VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

363-1135-00L 4 Credits MSC , NDS D-MTEC

Digital Health in Practice (University of Zurich)

No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH. UZH Module Code: 04SM22MAS100 Mind the enrolment deadlines at UZH:
VVZ CR n/a

Last Updated: 2026-02-05 16:16:51

Abstract

Today, we face the challenge of chronic conditions. Personal coaching approaches are neither scalable nor financially sustainable. The question arises, therefore, to which degree Digital Health Interventions (DHIs) are appropriate to address this challenge. In this lecture, students will learn about the need for, as well as the design, implementation, and assessment of DHIs.

Objective

• To understand the importance of digital health interventions for the prevention, management, and treatment of non-communicable diseases and common mental disorders • To discuss the opportunities and challenges of digital health interventions (e.g., data collection with wearables, smartphone- and chatbot-delivered health interventions) • To gain hands-on experience in the conceptual design, implementation and evaluation of a wearable- and smartphone-based digital health intervention

Content

Fitbits detect lasting changes after Covid-19 (New York Times, 2022), The promise of the metaverse in cardiovascular health (European Heart Journal, 2022), Can Virtual Reality Help Ease Chronic Pain? (The New York Times Magazine, 2022), First of its Kind Alexa Experience Provides Hands-Free Access at Home to General Medical Care (GlobeNewswire, 2022), Can digital technologies improve health? (The Lancet, 2021), Predictive analytics and tailored interventions improve clinical outcomes (npj Digital Medicine, 2021), Q1 2022 Digital Health Funding Reaches $6B Across 183 Deals (Rock Health, 2022). Digital health applications use information, sensor and communication technology to understand, prevent, manage, or treat diseases. The design of these applications requires interdisciplinary expertise at the intersection of medicine, psychology, computer science, technology, management, economics, and law. Only a close collaboration between experts from these disciplines and a specific target population can lead to a shared understanding of the problem at hand and, as a result, highly effective digital health applications. For this reason, national and international students studying computer science, business informatics, psychology, management, economics, or law are invited to work collaboratively with medical students. Digital health applications and companies have the goal of advancing health care services to fight the ongoing increase of non-communicable diseases (NCDs) and common mental disorders (CMDs) in developed countries. To this end, the question arises of how to develop evidence- based digital health interventions (DHI) that allow medical doctors and other caregivers to scale and tailor long-term treatments to individuals in need at sustainable costs. Through input lectures and practical applications, this module has, therefore, the objective to help students to better understand the need, design, implementation, and evaluation of DHIs. The following topics are covered: 1. DHIs for the prevention, management, and treatment of NCDs and CMDs 2. Strategies for long-term compliance with DHI 3. Conceptual design of a wearable- and smartphone-based DHI 4. Technical implementation of a wearable- and smartphone-based DHI 5. Evaluation of a wearable- and smartphone-based DHI

Resources

Literature

All relevant learning material will be made available via the online learning platform. Moreover, the content of this module is drawn from the experience of the lecturers and the following work: 1. Balbim GM, IG Marques, DX Marquez, et al. (2021) Using Fitbit as an mHealth Intervention Tool to Promote Physical Activity: Potential Challenges and Solutions, Journal of Medical Internet Research (JMIR) Mhealth Uhealth 9(3):e25289, 10.2196/25289 2. Collins LM (2018) Optimization of Behavioral, Biobehavioral, and Biomedical Interventions: The Multiphase Optimization Strategy (MOST), New York: Springer, 10.1007/978-3-319-72206-1 3. Jacobson N, T Kowatsch & LA Marsch (2022) Digital Therapeutics for Mental Health and Addiction: The State of the Science and Vision for the Future (1st ed.), Cambridge: Elsevier, Academic Press, 978-0-323- 90045-4 4. Kowatsch T & Fleisch E (2021) Digital Health Interventions, in: Gassmann, O.; Ferrandina, F. (eds): Connected Business, Springer: Cham, 10.1007/978-3-030-76897-3_4 5. Kowatsch T, L Otto, S Harperink, A Cotti & H Schlieter (2019) A Design and Evaluation Framework for Digital Health Interventions, it- Information Technology 61(5-6), 253-263, 10.1515/itit-2019-0019 6. Kowatsch T, T Schachner, S Harperink 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 (JMIR) 23(2):e25060, 10.2196/25060 7. Sim I. (2019) Mobile Devices and Health, New England Journal of Medicine (NEJM) 381(10):956-968, 10.1056/NEJMra1806949

General Information

Language
English
Levels
MSC , NDS
Frequency
Yearly recurring

Examination

Type
ungraded semester performance
Registration modalities, date and venue of this performance assessment are specified solely by the UZH.

Course Components

Type Title Time & Place Hours
lecture Digital Health in Practice (University of Zurich)
**Course at University of Zurich**
No time listed 44 h semesterly

Offered In