Abstract

When assessing the perceptual abilities of children, researchers tend to use psychophysical techniques designed for use with adults. However, children’s poorer attentiveness might bias the threshold estimates obtained by these methods. Here, we obtained speed discrimination threshold estimates in 6- to 7-year-old children in UK Key Stage 1 (KS1), 7- to 9-year-old children in Key Stage 2 (KS2), and adults using three psychophysical procedures: QUEST, a 1-up 2-down Levitt staircase, and Method of Constant Stimuli (MCS). We estimated inattentiveness using responses to “easy” catch trials. As expected, children had higher threshold estimates and made more errors on catch trials than adults. Lower threshold estimates were obtained from psychometric functions fit to the data in the QUEST condition than the MCS and Levitt staircases, and the threshold estimates obtained when fitting a psychometric function to the QUEST data were also lower than when using the QUEST mode. This suggests that threshold estimates cannot be compared directly across methods. Differences between the procedures did not vary significantly with age group. Simulations indicated that inattentiveness biased threshold estimates particularly when threshold estimates were computed as the QUEST mode or the average of staircase reversals. In contrast, thresholds estimated by post-hoc psychometric function fitting were less biased by attentional lapses. Our results suggest that some psychophysical methods are more robust to attentiveness, which has important implications for assessing the perception of children and clinical groups.

Highlights

  • ObjectivesThe aim of the current study was to expand on this work by directly testing the effects of attentional lapses on children’s threshold estimates, using a large dataset combined with computer simulations

  • A common way to characterize the sensitivity of a perceptual system is by measuring its perceptual threshold: the minimum stimulus intensity required to reach a specified level of performance (e.g., 70.7% correct; Green & Swets, 1974)

  • We found a significant difference between estimation methods, F(1,67) = 88.02, p < .001, ηp2 = .57, with the QUEST mode leading to higher threshold estimates (M = 1.75 °/s, 95% CI 1.52–2.00) than those derived from the posthoc fitting of a psychometric function (M = .93 °/s, 95% CI .75– 1.12)

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Summary

Objectives

The aim of the current study was to expand on this work by directly testing the effects of attentional lapses on children’s threshold estimates, using a large dataset combined with computer simulations

Methods
Results
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