Attentional control data collection: a resource for efficient data reuse

Publicly available data are required to (1) assess the reproducibility of each individual findings in the literature, and (2) promote the reuse of data for a more efficient use of participants’ time and public resources. Current data-sharing efforts are well suited for the first goal, yet they do no...

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Bibliographic Details
Main Authors: Haaf, Julia M. (Author) , Hoffstadt, Madlen (Author) , Lesche, Sven (Author)
Format: Article (Journal)
Language:English
Published: August 2025
In: Behavior research methods
Year: 2025, Volume: 57, Issue: 8, Pages: 1-14
ISSN:1554-3528
DOI:10.3758/s13428-025-02717-z
Online Access:Verlag, kostenfrei, Volltext: https://doi.org/10.3758/s13428-025-02717-z
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Author Notes:Julia M. Haaf, Madlen Hoffstadt, Sven Lesche
Description
Summary:Publicly available data are required to (1) assess the reproducibility of each individual findings in the literature, and (2) promote the reuse of data for a more efficient use of participants’ time and public resources. Current data-sharing efforts are well suited for the first goal, yet they do not sufficiently address the second goal. Here, we show how structured collections of open data can be useful, as they allow a larger community of researchers easy access to a large body of data from their own research area. We introduce the Attentional Control Data Collection, a SQL database for attentional control experiments. We illustrate the structure of the database, how it can be easily accessed using a Shiny app and an R-package, and how researchers can contribute data from their studies to the database. Finally, we conduct our own initial analysis of the 64 data sets in our database, assessing the reliability of individual differences. The analysis highlights that reliability is generally low, and provides insights into planning future studies. For example, researchers should consider increasing the number of trials per person and condition to at least 400. The analysis highlights how an open database like ACDC can aid meta-analytic efforts as well as methodological innovation.
Item Description:Online veröffentlicht: 24. Juni 2025
Gesehen am 03.11.2025
Physical Description:Online Resource
ISSN:1554-3528
DOI:10.3758/s13428-025-02717-z