Webinar highlights: How do we translate eHealth research to real-world use?

Lack of contextual adaptation. Digital tools must be tailored to the local context—including cultural norms, healthcare systems, and user needs—to be effective in real-world settings. Generic tools, even if well-designed, often fail when local relevance is not prioritised.

Weak accountability structures. Policymakers frequently focus on short-term wins, such as launching visible programs, rather than making evidence-based decisions. Researchers, too, should be held accountable for ensuring their work translates into real-world impact, beyond academic outputs like randomised controlled trials or publications.

Challenges with integration into existing systems. Even when tools are effective, they often face resistance when integrating into established institutional workflows. Health systems tend to be rigid, and successful integration requires alignment with their existing operations, priorities, and infrastructure.

Fragmentation and lack of coordination. Although individual projects may achieve positive outcomes, there is rarely a coordinated effort to bring these initiatives together or scale them across regions or systems. As a result, each project ends up promoting its own tool in isolation, which is inefficient and unsustainable.

Multiplicity of barriers, varying by context. Barriers to implementation are not uniform—they vary depending on the type of intervention, the identity of the end users, the financing model, and the implementation environment, whether that be hospitals, clinics, or community settings.

Need for structured implementation frameworks. Frameworks like the Consolidated Framework for Implementation Research (CFIR) are valuable for identifying and navigating complex, context-specific implementation barriers. Even when the intervention remains the same, the implementation approach must be adapted to fit each unique setting.

Overall, the panel emphasised that translating research into real-world practice is not a linear process. It requires adaptation, accountability, systemic integration, stakeholder engagement, and flexible implementation strategies tailored to the context in which the tool is deployed.

Technology obsolescence & platform flexibility. Tools built for current technologies, such as mobile phones in 2023, risk becoming outdated by the time multi-year projects conclude, potentially as late as 2027. To remain relevant and sustainable, platforms must be open, adaptable, and designed to accommodate emerging devices and evolving standards.

Delayed cost-effectiveness of prevention. Prevention programs—especially in areas like youth mental health—often yield measurable benefits only after a significant delay. This lag in demonstrating value poses a challenge for typical funding and evaluation models, which are structured around short-term outcomes.

Cross-disciplinary communication barriers. Collaboration between teams from technical, clinical, and academic backgrounds can be complicated by differences in language, assumptions, and working styles. Even within clinical teams, varied professional training can lead to miscommunication and coordination difficulties.

Lack of early alignment on goals and frameworks. Projects frequently begin without a shared understanding of overarching goals or implementation strategies. Investing time early in the process to build trust, define roles, and agree on frameworks is essential to avoid confusion and inefficiencies later on.

Technical & regulatory barriers. Several implementation challenges must be addressed from the start, including data storage requirements, server location decisions, compliance with privacy regulations like GDPR, ensuring interoperability between systems, and managing conflicting timelines and incentives across academic and commercial partners.

Need for policy frameworks to support integration. The EU’s Digital Services Act signals growing support for digital mental health, but significant gaps remain—particularly in translating policy into practice within educational settings. A clear divide exists between care systems, which are regulated and better funded, and prevention efforts, which often lack structural and financial support. In the Netherlands, innovation is fast-paced but followed by poor implementation, whereas Germany, despite its bureaucratic approach, has established the DiGA framework that allows digital tools to be prescribed and reimbursed, setting a structured example for others.

Importance of long-term, dedicated funding. To move beyond the pilot stage, successful projects require long-term funding that supports integration into public systems after the research phase ends. This investment must be accompanied by regulatory evolution to accommodate the novel digital and methodological approaches these tools often bring.

Local-level policy resistance and disconnection. At the local level, evidence-based tools are sometimes disregarded by policymakers if they do not see a direct political advantage. Bridging this gap requires structured, accountable communication among researchers, policymakers, and users—with clear follow-ups like meeting records and defined action points to ensure progress.

DiGA as a Model Framework for Europe. Germany’s Digital Health Applications (DiGA) framework offers a structured path for assessing digital mental health tools for evidence and cost-effectiveness, and enables their prescription and reimbursement through the national insurance system. While not without flaws, it represents a pioneering approach that could be adapted or expanded across Europe to support implementation efforts beyond the research stage.

Overall takeaway: Sustainable integration of digital mental health tools requires structured policy support, long-term funding, regulatory flexibility, and coordinated engagement across national and local levels. Frameworks like Germany’s DiGA offer a strong foundation that other countries—and the EU—can build on to avoid letting effective tools go unused after project funding ends.

Blend digital tools with human support. Mobile interventions are most effective when paired with human interaction, such as guided self-help or periodic check-ins with a therapist. This combination fosters healthier engagement and helps users see the tool as a supportive resource rather than something addictive.

Design for short-term, skill-building use. Digital tools should be designed with a clear timeframe and aim to equip users with practical coping skills. The goal is for users to eventually "graduate" from the app, achieving independence rather than developing reliance on the tool.

Establish structured, time-bound interactions. Implementing scheduled messaging systems—where interactions occur at set times and responses are deliberately delayed—encourages mindful, purposeful use. Unlike constant access on platforms like WhatsApp, this structure discourages compulsive behavior and supports intentional engagement.