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Tests of the Accuracy and Speed of Categorizing Foods into Child vs Professional Categories Using Two Methods of Browsing with Children

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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.

Section snippets

Design

In an experiment, children (n=104, both sexes, from the Houston, TX area) were randomly assigned to either the tree-view or cover-flow interfaces for displaying the two types of food categories (between-groups factor). All children categorized 26 commonly consumed foods (as determined from National Health and Nutrition Examination Survey data for children this age) twice, once into child- and again into professionally generated categories with the sequence randomly assigned (within-groups

Results and Discussion

The sample (n=104) was split evenly by sex. Nearly one fourth of the sample was black (23%) or Hispanic (29%) and less than one half (43%) was white. The remaining 5% self-identified as “other” race/ethnicity. Nearly one-half (49%) of participants came from homes with an annual household income ≥$70,000 and most participants (70%) were from homes in which a parent/guardian had a college degree. Age groups were reasonably evenly divided with 39%, 30%, and 31% ages 8 and 9 years, 10 to 11 years,

Conclusion

Accuracy of children's food categorization into hierarchically organized groups was not clearly aided by using child-derived categories or a graphically appealing browse procedure (cover flow). Alternatively, speed of categorization was substantially facilitated by child categories and tree-view browse structure. Tree view with child categories appears to be the preferred method of browsing for this computerized diet assessment program. Children younger than 10 years may have more difficulty

T. Baranowski is professor of pediatrics at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

References (11)

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T. Baranowski is professor of pediatrics at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

A. Beltran is research dietitian at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

S. Martin is research dietitian at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

S. Robertson is research dietitian at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

H. Dadabhoy is research dietitian at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

K. B. Watson is an instructor at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

N. Islam is nutritionist II at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

S. Berno is nutritionist II at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

K. Cullen is an associate professor at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

D. Thompson is US Department of Agriculture, Agricultural Research Service scientist/nutritionist and assistant professor of pediatrics, Houston TX.

J. Baranowski is assistant professor at the US Department of Agriculture, Agricultural Research Service, Children's Nutrition Research Center and the Department of Pediatrics, Baylor College of Medicine, Houston TX.

R. Buday is president, Archimage, Inc, Houston TX.

A. F. Subar is research nutritionist, National Cancer Institute, Division of Cancer Control and Population Sciences, Applied Research Program, Risk Factor Monitoring and Methods Branch, Bethesda, MD.

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