How often have we heard this? YOU ARE WRONG! MY TREATMENT DOES WORK!!! ONLY THE OTHER DAY, I HAD A PATIENT WHO WAS CURED BY IT.
Take for instance this tweet I got yesterday:
You go too far @EdzardErnst. In fact I was consulted about a child who hadn’t grown after an accident. She responded well to homoeopathy and grew. How much are you being paid for your attempts to deny people’s health choices?
The tweet refers to my last post where I exposed homeopathic child abuse. Having thought about Thomas’ tweet, I must say that I find it too to be abusive – even abusive on 4 different levels.
- First, the tweet is obviously a personal attack suggesting that I am bribed into doing what I do. I have stated it many times, and I do so again: I receive no payment from anyone for my work. How then do I survive? I have a pension and savings (not that this is anyone’s business).
- Second, it is abusive because it claims that children who suffer from a pathological growth retardation can benefit from homeopathy. There is no evidence for that at all, and making false claims of this nature is unethical and, in this case, even abusive.
- Third, if Thomas really did make the observation she suggests in her tweet and is convinced that her homeopathic treatment was the cause of the child’s improvement, she has an ethical duty to do something more about it than just shooting off a flippant tweet. She could, for instance, run a clinical trial to find out whether her observation was correct. I admit this might be beyond her means. So alternatively, she could write up the case in full detail and publish it for all of us to scrutinise her findings. This is the very minimum a responsible clinician ought to do when she comes across a novel and potentially important result. Anything else is my view unethical and hinders progress.
I do, of course, sympathise with lay people who fail to fully understand the concept of causality. But surely, healthcare professionals who pride themselves of taking charge of patients ought to have some comprehension of it. They should know that clinical improvements after a treatment is not necessarily the same as clinical improvement because of the treatment. Is it really too much to ask of them to know the criteria for causality? There is plenty of easy-reading on the subject; even Wikipedia has a good article on it:
In 1965, the English statistician Sir Austin Bradford Hill proposed a set of nine criteria to provide epidemiologic evidence of a causal relationship between a presumed cause and an observed effect. (For example, he demonstrated the connection between cigarette smoking and lung cancer.) The list of the criteria is as follows:
- Strength (effect size): A small association does not mean that there is not a causal effect, though the larger the association, the more likely that it is causal.
- Consistency (reproducibility): Consistent findings observed by different persons in different places with different samples strengthens the likelihood of an effect.
- Specificity: Causation is likely if there is a very specific population at a specific site and disease with no other likely explanation. The more specific an association between a factor and an effect is, the bigger the probability of a causal relationship.
- Temporality: The effect has to occur after the cause (and if there is an expected delay between the cause and expected effect, then the effect must occur after that delay).
- Biological gradient: Greater exposure should generally lead to greater incidence of the effect. However, in some cases, the mere presence of the factor can trigger the effect. In other cases, an inverse proportion is observed: greater exposure leads to lower incidence.
- Plausibility: A plausible mechanism between cause and effect is helpful (but Hill noted that knowledge of the mechanism is limited by current knowledge).
- Coherence: Coherence between epidemiological and laboratory findings increases the likelihood of an effect. However, Hill noted that “… lack of such [laboratory] evidence cannot nullify the epidemiological effect on associations”.
- Experiment: “Occasionally it is possible to appeal to experimental evidence”.
- Analogy: The effect of similar factors may be considered.
And this brings me to my 4th and last level of abuse in relation to the above tweet and most other claims of this nature: being ill-informed and stupid while insisting to make a nonsensical point is, in my view, offensive – so much so that it can reach the level of abuse.