Dataset Information

Evoked emotions predict food choice.

ABSTRACT: In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

SUBMITTER: Dalenberg JR

PROVIDER: S-EPMC4270769 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Evoked emotions predict food choice.

Dalenberg Jelle R JR Gutjar Swetlana S Ter Horst Gert J GJ de Graaf Kees K Renken Remco J RJ Jager Gerry G

PloS one 20141218 12

In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well sco ...[more]

PMID: 25521352

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Project description:A central assumption in the behavioral sciences is that choice behavior generalizes enough across individuals that measurements from a sampled group can predict the behavior of the population. Following from this assumption, the unit of behavioral sampling or measurement for most neuroimaging studies is the individual; however, cognitive neuroscience is increasingly acknowledging a dissociation between neural activity that predicts individual behavior and that which predicts the average or aggregate behavior of the population suggesting a greater importance of individual differences than is typically acknowledged. For instance, past work has demonstrated that some, but not all, of the neural activity observed during value-based decision-making is able to predict not just individual subjects' choices but also the success of products on large, online marketplaces-even when those two behavioral outcomes deviate from one another-suggesting that some neural component processes of decision-making generalize to aggregate market responses more readily across individuals than others do. While the bulk of such research has highlighted affect-related neural responses (i.e. in the nucleus accumbens) as a better predictor of group-level behavior than frontal cortical activity associated with the integration of more idiosyncratic choice components, more recent evidence has implicated responses in visual cortical regions as strong predictors of group preference. Taken together, these findings suggest a role of neural responses during early perception in reinforcing choice consistency across individuals and raise fundamental scientific questions about the role sensory systems in value-based decision-making processes. We use a multivariate pattern analysis approach to show that single-trial visually evoked electroencephalographic (EEG) activity can predict individual choice throughout the post-stimulus epoch; however, a nominally sparser set of activity predicts the aggregate behavior of the population. These findings support an account in which a subset of the neural activity underlying individual choice processes can scale to predict behavioral consistency across people, even when the choice behavior of the sample does not match the aggregate behavior of the population.

Project description:In 2020, a single-response-based, valence × arousal circumplex-inspired emotion questionnaire (CEQ) was developed. Using a between-participants design, previous studies have found that a multiple response (MR) condition better discriminated test samples (e.g., written food names) based on their evoked emotions than a single response (SR) condition. This research, comprising Studies 1 and 2, aimed to determine the effect of response conditions (i.e., SR vs. MR) on emotional responses to food image samples, using a within-participants design. In Study 1, 105 Korean participants were asked to select a pair of emotion terms (i.e., SR condition) or select all pairs representing their evoked emotions (i.e., MR condition) from a list of 12 pairs of emotion terms of the CEQ, in response to the 14 food images. Both SR and MR conditions were tested within a remote (online) session. To minimize both a potential carry-over effect of the "within-participants design" and an influence of environmental factors in the remote testing, Study 2 asked 64 U.S. participants to do so over two separated sessions on two different days in a controlled laboratory setting. In both Studies 1 and 2, participants selected the CEQ's emotion-term pairs in the MR condition more frequently than in the SR condition, leading to the MR condition's higher capacity to discriminate test samples. While the configurations of the correspondence analysis biplots drawn in the SR and MR conditions were similar, those in the MR condition were more likely to be similar to the configurations of the principal component analysis biplots drawn from the ratings of valence and arousal for food image samples. In conclusion, this study provides robust empirical evidence that the MR condition can perform better in capturing sample differences in food-evoked emotions, while the SR condition is also effective in characterizing emotional profiles of test samples. Our findings will provide practical insights to sensory professionals, enabling them to effectively leverage the CEQ or its variants when measuring food-evoked emotions.

Dataset Information

Evoked emotions predict food choice.

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Evoked emotions predict food choice.

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