Training to be a scientist includes the ability to figure out which science articles might not have enough results to back-up its claim. It also includes the ability to identify if there are any results that could have been affected by bias. Being able to figure out if something might not be reliable is important because it might protect you from being steered in the wrong direction.
This might be a frightening fact but it has been reported that 80% of Chinese clinical trials have been fabricated in some way (Fiona Macdonald). These are clinical trials, not scientific discoveries! This means that these are the studies that may eventually result in a drug approval and be used for a particular condition. I am shocked that the values are so incredibly high on irreproducible/fabricated clinical data in China. The Chinese State Food and Drug Administration (SFDA) reported that results were written before the clinical trials took place, statistical data was designed to look significant, and/or data was completely left out (to make positive results look consistent). Fabrication is a form of bias because it is in the self interest of the researcher to publish and gain recognition. But why do these individuals not get exposed if the fabrication is so obvious?
Reviewers in China seem to be more passive with “Sketchy” science and it is their responsibility to change the vicious cycle of publishing fraudulent or bad science. Jeremy Berg emphasized the importance of catching clear flaws and making sure enough information is included to allow experimental replication. Reviewers and editors of manuscripts should always have the highest expectations for the journals they wish to publish. The everyday person should be concerned about the amount of fraud, malpractice, fabrication. The government uses tax money to fund research and billions are lost each year to fraudulent research. An article from Jocelyn Kaiser stated that $28 billion a year (in the US) is spent on irreproducible biomedical research. People are more likely to follow rules that are strictly enforced and this includes rules about methods described in journal articles.