p-hacking consists of the exhaustive exploitation of data through the use of different analytical models and/or the manipulation of the application criteria of these models until statistically significant results are obtained.

p-hacking can be described in a simpler manner has the art of torturing data until they confess something.

While publication bias removes from the scientific literature true or false negatives the p-hacking brings to the scientific literature true or false positives.

Conditioned scientific literature (i.e. the absence of false negatives and the presence of false positives) will bias the results of secondary studies aiming to synthesise scientific evidence, such as meta-analyses, that inform clinical guidelines and evidence-based decision making.

Here, I present a call for health ethics committees to assess the manifestation of researchers’ analytical intent in research protocols (i.e. pre-specified or exploratory) as a way to help prevent and further study the p-hacking bias.

p-Hacking – A call for ethics | PDF. Available from: