12
Oddsun exp n21 / n22
Unexposed n21 n22
Odds P p21 p22
P ; Odds
1 Odds 1 P

23. Risks, Odds, and Probabilities
‘explained’
… a RR equal to 2.0 means that an unexposed person is twice as likely
to have and adverse outcome as one who is not exposed …
(Sistrom&Garvan 2004)
… odds and probabilities are different ways of expressing the chance
that an outcome may occur…
(Sistrom&Garvan 2004)
… the probability that a child with eczema will also have fever is
estimated by the proportion 141/561 (25.1%) …
(Bland & Altman 2000)

24. Risks, Odds, and Probabilities
explained
‘unexposed person’, ‘child’ are statistical individuals
individuals randomly sampled from the population
Odds and risks compare proportions in groups
They have a generic interpretation
The corresponding probabilities are generic too
They are not directly applicable to the single-case
To be applicable they need to be constrained by further single
case knowledge
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25. FOR WHOM?
LAYMEN
What do laymen understand:
Out of doctor’s explanation?
In self, web-based diagnoses?
In 123&me genetic mapping?
In Wiki Medicare?
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26. FOR WHOM?
MEDICAL
PRACTITIONERS
How can a better
understanding
of phil med issues
improve medical
practitioners’
explanations?
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27. For What?
FIGHT STATISTICAL HEGEMONY
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28. Evidence-based people claim they can get
‘medical causes’ out of statistics
Not so sure, though
A point about philosophy of science
What information is conveyed by statistics
A point about communication of science
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29. For What?
RECONCILE WESTERN AND
NON-WESTERN HEALINGS
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30. Compare, set up a dialogue
What can Western medicine learn from other ways of
healing? And vice-versa.
Salvage expert knowledge in the era of evidence.
After ethno-biology, ethno-medicine?
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31. To sum up
A gentle introduction to phil med for non-philosophers
(Hopefully!)
Medical humanities, philsci in medicine
Causes and probabilities for health
For populations, for individuals
Medical knowledge, diagnosis
Whom is this philosophy good for? (Hopefully!)
Laymen, medical practitioners
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