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QRTEngine: An easy solution for running online reaction time experiments using Qualtrics

Overview of attention for article published in Behavior Research Methods, November 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
7 X users
peer_reviews
1 peer review site
facebook
2 Facebook pages
wikipedia
1 Wikipedia page

Citations

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119 Dimensions

Readers on

mendeley
256 Mendeley
Title
QRTEngine: An easy solution for running online reaction time experiments using Qualtrics
Published in
Behavior Research Methods, November 2014
DOI 10.3758/s13428-014-0530-7
Pubmed ID
Authors

Jonathan S. Barnhoorn, Erwin Haasnoot, Bruno R. Bocanegra, Henk van Steenbergen

Abstract

Performing online behavioral research is gaining increased popularity among researchers in psychological and cognitive science. However, the currently available methods for conducting online reaction time experiments are often complicated and typically require advanced technical skills. In this article, we introduce the Qualtrics Reaction Time Engine (QRTEngine), an open-source JavaScript engine that can be embedded in the online survey development environment Qualtrics. The QRTEngine can be used to easily develop browser-based online reaction time experiments with accurate timing within current browser capabilities, and it requires only minimal programming skills. After introducing the QRTEngine, we briefly discuss how to create and distribute a Stroop task. Next, we describe a study in which we investigated the timing accuracy of the engine under different processor loads using external chronometry. Finally, we show that the QRTEngine can be used to reproduce classic behavioral effects in three reaction time paradigms: a Stroop task, an attentional blink task, and a masked-priming task. These findings demonstrate that QRTEngine can be used as a tool for conducting online behavioral research even when this requires accurate stimulus presentation times.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 256 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 3%
Netherlands 2 <1%
United Kingdom 2 <1%
Chile 1 <1%
Germany 1 <1%
Canada 1 <1%
Switzerland 1 <1%
Unknown 241 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 72 28%
Student > Master 36 14%
Researcher 33 13%
Student > Doctoral Student 20 8%
Student > Bachelor 20 8%
Other 48 19%
Unknown 27 11%
Readers by discipline Count As %
Psychology 127 50%
Business, Management and Accounting 20 8%
Social Sciences 18 7%
Medicine and Dentistry 9 4%
Linguistics 8 3%
Other 35 14%
Unknown 39 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 April 2021.
All research outputs
#4,102,507
of 25,373,627 outputs
Outputs from Behavior Research Methods
#490
of 2,525 outputs
Outputs of similar age
#54,351
of 369,967 outputs
Outputs of similar age from Behavior Research Methods
#5
of 27 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,525 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done well, scoring higher than 80% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 369,967 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.