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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 und Palermo, Romina und Neumann, Markus F. und Housley, Regan und 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, Seiten 189-196. Elsevier. doi: 10.1016/j.appet.2019.04.017. ISSN 0195-6663.

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

Kurzfassung

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.

elib-URL des Eintrags:https://elib.dlr.de/128743/
Dokumentart:Zeitschriftenbeitrag
Titel:Can People Accurately Estimate the Calories in Food Images? An Optimised Set of Low- and High- Calorie Images from the food-pics database
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Horne, DielleUniversity of Western AustraliaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Palermo, RominaUniversity of Western AustraliaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Neumann, Markus F.German Aerospace Center (DLR), Institute of Aerospace Medicine, Department of Aviation and Space PsychologyNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Housley, ReganUniversiy of Western AustraliaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Bell, JasonUniversiy of Western AustraliaNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Datum:1 August 2019
Erschienen in:Appetite
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Ja
Band:139
DOI:10.1016/j.appet.2019.04.017
Seitenbereich:Seiten 189-196
Verlag:Elsevier
ISSN:0195-6663
Status:veröffentlicht
Stichwörter:Eating behaviour, caloric, Food-pics, ratings
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Luftfahrt
HGF - Programmthema:Luftverkehrsmanagement und Flugbetrieb
DLR - Schwerpunkt:Luftfahrt
DLR - Forschungsgebiet:L AO - Air Traffic Management and Operation
DLR - Teilgebiet (Projekt, Vorhaben):L - Faktor Mensch und Sicherheit in der Luftfahrt (alt)
Standort: Hamburg
Institute & Einrichtungen:Institut für Luft- und Raumfahrtmedizin > Luft- und Raumfahrtpsychologie
Hinterlegt von: Neumann, Markus
Hinterlegt am:12 Sep 2019 09:17
Letzte Änderung:12 Sep 2019 09:17

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