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 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.

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Institutions

Publication Details

Journal
Behavior Research Methods
Published
2025-06-24
DOI
https://doi.org/10.3758/s13428-025-02717-z
Citations
2
Primary Topic
Neural and Behavioral Psychology Studies
Type
article
Field-Weighted Citation Impact
2.86

Funders

Controls
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article

Attentional control data collection: A resource for efficient data reuse

Madlen Hoffstadt, Julia M. Haaf, Sven Lesche
2 citations
Behavior Research Methods
Neural and Behavioral Psychology Studies
2.86
article

Attentional control data collection: A resource for efficient data reuse

Madlen Hoffstadt, Julia M. Haaf, Sven Lesche
article en
2 citations

Abstract

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.

Behavior Research MethodsVol. 57(8)
University of Potsdam (DE), Heidelberg University (DE), University of Amsterdam (NL)
Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Amsterdam Brain and Cognition
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Neural and Behavioral Psychology Studies
2.86
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Attentional control data collection: A resource for efficient data reuse — Madlen Hoffstadt, Julia M. Haaf, et al. · Behavior Research Methods (2025) | TGRS Research Map | TGRS