The problem is not the value 0.05 but researchers cheating with their data. If researchers were honest, by the definition of statistical test 5% of papers shoul

The problem is not the value 0.05 but researchers cheating with their data. If researchers were honest, by the definition of statistical test 5% of papers should turn out to be actually false. If that number is more like 30% it only means that some 25% of researchers were not honest, did selection, sanitized their data, or were guilty of some other form of data dredging/p-hacking. Switching p-value requirement to 0.005 will only mean that these dishonest researchers will now have to spend a bit more time fishing for data that matches their preconceived claim. Statistics will always remain only statistics and it heavily depends on whether people participating have enough discipline to not cheat. With current structure of incentives in science I suspect many will still be tempted (perhaps even subconsciously) to p-hack.