Good catch on the journal name.

If the purpose of the study is to see whether X has a statistically significant effect on Y, you can't just up the sample until your p-value reaches an acceptable level. This is p-hacking taken to the extreme, and the authors nonchalantly admit to it.

If your data has substantial variability, then it should be hard to obtain statistical significance. That's the whole point. If you want to claim there's a large effect size, that's fine. If you want to claim hypothesis testing is unnecessary and that you're just providing summary statistics, that's more or less fine. But you can't have your cake and eat it too by doing hypothesis testing and then explicitly changing the parameters of the study until you get the desired result. Or at least you shouldn't admit to doing it.