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PERSPECTIVE article
Front. Digit. Health
Sec. Digital Mental Health
Volume 7 - 2025 | doi: 10.3389/fdgth.2025.1541676
This article is part of the Research TopicDigital Health Past, Present, and FutureView all 22 articles
More than a Chatbot: A Practical Framework to Harness Artificial Intelligence across Key Components to Boost Digital Therapeutics Quality
Provisionally accepted- University of Haifa, Haifa, Israel
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The rapid advancement of Artificial Intelligence (AI)-powered large language models has highlighted the potential of AI-based chatbots to create a new era for digital therapeutics (DTx)-digital behavioral and mental health interventions. However, fully realizing AI-potential requires a clear understanding of how DTx function, what drives their effectiveness, and how AI can be integrated strategically. This paper presents a practical framework for harnessing AI to enhance the quality of DTx by dismantling them into five key components: Therapeutic Units, Decision Maker, Narrator, Supporter, and Therapist. Each represents an aspect of intervention delivery where AI can be applied.AI can personalize Therapeutic Units by dynamically adapting content to individual contexts, achieving a level of customization not possible with manual methods. An AI-enhanced Decision Maker can recommend and sequence therapeutic pathways based on real-time data and adaptive algorithms, eliminating the reliance on predefined decision trees or exhaustive logic-driven ruling. AI can also transform the Narrator by generating personalized narratives that unify intervention activities into cohesive experiences. As a Supporter, AI can mimic remotely administered human support, automating technical assistance, adherence encouragement, and clinical guidance at scale. Lastly, AI enables the creation of a Therapist to deliver real-time, interactive, and tailored therapeutic dialogues, adapting dynamically to user feedback and progress in ways that were previously impractical before. This framework provides a structured method to integrate AI-driven improvements, while also enabling to focus on a specific component during the optimization process.
Keywords: artificial intelligence, digital health intervention, digital mental health, User engagement, Intervention quality, Chatbot
Received: 08 Dec 2024; Accepted: 08 Apr 2025.
Copyright: © 2025 Baumel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Amit Baumel, University of Haifa, Haifa, Israel
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