ArticlePsychological methods2025
Error tight: Exercises for lab groups to prevent research mistakes.
Article in Psychological methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Building Open Science into Graduate Training in Clinical Psychology.Clinical psychological science : a journal of the Association for Psychological Science · 2026Article
- Opening the black box of article retractions: exploring the causes and consequences of data management errors.Royal Society open science · 2024Article
- mmodel: A workflow framework to accelerate the development of experimental simulations.The Journal of chemical physics · 2023Article
- Reproducibility in Small-Journal of speech, language, and hearing research : JSLHR · 2023Article
- Evaluating the effects of a programming error on a virtual environment measure of spatial navigation behavior.Journal of experimental psychology. Learning, memory, and cognition · 2023Article
- The art and science of using quality control to understand and improve fMRI data.Frontiers in neuroscience · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
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. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.