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

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.

Keywords: Amazon Mechanical Turk; JavaScript; Online experiments; Open-source; Qualtrics.

Fig. 1

(a) Screenshot of what the embedded data overview should look like for the Stroop reaction time (RT) task. (b) Screenshot of the Loop & Merge list. In the Stroop RT task, 96 trials will be displayed, and four columns are needed to define the variable content for each trial. (c) Screenshot of the question block along with the JavaScript for each question. Each question represents a screen in the task. (d) Schematic overview of a trial in the Stroop RT task

Fig. 2

Mean reaction time (RT) and error rate for each condition in the Stroop task

Fig. 3

Mean Target 2 (T2) proportions correct as a function of T1–T2 lag

Fig. 4

Mean reaction times (RTs) and error rates for each condition in the masked-priming task. Note the typical reversal of the compatibility effect for the shorter prime durations