title: Tests of the accuracy and speed of categorizing foods into child vs professional categories using two methods of browsing with children.
abstract: This research tested whether children could categorize foods more accurately and speedily when presented with child-generated rather than professionally generated food categories, and whether a graphically appealing browse procedure similar to the Apple iTunes (Cupertino, CA) "cover flow" graphical user interface accomplished this better than the more common tree-view structure. In Fall 2008, 104 multiethnic children ages 8 to 13 were recruited at the Baylor College of Medicine (Houston, TX) and randomly assigned to two browse procedures: cover flow (collages of foods in a category) or tree view (food categories in a list). Within each browse condition children categorized the same randomly ordered 26 diverse foods to both child and professionally organized categories (with method randomly sequenced per child). Acceptance of categorization was determined by registered dietitians. Speed of categorization was recorded by the computer. Differences between methods were determined by repeated measures analysis of variance. Younger children (8 to 9 years old) tended to have lower acceptance and longer speeds of categorization. The quickest categorization was obtained with child categories in a tree structure. Computerized dietary reporting by children can use child-generated food categories and tree structures to organize foods for browsing in a hierarchically organized structure to enhance speed of categorization, but not accuracy. A computerized recall may not be appropriate for children 9 years of age or younger.
authors.affiliation: US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center, Houston, TX 77030-2600, USA. tbaranow@bcm.tmc.edu
authors.forename: Tom
authors.initials: T
authors.lastname: Baranowski
authors.forename: Alicia
authors.initials: A
authors.lastname: Beltran
authors.forename: Shelby
authors.initials: S
authors.lastname: Martin
authors.forename: Kathleen B
authors.initials: KB
authors.lastname: Watson
authors.forename: Noemi
authors.initials: N
authors.lastname: Islam
authors.forename: Shay
authors.initials: S
authors.lastname: Robertson
authors.forename: Stephanie
authors.initials: S
authors.lastname: Berno
authors.forename: Hafza
authors.initials: H
authors.lastname: Dadabhoy
authors.forename: Debbe
authors.initials: D
authors.lastname: Thompson
authors.forename: Karen
authors.initials: K
authors.lastname: Cullen
authors.forename: Richard
authors.initials: R
authors.lastname: Buday
authors.forename: Amy F
authors.initials: AF
authors.lastname: Subar
authors.forename: Janice
authors.initials: J
authors.lastname: Baranowski
mesh_terms: D000293:Adolescent; D017677:Age Distribution; D000704:Analysis of Variance; D002648:Child; D034201:Computers, Handheld; D005260:Female; D005502:Food / Q000145:classification*; D006801:Humans; D008297:Male; D011939:Mental Recall; D015596:Nutrition Assessment; D002666:Psychology, Child; D015203:Reproducibility of Results; D013997:Time Factors