User trust is pivotal for the adoption of digital health systems interventions (DHI). In response, numerous trust-building guidelines have recently emerged targeting DHIs such as artificial intelligence. The common aim of these guidelines aimed at private sector actors and government policy makers is to build trustworthy DHI. While these guidelines provide some indication of what trustworthiness is, the guidelines typically only define trust and trustworthiness in broad terms, they rarely offer guidance about economic considerations that would allow implementers to measure and balance trade-offs between costs and benefits. These considerations are important when deciding how best to allocate scarce resources (eg, financial capital, workforce, or time). The missing focus on economics undermines the potential usefulness of such guidelines. We propose the development of actionable trust-performance-indicators (including but not limited to surveys) to gather evidence on the cost-effectiveness of trust-building principles as a crucial step for successful implementation. Furthermore, we offer guidance on navigating the conceptual complexity surrounding trust and on how to sharpen the trust discourse. Successful implementation of economic considerations is critical to successfully build user trust in DHI.
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