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Therapeutic Twins for Creative Digital Mental Health: A Review Through a Trust-in-Automation Lens

  • Yuhua Zhang
  • , Gailing Yue
  • , Zhengming Si*
  • *Corresponding author for this work
  • Harbin institute of technology
  • Northeast Forestry University

Research output: Contribution to journalReview articlepeer-review

Abstract

This review systematically maps the existing literature on the integration of AI chatbots, therapeutic avatars, and digital art therapy, and examines emerging insights in this area. AI chatbots and avatars have demonstrated potential for delivering mental healthcare at scale, and digital art therapy offers a structured channel for non-verbal expression, but their combined use has not been studied in depth, and trust, as a vital element in examining these automated agents also needs to be investigated. A scoping review was conducted following PRISMA guidelines. Two primary avatar roles were identified: Therapist-Twin and Self-Twin. The review used thematic analysis combining with Dual-Process Resonance Model (DPRM) to explain how these roles evolve over time. An Integrated Interaction Model was introduced, identifying three core mechanisms: Sequential Scaffolding, Analytical Bridging, and Synchronous Co-Creation. The integration of avatars and AI chatbots with digital art therapy represents a promising approach to support mental health.

Original languageEnglish
JournalInternational Journal of Human-Computer Interaction
DOIs
StateAccepted/In press - 2026
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • conversational AI
  • Digital art therapy
  • multimodal interaction
  • therapeutic avatars
  • trust in automation

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