What is not discussed is that in science as in life it's all about incentives. All you have to is look at who is paying for these studies, directly (through research grants) or indirectly (speaking or consulting fees), and things will become much clearer. The biomedical and life sciences are most vulnerable to corruption because the incentives are very high, successful drug/treatments are worth a lot of money. Even unsuccessful ones, given the proper appearance of effectiveness are worth money.
Other sciences are less susceptible because there is no incentive to hype the results, not because those scientists are more ethical. There is two solutions for the problem. One is to remove incentives, which would mean overhauling the whole system of scientific funding. The other is to mandate raw data sharing. This would make it easier for people to reanalyze the data without actually redoing the experimental parts.
A good example of this is Reinhart-Rogoff controversy in economics, where they claimed one thing in their widely publicized 2010 paper (high debt levels impede growth), but their statistical analysis was shown to be riddled with errors, skewing the data to the desired conclusion. This was discovered the when they shared their raw data with a University of Massachusetts grad student.
While data sharing would not eliminate these issues it would make is harder to perform "statistical" analysis that introduces biases.