Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-10T11:46:30.116Z Has data issue: false hasContentIssue false

Negative affect, affect regulation, and food choice: A value-based decision-making analysis

Published online by Cambridge University Press:  13 August 2021

D. O’Leary
Affiliation:
Department Of Psychology, University of Chicago Booth School of Business, Chicago, United States of America
A. Brytek-Matera*
Affiliation:
Katowice Faculty Of Psychology, SWPS University of Social Sciences and Humanities, Katowice, Poland
J. Gross
Affiliation:
Department Of Psychology, Stanford University, Stanford, United States of America
*
*Corresponding author.

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Introduction

Research has shown that negative affect leads to unhealthy eating, the top cause of death in the United States.

Objectives

This project examined whether AR (Affect Regulation) can be applied to incidental negative affect to improve eating behavior.

Methods

We conducted four studies.

Results

In Studies 1 and 2 (n=80), we developed a autobiographical negative affect induction, showed that it induces negative affect, and demonstrated that participants can learn to downregulate this negative affect. In Study 3 (n=40), participants completed a three-phase dietary food choice task. In phase 1, participants made food choices under neutral conditions. In phase 2, participants made food choices after receiving the negative affect induction from Studies 1 and 2. In phase 3, participants made food choices while downregulating the negative affect caused by the induction. In phase 2, participants placed less importance on health (b=-0.15, z=-5.99, p<.001) when making food choices than under neutral conditions (phase 1). In phase 3, participants successfully downregulated their negative affect (b=-1.2, t=-22.01, p<.001) and placed the same level of importance on health when making food choices as in phase 1, indicating that AR applied to incidental affect is an effective method for improving eating behavior. In Study 4 (n=120), we pre-registered and replicated our findings from Study 3. In addition, we fit drift-diffusion models to participants reaction time data and show that these results extent to the by-participant weights participants place on health when making food choices.

Conclusions

These results are a step towards scalable AR interventions to improve eating behavior.

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
Submit a response

Comments

No Comments have been published for this article.