That's not what negative means here. For these studies the conclusion is a statistical test -- accept or reject the null hypothesis. If a drug doesn't give resu

That's not what negative means here. For these studies the conclusion is a statistical test -- accept or reject the null hypothesis. If a drug doesn't give results significantly different from a placebo, that's "negative". More to the point, when a researcher collects a pile of data, does some analysis, and can't see a damn thing either way, then either the experiment was flawed to begin with, or that absence of meaning is a real, useful result. Maybe the sample size just wasn't large enough to show a small but significant trend. It takes a fair amount of confidence in one's skills to rule out the first possibility and announce loudly that there's nothing to be seen further down the path you took.