Reference data for Bayesian adaptive QUEST-based taste recognition thresholds from pooled individual participant data

Reliable and standardized assessment of human taste function remains a critical need in clinical and research settings. Here, we pooled individual participants' data of gustatory recognition thresholds from 6 studies (N > 500) that employed a unified methodology combining taste sprays with an adaptive Bayesian algorithm (QUEST) across 4 basic tastes: sweet, salty, sour, and bitter. Thresholds were estimated using a yes-no task format and psychometrically controlled stimuli, enabling efficient and precise estimation across individuals. Results revealed approximately normal distributions of thresholds within each modality, spanning 2 to 3 log units, and modest but consistent correlations between tastes. Gender and age influenced sensitivity, with women generally showing lower (better) thresholds than men, and older adults exhibiting reduced sensitivity, particularly for bitter and sweet tastes. A composite taste score derived from z-standardized thresholds showed stronger age- and gender-related effects than individual modalities, supporting its utility as a general index of taste function. These findings validate the use of the QUEST algorithm for gustatory psychophysics and provide preliminary normative data for taste sensitivity using time-efficient procedures. The consistency of results across studies supports the development of standardized protocols for clinical and population-level taste testing. Future research should extend this framework to broader populations and additional taste qualities to establish comprehensive benchmarks for gustatory health.