When words collide: Bayesian meta-analyses of distractor and target properties in the picture-word interference paradigm
Audrey B\"urki, F.-Xavier Alario, Shravan Vasishth

TL;DR
This study uses Bayesian meta-analyses on 35 datasets to quantify how distractor and target word properties, like frequency and length, influence picture naming times in the picture-word interference paradigm.
Contribution
It provides precise estimates of distractor frequency effects and reveals interactions with target word frequency, advancing understanding of lexical processing in visual tasks.
Findings
A one-unit increase in distractor log frequency decreases response time by about 4ms.
Distractor length and orthographic neighborhood also influence naming times.
The effect of distractor frequency diminishes as target word frequency increases.
Abstract
In the picture-word interference paradigm, participants name pictures while ignoring a written or spoken distractor word. Naming times to the pictures are slowed down by the presence of the distractor word. Various properties of the distractor modulate this slow down, for example naming times are shorter with frequent vs. infrequent distractors. Building on this line of research, the present study investigates in more detail the impact of distractor and target word properties on picture naming times. We report the results of several Bayesian meta-analyses, based on 35 datasets. The aim of the first analysis was to obtain an estimation of the size of the distractor frequency effect, and of its precision, in typical picture-word interference experiments where this variable is not manipulated. The analysis shows that a one-unit increase in log frequency results in response times to the…
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