Abstract
China Northeast Forestry University Emerging research indicates that chatbot-human interaction may psychologically heal adolescents, yet the ongoing healing processes and mechanisms remain under explored. This study investigates how healing effects evolve in sustained chatbot use and how interaction design can enhance outcomes for adolescents. Using the “Mood Talker” chatbot, an AI chatbot system featuring a consistent anthropomorphic character, we recruited 12 adolescents to conduct semi-structured interviews. Guided by social penetration theory, and thematic analysis revealed a stage-dependent model of healing impacts and interaction frequency patterns, informing design strategies to mitigate negative effects. This study advances understanding of digital companionship and provides practical insights for developing secure, supportive AItoolsforadolescentmentalhealth.
Keywords
Chatbot; Human-Computer Interaction; Healing; Adolescents; Mental Health
DOI
https://doi.org/10.21606/iasdr.2025.272
Citation
Yu, J.(2025) AI as a Healing Companion: Exploring Chatbot Design Strategies for in Nurturing Adolescent Emotional Well-Being, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.272
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 4 - Human-Centered AI
AI as a Healing Companion: Exploring Chatbot Design Strategies for in Nurturing Adolescent Emotional Well-Being
China Northeast Forestry University Emerging research indicates that chatbot-human interaction may psychologically heal adolescents, yet the ongoing healing processes and mechanisms remain under explored. This study investigates how healing effects evolve in sustained chatbot use and how interaction design can enhance outcomes for adolescents. Using the “Mood Talker” chatbot, an AI chatbot system featuring a consistent anthropomorphic character, we recruited 12 adolescents to conduct semi-structured interviews. Guided by social penetration theory, and thematic analysis revealed a stage-dependent model of healing impacts and interaction frequency patterns, informing design strategies to mitigate negative effects. This study advances understanding of digital companionship and provides practical insights for developing secure, supportive AItoolsforadolescentmentalhealth.