Personality traits affect the influences of intensity perception and emotional responses on hedonic rating and preference rank toward basic taste solutions

Shilpa S Samant

Han-Seok Seo

Abstract: This study aimed at determining, based on independent predictors of taste intensity and emotional response, whether individual personality traits could affect prediction models of overall liking and preference rank toward basic taste solutions. Sixty-seven participants rated taste intensities (TI) of four basic-taste solutions at both low and high concentrations, and of plain water. Emotional responses toward each sample were measured using a self-reported emotion questionnaire (SE), facial expressions (FE), and/or autonomic nervous system responses (ANS). Participants rated overall liking of the samples and ranked their preferences. Based on the results of a hierarchical cluster analysis of five personality traits measured using the Big Five Inventory, participants were classified into two clusters: cluster N (high neuroticism) and cluster E (high extraversion). Results showed that the SE measure for both clusters N and E was better than the TI, FE, and ANS measures in explaining variances of overall liking or preference rank. A measurement of effect size found that using FE and/or taste intensity measures, along with self-reported emotion measure, could enhance model predictability of overall liking or preference rank toward taste samples for cluster N, while the contribution to the prediction model for cluster E was minimal. ANS measures showed little contribution to the prediction model of overall liking for either cluster. In conclusion, this study shows that personality traits, in particular traits of extraversion and neuroticism, affect not only optimum measures of emotional responses, but also modulate predicting overall liking and preference rank toward basic taste solutions.

Keywords: emotional response; extraversion; hedonic rating; liking; neuroticism; personality traits; preference; taste intensity.

This publication uses Facial Expression Analysis which is fully integrated into iMotions Lab

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