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

被引：6

作者：

Jo E. ^{[1
]}

Bang H. ^{[2
]}

Ryu M. ^{[3
]}

Sung E.J. ^{[1
]}

Leem S. ^{[1
]}

Hong H. ^{[1
]}

机构：

[1] Seoul National University, Seoul

[2] Yonsei University, Seoul

[3] Purdue University, West Lafayette

来源：

Proceedings of the ACM on Human-Computer Interaction | 2020年 / 4卷 / CSCW1期

基金：

新加坡国家研究基金会;

关键词：

children; eating behavior; family mealtime; magnetometer; parent - child interaction; semi-automated tracking; speech recognition;

D O I：

10.1145/3392876

中图分类号：

学科分类号：

摘要：

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. © 2020 ACM.

引用

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