Transparent reporting requires transparent recording, because our current selves are often unreliable narrators of our past conduct. For example, perhaps our past-self tried multiple types of analyses before focusing on the clearest result, but our current-self, returning to these results months later, only remembers the statistically significant findings (‘p-hacking’ and ‘cherry picking’) [5]. Blinded by hindsight, our study could seemingly test a hypothesis that we had not planned to test (HARKing = ‘Hypothesizing After Results are Known’). These and other common biases [2] result in information gaps between our current and former selves. Complete information is then inaccessible to research consumers, making it harder to assess research reliability.
Transparent recording begins by describing a planned study prior to key events (e.g. data collection, exploration, and modelling) in an unalterable and publicly available document [1]. These ‘preregistration’ documents can be made for any type of study and reduce the potential for researcher self-deception while revealing the breadth of primary research before the filter of publication [6]. For example, mandatory registries for planned clinical trials revealed publication bias in drug development research [7]. Beyond controlled experiments, preregistration templates are expanding to include exploratory, descriptive, and theoretical work (e.g. guidance for preregistering modelling studies: https://osf.io/2qbkc/).
The benefits of preregistrations are amplified by ‘registered reports’, a style of publication first trialled in 2013 (a list of participating journals, such as BMC Biology and Conservation Biology, can be found at https://cos.io/rr). Registered reports are accepted on the strength of their study rationale, methods, and planned analyses, freeing researchers from results anxiety. Whereas traditional journal articles are reviewed (and revised) after a study is completed, registered reports are reviewed before and after the results are known (allowing studies to be critiqued and improved before it is too late to fix major flaws). While the delay in data collection might be difficult for researchers expected to generate results quickly (e.g. in many countries, doctoral students are expected to write three or more publishable chapters within 3–6 years), overcoming cultural and institutional barriers to registered reports could drastically reduce publication bias, while improving research quality, at the level of both researchers and publishers.