Error Tight: Exercises for Lab Groups to Prevent Research Mistakes

Scientists, being human, make mistakes. We transcribe things incorrectly, we make errors in our code, and we intend to do things and then forget. The consequences of errors in research may be as minor as wasted time and annoyance, but may be as severe as losing months of work or having to retract an article. The purpose of this tutorial is to help lab groups identify places in their research workflow where errors may occur and identify ways to avoid them. To do this, this article applies concepts from human factors research on how to create lab cultures and workflows that are intended to minimize errors. This article does not provide a one-size-fits-all set of guidelines for specific practices to use (e.g., one platform on which to backup data); instead, it gives examples of ways that mistakes can occur in research along with recommendations for systems that avoid and detect them. This tutorial is intended to be used as a discussion prompt prior to a lab meeting to help researchers reflect on their own processes and implement safeguards to avoid future errors.Translational Abstract Everyone makes mistakes. In science, mistakes can occur in many ways: Researchers may transcribe things incorrectly, make typos when writing code to analyze data, forget to do something they intended to, and so forth. These mistakes may simply waste time or require redoing work, but in more serious cases, they can ruin an experiment or lead to false conclusions. However, learning how to avoid errors in research isn't a standard part of training. This tutorial is intended to help lab groups identify places in the research process where errors may occur and identify ways to avoid them. To do so, this article draws on lessons from high-risk fields such as aviation, surgery, and construction, all of which have developed explicit, practical strategies to reduce mistakes on the job. This tutorial is intended to be used as a discussion prompt before a lab meeting to help researchers reflect on their own processes and implement safeguards to avoid future errors.