Causality is one of the most important concepts in research, because humans are naturally prone to finding patterns where none exist. We are all easily fooled, and regularly even by ourselves.
Mistaking a correlation (two things coincidentally happening in sequence) for a cause (one thing creating the other) can lead to wrong decisions, useless treatments, wasted resources, and often to significant harm. To prevent us making such errors, scientists have long relied on structured frameworks to prove when one event truly prompts another.
In the late 19th century, the German physician Robert Koch wanted a define way to demonstrate that a specific microbe caused a specific disease. He developed “Koch’s Postulates”, a four-step checklist that would transform medicine:
- The microbe must be present in every case of the disease.
- The microbe must be isolated from the sick host and grown in a laboratory.
- The laboratory-grown microbe must cause the same disease when introduced to a healthy host.
- The microbe must be isolated again from the newly infected host.
These rules generally worked fine in most situations; but for many infectious diseases, they proved to have limits. For example, some viruses cannot be grown easily in the laboratory, and some people carry bacteria without ever getting sick. And, of course, there are many diseases that are not caused by microbes at all.
As medicine tackled chronic, non-infectious conditions like heart disease or cancer, Koch’s checklist fell short. For instance, smoking causes lung cancer, but you cannot easily isolate smoking in a laboratory, nor does every smoker get cancer.
To improve our understanding, the UK epidemiologist Austin Bradford Hill introduced a broader toolkit in 1965. It is today known as the “Bradford Hill Criteria”. Instead of a strict pass or fail test, they use several simple viewpoints to weigh the evidence:
- Strength: Is the connection powerful?
- Consistency: Do different studies produce the same result?
- Temporality: Did the cause occur before the effect?
- Biological Gradient: Does more exposure lead to stronger effects?
- Biological plausibility: Does the connection fit into what we already know?
Koch’s postulates gave us the clarity to cure infections, and the Bradford Hill criteria allowed us to tackle non-infectious public health threats. Together, these criteria allowed us to ensure that medicine is built on truth rather than guesswork.
In the realm of so-called alternative medicine (SCAM), causality has a particularly important role, not least because proponents often claim causality while science rejects it. Here are just four examples:
Homeopathy
Proponent claim: The fact that many patients get better after taking a homeopathic remedy proves that homeopathy works.
Reality: There are many other, more convincing explanations for this outcome – e.g. placebo effects, or regression towards the mean.
Applied Kinesiology
Proponent claim: Muscle response at manual testing indicates nutrient deficiencies, toxin exposure, or food allergies.
Reality: There is no consistent relationship between muscle testing results and health. The practice fails basic reliability tests; different practitioners get different results from the same patient.
Reiki
Proponent claim: Healers channel “healing energy” from assumed sources into the body of the patient that improves health and prompts recovery.
Reality: No such energy exists. Controlled studies show Reiki performs no better than placebo. The claimed energy has no basis in physics or biology.
Acupuncture
Proponent claim: Inserting needles at specific points along “meridians” releases blocked qi and cures various conditions.
Reality: Most of the adequately blinded trials show no difference between true acupuncture and placebo acupuncture – needles placed randomly or not penetrating skin. Cochrane Reviews find acupuncture does no better than placebo. The meridian system has no anatomical basis.
These examples illustrate a fundamental problem in SCAM: proponents routinely mistake correlation for causation and propose causal mechanisms that have no basis in fact. Thanks to the above-mentioned criteria, the claims of SCAM advocates can readily be identified for what they are: unproven speculations borne out of wishful thinking.
