Knowing what isn`t so

When it comes to health and medicine, there are an abundance of beliefs, philosophies and practices floating around out there. Unfortunately, many of these have no real evidence to back them up but are still used and strongly supported.

Often, erroneous beliefs about medicine are not only wrong, but expensive to the user and even downright harmful. Coined in an old saying, it is not the things we don't know that get us into trouble, but the things we do know but that aren't true.

Where do all these ideas come from and why are we so easily misled? This question has troubled scientists for a long time and much research has been done in the area.

Firstly, people tend to see what they want to believe. In medicine this can be particularly rampant as we hear positive testimonials from people and want to accept positive claims about 'miracle' products.

Unfortunately, this tendency to see what we want to believe often makes it difficult to accept findings or observations that are at odds with what we believe to be true about a given treatment method or product.

Scientists are not immune to this problem and that is why good medical studies often use a double-blind approach in their design. If neither the experimenter nor the subject is aware of which treatment is being given, it will not be possible to impose pre-conceptions on the results.

Another tendency inherent to humans is the preference for black and white solutions rather than grey areas. This contributes to the over-simplification of complex conditions and results in simplified beliefs being held with excessive confidence. When we hear of products that seem too good to be true, we want to believe they will work even though this is rarely the case.

In general, people like the idea that we can control everything that happens to us, when this is often not possible. There are many diseases that are not preventable and do not come as a result of any fault of the sufferer, yet people often feel responsible for their ill health or are blamed by others for it.

Depression is a good example of an illness that is often thought of in this way. Many still believe that depressed people simply need to try harder to cheer up.

Now that we've explored why it's easy to believe treatments that are not scientifically proven, we should examine why it is that so many new treatments trumpeted as breakthroughs are eventually discredited.

This occurs because early observations and research tend to be less well-controlled than later studies. Initial observations about a new treatment are often discovered by accident or in the form of positive reports from people. At these early stages, the perceived potential makes the treatment more susceptible to bias.

In these cases, promising treatments are followed up with better research. After further study, yesterday's breakthrough sometimes becomes tomorrow's unfulfilled promise.

In new treatments as well as highly publicized miracle treatments, the existence of a large number of studies or positive testimonials do not compensate for a lack of quality in research.

We often hear of treatments that are touted as proven because of the sheer number of positive reports. Unfortunately, when people really want to believe a treatment will work there is a strong placebo effect, which can seriously bias the reporting.

Often, we see structure and coherence in random patterns. For example, when repeatedly flipping a coin we expect the result to alternate more often than it does. When it lands on heads several times in a row we often feel this is somehow significant.

Statistical analysis is important because chance sequences do not always look the way we might expect them to. This is another reason clinical research needs to be repeated and tested on large numbers of people rather than a small handful of volunteers.

It may take years and a lot of money to conduct studies with the necessary controls before we can really be confident of a treatment's effectiveness. In fact, it usually takes 12 to 15 years and more than $500 million to bring a single new drug to market.


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