StoryEcho: A Generative Child-as-Actor Storytelling System for Picky-Eating Intervention

Fuente: arXiv
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Autores principales: Zhou, Yanuo, Fang, Jun, Wang, Yuntao, Wang, Yi, Gao, Nan, Liu, Jinlei, Shi, Yuanchun
Formato: Preprint
Publicado: 2026
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author Zhou, Yanuo
Fang, Jun
Wang, Yuntao
Wang, Yi
Gao, Nan
Liu, Jinlei
Shi, Yuanchun
author_facet Zhou, Yanuo
Fang, Jun
Wang, Yuntao
Wang, Yi
Gao, Nan
Liu, Jinlei
Shi, Yuanchun
contents Picky eating in children can undermine dietary diversity and the development of healthy eating habits, while also creating recurring tension in family feeding routines. Prior interventions have explored food-centered designs, enhanced utensils, and mealtime interactive systems, but few position children as active participants in intervention processes that extend beyond single mealtime interactions. To better understand everyday responses to picky eating and child-acceptable intervention mechanisms, we conducted a formative study with caregivers and kindergarten teachers. Based on the resulting design considerations and iterative stakeholder review, we designed StoryEcho, a generative child-as-actor storytelling system for picky eating intervention. StoryEcho engages children outside mealtimes through personalized stories in which the child appears as a persistent story character and later shapes story development through real-world food-related behavior. The system combines non-mealtime story engagement, lightweight post-meal feedback, and behavior-informed story updates to support repeated intervention across everyday family routines. We evaluated StoryEcho in a between-group field study with 11 families of preschool children. Results provide preliminary evidence that StoryEcho can significantly increase children's willingness to approach and try target low-preference foods while reducing parental pressure around feeding. These findings suggest the promise of generative child-as-actor storytelling as a design approach for home-based behavior support that unfolds through recurring family routines.
format Preprint
id arxiv_https___arxiv_org_abs_2604_08114
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle StoryEcho: A Generative Child-as-Actor Storytelling System for Picky-Eating Intervention
Zhou, Yanuo
Fang, Jun
Wang, Yuntao
Wang, Yi
Gao, Nan
Liu, Jinlei
Shi, Yuanchun
Human-Computer Interaction
Picky eating in children can undermine dietary diversity and the development of healthy eating habits, while also creating recurring tension in family feeding routines. Prior interventions have explored food-centered designs, enhanced utensils, and mealtime interactive systems, but few position children as active participants in intervention processes that extend beyond single mealtime interactions. To better understand everyday responses to picky eating and child-acceptable intervention mechanisms, we conducted a formative study with caregivers and kindergarten teachers. Based on the resulting design considerations and iterative stakeholder review, we designed StoryEcho, a generative child-as-actor storytelling system for picky eating intervention. StoryEcho engages children outside mealtimes through personalized stories in which the child appears as a persistent story character and later shapes story development through real-world food-related behavior. The system combines non-mealtime story engagement, lightweight post-meal feedback, and behavior-informed story updates to support repeated intervention across everyday family routines. We evaluated StoryEcho in a between-group field study with 11 families of preschool children. Results provide preliminary evidence that StoryEcho can significantly increase children's willingness to approach and try target low-preference foods while reducing parental pressure around feeding. These findings suggest the promise of generative child-as-actor storytelling as a design approach for home-based behavior support that unfolds through recurring family routines.
title StoryEcho: A Generative Child-as-Actor Storytelling System for Picky-Eating Intervention
topic Human-Computer Interaction
url https://arxiv.org/abs/2604.08114