Digital Therapeutics, Fall 2025, University of St.Gallen
Generative AI Chatbot for Mental Health Treatment (NEJM AI, 2025) Mobile health intervention CanRelax reduces distress in people with cancer, (npj Digital Medicine 2025) Therabot for the treatment of mental disorders (Nature Mental Health 2025), A Hybrid Rule- and LLM-based Embodied Voice Assistant for Cognitive Stimulation in Older Adults (JMIR Preprints 2025), Success factors of growth-stage digital health companies (BMC Health Services Research 2025)
What are the implications and rationale behind the recent developments in digital therapeutics?
Digital therapeutics (DTx) are software-delivered interventions for managing and treating disease. DTx may leverage digital biomarkers, digital coaches and healthcare chatbots, telemedicine, mobile and wearable computing, self‐tracking, personalized medicine, connected health, smart homes, or smart cars.
In the 20th century, healthcare systems specialized in acute care. In the 21st century, we now face the challenge of dealing with the specific characteristics of chronic conditions. These are now responsible for around 70% of all deaths worldwide and 85% of all deaths in Europe and are associated with an estimated economic loss of $7 trillion between 2011 and 2025. Chronic diseases require an intervention paradigm that focuses on health-promoting behavior. Lifestyle (e.g., diet, physical activity, tobacco, or alcohol consumption) can reduce the risk of suffering from a chronic condition. However, a lifestyle change is only implemented by a fraction of those affected, partly because of missing or inadequate interventions or health literacy, partly due to sociocultural influences. Individual personal coaching of these individuals is neither scalable nor financially sustainable.
Against this background, the question arises of how to develop evidence-based DTx that allow medical doctors and other caregivers to scale and tailor long-term treatments to individuals in need at sustainable costs. At the intersection of health economics, information systems research, computer science, and behavioral medicine, this lecture aims to help students and upcoming healthcare executives interested in the multi-disciplinary field of DTx to understand better the need, design, assessment, and reimbursement of DTx.
After the course, students will be able to…
- understand the importance of DTx for the management of chronic conditions
- understand the anatomy of DTx
- know frameworks for the design of DTx
- know evaluation criteria for DTx
- know technologies for DTx
- assess DTx
- know about reimbursement strategies of DTx
- discuss the advantages and disadvantages of DTx
To reach these learning objectives, the following topics are covered in the lecture and will be discussed based on concrete national and international examples, including those from the Centre for Digital Health Interventions (www.c4dhi.org), a joint initiative of the Institute for Implementation Science in Health Care, University of Zurich, the Department of Management, Technology, and Economics at ETH Zurich, and the Institute of Technology Management and School of Medicine at the University of St.Gallen:
1. Motivation for Digital Therapeutics (DTx)
- The rise of chronic diseases in developed countries
- The discrepancy between acute care and care for chronic diseases
- From excellence of care in healthcare institutions to excellence of care in the everyday life with DTx
- Definition of DTs
2. Anatomy of DTx
- Just-in-time adaptive interventions
- Digital biomarker for predicting states of vulnerability
- Digital biomarker for predicting states of receptivity
- Digital coaching and healthcare chatbots
3. Design & Evaluation of Digital Health Interventions
- Overview of design frameworks
- Preparation of DTx
- Optimization of DTx
- Evaluation of DTx
- Implementation of DTx
DTx Technologies
- Technologies for telemedicine
- Mobile medical devices
- Virtual and aufgmented-reality applications, incl. live demonstrations
- Privacy and regulatory considerations
Course structure
The lecture is structured in two parts, with on-site sessions and complementary online exercises. In the first part, students will learn and discuss the topics of the four learning modules in weekly on-site sessions. Complementary learning material (e.g., video and audio clips), multiple-choice questions, and exercises are provided online via Canvas.
In the second part, students work in teams and will use their acquired knowledge to assess DTx critically. Each team will then present and discuss the assessment findings with fellow students who provide peer reviews. Additional on-site coaching sessions are offered to support the teams in preparing their presentations.
