"We tried to prove this hypothesis wrong and could not" is the main thing you want a study to do. Having everyone try to prove your hypothesis wrong, and failing, is the main way that science advances.
The first step is Observation. Sometimes split out into Observation, then Research.
Then comes the formulation of a hypothesis.
After that is constructing a way to test the hypothesis. Not to prove it wrong, not to prove it right, but to test it.
There's more after that, it's an iterative process and a single test of a hypothesis isn't always definitive, often it is not. But "Prove me wrong" is not the starting point.
You accomplish very little trying to prove a hypothesis wrong, because most are.
The p-value of a scientific study is the probability that the given data would have been observed, given that there is no effect. Hence why small p-values can be associated with the success of the alternative hypothesis (i.e. what a scientist actually thinks will happen).
You can't prove an hypothesis is correct. All models are temporal until they are disprove.
But is it correct? To find out, we need to try to invalidate it. Try opening the can without tapping it first. If the Coke doesn't spill, the hypothesis is clearly wrong. It the Coke does spill now, it's quite strong evidence in favor of the hypothesis.