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Can People Accurately Estimate the Calories in Food Images? An Optimised Set of Low- and High- Calorie Images from the food-pics database

Horne, Dielle and Palermo, Romina and Neumann, Markus F. and Housley, Regan and Bell, Jason (2019) Can People Accurately Estimate the Calories in Food Images? An Optimised Set of Low- and High- Calorie Images from the food-pics database. Appetite, 139, pp. 189-196. Elsevier. DOI: 10.1016/j.appet.2019.04.017 ISSN 0195-6663

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Official URL: http://dx.doi.org/10.1016/j.appet.2019.04.017

Abstract

Calorie intake plays an important role in maintaining a healthy weight. As such, researchers often use the calorie content of food as a distinction when investigating appetite related brain processes and eating behaviour. This distinction assumes that observers accurately perceive caloric content. However, there is evidence suggesting this is not always the case. The current study examined how accurately observers could estimate the caloric content of food images from the widely used “Food-pics” database. Eight hundred and forty psychology undergraduate students (aged 16–60, 64% female) estimated the caloric value of 178 high and 182 low calorie foods. Calorie content of food from both categories was significantly overestimated. Additionally, 7.7% of low calorie images were misperceived as being high calorie images and 35% of high calorie images were misperceived as being low calorie foods. Neither participants’ gender, nor the recognisability and likability of the food images, influenced calorie estimation. Our findings show that most people are unable to accurately estimate caloric content of most food. Despite this, a selection of food images were judged accurately, and we advocate the use of these in research where it is important to have low- and high-calorie food images. Specifically, we propose an optimised stimulus set of 25 high and 25 low calorie food images that are accurately judged by adult participants. In addition, we provide the open source dataset of our ratings of Food-pics images which, when added to the existing Food-pics attributes, creates an enhanced tool for researchers selecting food stimuli.

Item URL in elib:https://elib.dlr.de/128743/
Document Type:Article
Title:Can People Accurately Estimate the Calories in Food Images? An Optimised Set of Low- and High- Calorie Images from the food-pics database
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Horne, DielleUniversity of Western AustraliaUNSPECIFIED
Palermo, RominaUniversity of Western AustraliaUNSPECIFIED
Neumann, Markus F.German Aerospace Center (DLR), Institute of Aerospace Medicine, Department of Aviation and Space PsychologyUNSPECIFIED
Housley, ReganUniversiy of Western AustraliaUNSPECIFIED
Bell, JasonUniversiy of Western AustraliaUNSPECIFIED
Date:1 August 2019
Journal or Publication Title:Appetite
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:139
DOI :10.1016/j.appet.2019.04.017
Page Range:pp. 189-196
Publisher:Elsevier
ISSN:0195-6663
Status:Published
Keywords:Eating behaviour, caloric, Food-pics, ratings
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Human factors and safety in Aeronautics
Location: Hamburg
Institutes and Institutions:Institute of Aerospace Medicine > Aviation and Space Psychology
Deposited By: Neumann, Markus
Deposited On:12 Sep 2019 09:17
Last Modified:12 Sep 2019 09:17

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