Responders and non-responders seem to be popular buzz words in the field of sport science these days. If a study shows no difference on average, people start to look at individual responses. Some individuals will have improved as a result of a treatment, training program or supplement. Some others show a decrement. On average there is no difference.
Responders and non-responders?
In some papers the ones that show positive effects are called responders and the ones with the negative effects are the non-responders. It is argued that looking at averages has little relevance for the individual athlete as they may be a responder or a non-responder. Although there might be some truth in this view, there are also serious concerns! I will explain those concerns here.
I will be the first to shout that it is important to have interventions that are relevant to the individual. Repeatedly I have given lectures about personalized sports nutrition and I have stated that I believe that personalized nutrition is the future of sports nutrition. The concept of responders and non-responders seems to fit well with those ideas.
Individual differences?
As mentioned above, some studies find no difference on average but individuals that improve with a treatment and individuals who get worse. Let's consider the following example. We have a diet that we hypothesise improves performance. The results show no difference on average. But looking at the individuals it is clear that some individuals had better performance with the new diet. If you now label the individual who responds in a positive as a responder you make a very important assumption. That is, that this individual will always respond in the same way to that diet. This, unfortunately, may not be true. Any athlete or coach can tell you that performance varies from day to day. Some days are better than others. There are on- and off days and these are usually notoriously hard to predict.
If you now label the individual who responds in a positive as a responder you make a very important assumption
Day to day variability
So when some individuals show a positive response, this could at least partly because they have an “on-day” and individuals who had a negative response may have had an “off-day”. If measurements and tests are used that have large day to day variability these differences can be substantial. For example if we use a cycling test to exhaustion at a moderate intensity, we know that there is very large day to day variation. The same person with the same diet may perform much better one day compared to another.
If measurements and tests are used that have large day to day variability these differences can be substantial
Thus the positive or negative response may have been a result of day to day variation rather than differences in individual responses. It is also possible that equipment measures slightly different one day compared with the next. Step on a scale to discover that you step on it three times and you get at least 2 different values.
Multiple trials
A study can only really determine that someone is a responder or non-responder by showing that the observed effects are consistently negative or consistently positive for that person. Very few papers that discuss responders and non-responders do not have multiple trials to provide this evidence. Therefore, it it not justified to refer to these individuals as responders and non-responders.
Next time you read about responders and non responders ask these questions:
Do we know the day to day variation of the measurement (variation that would exists if the treatment was the same)>
Did they base conclusions of responders and non responders on repeated measurements or just a single measurement per treatment?
I am sure that there are responders and non-responders in many cases and it makes sense to use the terms. However, the terms are often being used without sufficient evidence.
