Abstract
INTRODUCTION: Digital therapeutics (DTx) require structured methodologies to translate evidence-based psychotherapy into immersive digital formats. In response to this need, this study proposes a practical framework for the digital transformation of Acceptance and Commitment Therapy (ACT) into an interactive virtual reality (VR) system. METHODS: DTx-ACT, designed as a therapeutic intervention for depression, is a VR-based system that delivers ACT through an immersive virtual experience. Its development followed five structured phases: preliminary research, design, development, advancement, and commercialization. The original ACT protocol was modularized into VR environments using the Session Structuring System (SSS) model. To enhance user engagement, gamification and multimodal arts strategies were incorporated. As part of the development process, evaluation metrics were defined to assess both clinical effectiveness and user interaction. RESULTS: The final system comprises five immersive VR sessions, each lasting 6 to 12 minutes. These modules incorporate ACT metaphors, interactive tasks, and multisensory feedback to enhance therapeutic engagement. To support the digital transformation of ACT, three core components were established: (1) an evidence-based therapeutic protocol, (2) interactive VR elements-including gamification and multimodal arts-based guidance, and (3) a data-driven evaluation framework. Evaluation metrics, derived from a pilot study, were integrated into the system, which collects clinical and interaction data-such as real-time behavioral patterns and sensor-based information-to enable comprehensive evaluation. DISCUSSION: Based on this development process, we propose a practical framework for designing interactive VR-based DTx. This framework bridges clinical structure, creative engagement, and real-time evaluation to support personalized and scalable applications in digital mental healthcare. It contributes to the standardization of digital transformation in evidence-based therapy and offers a transferable model for future therapeutic content development.