Preventive Digital Health Interventions: Identifying Major Risks

This article, titled “Preventive Digital Health Interventions: Identifying the major risks” by Keld Pedersen, addresses the growing challenges posed by increasing rates of chronic disease and rising healthcare costs, particularly those linked to unhealthy lifestyles. It highlights the significant economic burden, noting that in Denmark, for instance, diabetes drugs (also used for weight loss) account for approximately 10% of the public sector medicine budget. The author proposes app-based preventive digital health initiatives (P-DHIs) as a potentially scalable solution, leveraging the widespread adoption of smartphones to provide individual-level support and potentially reduce reliance on direct healthcare professional intervention.

The research identifies a critical gap in understanding the major risks associated with large-scale implementations of P-DHIs. While randomized controlled trial (RCT) studies on P-DHIs have yielded mixed outcomes, it is not guaranteed that these results can be replicated in real-world scenarios. Therefore, the study specifically investigates: “What are the major risks in public health initiatives based on P-DHI and how are they related to the various components in a P-DHI?“. The focus is on P-DHIs related to diet and physical activity, which are crucial for preventing many chronic diseases.

To answer this question, the research employs a scoping multidisciplinary literature review. It draws on information systems (IS) theory concerning IT value creation, alongside mHealth and behavioral change literature. The methodology involves developing a risk model that illustrates key risk categories, covering aspects from the delivery of healthcare services through P-DHIs (such as organizational resistance) to the actual use by end-users (such as lack of motivation). The article details a comprehensive set of identified risks, categorized by their relation to healthcare organizations’ macro- and micro-environments, healthcare resources (including professionals’ attitudes and capabilities), healthcare IT resources, service delivery change processes, users’ resources (like motivation and knowledge), users’ IT, the P-DHI itself (e.g., app quality and support access), and users’ behavioral change processes, as well as their macro- and micro-environments (e.g., physical, food, social, and technological environments).

The findings offer significant implications for both practice and theory. The developed model can assist healthcare organizations in identifying and managing key risks when considering P-DHI implementations. The research emphasizes that while P-DHIs may seem simple to implement, the inherent complexity in coordinating numerous uncoordinated stakeholders with potentially opposing interests (e.g., health authorities, government, food producers, end-users) makes prevention a “wicked problem” that demands ongoing collaborative risk management. It highlights the need for more empirical research focused on the implementation process of P-DHIs and how to effectively manage these identified risks.

Reference: Pedersen, K. (2025). Preventive Digital Health Interventions: Identifying the major risks. Procedia Computer Science, 256, 900–908. https://doi.org/10.1016/j.procs.2025.02.193