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

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-choicequestions, 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.

1. Bakoyiannis, I. (2025). Therabot for the treatment of mental disorders. Nature Mental Health, 3, 485, https://doi.org/10.1038/s44220-025-00439-x.
2. Barth, J., Schläpfer, S., Schneider, F., Santhanam, P., Kowatsch, T., Heinz, P., Held, U., Eicher, M., & Witt, C. M. (2025). Mobile health intervention CanRelax reduces distress in people with cancer in a randomized controlled trial. npj Digital Medicine, 8, 269, https://doi.org/10.1038/s41746-025-01688-x.
3. Bitomsky, L., Pfitzer, E., Nißen, M., & Kowatsch, T. (2025). Advancing health equity and the role of digital health technologies: A scoping review. BMJ Open, 15(6), e099306, https://doi.org/10.1136/bmjopen-2025-099306.
4. Brill, E., Vinay, R., Nißen, M., Joshi, P., Klöppel, S., & Kowatsch, T. (2025). Toward a smartphone-based and conversational agent–delivered just-in-time adaptive holistic lifestyle intervention for older adults affected by cognitive decline: Two-week proof-of-concept study. JMIR Formative Research, 9, e66885, https://doi.org/10.2196/66885.
5. Holfelder, A., de Terrasson de Montleau, A., Vinay, R., Nißen, M., Klöppel, S., Kowatsch, T., & Brill, E. (2026). Sensor-augmented conversational agent for personalized lifestyle support in older adults with mild cognitive impairment: Two-week feasibility study. JMIR Preprints, 105520 (25 June 2026), https://doi.org/10.2196/preprints.105520.
6. 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, 1039171, https://doi.org/10.3389/fdgth.2023.1039171.
7. 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.
8. Heinz, M. V., …, Jacobson, N. C. (2025). Randomized trial of a generative AI chatbot for mental health treatment. NEJM AI, 2(4), AIoa2400802, https://doi.org/10.1056/AIoa2400802.
9. Jacobson, N. C., Kowatsch, T., & Marsch, L. A. (2023) (Eds.). Digital therapeutics for mental health and addiction: The state of the science and vision for the future (1st ed.). Academic Press, https://doi.org/10.1016/C2020-0-02801-X.
10. Pfitzer, E., Giger, O., 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, https://doi.org/10.1186/s12913-025-12748-z.
11. Pfitzer, E., Bitomsky, L., Nißen, M., Kausch, C., & Kowatsch, T. (2024). Success factors of growth-stage digital health companies: Systematic literature review. Journal of Medical Internet Research, 26, e60473, https://doi.org/10.2196/60473.
12. 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.
13. 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.
14. Kowatsch, T., Schachner, T., Harperink, S., et al. (2021). Conversational agents as mediating social actors in chronic disease management involving health care professionals, patients, and family members: Multisite single-arm feasibility study. Journal of Medical Internet Research, 23(2), e25060, https://doi.org/10.2196/25060.
15. 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, 23(2), e23612, https://doi.org/10.2196/23612.
16. Liévin, V., Palepu, A., Weng, W.-H., et al. (2026). Towards conversational artificial intelligence for disease management. Nature, 655, 1292–1299, https://doi.org/10.1038/s41586-026-10764-5.
17. Mishra, V., Künzler, F., Kramer, J.-N., Fleisch, E., Kowatsch, T., & Kotz, D. (2021). Detecting receptivity for mHealth interventions in the natural environment. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 5(2), Article 74, https://doi.org/10.1145/3463492.
18. Moser, F., Vinay, R., & Kowatsch, T. (2026). STELLA: An open-source platform for auditable voice-first conversational health coaching agents. In Proceedings of the 8th ACM Conference on Conversational User Interfaces (CUI ’26) (Article 88, pp. 1–7). Association for Computing Machinery, https://doi.org/10.1145/3816046.3816293.
19. 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. Annals of Behavioral Medicine, 52(6), 446–462, https://doi.org/10.1007/s12160-016-9830-8.
20. Sim, I. (2019). Mobile devices and health. New England Journal of Medicine, 381(10), 956–968, https://doi.org/10.1056/NEJMra1806949.
21. Vinay, R., Uetova, E., Tommila, N. C., Biller-Andorno, N., & Kowatsch, T. (2025). A hybrid rule- and large language model–based embodied voice assistant (GRACE) for cognitive stimulation in older adults: Usability study assessing technical feasibility, technology acceptance, and working alliance. JMIR Aging, 8, e76489, https://doi.org/10.2196/76489.
22. Vinay, R., Staub, L. F., & Kowatsch, T. (2026). Stakeholder-perceived value and reimbursement pathways for a voice assistant in dementia care: Evidence from Switzerland. Health Policy and Technology, 15(10), 101305, https://doi.org/10.1016/j.hlpt.2026.101305.
23. 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.