4.2 Article

MEASURING CHILDREN'S FOOD PREFERENCES: USING PICTURES IN A COMPUTERIZED CONJOINT ANALYSIS

Journal

JOURNAL OF SENSORY STUDIES
Volume 27, Issue 4, Pages 264-276

Publisher

WILEY
DOI: 10.1111/j.1745-459X.2012.00391.x

Keywords

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Funding

  1. Danish Agency for Science, Technology and Innovation [3304-FSE-06-0504]

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The aim of this study is to investigate if children's food preferences can be reliable measured by using pictures of foods presented on a computer screen in a conjoint layout. We investigate reproducibility (testretest) and infer validity by comparison with traditional hedonic evaluations of tangible products and a choice test. In total, 300 children from schools in Copenhagen participated in the study. Two product cases were included: 32 buns and 8 juices. Pictures of the products were presented and evaluated on a computer screen using a conjoint layout. Right after the test, four buns and two juices (tangible products), chosen to span the preference spectrum, were hedonically evaluated for appearance and taste. Finally, an actual product choice was performed by having the children choose between two buns and two juices. Results showed that the computer evaluations with pictures of foods provided reproducible information about the children's visual food preferences, which were in concordance with both hedonic measures and products choices, and can thus be considered valid. PRACTICAL APPLICATIONS The paper describes a new combination of methods for measuring food preferences in children using pictures of foods manipulated on visually apparent product attributes in a computerized conjoint layout. Results were reproducible, and products choices performed in the picture-based computer program were in concordance with hedonic evaluations of appearance and taste, as well as actual product choices of tangible products. Thus, using pictures in a computerized conjoint analysis facilitates fast and reliable measurement of food preferences in children and enables direct evaluation of the impact of individual product attributes. The method is easy and inexpensive to use, requires little time and effort from participants, is suitable for online testing and can quickly be applied to high numbers of participants.

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