Abstract

Taste perception, although vital for nutrient sensing, has long been overlooked in sensory assessments. This can, at least in part, be attributed to challenges associated with the handling of liquid, perishable stimuli, but also with scarce efforts to optimize testing procedures to be more time-efficient. We have previously introduced an adaptive, QUEST-based procedure to measure taste sensitivity thresholds that was quicker than other existing approaches, yet similarly reliable. Despite its advantages, the QUEST procedure lacks experimental control of false alarms (i.e., response bias) and psychometric function slope. Variations of these parameters, however, may also influence the threshold estimate. This raises the question as to whether a procedure that simultaneously assesses threshold, false-alarm rate, and slope might be able to produce threshold estimates with higher repeatability, i.e., smaller variation between repeated measurements. Here, we compared the performance of QUEST with a method that allows measurement of false-alarm rates and slopes, quick Yes–No (qYN), in a test–retest design for citric acid, sodium chloride, quinine hydrochloride, and sucrose recognition thresholds. We used complementary measures of repeatability, namely test–retest correlations and coefficients of repeatability. Both threshold procedures yielded largely overlapping thresholds with good repeatability between measurements. Together the data suggest that participants used a conservative response criterion. Furthermore, we explored the link between taste sensitivity and taste liking or which we found, however, no clear association.

Highlights

  • The ability to taste is undoubtedly crucial for nutrient sensing

  • Using a Bayesian adaptive testing framework [1], we previously showed that taste sensitivity can be precisely and reliably measured in a fraction of the time needed with conventional, non-adaptive methods [2,3]

  • Using two Bayesian procedures, based on QUEST [1] and quick Yes–No (qYN) [8], we explored the impact of false-alarm rate and psychometric function slope estimation on the precision and accuracy of taste sensitivity measurements

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Summary

Introduction

The ability to taste is undoubtedly crucial for nutrient sensing. it is scarcely assessed in large cohorts, and precise and “practical” methods for the measurement of taste sensitivity are needed to get a better understanding of the extent to which taste shapes preferences and eating behavior.The precise and reasonably quick measurement of sensory sensitivity has been a challenge for all senses. Using a Bayesian adaptive testing framework [1], we previously showed that taste sensitivity can be precisely and reliably measured in a fraction of the time needed with conventional, non-adaptive methods [2,3]. Bayesian adaptive methods such as QUEST [1] typically produce estimates of psychometric function parameters more quickly than conventional staircase procedures, especially if the number of possible stimuli is large. This is mainly due to two features specific to Bayesian methods: firstly, they can incorporate prior knowledge by assigning a probability to each individual parameter value; and, Nutrients 2020, 12, 24; doi:10.3390/nu12010024 www.mdpi.com/journal/nutrients

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