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How far in the future can we predict others’ affective states?

Published online by Cambridge University Press:  13 August 2021

E. Cappello*
Affiliation:
Momilab - Sane Group, IMT School for Advances Studies Lucca, Lucca, Italy
G. Lettieri
Affiliation:
Momilab - Sane Group, IMT School for Advanced Studies Lucca, Lucca, Italy
G. Handjaras
Affiliation:
Momilab - Sane Group, IMT School for Advanced Studies Lucca, Lucca, Italy
E. Ricciardi
Affiliation:
Momilab, IMT School for Advanced Studies, Lucca, Italy
P. Pietrini
Affiliation:
Momilab, IMT School for Advanced Studies, Lucca, Italy
L. Cecchetti
Affiliation:
Momilab - Sane Group, IMT School for Advanced Studies Lucca, Lucca, Italy
*
*Corresponding author.

Abstract

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Introduction

Human social interactions are rooted in the ability to understand and predict one’s own and others emotions. Individuals develop accurate mental models of emotional transitions (MMET) by observing regularities in affective experiences (DOI: 10.1073/pnas.1616056114) and a failure in this regard can produce maladaptive behaviors, one of the hallmark features in several psychiatric conditions.

Objectives

To investigate whether MMET are stable over time and which emotion dimensions (e.g., valence, dominance) influence MMET over time.

Methods

We selected thirty-seven emotion categories (DOI: 10.1177/0539018405058216) and five different time intervals (from 15 minutes to 4 days). Sixty-two healthy participants rated the likelihood of transition between all possible pairs of affective states at each time interval.

Results

As expected, we observed a trend toward uncertainty as the timescale increased. In addition, the probability of shifting between two affective states having the same valence (e.g., happiness and contentment) was rated higher than for emotions with opposite polarity (e.g., happiness and sadness). Even though this pattern becomes gradually noisier for predictions far in the future, it is still present for infradian intervals (Fig.1).

Conclusions

Our results suggest that MMET are informed by the valence dimension and moderately influenced by the timescale of the prediction. These findings in the healthy population may prompt the exploration of emotion dynamics in psychiatric conditions. Future studies could leverage the MMET approach to test whether specific psychiatric disorders (e.g., bipolar disorder) are associated with abnormal patterns of emotion transitions.

Disclosure

No significant relationships.

Type
Abstract
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the European Psychiatric Association
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