Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth

by Stuart Ritchie

the scientist means well and wants to feel like their research is beneficial. We could even call this the ‘meaning well bias’. It’s crushing when the trial you’ve designed to test your new treatment provides null results, meaning we’re no closer to helping sick people. It’s disheartening when you hypothesise about the link of some biological factor to a disease, and it turns out you’ve been barking up the wrong tree. Or, at least, it might feel that way if you have the wrong attitude to science. The currency of positive, statistically significant results in science is so strong that many researchers forget that null results matter too. To know that a treatment doesn’t work, or that a disease isn’t related to some bio-marker, is useful information: it means we might want to spend our time and money elsewhere in future. If it’s properly designed, a study should be of interest whether it produces positive or null results.