In recent years, digital behavioral health has emerged as a transformative force in healthcare, promising scalable, accessible interventions for mental health and wellbeing. However, as these technologies advance at a rapid pace, one foundational element remains profoundly underexplored and undervalued: trust. Trust is no longer a peripheral feature but must be recognized as the critical infrastructure underpinning the design, deployment, and evaluation of digital behavioral health systems. This insight is at the core of a groundbreaking commentary by Trevor van Mierlo, DBA, featured in the Journal of Medical Internet Research, articulating a complex narrative that reframes trust as a multifaceted, dynamic, and socially-rooted phenomenon essential to digital health’s future.
Van Mierlo’s exploration diverges from simplistic equations that presume user engagement equates to trust. Through extensive interviews with experts spanning informatics, cybersecurity, behavioral health, and public digital infrastructure, he reveals that engagement metrics are insufficient and potentially misleading indicators of genuine trust. Users may interact with digital health platforms from necessity rather than confidence, often masking true symptoms or providing sanitized information that compromises clinical accuracy. This distortion challenges the validity of data-driven insights and the efficacy of digital therapeutic strategies that rely on authentic user inputs. Hence, engagement devoid of trust can undermine the very goals these systems aim to achieve.
Central to this discourse is the destabilization of traditional privacy mechanisms, such as static consent forms and opaque data policies. With behavioral health platforms continuously harvesting user interaction data, these dated approaches fall short of ensuring transparency and user agency. Van Mierlo, drawing from thought leaders like Benjamin Schooley and Kavya Pearlman, argues for a paradigm shift toward “computable governance,” where privacy and consent are not static documents but dynamic, enforceable, and algorithmically integrated frameworks. Such governance must incorporate cryptographically verifiable audit trails to establish immutable records of data usage and AI decision-making processes. This level of accountability is crucial for maintaining user trust and safeguarding sensitive behavioral data against misuse.
Beyond technology and policy, trust is inherently social. The foundation of trust—or mistrust—often predates any technological interaction and is shaped by broad socio-cultural factors, including institutional histories, digital literacy disparities, and the pervasive influence of misinformation. Van Mierlo highlights that digital behavioral health technologies do not operate in a vacuum but are embedded within complex social ecosystems. Vulnerability is intrinsic to behavioral health, where individuals must often cede interpretative authority to algorithm-driven systems they may scarcely comprehend. This asymmetry creates a fertile ground for mistrust and skepticism that no amount of technical sophistication alone can assuage.
The commentary insists that trust-building requires intentional engineering and iterative auditing. It calls for multidisciplinary collaboration involving behavioral scientists, technologists, ethicists, and communities to co-create digital health infrastructures that are not only functional but also transparent, inclusive, and empathetic. The integration of explainable AI techniques, user-centric privacy controls, and responsive governance models exemplifies this ethos. In contrast to ephemeral features or superficial metrics, trust is posited as a living infrastructure—continually constructed, validated, and renewed through social and technical mechanisms alike.
One of the pivotal insights underscores that as artificial intelligence increasingly becomes embedded in behavioral health assessments and interventions, the notion of “does it work?” is insufficient. The question must evolve to include “can it be trusted?” Trust influences acceptance, adherence, and ultimately, outcomes. Systems that fail to engender trust risk alienating users, perpetuating health disparities, and eroding the credibility of digital health innovations. As technologies become more autonomous and complex, ensuring trust transcends user interface design; it is about embedding trustworthiness into the very architecture of data collection, AI modeling, and system governance.
Van Mierlo’s work also engages with the ethical dimensions of behavioral data in digital systems. The sensitivity of mental health information demands heightened scrutiny and rigorous protections. Transparent disclosure about how data informs AI-driven decisions is not just a technical requirement but an ethical imperative. Users must be empowered with clear, accessible knowledge about data flows and system functionalities to make informed decisions about their participation. This empowerment is essential to mitigate power imbalances and support vulnerable populations whose voices have historically been marginalized or silenced in digital health discourses.
The commentary further problematizes the prevalent industry reliance on quantitative metrics to evaluate behavioral health technologies. By juxtaposing engagement with trust, it challenges stakeholders to recalibrate evaluation frameworks to account for qualitative, context-sensitive measures of user experience. Incorporating feedback loops, participatory design methods, and longitudinal studies can unveil the nuanced landscape of trust dynamics and inform adaptive interventions that resonate authentically with users’ lived realities. Without such recalibrations, digital behavioral health risks perpetuating superficial successes while neglecting deeper systemic issues.
Moreover, van Mierlo recognizes the imperative for ongoing governance strategies that adapt as AI and data practices evolve. The complexity of AI systems—including machine learning models that continuously update based on new data—requires governance that is not monolithic but iterative and reflexive. This necessitates advanced computational methods capable of real-time monitoring, compliance verification, and user-centric control adjustments. By championing computable governance, the commentary envisions a future where trust is safeguarded by technologies themselves, reducing reliance on external audits or post-hoc regulations alone.
The framing of trust as a social and infrastructural construct invites a broader interdisciplinary dialogue and policy engagement. It compels digital health developers, regulators, and funders to move beyond technical innovation toward cultivating social legitimacy and ethical stewardship. Building this infrastructure demands robust investment not only in technology but in community engagement, education, and transparent communication strategies that demystify digital behavioral health and foster collective ownership over these emerging systems.
In conclusion, Trevor van Mierlo’s commentary elucidates a critical, yet often overlooked, dimension of digital behavioral health: trust as an indispensable and complex infrastructure. As digital platforms promise to revolutionize mental health care delivery, embedding trust at every layer—technical, social, ethical, and governance—is paramount. This foundational shift is essential not only for realizing the full potential of digital interventions but also for ensuring these technologies empower rather than alienate the very individuals they seek to support. Trust, as Van Mierlo compellingly argues, must be the first and unyielding step in the journey toward a future where digital behavioral health is effective, equitable, and human-centered.
Subject of Research: People
Article Title: You Can’t Launch This: Trust as Infrastructure in Digital Behavioral Health
News Publication Date: 23-Jun-2026
Web References: https://www.jmir.org/2026/1/e104731/
References: van Mierlo T. You Can’t Launch This: Trust as Infrastructure in Digital Behavioral Health. J Med Internet Res 2026;28:e104731. doi: 10.2196/104731
Image Credits: Image provided by the author (Trevor van Mierlo, DBA)
Keywords: digital behavioral health, trust infrastructure, artificial intelligence, computable governance, mental health, data privacy, user engagement, ethical AI, behavioral data integrity, explainable AI, cybersecurity, social determinants of trust
Tags: authentic data in digital therapybuilding trust in digital healthcybersecurity in behavioral healthdigital behavioral health trustdigital health user engagement challengesdigital mental health interventionsevaluating digital health systemsmental health technology trustsocial dimensions of digital trusttrust and clinical accuracytrust as healthcare infrastructureuser confidence in health platforms