Course literature
- Bakoyiannis, I. Therabot for the treatment of mental disorders. Nat. Mental Health 3, 485 (2025). https://doi.org/10.1038/s44220-025-00439-x
- Barth, J., Schläpfer, S., Schneider, F., Santhanam, P., Kowatsch, T., Heinz, P., Held, U., Eicher, M., Witt, C., Mobile health intervention CanRelax reduces distress in people with cancer in a randomized controlled trial, npj Digital Medicine 8, 269 (2025), 10.1038/s41746-025-01688-x
- Bitomsky, L., Pfitzer, E., Nißen, M.K., Kowatsch, T. (2025) Advancing health equity and the role of digital health technologies: a scoping review, BMJ Open 2025;15:e099306, 10.1136/bmjopen-2025-099306
- Brill, E., Vinay, R., Nißen, M., Joshi, P., Klöppel, S., Kowatsch, T. (2025) Towards a smartphone-based and conversational agent delivered just-in-time adaptive holistic lifestyle intervention for seniors affected by cognitive decline: Two-week proof-of-concept study, JMIR Formative Research, 12/05/2025:66885 10.2196/66885
- Castro, O., Mair, J. L., … Kowatsch, T. (2023). Development of “LvL UP 1.0”: a smartphone-based, conversational agent-delivered holistic lifestyle intervention for the prevention of non-communicable diseases and common mental disorders. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1039171
- Collins, L. M. (2018). Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST). Springer. https://doi.org/10.1007/978-3-319-72206-1
- Heinz M., … Jacobson Nicholas, C. (2025). Randomized Trial of a Generative AI Chatbot for Mental Health Treatment. NEJM AI, 2(4), AIoa2400802. https://doi.org/10.1056/AIoa2400802
- Jacobson, N., Kowatsch, T., & Marsch, L. (Eds.). (2023). Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future (1st ed.). Elsevier, Academic Press. https://doi.org/10.1016/C2020-0-02801-X.
- Pfitzer, E., Giger, O.F., Kausch, C., Kowatsch, T. (2025) Success Factors and Measures for Scaling Patient-Facing Digital Health Technologies from Leaders Insights, BMC Health Services Research 25(632) 10.1186/s12913-025-12748-z
- Pfitzer, E., Bitomsky, L., Nißen, M., Kausch, C., Kowatsch, T. (2024) Success factors of growth-stage digital health companies: a systematic literature review, J Med Internet Res 2024;26:e60473 10.2196/60473
- Kowatsch, T., Otto, L., Harperink, S. et al. (2019). A design and evaluation framework for digital health interventions. it – Information Technology, 61(5-6), 253-263. https://doi.org/10.1515/itit-2019-0019
- Kowatsch, T., & Fleisch, E. (2021). Digital Health Interventions. In O. Gassmann & F. Ferrandina (Eds.), Connected Business: Create Value in a Networked Economy (pp. 71-95). Springer International Publishing. https://doi.org/10.1007/978-3-030-76897-3_4
- Kowatsch, T., Schachner, T., Harperink, S. et al. (2021). Conversational Agents as Mediating Social Actors in Chronic Disease Management Involving Healthcare Professionals, Patients, and Family Members: Intervention Design and Results from a Multi-site, Single-arm Feasibility Study. J Med Internet Res, 23(2). https://doi.org/10.2196/25060
- Kowatsch, T., Lohse, K.-M., Erb, V. et al. (2021). Hybrid Ubiquitous Coaching With a Novel Combination of Mobile and Holographic Conversational Agents Targeting Adherence to Home Exercises: Four Design and Evaluation Studies. Journal of Medical Internet Research (JMIR), 23(2). https://doi.org/10.2196/23612
- Mishra, V., Künzler, F., Kramer, J.-N., Fleisch, E., Kowatsch, T., & Kotz, D. (2021). Detecting Receptivity for mHealth Interventions in the Natural Environment. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 5(2), Article 74. https://doi.org/10.1145/3463492
- Nahum-Shani, I., Smith, S. N., Spring, B. J. et al. (2018). Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Ann Behav Med, 52(6), 446-462. https://doi.org/10.1007/s12160-016-9830-8
- Sim, I. (2019). Mobile Devices and Health. N Engl J Med, 381(10), 956-968. https://doi.org/10.1056/NEJMra1806949
- Vinay, R., Uetova, E., Tommila, N., Biller-Andorno, N., Kowatsch, T. (2025) GRACE, A Hybrid Rule- and LLM-based Embodied Voice Assistant for Cognitive Stimulation in Older Adults: A Pilot Study Assessing Technical Feasibility, Technology Acceptance, and Working Alliance, JMIR Preprints. 09/05/2025:76489, 10.2196/preprints.76489
- Wang, C., Lee, C., & Shin, H. (2023). Digital therapeutics from bench to bedside. npj Digital Medicine, 6(1), 38. https://doi.org/10.1038/s41746-023-00777-z
Summary
Digital Therapeutics (11,702), University of St.Gallen, Fall Semester 2025, 2 ECTS
Lecturer
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