When I was scouting out potential PhD supervisors, I attended a meeting in which the scientist said “life is a normal curve” in reference to the significance of the results he had obtained from a study with a relatively large sample size. As I critically evaluated his presentation, I realized that while his findings were statistically significant, they would do little for an individual who did not fit the “average”.
The foundation of most scientific experimentation is comparing the average change that occurs between two groups receiving different types of treatments (e.g. a form of exercise, a supplement, a dietary strategy). Statistical significance is based on the probability of that result having occurred. It’s basically like determining whether the observed change was due to to a “real effect” or simply due to chance alone. Without getting into too much statistical jargon, as the sample size or number of subjects in the study increases, the probability of detecting a “real effect” increases. This is great for scientists who are looking to answer a question or test a hypothesis but how does this affect the individual person who is trying to seek the best course of action for his or her own goals or situation? What happens if you aren’t the average person?
Consider the normal curve or Bell curve (Figure 1). In the context of sport and exercise science, the normal curve or normal distribution represents the distribution of a large number of subjects with respect to a certain variable. Let’s take vertical jumping ability: if I took 100 people and tested there vertical jump, there would be an average score, which is the highest point on the normal curve. This would be where the majority of the subjects would fall in terms of their jumping ability. However, there would also be outliers or subjects who had amazing vertical jumps (e.g. elite athletes) and the outliers on the other end of the spectrum or those with terrible vertical jumps (e.g. washed up strength coaches – yes I’m taking a shot at my profession).
So, if you refer back to my question at the end of the second paragraph, how does this affect the individual who is trying to sift through vast amounts of scientific findings to determine the right course of action with respect to a fitness goal? Suppose we are now talking about a dietary strategy, and a particular study comes out that clearly demonstrates a statistically significant finding based on comparing the average response between two groups as described above. What happens if you, the individual, happen to be an outlier, meaning you aren’t going to respond like the average person? You could spend a lot of money, time and energy trying to make something happen that is NEVER going to happen. On the other side of the equation, many sport scientists, trainers and coaches are way too quick to attribute a client’s lack of progress to poor dedication, commitment, and work ethic before answering the basic question “is this diet or style of exercise RIGHT for this person?”.
If you frame research in this line of thinking, it makes more sense to evaluate some aspects of exercise and nutrition in terms of whether or not you are a responder, an extreme-responder or a non-responder. I call this the Responder-Factor. If we approach health, fitness and performance in this manner, the important question is no longer whether a finding was statistically significant based on the average change of a large number of subjects but instead where do you, the individual, fit on a normal curve… or what is your Responder-Factor? It is absolutely essential to know whether or not you are an extreme-responder (e.g. that diet worked fantastic for you), a responder (e.g that diet worked pretty well for you and you displayed a typical response), or a non-responder (e.g. that diet did absolutely nothing for you!) if you are going to find the right strategies to help you achieve your goals.
As I mentioned above, this approach is important for many different aspects of the health, fitness and performance domains. It can be used to evaluate the effectiveness of many commonly espoused beliefs around exercise and nutrition programs like the benefits of a particular supplement, eating a high carbohydrate diet vs. a high protein diet or performing high intensity interval training vs. long slow distance training.
In summary, remember that you are an individual and just because everyone responded to a particular diet or type of exercise it doesn’t mean you will too. On the flip side it also means that just because you found something that works for you it doesn’t mean that it will work for everyone so don’t force your belief on others unless you know it will be helpful to the cause. My advice to you is to try to determine where you fit on a normal curve or your Responder-Factor. Although this can sometimes be challenging, it’s the best way to truly individualize your approach to health, fitness and performance.