Or do you just like to post meaningless studies and regurgitate theory as if that would make your point valid.
Touche...
The study states: fatigue and perceived effort during exercise were compared in
untrained, overweight adults adhering to a ketogenic low-carbohydrate diet or to a control diet low in carbohydrate, but not ketogenic (5%, 65%, and 30% or 40%, 30%, and 30% of energy from carbohydrate, fat, and protein, respectively).
It was a 2 week study!!! Seriously...2 weeks for obese untrained adults to adapt to a ketogenic diet? It is well known that 1-2 weeks is what it takes for people to switch over. All people who go ketogenic face the keto flu symptoms but if thye stick with it through adaptation all those symptoms go away. So SURPRISE..keto test subjects were tired and in bad moods during the whole 2 weeks of the study.
Obese people on restricted calorie diet means BOTH groups will be fatigued. Study never said control group was not fatigued.
That alone before i looked at the data showed the study was shit.
lets look at the summary of the data:
correlated significantly with perceived exercise effort (r2=0.22, P=0.049). Blood beta-hydroxybutyrate was also significantly correlated to feelings of "fatigue" (r=0.458, P=0.049) and to "total mood disturbance" (r=0.551, P=0.015) while exercising.
R-squared score of .22? R-scores of .45 to .55? If you studied statistics, these figures prove low to moderate correlation. If I got an R-squared score of .22 on a correlation/regression analysis I would throw it in the trash.
Despite the P-scores, the conclusions cannot be fully supported by the data in any statistical analysis. In fact I could just as easily explain the results by the fact that you took untrained obese adults and subjected them to 2 weeks of calorie restrictions and exercise, and some of them you told them no carbs.
This is my point, do not just cite a study, dig in to it to see the methodology and the statistical data to check for significance or proper development of a conclusion from the data.
Just because it is a university or someone with a ph.d, don't assume the methodology is accurate or the hypothesis and conclusions are supported by the data.