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Not all scientific studies are created equal - David H. Schwartz
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Not all scientific studies are created equal - David H. Schwartz

 
Studies have shown that taking vitamins is good for your health and bad for your health. That newly discovered herb can improve your memory or destroy your liver. Headlines proclaim a promising new cancer treatment and never mention it again. On a daily basis, we are bombarded with attention-grabbing news, backed up by scientific studies, but what are these studies? How are they performed? And how do we know whether they're reliable? When it comes to dietary or medical information, the first thing to remember is that while studies on animals or individual cells can point the way towards further research, the only way to know how something will affect humans is through a study involving human subjects. And when it comes to human studies, the scientific gold standard is the randomized clinical trial, or RCT. The key to RCTs is that the subjects are randomly assigned to their study groups. They are often blinded to make them more rigorous. This process attempts to ensure that the only difference between the groups is the one the researchers are attempting to study. For example, when testing a new headache medication, a large pool of people with headaches would be randomly divided into two groups, one receiving the medication and another receiving a placebo. With proper randomization, the only significant overall difference between the two groups will be whether or not they received the medication, rather than other differences that could affect results. Randomized clinical trials are incredible tools, and, in fact, the US Food and Drug Administration often requires at least two to be conducted before a new drug can be marketed. But the problem is that an RCT is not possible in many cases, either because it's not practical or would require too many volunteers. In such cases, scientists use an epidemiological study, which simply observes people going about their usual behavior, rather than randomly assigning active participants to control invariable groups. Let's say we wanted to study whether an herbal ingredient on the market causes nausea. Rather than deliberately giving people something that might make them nauseated, we would find those who already take the ingredient in their everyday lives. This group is called the cohort. We would also need a comparison group of people who do not have exposure to the ingredient. And we would then compare statistics. If the rate of nausea is higher in the herbal cohort, it suggests an association between the herbal supplement and nausea. Epidemiological studies are great tools to study the health effects of almost anything, without directly interfering in people's lives or assigning them to potentially dangerous exposures. So, why can't we rely on these studies to establish causal relationships between substances and their effects on health? The problem is that even the best conducted epidemiological studies have inherent flaws. Precisely because the test subjects are not randomly assigned to their groups. For example, if the cohort in our herbal study consisted of people who took the supplement for health reasons, they may have already had higher rates of nausea than the other people in the sample. Or the cohort group could've been composed of people who shop at health food stores and have different diets or better access to healthcare. These factors that can affect results, in addition to the factor being studied, are known as confounding variables. These two major pitfalls, combined with more general dangers, such as conflicts of interest or selective use of data, can make the findings of any particular epidemiological study suspect, and a good study must go out of its way to prove that its authors have taken steps to eliminate these types of errors. But even when this has been done, the very nature of epidemiological studies, which examine differences between preexisting groups, rather than deliberately inducing changes within the same individuals, means that a single study can only demonstrate a correlation between a substance and a health outcome, rather than a true cause and effect relationship. At the end of the day, epidemiological studies have served as excellent guides to public health, alerting us to critical health hazards, such as smoking, asbestos, lead, and many more. But these were demonstrated through multiple, well-conducted epidemiological studies, all pointing in the same direction. So, the next time you see a headline about a new miracle cure or the terrible danger posed by an everyday substance, try to learn more about the original study and the limitations inherent in any epidemiological study or clinical trial before jumping to conclusions.

TED, TED-Ed, TED Ed, TEDEducation, David Schwartz, Augenblick Studios, science, scientific studies, scientific study, scientific method, skepticism

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