We define preregistration as a time-stamped, non-modifiable public record of your research protocol and analysis plan. It helps to avoid selective revealing or suppression of results and helps peers in setting up their study.

What is preregistration?

Here we define preregistration as making public your research plan and analysis plan; a time-stamped, non-modifiable public record of detailed research and analysis plans before the data collection starts. As such it is a publicly available building block in a wider system that helps counteract suppression (or selective revealing) of results and publication bias .

Why is preregistration important?

Pre-registration is no cure-all. There is excellent research that has not been preregistered and some preregistered research is quite poor. Nevertheless, we believe that with correct use, timely preregistration in the public domain will help making the total scientific record more reliable. It counteracts suppression (or selective revealing) of results and publication bias . It thus helps provide an unbiased public record of all research findings worldwide. Preregistration also prevents data dredging and finally, you provide examples for others who need to write a protocol or analysis plan.

First, preregistration creates a strong incentive to carefully write your protocol and analysis plan. It also serves as proof (DOI, trial registration number) to editors, reviewers and others that you stuck to your (last amended and time-stamped) protocol/plan. Second, it creates a stronger incentive to do as you promised and to stick to your protocol/plan. Third, preregistration can prove priority of ideas , which still is important to many scholars. Fourth, preregistration increases your readers’ confidence that you are reporting honestly. Fifth, you contribute to the reliability of systematic reviews in which your research may end up.

First, if you make your plans public, others may see what you are planning and scoop you (i.e. copy the idea and publish (results) before you). Second, preregistration is like voluntarily tying your hands and restricts your flexibility (during data analysis). Sadly, finding fewer statistically significant results might hurt your research career. Let us put these seemingly strong arguments into perspective. First, only seldom will you have truly unique plans. Ideas are in the air most of the time and colleagues are working on very similar stuff. Second, we already explained that voluntarily reducing your data-analytic flexibility is not a bad thing (you gain time and there is less opportunity for data-dredging). Finally, the focus on statistically significant findings is a very poor focus. If you want to understand more about the misinterpretations of p-values and the behaviors that it brings about read what the American Statistical Association had to say on this.

What, when and where?

What should you preregister?

  • For quantitative research: preregister a research protocol and the plan for data analysis (SAP).
  • For qualitative research: preregister the research plan including the design.

When should you preregister?

  • Preregister before data collection starts. Do it after you have obtained ethics approval by an ethics committee to incorporate any changes that such assessments may bring about.

Where should you preregister?

  • If your research is a trial or falls under the Dutch law (WMO) and needs a Trial Registration Number (TRN), then you should preregister in the Netherlands Trial Register (NTR). Mind you, NTR does not allow registering retrospectively.

  • In all other cases, we advise preregistering in UvA/HvA figshare .
  • If you really dislike using UvA/HvA figshare for preregistration, consider using the Open Science Framework (OSF). Here are examples of preregistrations on OSF.

Alternatives to preregistration via NTR, UvA/HvA figshare or OSF?

You may submit your protocol/plan to

  • an Open Access journal as a formal publication (amendments cannot easily be made, but this approach can be combined with the use of UvA/HvA figshare)
  • a preprint server such as medRχiv . Here you can check if your target journal will accept your manuscript after it has been out on a preprint server.
  • a journal accepting registered reports .
  • a journal that is between a preprint server and a traditional journal, such as F1000 .
Published by  Urban Vitality 11 November 2021