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Historically, there has been a huge gap between the scientists doing studies in labs and bodybuilders stepping on stage. Recently, there has been a shift in the sport of bodybuilding towards using science-based approach to contest preparation. It has gotten to the point where when I scroll down my facebook news feed, it seems like everyone is now citing this study or that study for why you “have to do” this new approach or “should never do” this other approach. However, I’ve noticed that many bodybuilders in general do not necessarily understand how to interpret research or how to apply it to themselves and what they are doing in the gym, kitchen, etc. As someone who is a bodybuilder, coach, performing primary research in a lab and has published multiple peer-reviewed papers, I hope that this article helps bodybuilders understand how to better use science in their own training.

The first part of this article will get into some of the nitty-gritty details of what to look for in a study and I will conclude with some practical recommendations on how to fit science into your own approach.

Finding Peer-Reviewed Studies

Before we can talk about how to interpret scientific studies, we should first talk about what peer-reviewed research is and where to find it. Here is an example of the peer-review process:

I perform an experiment, analyze the data, and write the paper.

I find a journal that suits the topic of my paper and submit.

The editor of the journal sends my paper out to other scientists who are experts in that area of research.

These scientists review my paper and recommend to the editor if my paper should be accepted, rejected, or if I need to make further revisions.

Once these experts and the editor of the journal are satisfied with my paper, it is accepted for publication.

Once published, there are numerous places you can find my new paper. Two examples of great places to search for studies are Pubmed www.pubmed.com or google scholar www.googlescholar.com I want to emphasize that these are websites where you can search for studies on nearly any topic and they are very valuable resources.



What to look for while reading a study

Now that we know where to find studies, we do some searching and come across a study that is of interest to us. This section will describe some of the basic things to be aware of when reading a study. It is not a complete list, but includes several things that are commonly overlooked.

Abstract:

Provides a brief summary of the study

Be Aware: Results shown in abstracts are what the author feels are most important Conclusions made in abstracts are the author’s interpretation of the data Therefore, you need to read the whole study to make your own conclusions.



DO NOT ONLY READ THE ABSTRACT!

In order to become truly knowledgeable, the goal should be to make your own conclusions based off of the data rather than just spitting back what the author thinks of the data. In addition, you should avoid searching for abstracts to support your beliefs. Instead, read entire papers and form your beliefs from the data.

Finally, avoid listening to abstract “know-it-all’s” who exclusively read and spit back information from abstracts to form their conclusions.

Introduction:

Provides a background of the problem the study is addresses, discusses the purpose of the study, lists hypothesis, and explains how this study will further scientific knowledge in this area.

Methods:

Explains what was done in the study in enough detail that the study can be replicated

Things to be aware of: What population is this study performed in? There are often large difference between responses of trained vs. untrained athletes, old vs. young, men vs. women, healthy vs. disease, etc. Is this study done in cell culture , animals , or humans ? If this is done in cell culture or animals, is this realistic of what happens in humans and has this been done in humans? Is this an acute study or long-term training study? Acute studies typically show us what is happening at a snap shot in time. This may be the same result observed in long-term studies, but this isn’t always necessarily the case depending upon what is being measured. What is the duration of the study? Is it long enough to detect a change in what is being measured? How large is the sample size ? Is it large enough to detect a difference between groups? Is the main outcome of interest measured in an appropriate way? Many outcomes can be measured by several techniques. Some techniques have more or less error associated with them than others. If this is a supplementation study, what was the dosage of supplement given? Is this dosage safe/practical?



METHODS TAKE HOME POINT:

I know I have thrown a lot at you in this section; however, the take home point is that the manner in which this study is executed is of utmost importance when trying to determine if the results found are applicable to real life.



Results:

Shows the data from the study in either words, tables, and/or figures.

Statistics should be included. Although not all of us are statisticians, here are some common things to look out for: Error Bars Graphs should have error bars to indicate the variance in their data. The first graph below is an example of the results of a study in which the data is presented without error bars. Based on this graph, it appears treatment 2 increased the variable being measured and treatment 1 had no effect. However, this is the same graph with error bars. From this graph, you can see that there is a large variance in the data and in fact, neither group had a significant effect on the variable measured. The take home point from this is that although both graphs show the same means, inclusion of error bars representing variance in the data shows a completely different story. Correlations: A correlation is an association between one variable and another. Pay attention to what the correlation graph looks like. For example, the conclusion from the graph below indicates that there is a positive relationship between variable 1 and variable 2: However, if you remove that 1 point, the story completely changes. Whether that point is a real person that is an outlier or a poor measurement is up to debate; however, the inclusion/exclusion of that point completely changes the story. Correlation vs. Causation As mentioned above, a correlation is an association between 2 variables. Causation refers to if the change in variable 2 is a result of a change in variable 1. Correlation does not mean that variable 1 caused the change in variable 2 or vice-versa. In the situation where 2 variables are found to be correlated, future studies would be needed to determine if a change in one of the variables was causing the change in the other. Biological vs. Statistical Significance Statistical significance is typically defined as p<0.05. Biological significance refers to if the difference is meaningful. Just because something is statistically significant does not mean that it is biologically significant. Look at the data yourself rather than just looking for statistical significance.



Discussion:

Summarizes findings, relates them to previous studies, lists study strengths and limitations, and gives conclusions.

Keep in mind this is the author’s interpretation of the data may not be the only possible interpretation of the data.

Applying Findings to Bodybuilding

You have read a great article and it supports the use of a certain supplement, nutritional approach or training technique. You are ready to implement this into your overall approach; however, rather than basing your entire decision on one study, you should first take a look at what the field as a whole says about this issue. A good way to do this is to take a look at systematic review papers, meta-analysis, and multiple papers on your topic.

If one particular study supports a technique, but the rest of the field of literature does not, it would probably be in your best interest to not waste your time.

Moving forward, let’s say that your technique is supported by the field of research as a whole and you want to implement it into your approach. However, there a few last things to consider. First off, how much time, effort, money, and stress are required to implement this technique? How large is the benefit of this technique? And most importantly, is the time, effort, money, and/or stress required to implement this technique worth the added benefit?

In my opinion, this is a very valuable question that most overlook. Keep in mind, most of the top natural pro bodybuilders are in their late 30’s and 40’s. In addition, most have been training and following some sort of nutrition plan for decades. Many people with a lot of potential start training; however, few reach the elite level and their full potential. One of the major reasons for this is becoming mentally/physically burnt out. A good way to avoid burnout is to have an approach that is effective and you can sustainably do for a long period of time.

The next time you see the hot new technique come out, ask yourself if the benefit is worth the added burden and if it is sustainable for a long period of time.

Take Home Points

There is an increased interest in a science-based bodybuilding approach; however, many people do not understand what to look for in a scientific paper

Reading abstracts will give you what the author thinks is most important and what their interpretation of the data is; however, you will need to read the entire paper in order to develop you own interpretation of the data.

of the data is; however, you will need to read the in order to develop you own interpretation of the data. Look at the entire field of study rather than an individual study when making decisions.

of study rather than an when making decisions. When implementing a science-based technique into your approach determine if the size of the benefits of the technique is worth the time, money, effort, and/or stress required to implement the technique.

Acknowledgements

I would like to thank all of my research advisors and statistics professors throughout the years for teaching me the information included in this article. I also thank Eric Helms and Cliff Wilson for their feedback on this article.