The use of crowdsourcing for dietary self-monitoring: crowdsourced ratings of food pictures are comparable to ratings by trained observers

Objective Crowdsourcing dietary ratings for food photographs, which uses the input of several users to provide feedback, has potential to assist with dietary self-monitoring. Materials and methods This study assessed how closely crowdsourced ratings of foods and beverages contained in 450 pictures f...

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Bibliographic Details
Published in:Journal of the American Medical Informatics Association : JAMIA 2015-04, Vol.22 (e1), p.e112-e119
Main Authors: Turner-McGrievy, Gabrielle M, Helander, Elina E, Kaipainen, Kirsikka, Perez-Macias, Jose Maria, Korhonen, Ilkka
Format: Article
Language:English
Subjects:
Beverages
Crowdsourcing
Diet
Food
Humans
Linear Models
Mobile Applications
Photography
Self Care
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Summary:Objective Crowdsourcing dietary ratings for food photographs, which uses the input of several users to provide feedback, has potential to assist with dietary self-monitoring. Materials and methods This study assessed how closely crowdsourced ratings of foods and beverages contained in 450 pictures from the Eatery mobile app as rated by peer users (fellow Eatery app users) (n = 5006 peers, mean 18.4 peer ratings/photo) using a simple ‘healthiness’ scale were related to the ratings of the same pictures by trained observers (raters). In addition, the foods and beverages present in each picture were categorized and the impact on the peer rating scale by food/beverage category was examined. Raters were trained to provide a ‘healthiness’ score using criteria from the 2010 US Dietary Guidelines. Results The average of all three raters’ scores was highly correlated with the peer healthiness score for all photos (r = 0.88, p
ISSN:1067-5027
1527-974X
DOI:10.1136/amiajnl-2014-002636