MAMAS: Supporting Parent - Child Mealtime Interactions Using Automated Tracking and Speech Recognition

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Many parents of young children find it challenging to deal with their children's eating problems, and parent - child mealtime interaction is fundamental in forming children's healthy eating habits. In this paper, we present the results of a three-week study through which we deployed a mealtime assistant application, MAMAS, for monitoring parent - child mealtime conversation and food intake with 15 parent - child pairs. Our findings indicate that the use of MAMAS helped 1) increase children's autonomy during mealtime, 2) enhance parents' self-awareness of their words and behaviors, 3) promote the parent - child relationship, and 4) positively influence the mealtime experiences of the entire family. The study also revealed some challenges in eating behavior interventions due to the complex dynamics of childhood eating problems. Based on the findings, we discuss how a mealtime assistant application can be better designed for parents and children with challenging eating behaviors.
Publisher
Association for Computing Machineryacmhelp
Issue Date
2020-05
Language
English
Article Type
Article
Citation

Proceedings of the ACM on Human-Computer Interaction, v.4, no.CSCW1

ISSN
2573-0142
DOI
10.1145/3392876
URI
http://hdl.handle.net/10203/287032
Appears in Collection
ID-Journal Papers(저널논문)
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